Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND

Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations.

METHODS

The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds.

FINDINGS

The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles.

INTERPRETATION

Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere.

FUNDING

Bill & Melinda Gates Foundation.

Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND

Understanding the health consequences associated with exposure to risk factors is necessary to inform public health policy and practice. To systematically quantify the contributions of risk factor exposures to specific health outcomes, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 aims to provide comprehensive estimates of exposure levels, relative health risks, and attributable burden of disease for 88 risk factors in 204 countries and territories and 811 subnational locations, from 1990 to 2021.

METHODS

The GBD 2021 risk factor analysis used data from 54 561 total distinct sources to produce epidemiological estimates for 88 risk factors and their associated health outcomes for a total of 631 risk-outcome pairs. Pairs were included on the basis of data-driven determination of a risk-outcome association. Age-sex-location-year-specific estimates were generated at global, regional, and national levels. Our approach followed the comparative risk assessment framework predicated on a causal web of hierarchically organised, potentially combinative, modifiable risks. Relative risks (RRs) of a given outcome occurring as a function of risk factor exposure were estimated separately for each risk-outcome pair, and summary exposure values (SEVs), representing risk-weighted exposure prevalence, and theoretical minimum risk exposure levels (TMRELs) were estimated for each risk factor. These estimates were used to calculate the population attributable fraction (PAF; ie, the proportional change in health risk that would occur if exposure to a risk factor were reduced to the TMREL). The product of PAFs and disease burden associated with a given outcome, measured in disability-adjusted life-years (DALYs), yielded measures of attributable burden (ie, the proportion of total disease burden attributable to a particular risk factor or combination of risk factors). Adjustments for mediation were applied to account for relationships involving risk factors that act indirectly on outcomes via intermediate risks. Attributable burden estimates were stratified by Socio-demographic Index (SDI) quintile and presented as counts, age-standardised rates, and rankings. To complement estimates of RR and attributable burden, newly developed burden of proof risk function (BPRF) methods were applied to yield supplementary, conservative interpretations of risk-outcome associations based on the consistency of underlying evidence, accounting for unexplained heterogeneity between input data from different studies. Estimates reported represent the mean value across 500 draws from the estimate's distribution, with 95% uncertainty intervals (UIs) calculated as the 2·5th and 97·5th percentile values across the draws.

FINDINGS

Among the specific risk factors analysed for this study, particulate matter air pollution was the leading contributor to the global disease burden in 2021, contributing 8·0% (95% UI 6·7-9·4) of total DALYs, followed by high systolic blood pressure (SBP; 7·8% [6·4-9·2]), smoking (5·7% [4·7-6·8]), low birthweight and short gestation (5·6% [4·8-6·3]), and high fasting plasma glucose (FPG; 5·4% [4·8-6·0]). For younger demographics (ie, those aged 0-4 years and 5-14 years), risks such as low birthweight and short gestation and unsafe water, sanitation, and handwashing (WaSH) were among the leading risk factors, while for older age groups, metabolic risks such as high SBP, high body-mass index (BMI), high FPG, and high LDL cholesterol had a greater impact. From 2000 to 2021, there was an observable shift in global health challenges, marked by a decline in the number of all-age DALYs broadly attributable to behavioural risks (decrease of 20·7% [13·9-27·7]) and environmental and occupational risks (decrease of 22·0% [15·5-28·8]), coupled with a 49·4% (42·3-56·9) increase in DALYs attributable to metabolic risks, all reflecting ageing populations and changing lifestyles on a global scale. Age-standardised global DALY rates attributable to high BMI and high FPG rose considerably (15·7% [9·9-21·7] for high BMI and 7·9% [3·3-12·9] for high FPG) over this period, with exposure to these risks increasing annually at rates of 1·8% (1·6-1·9) for high BMI and 1·3% (1·1-1·5) for high FPG. By contrast, the global risk-attributable burden and exposure to many other risk factors declined, notably for risks such as child growth failure and unsafe water source, with age-standardised attributable DALYs decreasing by 71·5% (64·4-78·8) for child growth failure and 66·3% (60·2-72·0) for unsafe water source. We separated risk factors into three groups according to trajectory over time: those with a decreasing attributable burden, due largely to declining risk exposure (eg, diet high in trans-fat and household air pollution) but also to proportionally smaller child and youth populations (eg, child and maternal malnutrition); those for which the burden increased moderately in spite of declining risk exposure, due largely to population ageing (eg, smoking); and those for which the burden increased considerably due to both increasing risk exposure and population ageing (eg, ambient particulate matter air pollution, high BMI, high FPG, and high SBP).

INTERPRETATION

Substantial progress has been made in reducing the global disease burden attributable to a range of risk factors, particularly those related to maternal and child health, WaSH, and household air pollution. Maintaining efforts to minimise the impact of these risk factors, especially in low SDI locations, is necessary to sustain progress. Successes in moderating the smoking-related burden by reducing risk exposure highlight the need to advance policies that reduce exposure to other leading risk factors such as ambient particulate matter air pollution and high SBP. Troubling increases in high FPG, high BMI, and other risk factors related to obesity and metabolic syndrome indicate an urgent need to identify and implement interventions.

FUNDING

Bill & Melinda Gates Foundation.

Decoding 2.3 million ECGs: interpretable deep learning for advancing cardiovascular diagnosis and mortality risk stratification

Aims

Electrocardiogram (ECG) is widely considered the primary test for evaluating cardiovascular diseases. However, the use of artificial intelligence (AI) to advance these medical practices and learn new clinical insights from ECGs remains largely unexplored. We hypothesize that AI models with a specific design can provide fine-grained interpretation of ECGs to advance cardiovascular diagnosis, stratify mortality risks, and identify new clinically useful information.

Methods and results

Utilizing a data set of 2 322 513 ECGs collected from 1 558 772 patients with 7 years follow-up, we developed a deep-learning model with state-of-the-art granularity for the interpretable diagnosis of cardiac abnormalities, gender identification, and hypertension screening solely from ECGs, which are then used to stratify the risk of mortality. The model achieved the area under the receiver operating characteristic curve (AUC) scores of 0.998 (95% confidence interval (CI), 0.995-0.999), 0.964 (95% CI, 0.963-0.965), and 0.839 (95% CI, 0.837-0.841) for the three diagnostic tasks separately. Using ECG-predicted results, we find high risks of mortality for subjects with sinus tachycardia (adjusted hazard ratio (HR) of 2.24, 1.96-2.57), and atrial fibrillation (adjusted HR of 2.22, 1.99-2.48). We further use salient morphologies produced by the deep-learning model to identify key ECG leads that achieved similar performance for the three diagnoses, and we find that the V1 ECG lead is important for hypertension screening and mortality risk stratification of hypertensive cohorts, with an AUC of 0.816 (0.814-0.818) and a univariate HR of 1.70 (1.61-1.79) for the two tasks separately.

Conclusion

Using ECGs alone, our developed model showed cardiologist-level accuracy in interpretable cardiac diagnosis and the advancement in mortality risk stratification. In addition, it demonstrated the potential to facilitate clinical knowledge discovery for gender and hypertension detection which are not readily available.

Combination of Tele-Cardiology Tools for Cardiovascular Risk Stratification in Primary Care: Data from the PROVAR+ Study

BACKGROUND

Tele-cardiology tools are valuable strategies to improve risk stratification.

OBJECTIVE

We aimed to evaluate the accuracy of tele-electrocardiography (ECG) to predict abnormalities in screening echocardiography (echo) in primary care (PC).

METHODS

In 17 months, 6 health providers at 16 PC units were trained on simplified handheld echo protocols. Tele-ECGs were recorded for final diagnosis by a cardiologist. Consented patients with major ECG abnormalities by the Minnesota code, and a 1:5 sample of normal individuals underwent clinical questionnaire and screening echo interpreted remotely. Major heart disease was defined as moderate/severe valve disease, ventricular dysfunction/hypertrophy, pericardial effusion, or wall-motion abnormalities. Association between major ECG and echo abnormalities was assessed by logistic regression as follows: 1) unadjusted model; 2) model 1 adjusted for age/sex; 3) model 2 plus risk factors (hypertension/diabetes); 4) model 3 plus history of cardiovascular disease (Chagas/rheumatic heart disease/ischemic heart disease/stroke/heart failure). P-values < 0.05 were considered significant.

RESULTS

A total 1,411 patients underwent echo; 1,149 (81%) had major ECG abnormalities. Median age was 67 (IQR 60 to 74) years, and 51.4% were male. Major ECG abnormalities were associated with a 2.4-fold chance of major heart disease on echo in bivariate analysis (OR = 2.42 [95% CI 1.76 to 3.39]), and remained significant after adjustments in models (p < 0.001) 2 (OR = 2.57 [95% CI 1.84 to 3.65]), model 3 (OR = 2.52 [95% CI 1.80 to3.58]), and model 4 (OR = 2.23 [95%CI 1.59 to 3.19]). Age, male sex, heart failure, and ischemic heart disease were also independent predictors of major heart disease on echo.

CONCLUSIONS

Tele-ECG abnormalities increased the likelihood of major heart disease on screening echo, even after adjustments for demographic and clinical variables.

Scalable Risk Stratification for Heart Failure Using Artificial Intelligence applied to 12-lead Electrocardiographic Images: A Multinational Study

Background

Current risk stratification strategies for heart failure (HF) risk require either specific blood-based biomarkers or comprehensive clinical evaluation. In this study, we evaluated the use of artificial intelligence (AI) applied to images of electrocardiograms (ECGs) to predict HF risk.

Methods

Across multinational longitudinal cohorts in the integrated Yale New Haven Health System (YNHHS) and in population-based UK Biobank (UKB) and Brazilian Longitudinal Study of Adult Health (ELSA-Brasil), we identified individuals without HF at baseline. Incident HF was defined based on the first occurrence of an HF hospitalization. We evaluated an AI-ECG model that defines the cross-sectional probability of left ventricular dysfunction from a single image of a 12-lead ECG and its association with incident HF. We accounted for the competing risk of death using the Fine-Gray subdistribution model and evaluated the discrimination using Harrel's c-statistic. The pooled cohort equations to prevent HF (PCP-HF) were used as a comparator for estimating incident HF risk.

Results

Among 231,285 individuals at YNHHS, 4472 had a primary HF hospitalization over 4.5 years (IQR 2.5-6.6) of follow-up. In UKB and ELSA-Brasil, among 42,741 and 13,454 people, 46 and 31 developed HF over a follow-up of 3.1 (2.1-4.5) and 4.2 (3.7-4.5) years, respectively. A positive AI-ECG screen portended a 4-fold higher risk of incident HF among YNHHS patients (age-, sex-adjusted HR [aHR] 3.88 [95% CI, 3.63-4.14]). In UKB and ELSA-Brasil, a positive-screen ECG portended 13- and 24-fold higher hazard of incident HF, respectively (aHR: UKBB, 12.85 [6.87-24.02]; ELSA-Brasil, 23.50 [11.09-49.81]). The association was consistent after accounting for comorbidities and the competing risk of death. Higher model output probabilities were progressively associated with a higher risk for HF. The model's discrimination for incident HF was 0.718 in YNHHS, 0.769 in UKB, and 0.810 in ELSA-Brasil. Across cohorts, incorporating model probability with PCP-HF yielded a significant improvement in discrimination over PCP-HF alone.

Conclusions

An AI model applied to images of 12-lead ECGs can identify those at elevated risk of HF across multinational cohorts. As a digital biomarker of HF risk that requires just an ECG image, this AI-ECG approach can enable scalable and efficient screening for HF risk.

Undernutrition, and overweight and obesity: the two faces of malnutrition in Brazil, analysis of the Global Burden of Disease, 1990 to 2019

OBJECTIVES

The objective of this study was to analyse the global burden of disease attributable to undernutrition and high body mass index (BMI) in Brazil and its 27 states, as well as its association with the socio-demographic index (SDI) from 1990 to 2019.

STUDY DESIGN

This is an epidemiological time-series study.

METHODS

This study analysed the undernutrition and high BMI estimated by the Global Burden of Disease study conducted from 1990 to 2019 for Brazil and its states, using the following metrics: absolute number of deaths, standardised mortality rate, and disability-adjusted life years (DALYs). This study also analysed the correlation between the percentage variation of mortality rates and SDI.

RESULTS

A decrease in the number of deaths (-75 %), mortality rate (-75.1 %), and DALYS (-72 %) attributable to undernutrition was found in Brazil and in all regions. As regarding the high BMI, an increase in the number of deaths was found (139.6 %); however, the mortality rate (-9.7) and DALYs (-6.4 %) declined in all regions, except in the North and Northeast regions, which showed an increase. A strong correlation was identified between undernutrition and high BMI with SDI.

CONCLUSION

Our study observed a double burden of malnutrition in Brazil, with a reduction in the burden of diseases due to malnutrition in Brazil and variation in the burden due to high BMI according to the socioeconomic status of the region. Public policies are necessary in order to guarantee the human right to a healthy and sustainable diet, together with food and nutrition security and a diminishing of social inequality.

Efficacy of three benznidazole dosing strategies for adults living with chronic Chagas disease (MULTIBENZ): an international, randomised, double-blind, phase 2b trial

BACKGROUND

Treatment with benznidazole for chronic Chagas disease is associated with low cure rates and substantial toxicity. We aimed to compare the parasitological efficacy and safety of 3 different benznidazole regimens in adult patients with chronic Chagas disease.

METHODS

The MULTIBENZ trial was an international, randomised, double-blind, phase 2b trial performed in Argentina, Brazil, Colombia, and Spain. We included participants aged 18 years and older diagnosed with Chagas disease with two different serological tests and detectable T cruzi DNA by qPCR in blood. Previously treated people, pregnant women, and people with severe cardiac forms were excluded. Participants were randomly assigned 1:1:1, using a balanced block randomisation scheme stratified by country, to receive benznidazole at three different doses: 300 mg/day for 60 days (control group), 150 mg/day for 60 days (low dose group), or 400 mg/day for 15 days (short treatment group). The primary outcome was the proportion of patients with a sustained parasitological negativity by qPCR during a follow-up period of 12 months. The primary safety outcome was the proportion of people who permanently discontinued the treatment. Both primary efficacy analysis and primary safety analysis were done in the intention-to-treat population. The trial is registered with EudraCT, 2016-003789-21, and ClinicalTrials.gov, NCT03191162, and is completed.

FINDINGS

From April 20, 2017, to Sept 20, 2020, 245 people were enrolled, and 234 were randomly assigned: 78 to the control group, 77 to the low dose group, and 79 to the short treatment group. Sustained parasitological negativity was observed in 42 (54%) of 78 participants in the control group, 47 (61%) of 77 in the low dose group, and 46 (58%) of 79 in the short treatment group. Odds ratios were 1·41 (95% CI 0·69-2·88; p=0·34) when comparing the low dose and control groups and 1·23 (0·61-2·50; p=0·55) when comparing short treatment and control groups. 177 participants (76%) had an adverse event: 62 (79%) in the control group, 56 (73%) in the low dose group, and 59 (77%) in the short treatment group. However, discontinuations were less frequent in the short treatment group compared with the control group (2 [2%] vs 11 [14%]; OR 0·20, 95% CI 0·04-0·95; p=0·044).

INTERPRETATION

Participants had a similar parasitological responses. However, reducing the usual treatment from 8 weeks to 2 weeks might maintain the same response while facilitating adherence and increasing treatment coverage. These findings should be confirmed in a phase 3 clinical trial.

FUNDING

European Community's 7th Framework Programme.

Outcomes of latent rheumatic heart disease: External validation of a simplified score in patients with and without secondary prophylaxis

BACKGROUND

Secondary antibiotic prophylaxis reduces progression of latent rheumatic heart disease (RHD) but not all children benefit. Improved risk stratification could refine recommendations following positive screening. We aimed to evaluate the performance of a previously developed echocardiographic risk score to predict mid-term outcomes among children with latent RHD.

METHODS

We included children who completed the GOAL, a randomized trial of secondary antibiotic prophylaxis among children with latent RHD in Uganda. Outcomes were determined by a 4-member adjudication panel. We applied the point-based score, consisting of 5 variables (mitral valve (MV) anterior leaflet thickening (3 points), MV excessive leaflet tip motion (3 points), MV regurgitation jet length ≥ 2 cm (6 points), aortic valve focal thickening (4 points) and any aortic regurgitation (5 points)), to panel results. Unfavorable outcome was defined as progression of diagnostic category (borderline to definite, mild definite to moderate/severe definite), worsening valve involvement or remaining with mild definite RHD.

RESULTS

799 patients (625 borderline and 174 definite RHD) were included, with median follow-up of 24 months. At total 116 patients (14.5%) had unfavorable outcome per study criteria, 57.8% not under prophylaxis. The score was strongly associated with unfavorable outcome (HR = 1.26, 95% CI 1.16-1.37, p < 0.001). Unfavorable outcome rates in low (≤6 points), intermediate (7-9 points) and high-risk (≥10 points) children at follow-up were 11.8%, 30.4%, and 42.2%, (p < 0.001) respectively (C-statistic = 0.64 (95% CI 0.59-0.69)).

CONCLUSIONS

The simple risk score provided an accurate prediction of RHD status at 2-years, showing a good performance in a population with milder RHD phenotypes.

Agreement between Handheld and Standard Echocardiography for Diagnosis of Latent Rheumatic Heart Disease in Brazilian Schoolchildren from High-Prevalence Settings (Agreement between Screening and Standard Echo for RHD)

Introduction: Handheld echocardiography (echo) is the tool of choice for rheumatic heart disease (RHD) screening. We aimed to assess the agreement between screening and standard echo for latent RHD diagnosis in schoolchildren from an endemic setting. Methods: Over 14 months, 3 nonphysicians used handheld machines and the 2012 WHF Criteria to determine RHD prevalence in consented schoolchildren from Brazilian low-income public schools. Studies were interpreted by telemedicine by 3 experts (Brazil, US). RHD-positive children (borderline/definite) and those with congenital heart disease (CHD) were referred for standard echo, acquired and interpreted by a cardiologist. Agreement between screening and standard echo, by WHF subgroups, was assessed. Results: 1390 students were screened in 6 schools, with 110 (7.9%, 95% CI 6.5-9.5) being screen positive (14 ± 2 years, 72% women). Among 16 cases initially diagnosed as definite RHD, 11 (69%) were confirmed, 4 (25%) reclassified to borderline, and 1 to normal. Among 79 cases flagged as borderline RHD, 19 (24%) were confirmed, 50 (63%) reclassified to normal, 8 (10%) reclassified as definite RHD, and 2 had mild CHD. Considering the 4 diagnostic categories, kappa was 0.18. In patients with borderline RHD reclassified to non-RHD, the most frequent WHF criterion was B (isolated mitral regurgitation, 64%), followed by A (2 mitral valve morphological features, 31%). In 1 patient with definite RHD reclassified to normal, the WHF criterion was D (borderline RHD in aortic and mitral valves). After standard echo, RHD prevalence was 3.2% (95% CI 2.3-4.2). Conclusions: Although practical, RHD screening with handheld devices tends to overestimate prevalence.

Spatial association of homicide rate with violence, sociodemographic, and public security factors: global burden of disease study 2018 for municipalities in Brazil

OBJECTIVES

To analyse spatial-temporal changes and spatial association of homicide rates with violence, sociodemographic, public security and human rights indicators in Brazilian municipalities.

STUDY DESIGN

An ecological study using homicide estimates from the Global Burden of Disease and population from the Brazilian Ministry of Health, 2000 to 2018. The explanatory variables come from the systems of mortality, notifications of violence and security, and the Brazilian Institute of Geography and Statistics.

METHODS

Moran indices and maps identified clusters of high and low risk for homicides in three trienniums (p < 0.05). Multivariate linear and spatial regressions estimated explanatory factors' contributions for the last triennium.

RESULTS

Municipalities with high rates of homicides (>34/100,000) doubled, reaching 21.5 %. Those rates were concentrated in big cities, and increased in smaller municipalities. Increases in critical areas were found in the Northeast and North regions: more than 40 % in the states of Sergipe, Bahia, Ceará, Rio Grande do Norte and Roraima. Decreases occurred in the Southeast and Midwest regions: more than 35 % in São Paulo and Rio de Janeiro states. The spatial model, with an 18.9 % higher R2 (0.706), showed a positive association for records of violence, Blacks, low-level education, municipalities >50,000 inhabitants and municipalities with homicide and municipal police.

CONCLUSIONS

An increase in and the interiorisation of homicide risk areas in Brazil was observed, with displacement among regions (from the Southeast to the North/Northeast). The level of violence was the main explanatory factor for homicides. Territorial space proved to be important to understand and prevent lethal crime.

Mortality by avoidable causes in Brazil from 1990 to 2019: data from the Global Burden of Disease Study

OBJECTIVES

The aim of this study was to analyse the trends of avoidable mortality in Brazil from 1990 to 2019 and its correlation with sociodemographic indexes (SDIs).

STUDY DESIGN

Epidemiological mortality trends.

METHODS

This study analysed data from the Global Burden of Disease database. The list of causes of avoidable death, as proposed by Nolte and McKee, was applied and included 32 causes. The current study used age-standardised mortality rates and the rates of change, in addition to a correlation analysis between avoidable death and the SDI.

RESULTS

Mortality rates decreased from 343.90/100,000 inhabitants in 1990 to 155.80/100,000 inhabitants in 2019. Infectious diseases showed the largest decline in mortality rates, but notable decreases were also found for diarrhoeal diseases (-94.9%), maternal conditions (-66.5%) and neonatal conditions (-60.5%). Mortality rates for non-communicable diseases (NCDs) also decreased (-48%) but maintained a similar absolute number of deaths in 2019 compared with 1990. Decreased mortality rates were also found for ischaemic heart disease (-49.1%), stroke (-61.4%) and deaths due to adverse effects caused by medical treatments (-26.2%). Avoidable mortality rates declined in all of the 27 Brazilian states, and a high correlation was found between deaths and SDI (R = -0.74; P < 0.000001).

CONCLUSIONS

A reduction in avoidable deaths was found throughout Brazil over the study period, although major regional inequalities were revealed. Richer states presented the best overall reduction in mortality rates. The biggest decreases in mortality were seen in maternal and paediatric infectious diseases in the poorest states due to the expansion of the Primary Health System and improvements in sanitation. Today, NCDs predominate and efforts should be made to formulate public policies for the prevention and control of NCDs.

Chagas disease deaths detected among garbage codes registered in mortality statistics in Brazil: a study from the buRden of ChAgas dISEase in the contemporary world (RAISE) project

OBJECTIVES

The objective of this study was to identify Brazil's most critical garbage codes (GCs) reclassified to Chagas disease (ChD) in mortality data and their proportions. We also estimated the potential impact of misclassification on the number of deaths attributed to ChD.

STUDY DESIGN

Population-based descriptive study.

METHODS

We used the Mortality Information System (SIM; in Portuguese) data before and after routine GC investigation in 2015-2019 to evaluate ChD deaths detected among them. We identified priority GCs, which contributed more than 0.1 % to the percentage of total ChD deaths registered. Spearman's correlation was used to evaluate the association between the reclassification of priority GCs and ChD prevalence. Then, we applied the GC correction factors to estimate the number of deaths attributed to ChD.

RESULTS

22,154 deaths were reported as ChD in the study period. Among them, 1004 deaths originally listed as priority GCs were deaths reclassified to ChD after an investigation in the SIM final database. Unspecific cardiomyopathy (10.2 %), unspecific heart diseases (4.7 %), and heart failure (2.8 %) were GCs with the highest proportions of reclassification to ChD in Brazil. Higher ChD prevalence at the state level was associated with a higher proportion of GC deaths reclassified as ChD. When applying correction factors identified after investigation, we estimated an increase of 26.4 % in registered ChD deaths, mostly in states with higher endemicity.

CONCLUSIONS

GCs might conceal deaths due to ChD, particularly in Brazil's states with higher endemicity. The approach suggested in this study may offer an alternative method for estimating ChD-related deaths in endemic countries.

Gastrointestinal Manifestations of Chagas Disease: A Systematic Review with Meta-Analysis

The aims of this study were to estimate the prevalence of gastrointestinal manifestations among individuals with positive serology for Chagas disease (ChD) and to describe the clinical gastrointestinal manifestations of the disease. A systematic review with meta-analysis was conducted based on the criteria and recommendations of the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. The PubMed, Scopus, Virtual Health Library, Web of Science, and Embase databases were used to search for evidence. Two reviewers independently selected eligible articles and extracted data. RStudio® software was used for the meta-analysis. For subgroup analysis, the studies were divided according to the origin of the individuals included: 1) individuals from health units were included in the health care service prevalence analysis, and 2) individuals from the general population were included in the population prevalence analysis. A total of 2,570 articles were identified, but after removal of duplicates and application of inclusion criteria, 24 articles were included and 21 were part of the meta-analysis. Most of the studies were conducted in Brazil. Radiological diagnosis was the most frequent method used to identify the gastrointestinal clinical form. The combined effect of meta-analysis studies showed a prevalence of gastrointestinal manifestations in individuals with ChD of 12% (95% CI, 8.0-17.0%). In subgroup analysis, the prevalence for studies involving health care services was 16% (95% CI, 11.0-23.0%), while the prevalence for population-based studies was 9% (95% CI, 5.0-15.0%). Megaesophagus and megacolon were the main forms of ChD presentation in the gastrointestinal form. The prevalence of gastrointestinal manifestations of ChD was 12%. Knowing the prevalence of ChD in its gastrointestinal form is an important step in planning health actions for these patients.

Adherence to the Dietary Approaches to Stop Hypertension (DASH) and Serum Urate Concentrations: A Longitudinal Analysis from the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil)

BACKGROUND

Increased serum urate (SU) and hyperuricemia (HU) are associated with chronic noncommunicable diseases and mortality. SU concentrations are affected by several factors, including diet, and are expected to rise with age. We investigated whether the Dietary Approaches to Stop Hypertension (DASH) diet alter this trend.

OBJECTIVE

The objective was to assess whether adherence to the DASH diet predicts a longitudinal change in SU concentrations and risk of HU in 8 y of follow-up.

METHODS

Longitudinal analyses using baseline (2008-2010, aged 35-74 y), second (2012-2014), and third (2016-2018) visits data from the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). The inclusion criteria were having complete food frequency questionnaire (FFQ) and urinary sodium measurement, in addition to having SU measurement at the 1st visit and at least 1 of the 2 follow-up visits. For the HU incidence analyses, participants had also to be free from HU at baseline. The final samples included 12575 individuals for the SU change analyses and 10549 for the HU incidence analyses. Adherence to DASH diet was assessed as continuous value. HU was defined as SU>6.8 mg/dL and/or urate-lowering therapy use. Mixed-effect linear and Poisson regressions (incidence rate ratio [IRR] and 95% confidence interval [CI]) were used in the analyses, adjusted for confounders.

RESULTS

The mean age was 51.4 (8.7) y, and 55.4% were females. SU means (standard deviation) were 5.4 (1.4) at 1st visit, 5.2 (1.4) at 2nd visit, and 5.1(1.3) mg/dL at 3rd visit. The HU incidence rate was 8.87 per 1000 person-y. Each additional point in adherence to the DASH diet accelerated SU decline (P< 0.01) and lowered the incidence of HU by 4.3% (IRR: 0.957; 95% CI: 0.938,0.977) in adjusted model.

CONCLUSION

The present study findings reinforce the importance of encouraging the DASH diet as a healthy dietary pattern to control and reduce the SU concentrations and risk of HU.

Vagal dysautonomia in patients with Chagas disease and mortality: 14-year results of a population cohort of the elderly

INTRODUCTION

Great part of Chagas disease (ChD) mortality occurs due to ventricular arrhythmias, and autonomic function (AF) may predict unfavorable outcomes. We aimed to evaluate the predictive value of AF indexes in ChD patients.

METHODS

The Bambuí Study of Aging is a prospective cohort of residents ≥60 years at study onset (1997), in the southeastern Brazilian city of Bambuí (15,000 inhabitants). Consented participants underwent annual follow-up visits, and death certificates were tracked. AF was assessed by the maximum expiration on minimum inspiration (E:I) ratio during ECG acquisition and by heart rate variability indices: SDRR (standard deviation of adjacent RR intervals) and RMSSD (square root of the mean of the sum of squares of the differences between adjacent RR intervals)), calculated using a computer algorithm. Cox proportional hazards regression was performed to access the prognostic value of AF indexes, expressed as terciles, for all-cause mortality, after adjustment for demographic, clinical and ECG variables.

RESULTS

From 1742 qualifying residents, 1000 had valid AF tests, being 321 with ChD. Among these, median age was 68 (64-74) years, and 32.5% were men. In Cox survival analyses, only SDRR was associated with all-cause mortality in non-adjusted models: SDRR (hazard ratio (HR): 1.26 (95% CI 1.08-1.47), p < 0.001), E:I ratio (HR: 1.13 (95% CI 0,98-1.31), p = 0.10) and RMSSD (HR: 0.99 (0.86-1.16), p = 0.95). After adjustment for sex and age, none of the indexes remained as independent predictors.

CONCLUSION

Among elderly patients with ChD, AF indexes available in this cohort were not independent predictors of 14-year mortality.

Percentiles of predicted 10-year cardiovascular disease risk by sex and age in Brazil and their association with estimated risk of long-term atherosclerotic events

OBJECTIVE

Expressing the cardiovascular disease (CVD) risk in relation to peers may complement the estimation of absolute CVD risk. We aimed to determine 10-year CVD risk percentiles by sex and age in the Brazilian population and evaluate their association with estimated long-term atherosclerotic CVD (ASCVD) risk.

METHODS

A cross-sectional analysis of baseline data from the ELSA-Brasil study was conducted in individuals aged 40-74 years without prior ASCVD. Ten-year CVD risk and long-term ASCVD risk were estimated by the WHO risk score and the Multinational Cardiovascular Risk Consortium tool, respectively. Ten-year risk percentiles were determined by ranking the calculated risks within each sex and age group.

RESULTS

Ten-year CVD risk versus percentile plots were constructed for each sex and age group using data from 13,364 participants (55% females; median age, 52 [IQR, 46-59] years). Long-term ASCVD risk was calculated in 12,973 (97.1%) participants. Compared to individuals at the <25th risk percentile, those at the ≥75th percentile had a greater risk of being in the highest quartile of long-term risk (ORs [95% CIs] 6.57 [5.18-8.30] in females and 11.59 [8.42-15.96] in males) in regression models adjusted for age, race, education, and 10-year CVD risk. In both sexes, the association between risk percentile and long-term risk weakened after age 50. A tool for calculating 10-year CVD risk and the corresponding percentile is available at https://bit.ly/3CzPUi6.

CONCLUSIONS

We established percentiles of predicted 10-year CVD risk by sex and age in the Brazilian population, which independently reflect the estimated long-term ASCVD risk in younger individuals.

ISE/ISHNE Expert Consensus Statement on ECG Diagnosis of Left Ventricular Hypertrophy: The Change of the Paradigm. The joint paper of the International Society of Electrocardiology and the International Society for Holter Monitoring and Noninvasive Electrocardiology

The ECG diagnosis of LVH is predominantly based on the QRS voltage criteria, i.e. the increased QRS complex amplitude in defined leads. The classical ECG diagnostic paradigm postulates that the increased left ventricular mass generates a stronger electrical field, increasing the leftward and posterior QRS forces. These increased forces are reflected in the augmented QRS amplitude in the corresponding leads. However, the clinical observations document increased QRS amplitude only in the minority of patients with LVH. The low sensitivity of voltage criteria has been repeatedly documented. We discuss possible reasons for this shortcoming and proposal of a new paradigm.

End-to-end risk prediction of atrial fibrillation from the 12-Lead ECG by deep neural networks

BACKGROUND

Atrial fibrillation (AF) is one of the most common cardiac arrhythmias that affects millions of people each year worldwide and it is closely linked to increased risk of cardiovas- cular diseases such as stroke and heart failure. Machine learning methods have shown promising results in evaluating the risk of developing atrial fibrillation from the electrocardiogram. We aim to develop and evaluate one such algorithm on a large CODE dataset collected in Brazil.

METHODS

We used the CODE cohort to develop and test a model for AF risk prediction for individual patients from the raw ECG recordings without the use of additional digital biomarkers. The cohort is a collection of ECG recordings and annotations by the Telehealth Network of Minas Gerais, in Brazil. A convolutional neural network based on a residual network architecture was implemented to produce class probabilities for the classification of AF. The probabilities were used to develop a Cox proportional hazards model and a Kaplan-Meier model to carry out survival analysis. Hence, our model is able to perform risk prediction for the development of AF in patients without the condition.

RESULTS

The deep neural network model identified patients without indication of AF in the presented ECG but who will develop AF in the future with an AUC score of 0.845. From our survival model, we obtain that patients in the high-risk group (i.e. with the probability of a future AF case being >0.7) are 50% more likely to develop AF within 40 weeks, while patients belonging to the minimal-risk group (i.e. with the probability of a future AF case being less than or equal to 0.1) have >85% chance of remaining AF free up until after seven years.

CONCLUSION

We developed and validated a model for AF risk prediction. If applied in clinical practice, the model possesses the potential of providing valuable and useful information in decision- making and patient management processes.

Heart age gap estimated by explainable advanced electrocardiography is associated with cardiovascular risk factors and survival

Aims

Deep neural network artificial intelligence (DNN-AI)-based Heart Age estimations have been presented and used to show that the difference between an electrocardiogram (ECG)-estimated Heart Age and chronological age is associated with prognosis. An accurate ECG Heart Age, without DNNs, has been developed using explainable advanced ECG (A-ECG) methods. We aimed to evaluate the prognostic value of the explainable A-ECG Heart Age and compare its performance to a DNN-AI Heart Age.

Methods and results

Both A-ECG and DNN-AI Heart Age were applied to patients who had undergone clinical cardiovascular magnetic resonance imaging. The association between A-ECG or DNN-AI Heart Age Gap and cardiovascular risk factors was evaluated using logistic regression. The association between Heart Age Gaps and death or heart failure (HF) hospitalization was evaluated using Cox regression adjusted for clinical covariates/comorbidities. Among patients [n = 731, 103 (14.1%) deaths, 52 (7.1%) HF hospitalizations, median (interquartile range) follow-up 5.7 (4.7-6.7) years], A-ECG Heart Age Gap was associated with risk factors and outcomes [unadjusted hazard ratio (HR) (95% confidence interval) (5 year increments): 1.23 (1.13-1.34) and adjusted HR 1.11 (1.01-1.22)]. DNN-AI Heart Age Gap was associated with risk factors and outcomes after adjustments [HR (5 year increments): 1.11 (1.01-1.21)], but not in unadjusted analyses [HR 1.00 (0.93-1.08)], making it less easily applicable in clinical practice.

Conclusion

A-ECG Heart Age Gap is associated with cardiovascular risk factors and HF hospitalization or death. Explainable A-ECG Heart Age Gap has the potential for improving clinical adoption and prognostic performance compared with existing DNN-AI-type methods.

Cardiovascular mortality in Brazil during the COVID-19 pandemic: a comparison between underlying and multiple causes of death

OBJECTIVES

The COVID-19 pandemic has differentially impacted cardiovascular disease (CVD) mortality worldwide. Causes of death misclassification may be one of the reasons. We evaluated the impact of the pandemic on CVD mortality in Brazil, comparing underlying causes (UCs) and multiple causes (MCs) of death.

STUDY DESIGN

Ecological time-series study.

METHODS

An ecological, time-series study was conducted analysing age-standardised death rates for CVD, from epidemiological week (EW) 10/2020 to 39/2021, using data from the Mortality Information System, Brazil. CVD was defined using the International Classification of Diseases (ICD-10) coding, if reported as UC or MC of death. Observed and expected data (mean for the same EW, 2017-2019) were compared. Risk ratios (RiRs) were analysed, and 95% confidence intervals (CIs) were calculated.

RESULTS

Age-standardised mortality rate for CVD as UC of death was 165.8 (95%CI: 165.4-166.3) per 100,000 inhabitants, similar to what was expected (165.6/100,000, 95%CI: 165.2-166.1, RiR = 1.00). There was increased out-of-hospital mortality (RiR = 1.18; 95%CI: 1.17-1.19) and deaths of ill-defined causes (RiR = 1.43; 95%CI: 1.42-1.44). The increase in out-of-hospital deaths was more pronounced in the North (RiR = 1.33; 95%CI 1.30-1.36) region, with a less resilient health system. Conversely, as MCs of death, there was a 10% increase in CVD mortality (observed: 243.2 [95%CI: 242.7-243.7], expected: 221.6 [95%CI: 221.1-222.1] per 100,000). An increase also occurred in the North and Central West regions (RiR = 1.16; 95%CI: 1.15-1.18), among men (RiR = 1.11; 95%CI: 1.11-1.12) and individuals aged ≥60 years (RiR = 1.11; 95%CI: 1.10-1.11).

CONCLUSIONS

During the pandemic, mortality rates for CVD as MCs of death increased in Brazil, whereas as UC mortality rates did not change. Higher out-of-hospital mortality, misclassification, and competing causes of death may explain this pattern.

Genetic architecture of spatial electrical biomarkers for cardiac arrhythmia and relationship with cardiovascular disease

The 3-dimensional spatial and 2-dimensional frontal QRS-T angles are measures derived from the vectorcardiogram. They are independent risk predictors for arrhythmia, but the underlying biology is unknown. Using multi-ancestry genome-wide association studies we identify 61 (58 previously unreported) loci for the spatial QRS-T angle (N = 118,780) and 11 for the frontal QRS-T angle (N = 159,715). Seven out of the 61 spatial QRS-T angle loci have not been reported for other electrocardiographic measures. Enrichments are observed in pathways related to cardiac and vascular development, muscle contraction, and hypertrophy. Pairwise genome-wide association studies with classical ECG traits identify shared genetic influences with PR interval and QRS duration. Phenome-wide scanning indicate associations with atrial fibrillation, atrioventricular block and arterial embolism and genetically determined QRS-T angle measures are associated with fascicular and bundle branch block (and also atrioventricular block for the frontal QRS-T angle). We identify potential biology involved in the QRS-T angle and their genetic relationships with cardiovascular traits and diseases, may inform future research and risk prediction.

What We Lost in the Fire: Endemic Tropical Heart Diseases in the Time of COVID-19

The COVID-19 pandemic has profoundly influenced the effort to achieve global health equity. This has been particularly the case for HIV/AIDS, tuberculosis, and malaria control initiatives in low- and middle-income countries, with significant outcome setbacks seen for the first time in decades. Lost in the calls for compensatory funding increases for such programs, however, is the plight of endemic tropical heart diseases, a group of disorders that includes rheumatic heart disease, Chagas disease, and endomyocardial fibrosis. Such endemic illnesses affect millions of people around the globe and remain a source of substantial mortality, morbidity, and health disparity. Unfortunately, these conditions were already neglected before the pandemic, and thus those living with them have disproportionately suffered during the time of COVID-19. In this perspective, we briefly define endemic tropical heart diseases, summarizing their prepandemic epidemiology, funding, and control statuses. We then describe the ways in which people living with these disorders, along with the healthcare providers and researchers working to improve their outcomes, have been harmed by the ongoing COVID-19 pandemic. We conclude by proposing the path forward, including approaches we may use to leverage lessons learned from the pandemic to strengthen care systems for these neglected diseases.

Impact of a large-scale telemedicine network on emergency visits and hospital admissions during the coronavirus disease 2019 pandemic in Brazil: Data from the UNIMED-BH system

INTRODUCTION

Triage by on-demand telemedicine is a strategy for healthcare surge control in the COVID-19 pandemic. We aimed to assess the impact of a large-scale COVID-19 telemedicine system on emergency department (ED) visits and all-cause and cardiovascular hospital admissions in Brazil.

METHODS

From March 18, 2020-May 18, 2020 we evaluated the database of a cooperative private health insurance, with 1.28 million clients. The COVID-19 telemedicine system consisted of: a) mobile app, which redirects to teleconsultations if indicated; b) telemonitoring system, with regular phone calls to suspected/confirmed COVID-19 cases to monitor progression; c) emergency ambulance system (EAS), with internet phone triage and counselling. ED visits and hospital admissions were recorded, with diagnoses assessed by the Diagnosis Related Groups method. COVID-19 diagnosis and deaths were identified from the patients' registries, and outcomes assessed until June 1st.

RESULTS

In 60 days, 24,354 patients accessed one of the telemedicine systems. The most frequently utilized was telemonitoring (16,717, 69%), followed by teleconsultation (13,357, 55%) and EAS (687, 3%). The rates of ED and hospital admissions were: telemonitoring 19.7% (3,296) and 4.7% (782); teleconsultation 17.3% (2,313) and 2.4% (318) and EAS: 55.9% (384) and 56.5% (388) patients. At total 4.1% (1,010) had hospital admissions, 36% (363) with respiratory diseases (44 requiring mechanical ventilation) and 4.4% (44) with cardiovascular diagnoses. Overall, 277 (1.1%) patients had confirmed COVID-19 diagnosis, and 160 (0.7%) died, 9 with COVID-19.

CONCLUSION

Telemedicine resulted in low rates of ED visits and hospital admissions, suggesting positive impacts on healthcare utilization. Cardiovascular admissions were remarkably rare.

Reasons for disagreement between screening and standard echocardiography in primary care: data from the PROVAR + study : Disagreement between screening and standard echo

We aimed to evaluate the reasons for disagreement between screening echocardiography (echo), acquired by nonexperts, and standard echo in the Brazilian primary care (PC). Over 20 months, 22 PC workers were trained on simplified handheld (GE VSCAN) echo protocols. Screening groups, consisting of patients aged 17-20, 35-40 and 60-65 years, and patients referred for clinical indications underwent focused echo. Studies were remotelyinterpreted in US and Brazil, and those diagnosed with major or severe HD were referred for standard echoperformed by an expert. Major HD was defined as moderate to severe valve disease, ventriculardysfunction/hypertrophy, pericardial effusion or wall-motion abnormalities. A random sample of exams wasselected for evaluation of variables accounting for disagreement. A sample of 768 patients was analyzed, 651(85%) in the referred group. Quality issues were reported in 5.8%, and the random Kappa for major HD between screening and standard echo was 0.51. The most frequent reasons for disagreement were: overestimation of mitral regurgitation (MR) (17.9%, N=138), left ventricular (LV) dysfunction (15.7%, N=121), aortic regurgitation (AR) (15.2%, N=117), LV hypertrophy (13.5%, N=104) and tricuspid regurgitation (12.7%, N=98). Misdiagnosis of mitral and aortic morphological abnormalities was observed in 12.4% and 3.0%, and underestimation of AR and MR occurred in 4.6% and 11.1%. Among 257 patients with suspected mild/moderate MR, 129 were reclassified to normal. In conclusion, although screening echo with task-shifting in PC is a promising tool in low-income areas, estimation of valve regurgitation and LV function and size account for considerable disagreement with standard exams.

Clinical and electrocardiographic outcomes evaluated by telemedicine of outpatients with clinical suspicion of COVID-19 treated with chloroquine compounds in Brazil†

Aims

To evaluate clinical and electrocardiographic outcomes of patients with COVID-19, comparing those using chloroquine compounds (chloroquine) to individuals without specific treatment.

Methods

Outpatients with suspected COVID-19 in Brazil who had at least one tele-electrocardiography (ECG) recorded in a telehealth system were enrolled in two arms (Group 1: chloroquine and Group 2: without specific treatment) and one registry (Group 3: other treatments). Outcomes were assessed through follow-up calls (phone contact, days 3 and 14) and linkage to national mortality and hospitalization databases. The primary outcome was composed of: hospitalization, intensive care admission, mechanical ventilation, and all-cause death, and the ECG outcome was the occurrence of major abnormalities by the Minnesota code. Significant variables in univariable logistic regression were included in 4 models: 1-unadjusted; 2-adjusted for age and sex; 3-model 2 + cardiovascular risk factors and 4-model 3 + COVID-19 symptoms.

Results

In 303 days, 712 (10.2%) patients were allocated in group 1, 3,623 (52.1%) in group 2 and 2,622 (37.7%) in group 3; 1,969 had successful phone follow-up (G1: 260, G2: 871, and G3: 838). A late follow-up ECG was obtained for 917 (27.2%) patients [group 1: 81 (11.4%), group 2: 512 (14.1%), group 3: 334 (12.7%)]. In adjusted models, chloroquine was independently associated with greater chance of the composite clinical outcome: phone contact (model 4): OR = 3.24 (95% CI 2.31-4.54), p < 0.001. Chloroquine was also independently associated with higher mortality, assessed by phone + administrative data (model 3): OR = 1.67 (95% CI 1.20-2.28). However, chloroquine did not associate with the occurrence of major ECG abnormalities [model 3; OR = 0.80 (95% CI 0.63-1.02, p = 0.07)]. Abstracts with partial results of this work was accepted in the American Heart Association Scientific Sessions, November 2022, in Chicago, IL, USA.

Conclusion

Chloroquine was associated with a higher risk of poor outcomes in patients suspected to have COVID-19 when compared to those who received standard care. Follow-up ECGs were obtained in only 13.2% of patients and did not show any significant differences in major abnormalities amongst the three groups. In the absence of early ECG changes, other side effects, late arrhythmias or deferral of care may be hypothesized to explain the worse outcomes.

On Merging Feature Engineering and Deep Learning for Diagnosis, Risk Prediction and Age Estimation Based on the 12-Lead ECG

OBJECTIVE

Over the past few years, deep learning (DL) has been used extensively in research for 12-lead electrocardiogram (ECG) analysis. However, it is unclear whether the explicit or implicit claims made on DL superiority to the more classical feature engineering (FE) approaches, based on domain knowledge, hold. In addition, it remains unclear whether combining DL with FE may improve performance over a single modality.

METHODS

To address these research gaps and in-line with recent major experiments, we revisited three tasks: cardiac arrhythmia diagnosis (multiclass-multilabel classification), atrial fibrillation risk prediction (binary classification), and age estimation (regression). We used an overall dataset of 2.3M 12-lead ECG recordings to train the following models for each task: i) a random forest taking FE as input; ii) an end-to-end DL model; and iii) a merged model of FE+DL.

RESULTS

FE yielded comparable results to DL while necessitating significantly less data for the two classification tasks. DL outperformed FE for the regression task. For all tasks, merging FE with DL did not improve performance over DL alone. These findings were confirmed on the additional PTB-XL dataset.

CONCLUSION

We found that for traditional 12-lead ECG based diagnosis tasks, DL did not yield a meaningful improvement over FE, while it improved significantly the nontraditional regression task. We also found that combining FE with DL did not improve over DL alone, which suggests that the FE were redundant with the features learned by DL.

SIGNIFICANCE

Our findings provides important recommendations on 12-lead ECG based machine learning strategy and data regime to choose for a given task. When looking at maximizing performance as the end goal, if the task is nontraditional and a large dataset is available then DL is preferable. If the task is a classical one and/or a small dataset is available then a FE approach may be the better choice.

Deaths Related to Chagas Disease and COVID-19 Co-Infection, Brazil, March–December 2020

We analyzed epidemiologic characteristics and distribution of 492 deaths related to Chagas disease and coronavirus disease (COVID-19) co-infection in Brazil during March‒December 2020. Cumulative co-infected death rates were highest among advanced age groups, persons of Afro-Brazilian ethnicity and with low education levels, and geographically distributed mainly in major Chagas disease‒endemic areas.

Estimated Global Proportions of Individuals With Persistent Fatigue, Cognitive, and Respiratory Symptom Clusters Following Symptomatic COVID-19 in 2020 and 2021

Importance

Some individuals experience persistent symptoms after initial symptomatic SARS-CoV-2 infection (often referred to as Long COVID).

Objective

To estimate the proportion of males and females with COVID-19, younger or older than 20 years of age, who had Long COVID symptoms in 2020 and 2021 and their Long COVID symptom duration.

Design, Setting, and Participants

Bayesian meta-regression and pooling of 54 studies and 2 medical record databases with data for 1.2 million individuals (from 22 countries) who had symptomatic SARS-CoV-2 infection. Of the 54 studies, 44 were published and 10 were collaborating cohorts (conducted in Austria, the Faroe Islands, Germany, Iran, Italy, the Netherlands, Russia, Sweden, Switzerland, and the US). The participant data were derived from the 44 published studies (10 501 hospitalized individuals and 42 891 nonhospitalized individuals), the 10 collaborating cohort studies (10 526 and 1906), and the 2 US electronic medical record databases (250 928 and 846 046). Data collection spanned March 2020 to January 2022.

Exposures

Symptomatic SARS-CoV-2 infection.

Main Outcomes and Measures

Proportion of individuals with at least 1 of the 3 self-reported Long COVID symptom clusters (persistent fatigue with bodily pain or mood swings; cognitive problems; or ongoing respiratory problems) 3 months after SARS-CoV-2 infection in 2020 and 2021, estimated separately for hospitalized and nonhospitalized individuals aged 20 years or older by sex and for both sexes of nonhospitalized individuals younger than 20 years of age.

Results

A total of 1.2 million individuals who had symptomatic SARS-CoV-2 infection were included (mean age, 4-66 years; males, 26%-88%). In the modeled estimates, 6.2% (95% uncertainty interval [UI], 2.4%-13.3%) of individuals who had symptomatic SARS-CoV-2 infection experienced at least 1 of the 3 Long COVID symptom clusters in 2020 and 2021, including 3.2% (95% UI, 0.6%-10.0%) for persistent fatigue with bodily pain or mood swings, 3.7% (95% UI, 0.9%-9.6%) for ongoing respiratory problems, and 2.2% (95% UI, 0.3%-7.6%) for cognitive problems after adjusting for health status before COVID-19, comprising an estimated 51.0% (95% UI, 16.9%-92.4%), 60.4% (95% UI, 18.9%-89.1%), and 35.4% (95% UI, 9.4%-75.1%), respectively, of Long COVID cases. The Long COVID symptom clusters were more common in women aged 20 years or older (10.6% [95% UI, 4.3%-22.2%]) 3 months after symptomatic SARS-CoV-2 infection than in men aged 20 years or older (5.4% [95% UI, 2.2%-11.7%]). Both sexes younger than 20 years of age were estimated to be affected in 2.8% (95% UI, 0.9%-7.0%) of symptomatic SARS-CoV-2 infections. The estimated mean Long COVID symptom cluster duration was 9.0 months (95% UI, 7.0-12.0 months) among hospitalized individuals and 4.0 months (95% UI, 3.6-4.6 months) among nonhospitalized individuals. Among individuals with Long COVID symptoms 3 months after symptomatic SARS-CoV-2 infection, an estimated 15.1% (95% UI, 10.3%-21.1%) continued to experience symptoms at 12 months.

Conclusions and Relevance

This study presents modeled estimates of the proportion of individuals with at least 1 of 3 self-reported Long COVID symptom clusters (persistent fatigue with bodily pain or mood swings; cognitive problems; or ongoing respiratory problems) 3 months after symptomatic SARS-CoV-2 infection.

ECG abnormalities and their relation to COVID-19 outcomes – a WHF study

Introduction

COVID-19 is a respiratory tract infection caused by the Coronavirus (SARS-CoV-2) and its main clinical manifestations are respiratory. The cardiovascular system can also be affected, especially in patients with severe acute respiratory syndrome [1].

On the other hand, cardiovascular disease (CVD) and risk factors have been shown to be predictors of poor outcomes in COVID-19 [2]. Diverse electrocardiographic abnormalities can be found in this condition [3], although their value as a prognostic predictor have not been properly established due to heterogeneity in abnormalities evaluation and small sample sizes in related studies [4].

Purpose

The aim of the present study is to evaluate the association of electrocardiogram (ECG) findings to poor COVID-19 outcomes

Methods

This is a multicentric cohort study that followed hospitalized adults due to COVID-19, from low-middle and high-income countries as part of the World Heart Federation (WHF) Global Study on CVD and COVID-19 initiative [5]. Participants were followed up from hospital admission until 30 days post discharge. For the present study, participants with a valid ECG were included. ECG findings were described according to standardized measurements [heart rate, PR interval, QRS duration and axis, corrected QT interval (QTc)] and abnormalities (according to the Minnesota code system). Abnormalities utilized were grouped into ischemic abnormalities (q waves and ST-T abnormalities), atrial fibrillation (AF), prolonged QTc, sinus tachycardia (defined for the study as above 120 bpm), right and left bundle branch block and presence of any major abnormality. The primary outcome was defined as death from any cause. The secondary outcomes were intensive care unit (ICU) admission and cardiovascular events (myocarditis, pericarditis, myocardial infarction, acute heart failure, ischemic and hemorrhagic stroke). Multiple logistic regression was used to evaluate the association of ECG abnormalities to the outcomes of interest. Adjustments were made in a step by step fashion including gender, age, country of residence, cardiovascular risk factors (diabetes, hypertension, tobacco use) and presence of comorbidities (CVD, asthma, cancer, immunosuppression and chronic kidney disease).

Results

The clinical characteristics of the cohort are described in table 1. Figure 1 represents the odds ratio and its 95% confidence interval of having the defined outcomes when presenting a ECG abnormality for the final regression model.

Conclusion

ECG abnormalities were independently related to poor outcomes in COVID-19 after accounting for multiple confounders. Significant associations were more frequently found for ischemic abnormalities, heart rate above 120 bpm, atrial fibrillation and having at least one major electrocardiographic abnormality.

Funding Acknowledgement

Type of funding sources: Other. Main funding source(s): Pfizer and Sanofi PasteurWorld Heart Federation

Epicardial Fat Volume Is Associated with Endothelial Dysfunction, but not with Coronary Calcification: From the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil)

BACKGROUND

The increase in epicardial fat volume (EFV) is related to coronary artery disease (CAD), independent of visceral or subcutaneous fat. The mechanism underlying this association is unclear. Coronary artery calcium (CAC) score and endothelial dysfunction are related to coronary events, but whether EFV is related to these markers needs further clarification.

OBJECTIVES

To evaluate the association between automatically measured EFV, cardiovascular risk factors, CAC, and endothelial function.

METHODS

In 470 participants from the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil) with measures of EFV, CAC score and endothelial function, we performed multivariable models to evaluate the relation between cardiovascular risk factors and EFV (response variable), and between EFV (explanatory variable) and endothelial function variables or CAC score. Two-sided p <0.05 was considered statistically significant.

RESULTS

Mean age was 55 ± 8 years, 52.3% of patients were men. Mean EFV was 111mL (IQ 86-144), and the prevalence of CAC score=0 was 55%. In the multivariable analyses, increased EFV was related to female sex, older age, waist circumference, and triglycerides (p<0.001 for all). Higher EFV was associated with worse endothelial function: as compared with the first quartile, the odds ratio for basal pulse amplitude were (q2=1.22, 95%CI 1.07-1.40; q3=1.50, 95%CI 1.30-1.74; q4=1.50, 95%CI 1.28-1.79) and for peripheral arterial tonometry ratio were (q2=0.87, 95%CI 0.81-0.95; q3=0.86, 95%CI 0.79-0.94; q4=0.80, 95%CI 0.73-0.89), but not with CAC score>0.

CONCLUSION

Higher EFV was associated with impaired endothelial function, but not with CAC. The results suggest that EFV is related to the development of CAD through a pathway different from the CAC pathway, possibly through aggravation of endothelial dysfunction and microvascular disease.

Assessment of the Impact of the Implementation of a Pre-Hospital Ambulance System on Acute Myocardial Infarction Mortality in a Developing Country

BACKGROUND

The effective management of patients with acute myocardial infarction (AMI) is time-dependent.

OBJECTIVES

To assess the impacts of the implementation of prehospital care on admission rates and mortality associated with AMI.

METHODS

Retrospective, ecological study, which assessed data from the Brazilian Universal Health System, from all 853 municipalities of Minas Gerais, from 2008 to 2016. Excessive skewness of general and in-hospital mortality rates was smoothed using the empirical Bayes method. This study assessed the relationship between Mobile Emergency Care Service (SAMU) in each municipality and the following 3 outcomes: mortality rate due to AMI, AMI in-hospital mortality, and AMI hospitalization rate, using the Poisson hierarchical model. Rates were corrected by age structure and detrended by seasonality and temporal influences. A confidence interval of 95% was adopted.

RESULTS

AMI mortality rates decreased throughout the study, on average 2% per year, with seasonal variation. AMI in-hospital mortality also showed a decreasing trend, from 13.81% in 2008 to 11.43% in 2016. SAMU implementation was associated with decreased AMI mortality (odds ratio [OR] = 0.967, 95% confidence interval [CI] 0.936 to 0.998) and AMI in-hospital mortality (OR = 0.914, 95% CI 0.845 to 0.986), with no relation with hospitalizations (OR = 1.003, 95% CI 0.927 to 1.083).

CONCLUSION

SAMU implementation was associated with a modest but significant decrease in AMI in-hospital mortality. This finding reinforces the key role of prehospital care in AMI care and the need for investments on this service to improve clinical outcomes in low- and middle-income countries.

The collateral damage of COVID-19 to cardiovascular services: a meta-analysis

AIMS

The effect of the COVID-19 pandemic on care and outcomes across non-COVID-19 cardiovascular (CV) diseases is unknown. A systematic review and meta-analysis was performed to quantify the effect and investigate for variation by CV disease, geographic region, country income classification and the time course of the pandemic.

METHODS AND RESULTS

From January 2019 to December 2021, Medline and Embase databases were searched for observational studies comparing a pandemic and pre-pandemic period with relation to CV disease hospitalisations, diagnostic and interventional procedures, outpatient consultations, and mortality. Observational data were synthesised by incidence rate ratios (IRR) and risk ratios (RR) for binary outcomes and weighted mean differences for continuous outcomes with 95% confidence intervals. The study was registered with PROSPERO (CRD42021265930). A total of 158 studies, covering 49 countries and 6 continents, were used for quantitative synthesis. Most studies (80%) reported information for high-income countries (HICs). Across all CV disease and geographies there were fewer hospitalisations, diagnostic and interventional procedures, and outpatient consultations during the pandemic. By meta-regression, in low-middle income countries (LMICs) compared to HICs the decline in ST-segment elevation myocardial infarction (STEMI) hospitalisations (RR 0.79, 95% confidence interval [CI] 0.66-0.94) and revascularisation (RR 0.73, 95% CI 0.62-0.87) was more severe. In LMICs, but not HICs, in-hospital mortality increased for STEMI (RR 1.22, 95% CI 1.10-1.37) and heart failure (RR 1.08, 95% CI 1.04-1.12). The magnitude of decline in hospitalisations for CV diseases did not differ between the first and second wave.

CONCLUSIONS

There was substantial global collateral CV damage during the COVID-19 pandemic with disparity in severity by country income classification.

Genetic analyses of the electrocardiographic QT interval and its components identify additional loci and pathways

The QT interval is an electrocardiographic measure representing the sum of ventricular depolarization and repolarization, estimated by QRS duration and JT interval, respectively. QT interval abnormalities are associated with potentially fatal ventricular arrhythmia. Using genome-wide multi-ancestry analyses (>250,000 individuals) we identify 177, 156 and 121 independent loci for QT, JT and QRS, respectively, including a male-specific X-chromosome locus. Using gene-based rare-variant methods, we identify associations with Mendelian disease genes. Enrichments are observed in established pathways for QT and JT, and previously unreported genes indicated in insulin-receptor signalling and cardiac energy metabolism. In contrast for QRS, connective tissue components and processes for cell growth and extracellular matrix interactions are significantly enriched. We demonstrate polygenic risk score associations with atrial fibrillation, conduction disease and sudden cardiac death. Prioritization of druggable genes highlight potential therapeutic targets for arrhythmia. Together, these results substantially advance our understanding of the genetic architecture of ventricular depolarization and repolarization.

A global systematic analysis of the occurrence, severity, and recovery pattern of long COVID in 2020 and 2021

Importance:

While much of the attention on the COVID-19 pandemic was directed at the daily counts of cases and those with serious disease overwhelming health services, increasingly, reports have appeared of people who experience debilitating symptoms after the initial infection. This is popularly known as long COVID.

Objective:

To estimate by country and territory of the number of patients affected by long COVID in 2020 and 2021, the severity of their symptoms and expected pattern of recovery

Design:

We jointly analyzed ten ongoing cohort studies in ten countries for the occurrence of three major symptom clusters of long COVID among representative COVID cases. The defining symptoms of the three clusters (fatigue, cognitive problems, and shortness of breath) are explicitly mentioned in the WHO clinical case definition. For incidence of long COVID, we adopted the minimum duration after infection of three months from the WHO case definition. We pooled data from the contributing studies, two large medical record databases in the United States, and findings from 44 published studies using a Bayesian meta-regression tool. We separately estimated occurrence and pattern of recovery in patients with milder acute infections and those hospitalized. We estimated the incidence and prevalence of long COVID globally and by country in 2020 and 2021 as well as the severity-weighted prevalence using disability weights from the Global Burden of Disease study.

Results:

Analyses are based on detailed information for 1906 community infections and 10526 hospitalized patients from the ten collaborating cohorts, three of which included children. We added published data on 37262 community infections and 9540 hospitalized patients as well as ICD-coded medical record data concerning 1.3 million infections. Globally, in 2020 and 2021, 144.7 million (95% uncertainty interval [UI] 54.8–312.9) people suffered from any of the three symptom clusters of long COVID. This corresponds to 3.69% (1.38–7.96) of all infections. The fatigue, respiratory, and cognitive clusters occurred in 51.0% (16.9–92.4), 60.4% (18.9–89.1), and 35.4% (9.4–75.1) of long COVID cases, respectively. Those with milder acute COVID-19 cases had a quicker estimated recovery (median duration 3.99 months [IQR 3.84–4.20]) than those admitted for the acute infection (median duration 8.84 months [IQR 8.10–9.78]). At twelve months, 15.1% (10.3–21.1) continued to experience long COVID symptoms.

Conclusions and relevance:

The occurrence of debilitating ongoing symptoms of COVID-19 is common. Knowing how many people are affected, and for how long, is important to plan for rehabilitative services and support to return to social activities, places of learning, and the workplace when symptoms start to wane.

Cardiovascular Risk Factors and Clinical Outcomes among Patients Hospitalized with COVID-19: Findings from the World Heart Federation COVID-19 Study

BACKGROUND AND AIMS

Limited data exist on the cardiovascular manifestations and risk factors in people hospitalized with COVID-19 from low- and middle-income countries. This study aims to describe cardiovascular risk factors, clinical manifestations, and outcomes among patients hospitalized with COVID-19 in low, lower-middle, upper-middle- and high-income countries (LIC, LMIC, UMIC, HIC).

METHODS

Through a prospective cohort study, data on demographics and pre-existing conditions at hospital admission, clinical outcomes at hospital discharge (death, major adverse cardiovascular events (MACE), renal failure, neurological events, and pulmonary outcomes), 30-day vital status, and re-hospitalization were collected. Descriptive analyses and multivariable log-binomial regression models, adjusted for age, sex, ethnicity/income groups, and clinical characteristics, were performed.

RESULTS

Forty hospitals from 23 countries recruited 5,313 patients with COVID-19 (LIC = 7.1%, LMIC = 47.5%, UMIC = 19.6%, HIC = 25.7%). Mean age was 57.0 (±16.1) years, male 59.4%, pre-existing conditions included: hypertension 47.3%, diabetes 32.0%, coronary heart disease 10.9%, and heart failure 5.5%. The most frequently reported cardiovascular discharge diagnoses were cardiac arrest (5.5%), acute heart failure (3.8%), and myocardial infarction (1.6%). The rate of in-hospital deaths was 12.9% (N = 683), and post-discharge 30 days deaths was 2.6% (N = 118) (overall death rate 15.1%). The most common causes of death were respiratory failure (39.3%) and sudden cardiac death (20.0%). The predictors of overall mortality included older age (≥60 years), male sex, pre-existing coronary heart disease, renal disease, diabetes, ICU admission, oxygen therapy, and higher respiratory rates (p < 0.001 for each). Compared to Caucasians, Asians, Blacks, and Hispanics had almost 2-4 times higher risk of death. Further, patients from LIC, LMIC, UMIC versus. HIC had 2-3 times increased risk of death.

CONCLUSIONS

The LIC, LMIC, and UMIC's have sparse data on COVID-19. We provide robust evidence on COVID-19 outcomes in these countries. This study can help guide future health care planning for the pandemic globally.

Incidence and Predictors of Progression to Chagas Cardiomyopathy: Long-Term Follow-Up of Trypanosoma cruzi-Seropositive Individuals

BACKGROUND

There are few contemporary cohorts of Trypanosoma cruzi-seropositive individuals, and the basic clinical epidemiology of Chagas disease is poorly understood. Herein, we report the incidence of cardiomyopathy and death associated with T. cruzi seropositivity.

METHODS

Participants were selected in blood banks at 2 Brazilian centers. Cases were defined as T. cruzi-seropositive blood donors. T. cruzi-seronegative controls were matched for age, sex, and period of donation. Patients with established Chagas cardiomyopathy were recruited from a tertiary outpatient service. Participants underwent medical examination, blood collection, ECG, and echocardiogram at enrollment (2008-2010) and at follow-up (2018-2019). The primary outcomes were all-cause mortality and development of cardiomyopathy, defined as the presence of a left ventricular ejection fraction <50% or QRS complex duration ≥120 ms, or both. To handle loss to follow-up, a sensitivity analysis was performed using inverse probability weights for selection.

RESULTS

We enrolled 499 T. cruzi-seropositive donors (age 48±10 years, 52% male), 488 T. cruzi-seronegative donors (age 49±10 years, 49% male), and 101 patients with established Chagas cardiomyopathy (age 48±8 years, 59% male). The mortality in patients with established cardiomyopathy was 80.9 deaths/1000 person-years (py) (54/101, 53%) and 15.1 deaths/1000 py (17/114, 15%) in T. cruzi-seropositive donors with cardiomyopathy at baseline. Among T. cruzi-seropositive donors without cardiomyopathy at baseline, mortality was 3.7 events/1000 py (15/385, 4%), which was no different from T. cruzi-seronegative donors with 3.6 deaths/1000 py (17/488, 3%). The incidence of cardiomyopathy in T. cruzi-seropositive donors was 13.8 (95% CI, 9.5-19.6) events/1000 py (32/262, 12%) compared with 4.6 (95% CI, 2.3-8.3) events/1000 py (11/277, 4%) in seronegative controls, with an absolute incidence difference associated with T. cruzi seropositivity of 9.2 (95% CI, 3.6-15.0) events/1000 py. T. cruzi antibody level at baseline was associated with development of cardiomyopathy (adjusted odds ratio, 1.4 [95% CI, 1.1-1.8]).

CONCLUSIONS

We present a comprehensive description of the natural history of T. cruzi seropositivity in a contemporary patient population. The results highlight the central importance of anti-T. cruzi antibody titer as a marker of Chagas disease activity and risk of progression.

Global prevalence and burden of depressive and anxiety disorders in 204 countries and territories in 2020 due to the COVID-19 pandemic

BACKGROUND

Before 2020, mental disorders were leading causes of the global health-related burden, with depressive and anxiety disorders being leading contributors to this burden. The emergence of the COVID-19 pandemic has created an environment where many determinants of poor mental health are exacerbated. The need for up-to-date information on the mental health impacts of COVID-19 in a way that informs health system responses is imperative. In this study, we aimed to quantify the impact of the COVID-19 pandemic on the prevalence and burden of major depressive disorder and anxiety disorders globally in 2020.

METHODS

We conducted a systematic review of data reporting the prevalence of major depressive disorder and anxiety disorders during the COVID-19 pandemic and published between Jan 1, 2020, and Jan 29, 2021. We searched PubMed, Google Scholar, preprint servers, grey literature sources, and consulted experts. Eligible studies reported prevalence of depressive or anxiety disorders that were representative of the general population during the COVID-19 pandemic and had a pre-pandemic baseline. We used the assembled data in a meta-regression to estimate change in the prevalence of major depressive disorder and anxiety disorders between pre-pandemic and mid-pandemic (using periods as defined by each study) via COVID-19 impact indicators (human mobility, daily SARS-CoV-2 infection rate, and daily excess mortality rate). We then used this model to estimate the change from pre-pandemic prevalence (estimated using Disease Modelling Meta-Regression version 2.1 [known as DisMod-MR 2.1]) by age, sex, and location. We used final prevalence estimates and disability weights to estimate years lived with disability and disability-adjusted life-years (DALYs) for major depressive disorder and anxiety disorders.

FINDINGS

We identified 5683 unique data sources, of which 48 met inclusion criteria (46 studies met criteria for major depressive disorder and 27 for anxiety disorders). Two COVID-19 impact indicators, specifically daily SARS-CoV-2 infection rates and reductions in human mobility, were associated with increased prevalence of major depressive disorder (regression coefficient [B] 0·9 [95% uncertainty interval 0·1 to 1·8; p=0·029] for human mobility, 18·1 [7·9 to 28·3; p=0·0005] for daily SARS-CoV-2 infection) and anxiety disorders (0·9 [0·1 to 1·7; p=0·022] and 13·8 [10·7 to 17·0; p<0·0001]. Females were affected more by the pandemic than males (B 0·1 [0·1 to 0·2; p=0·0001] for major depressive disorder, 0·1 [0·1 to 0·2; p=0·0001] for anxiety disorders) and younger age groups were more affected than older age groups (-0·007 [-0·009 to -0·006; p=0·0001] for major depressive disorder, -0·003 [-0·005 to -0·002; p=0·0001] for anxiety disorders). We estimated that the locations hit hardest by the pandemic in 2020, as measured with decreased human mobility and daily SARS-CoV-2 infection rate, had the greatest increases in prevalence of major depressive disorder and anxiety disorders. We estimated an additional 53·2 million (44·8 to 62·9) cases of major depressive disorder globally (an increase of 27·6% [25·1 to 30·3]) due to the COVID-19 pandemic, such that the total prevalence was 3152·9 cases (2722·5 to 3654·5) per 100 000 population. We also estimated an additional 76·2 million (64·3 to 90·6) cases of anxiety disorders globally (an increase of 25·6% [23·2 to 28·0]), such that the total prevalence was 4802·4 cases (4108·2 to 5588·6) per 100 000 population. Altogether, major depressive disorder caused 49·4 million (33·6 to 68·7) DALYs and anxiety disorders caused 44·5 million (30·2 to 62·5) DALYs globally in 2020.

INTERPRETATION

This pandemic has created an increased urgency to strengthen mental health systems in most countries. Mitigation strategies could incorporate ways to promote mental wellbeing and target determinants of poor mental health and interventions to treat those with a mental disorder. Taking no action to address the burden of major depressive disorder and anxiety disorders should not be an option.

FUNDING

Queensland Health, National Health and Medical Research Council, and the Bill and Melinda Gates Foundation.

Accuracy and reliability of focused echocardiography in patients with Chagas disease from endemic areas: SaMi-Trop cohort study

BACKGROUND

Chagas disease remains a major cause of cardiovascular death in endemic areas. Focused echocardiography (FoCUS) is a point-of-care means of assessing cardiac function which can be useful for the diagnosis of cardiac involvement.

OBJECTIVE

This study aims evaluating the characteristics of validity and reliability of FoCUS applied on Chagas disease patients.

METHODS

Patients with Chagas disease coming from an endemic area were selected from a large cohort (SaMi-Trop). A simplified echocardiogram with only three images was extracted from the conventional echocardiogram performed in this cohort. The images were evaluated by an observer who was blinded to the clinical and echocardiographic data, to determine the accuracy and reliability of FoCUS for cardiac assessment. The analysis constituted of 5 prespecified variables, dichotomized in absence or presence: left ventricular (LV) size and systolic function, right ventricular (RV) size and systolic function, and LV aneurysm.

RESULTS

We included 725 patients with a mean age of 63.4 ± 12.3 years, 483 (67%) female. Abnormal electrocardiogram was observed in 81.5% of the patients. Left and right ventricular dysfunctions were found in 103 (14%) and 49 (7%) of the patients, respectively. Sensitivity, specificity, positive predictive value and negative predictive value were 84%, 94%, 70% and 97% for LV enlargement and 81%, 93%, 68% and 97% for LV systolic dysfunction, respectively, and 46%, 99%, 60% and 98% for RV dilatation, and 37%, 100%, 100% and 96% for RV dysfunction, respectively. Inter and intraobserver agreement were 61% and 87% for LV enlargement and 63% and 92% for LV dysfunction, respectively, and 50% and 49% for RV size and 46% and 79% for RV dysfunction, respectively. LV apical aneurysm was found in 45 patients (6.2%) with the lowest sensitivity of FoCUS study (11%; 95% CI 2-28%).

CONCLUSIONS

FoCUS showed satisfactory values of validity and reliability for assessment of cardiac chambers in patients with Chagas disease, except for apical aneurysm. This tool can identify heart disease with potential impact on patient management in the limited-resource setting.

Burden of cardiovascular diseases attributable to risk factors in Brazil: data from the Global Burden of Disease 2019 study

Introduction

Cardiovascular diseases (CVD) continue to be the main cause of death in Brazil, a middle-income country. As such, it is essential to understand the trends of risk factors (RFs) for CVDs in order to implement effective and tailored public policies.

Purpose

The present study sought to analyze the trend of RF for CVD and the disease burden attributable to these from 1990 to 2019, in Brazil and its states, based on estimates from the Global Burden of Disease Study 2019 (2019 GBD).

Methods

To estimate RF exposure, the Summary Exposure Value (SEV) (risk-weighted prevalence) was used, whereas for disease burden attributed to RFs, mortality and Disability-adjusted life-years (DALY) by CVD were used. For comparisons over time and between states, the age-standardized rates were considered. The sociodemographic index (SDI) was used as a marker of socioeconomic conditions.

Results

In 2019, 82% of CVD mortality in Brazil was attributable to RFs. For SEV, there was a reduction in smoking and environmental RFs, as well as an increase in metabolic RFs. High systolic blood pressure and dietary risks continue to be the main RFs for CVD mortality and DALY (Figure 1). While there was a decline in age-standardized mortality rates attributable to the evaluated RFs, there was also a stability or increase in crude mortality rates, with the exception of smoking. It is important to highlight the increase in the risk of death attributable to a high body mass index (BMI) (35 to 46/100,000 in habitants in 1990 and 2019). Regarding the analysis per state, SEVs and mortality attributable to RF were higher in those states with lower SDIs.

Conclusion

Despite the reduction in CVD mortality and DALY rates attributable to RF, the stability or increase in crude rates attributable to metabolic RFs is worrisome, requiring investments and a renewal of health policies.

Funding Acknowledgement

Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Health Surveillance Secretariat, Brazilian Ministry of Health Figure 1

Changes in the pattern of valvular heart disease following the epidemiological transition in Brazil from 1990 to 2019: data from the Global Burden of Disease 2019 study

Introduction

Valvular heart disease is one of the leading causes of cardiovascular death in Brazil, with a great contribution of Rheumatic Heart Disease (RHD), the most socially driven etiology. However, as socioeconomic conditions improved, an increasing contribution of non-rheumatic valvular heart disease (NRVD) is being observed.

Objectives

We aimed to evaluate the changes in trends of prevalence, mortality and burden of RHD and non-rheumatic valvular heart disease in Brazil from 1990 to 2019, according to the Global Burden of Disease (GBD) 2019 study estimates.

Methods

We used available vital registration data, epidemiological survey data, and hospital claims data to estimate the cause-specific mortality rate, prevalence, and burden of RHD and NRVD using the GBD modelling framework. Burden estimates in Brazil were estimated for each sex, 5-year age group, federal unit, and year from 1990 to 2019. We also explored the correlation of disease burden and the sociodemographic index (SDI).

Results

From 1990 to 2019, age-standardized prevalence of RHD increased slightly (2.1% (95%UI 0.2–4.0)) in Brazil, from 899.6 (95%UI 699.8–1119.1) to 918.5 (95%UI 716–1142.5) per 100,000, remaining higher in women in the whole period. In contrast, age-standardized prevalence of NRVD had a marked 54.3% increase from 25.3 (95% UI 22.4–27.8) per 100,000 in 1990 to 39 (95% UI 33.9–44.6) per 100,000 in 2019. The percent change was considerably higher for men compared to women (105.9% vs. 20.9%). For mortality, age-standardized rates attributable to RHD significantly decreased 59.4%, from 2.8 (95%UI 2.7–3.0) to 1.2 (95%UI 1.1–1.2) per 100,000, whereas NRVD had a less pronounced 16.2% decrease in the period. However, crude NRVD mortality increased (51.9% (95%UI 39.8–62.7)), with a considerable contribution of older ages, noticeably over 70 years (17.2% (95%UI 5.4–27.4)), specifically driven by calcific aortic valve disease mortality, with a marked 17% (95%UI 2.0–38.5) increase in the elderly. RHD dropped from 12th to 10th in the mortality ranking, while aortic and mitral degenerative diseases rose in the period (Figure 1). There was a significant negative correlation between the percent change in age-standardized RHD mortality rates and SDI in 1990 (r=−0.41, p=0.03) and in 2019 (r=−0.44, p=0.02), and an opposite trend for NRVD, with positive correlations in 1990 (r=−0.55, p=0.003), and 2019 (r=−0.58, p=0.001), suggesting that SDI was a major driver for the observed trends.

Conclusion

Mortality and disease burden attributable to RHD decreased significantly in Brazil over the past decades, still with a stable prevalence trend. This contrasts with increasing prevalence and crude mortality estimates for NRVD, especially in older ages, and driven by degenerative conditions. Changes in mortality rates strongly correlated with SDI, depicting the effects of socioeconomic markers of the pattern of valve disease in Brazil.

Funding Acknowledgement

Type of funding sources: Public grant(s) – National budget only. Main funding source(s): This study used data from the Institute of Health Metrics and Evaluation, funded by the Bill & Melinda Gates Foundation. This work was supported by the Brazilian Ministry of Health through resource transfer from the National Health Fund. Figure 1. Ranking of mortality rates.

Conquering stroke epidemiological statistics in Brazil an innovative initiative from the Brazilian Society of Cardiology

Background

Stroke has been the second major cause of death in Brazil in the last decades. A better understanding on epidemiological statistics as well as on the diseases burden is crucial for enabling stakeholders to better tackle the disease.

Purpose

This project aims to continuously monitor and evaluate the data sources on heart disease and stroke in Brazil to provide the most up-to-date information on the epidemiology of these diseases to Brazilian society annually.

Methods

This initiative is based on the Heart Disease & Stroke Statistics Update methodology of the American Heart Association, with the support of the Brazilian Society of Cardiology, the Global Burden of Diseases Brazil network and an international committee. The project incorporates official statistics provided by the Brazilian Ministry of Health and other government agencies, as well as data generated by other sources and scientific studies on heart disease, stroke, and other CVD, including GBD/IHME data.

Results

The age-standardized prevalence rates per 100.000 for ischemic stroke in 1990 was 1327,6 (1151.2 to 1516) and 870.1 (761.1 to 992.8) in 2019 representing a percent change of −34.5 (−36.7 to −0.3). The age-standardized prevalence rates for intracerebral hemorrhage in 1990 was 507.5 (438.9 to584.1) and 315.9 (275 to 361.4) in 2019 representing a percent change of −37.7 (−40.5 to −0.3). The age-standardized incidence rates for stroke in 1990 was 224.6 (201.6 to 251.8) and 127 (113.8 to 142.1) in 2019 representing a percent change of −43.5 (−44.7 to −0.4). the age-standardized mortality rates for stroke in 1990 was 137.8 (127.8 to 144) and 58.1 (52.6 to 61.8) in 2019 representing a percent change of −57.8 (−60.4 to −0.6). The age-standardized DALY rates for stroke in 1990 was 2959 (2829.6 to 3063) and 1219.6 (1142 to 1285.5) in 2019 representing a percent change of −58.8 (−61 to −0.6).

Conclusion

This project represents a fundamental step on a better understanding on the stroke epidemiology in Brazil. While we observed a significant decrease in mortality rates from 1990 to 2019, we also raise a concern on a possible shift for a plateau curve or even increased rates in the next years.

Funding Acknowledgement

Type of funding sources: Other. Main funding source(s): Brazilian Society of Cardiology

A Genome-Wide Association Study Identifies Novel Susceptibility loci in Chronic Chagas Cardiomyopathy

BACKGROUND

Chagas disease is an infectious disease caused by the parasite Trypanosoma cruzi and is endemic from Latin American countries. The goal of our study was to identify novel genetic loci associated with chronic Chagas cardiomyopathy development in Chagas disease patients from different Latin American populations.

METHODS

We performed a cross-sectional, nested case-control study including 3 sample collections from Colombia, Argentina, and Bolivia. Samples were genotyped to conduct a genome-wide association study (GWAS). These results were meta-analyzed with summary statistic data from Brazil, gathering a total of 3413 Chagas disease patients. To identify the functional impact of the associated variant and its proxies, we performed an in silico analysis of this region.

RESULTS

The meta-analysis revealed a novel genome-wide statistically significant association with chronic Chagas cardiomyopathy development in rs2458298 (OR = 0.90, 95%CI = 0.87-0.94, P-value = 3.27 × 10-08), nearby the SAC3D1 gene. In addition, further in silico analyses displayed functional relationships between the associated variant and the SNX15, BAFT2, and FERMT3 genes, related to cardiovascular traits.

CONCLUSIONS

Our findings support the role of the host genetic factors in the susceptibility to the development of the chronic cardiac form of this neglected disease.

Outcomes of Echocardiography-Detected Rheumatic Heart Disease: Validating a Simplified Score in Cohorts From Different Countries

Background The natural history of latent rheumatic heart disease (RHD) detected by echocardiography remains unclear. We aimed to assess the accuracy of a simplified score based on the 2012 World Heart Federation criteria in predicting mid-term RHD echocardiography outcomes in children from 4 different countries. Methods and Results Patient-level baseline and follow-up data of children with latent RHD from 4 countries (Australia, n=62; Brazil, n=197; Malawi, n=40; New Zealand, n=94) were combined. A simplified echocardiographic scoring system previously developed from Brazilian and Ugandan cohorts, consisting of 5 point-based variables with respective weights, was applied: mitral valveanterior leaflet thickening (weight=3), excessive leaflet
tip motion (3), regurgitation jet length ≥2 cm (6), aortic valve
focal thickening (4), and any regurgitation (5). Unfavorable outcome was defined as worsening diagnostic category, persistent definite RHD or development/worsening of valve regurgitation/stenosis. The score model was updated using methods for recalibration. 393 patients (314 borderline, 79 definite RHD) with median follow-up of 36 (interquartile range, 25-48) months were included. Median age was 14 (interquartile range, 11-16) years and secondary prophylaxis was prescribed to 16%. The echocardiographic score model applied to this external population showed significant association with unfavorable outcome (hazard ratio, 1.10; 95% CI, 1.04-1.16; P=0.001). Unfavorable outcome rates in low (≤5 points), intermediate (6-9), and high-risk (≥10) children at 3-year follow-up were 14.3%, 20.8%, and 38.5% respectively (P<0.001). The updated score model showed good performance in predicting unfavorable outcome. Conclusions The echocardiographic score model for predicting RHD outcome was updated and validated for different latent RHD populations. It has potential utility in the clinical and screening setting for risk stratification of latent RHD.

Deep neural network-estimated electrocardiographic age as a mortality predictor

The electrocardiogram (ECG) is the most commonly used exam for the evaluation of cardiovascular diseases. Here we propose that the age predicted by artificial intelligence (AI) from the raw ECG (ECG-age) can be a measure of cardiovascular health. A deep neural network is trained to predict a patient's age from the 12-lead ECG in the CODE study cohort (n = 1,558,415 patients). On a 15% hold-out split, patients with ECG-age more than 8 years greater than the chronological age have a higher mortality rate (hazard ratio (HR) 1.79, p < 0.001), whereas those with ECG-age more than 8 years smaller, have a lower mortality rate (HR 0.78, p < 0.001). Similar results are obtained in the external cohorts ELSA-Brasil (n = 14,236) and SaMi-Trop (n = 1,631). Moreover, even for apparent normal ECGs, the predicted ECG-age gap from the chronological age remains a statistically significant risk predictor. These results show that the AI-enabled analysis of the ECG can add prognostic information.

Atrial fibrillation risk prediction from the 12-lead electrocardiogram using digital biomarkers and deep representation learning

Aims

This study aims to assess whether information derived from the raw 12-lead electrocardiogram (ECG) combined with clinical information is predictive of atrial fibrillation (AF) development.

Methods and results

We use a subset of the Telehealth Network of Minas Gerais (TNMG) database consisting of patients that had repeated 12-lead ECG measurements between 2010 and 2017 that is 1 130 404 recordings from 415 389 unique patients. Median and interquartile of age for the recordings were 58 (46-69) and 38% of the patients were males. Recordings were assigned to train-validation and test sets in an 80:20% split which was stratified by class, age and gender. A random forest classifier was trained to predict, for a given recording, the risk of AF development within 5 years. We use features obtained from different modalities, namely demographics, clinical information, engineered features, and features from deep representation learning. The best model performance on the test set was obtained for the model combining features from all modalities with an area under the receiver operating characteristic curve (AUROC) = 0.909 against the best single modality model which had an AUROC = 0.839.

Conclusion

Our study has important clinical implications for AF management. It is the first study integrating feature engineering, deep learning, and Electronic medical record system (EMR) metadata to create a risk prediction tool for the management of patients at risk of AF. The best model that includes features from all modalities demonstrates that human knowledge in electrophysiology combined with deep learning outperforms any single modality approach. The high performance obtained suggest that structural changes in the 12-lead ECG are associated with existing or impending AF.

Health education: the effects of an educational program on the health of hypertensive patients with low educational level

Funding Acknowledgements

Type of funding sources: Public grant(s) – National budget only. Main funding source(s): FAPEMIG

Introduction

Health education is one of the most complete practices for supporting of patients with chronic diseases such as hypertension. It is important, however, to investigate which strategies would be more assertive in this process, depending on the objective and profile of the patient. Objective: The aim of this study was to evaluate the effect of an interactive educational program on the health of hypertensive patients with low educational level in a Basic Health Unit in Brazil.  Methods: This is an almost experimental study, with a multidisciplinary approach, with 6 months of duration. Interactive workshops were held where topics related to hypertension, such as: pathophysiology, complications, drug and non-drug therapeutic approach and lifestyle change. It is important to emphasize that the work used interactive and playful sessions, such as games, videos and group dynamics.  The sample consisted of 35 hypertensive individuals submitted to blood pressure (systolic = SBP and diastolic = DBP) measurement, quality of life (Minichal), adherence to treatment (Martín-Bayarre-Grau), level of knowledge of the disease, physical activity (IPAQ) and anthropometric study evaluation. In addition, for analysis of the data, the sample was divided into two subgroups, according to the participation in the activities: adhered (n = 11) or not adhered (n = 24). Initially, descriptive statistics were used to present the study variables. Subsequently, the WILCOXON test was used to compare before and after and MANN-WHITNEY to compare the two groups, p = 0.05 was considered significant. Results: No significant difference was found relating the initial data in the two subgroups. After the educational program, a significant reduction was observed in relation to the SBP values: 9.8 mmHg in the adherent subgroup. On the other hand, there was increased 0.7 mmHg among non-adherents. The other evaluations did not change. It should be emphasized that the studied population demonstrated a satisfactory level of knowledge of the pathology and the therapeutic process necessary since the initial evaluation in both groups. Such finding, however, was not related to adherence to treatment. Conclusion: the findings suggest that an adapted educational approach could help to control blood pressure levels of hypertensive patients with low educational level. In addition, it was observed that knowledge does not seem to be associated with action, and it is necessary to develop strategies that can increase adherence to therapeutic interventions.

Deriving a parsimonious cardiac endpoint for use in epidemiological studies of Chagas disease: results from the Retrovirus Epidemiology Donor Study-II (REDS-II) cohort

Chagas cardiomyopathy (ChCM) is a severe consequence of Trypanosoma cruzi infection and has a range of electrocardiographic (ECG) and echocardiographic (ECHO) manifestations. There is a need for a standard and parsimonious research cardiac end point that does not rely on expert panel adjudication, and it is not intended to change the ChCM definition. We use data from the REDS-II cohort to propose a simplified cardiac endpoint. A total of 499 T. cruzi-seropositive blood donors were included. All participants underwent a 12-lead ECG, echocardiogram and clinical examination, and those with abnormal findings were reviewed by a panel of cardiologists who classified cases as having Chagas cardiomyopathy or not. We created an exhaustive set of ECG and ECHO finding combinations and compared these with the panel's classification. We selected the simplest combination that most accurately reproduced the panel's results. Individual ECG and ECHO variables had low sensitivity for panel-defined cardiomyopathy. The best performing combination was right bundle branch block and/or ECHO evidence of left ventricular hypocontractility. This combination had 98% specificity and 85% sensitivity for panel-defined ChCM. It was not possible to improve the overall accuracy by addition of any other ECG or ECHO variable. Substituting right bundle branch block for the more inclusive finding of QRS interval > 120 ms produced similar results. The combination of prolonged QRS interval and/or left ventricular hypocontractility closely reproduced the REDS-II expert panel classification of Chagas ChCM. In conclusion, the simple and reproducible research endpoint proposed here captures most of the spectrum of cardiac abnormalities in Chagas disease.

Global Burden of Cardiovascular Diseases and Risk Factors, 1990-2019: Update From the GBD 2019 Study

Cardiovascular diseases (CVDs), principally ischemic heart disease (IHD) and stroke, are the leading cause of global mortality and a major contributor to disability. This paper reviews the magnitude of total CVD burden, including 13 underlying causes of cardiovascular death and 9 related risk factors, using estimates from the Global Burden of Disease (GBD) Study 2019. GBD, an ongoing multinational collaboration to provide comparable and consistent estimates of population health over time, used all available population-level data sources on incidence, prevalence, case fatality, mortality, and health risks to produce estimates for 204 countries and territories from 1990 to 2019. Prevalent cases of total CVD nearly doubled from 271 million (95% uncertainty interval [UI]: 257 to 285 million) in 1990 to 523 million (95% UI: 497 to 550 million) in 2019, and the number of CVD deaths steadily increased from 12.1 million (95% UI:11.4 to 12.6 million) in 1990, reaching 18.6 million (95% UI: 17.1 to 19.7 million) in 2019. The global trends for disability-adjusted life years (DALYs) and years of life lost also increased significantly, and years lived with disability doubled from 17.7 million (95% UI: 12.9 to 22.5 million) to 34.4 million (95% UI:24.9 to 43.6 million) over that period. The total number of DALYs due to IHD has risen steadily since 1990, reaching 182 million (95% UI: 170 to 194 million) DALYs, 9.14 million (95% UI: 8.40 to 9.74 million) deaths in the year 2019, and 197 million (95% UI: 178 to 220 million) prevalent cases of IHD in 2019. The total number of DALYs due to stroke has risen steadily since 1990, reaching 143 million (95% UI: 133 to 153 million) DALYs, 6.55 million (95% UI: 6.00 to 7.02 million) deaths in the year 2019, and 101 million (95% UI: 93.2 to 111 million) prevalent cases of stroke in 2019. Cardiovascular diseases remain the leading cause of disease burden in the world. CVD burden continues its decades-long rise for almost all countries outside high-income countries, and alarmingly, the age-standardized rate of CVD has begun to rise in some locations where it was previously declining in high-income countries. There is an urgent need to focus on implementing existing cost-effective policies and interventions if the world is to meet the targets for Sustainable Development Goal 3 and achieve a 30% reduction in premature mortality due to noncommunicable diseases.