Population risk factors for severe disease and mortality in COVID-19: A global systematic review and meta-analysis

Occurrence and clinical correlates of SARS-CoV-2 viremia in two German patient cohorts

Viremia defined as detectable SARS-CoV-2 RNA in the blood is a potential marker of disease severity and prognosis in COVID-19 patients. Here, we determined the frequency of viremia in serum of two independent COVID-19 patient cohorts within the German National Pandemic Cohort Network (German: Nationales Pandemie Kohorten Netzwerk, NAPKON) with diagnostic RT-PCR against SARS-CoV-2. A cross-sectional cohort with 1122 COVID-19 patients (German: Sektorenuebergreifende Platform, SUEP) and 299 patients recruited in a high-resolution platform with patients at high risk to develop severe courses (German: Hochaufloesende Plattform, HAP) were tested for viremia. Our study also involved a comprehensive analysis and association of serological, diagnostic, and clinical parameters of the NAPKON medical dataset. Prevalence of viremia at the recruitment visit was 12.8% (SUEP) and 13% (HAP), respectively. Serological analysis revealed that viremic patients had lower levels of SARS-CoV-2 specific antibodies as well as lower neutralizing antibodies compared to aviremic patients. Viremia was associated with severity (<0.0001 SUEP; 0.002 HAP) and mortality of COVID-19 (both cohorts <0.0001) compared to aviremic patients. While rare, viremia was also detected in patients with mild disease (0.7%). In patients of the SUEP cohort with acute kidney disease (p = 0.0099) and hematooncological conditions (p = 0.0091), viremia was detected more frequently. Compared to the aviremic group, treatment with immunomodulating drugs as well as elevated levels of inflammatory markers in the blood was more frequent in the viremic group. In conclusion, our analysis revealed that detectable viremia correlates with hyperinflammatory conditions and higher risk for severe COVID-19 disease.

Evolution of COVID-19 mortality risk: A retrospective study of three epidemic waves in Faridabad, India

PURPOSE

The study aimed to compare the sociodemographic, comorbidity, and clinical variables associated with coronavirus disease 2019 (COVID-19) mortality across three distinct epidemic waves in Faridabad, India.

METHODS

A retrospective analysis of the medical records of patients admitted with COVID-19 was conducted at a tertiary care center at Faridabad, India. COVID-19 epidemic waves were categorized into the first wave (April 2020-January 2021), second wave (March 2021-June 2021), and third wave (December 2021-February 2022). Sociodemographic, comorbidity, and clinical parameters were assessed for their association with mortality in each of the waves by the Chi-square test. The Cochran-Armitage test for trend was used to assess changes in these associations with respect to the mortality rate across the epidemic waves.

RESULTS

A total of 5217 patient records were assessed, with 4066 in the first wave, 895 in the second wave, and 256 in the third wave. Across all waves, comorbidities (diabetes and hypertension), multimorbidity, severe disease (requiring intensive care unit admission and ventilator support) were consistently associated (p<0.05) with higher mortality. While sociodemographic factors were significant (p<0.05) in the first two waves, their impact diminished in the third. Clinical symptoms, particularly 'cold and flu' showed consistent significance (p<0.05) across all waves. COVID-19 mortality trend peaked in the second wave, disproportionately (p<0.05) affecting females, older patients, and those with comorbidities or severe symptoms.

CONCLUSIONS

Understanding the shifting risk factors across COVID-19 epidemic waves is crucial for targeted interventions. Prioritizing high-risk groups, particularly during peak waves, can optimize resource allocation and minimize mortality.

Reformulating patient stratification for targeting interventions by accounting for severity of downstream outcomes resulting from disease onset: a case study in sepsis

OBJECTIVES

To quantify differences between (1) stratifying patients by predicted disease onset risk alone and (2) stratifying by predicted disease onset risk and severity of downstream outcomes. We perform a case study of predicting sepsis.

MATERIALS AND METHODS

We performed a retrospective analysis using observational data from Michigan Medicine at the University of Michigan (U-M) between 2016 and 2020 and the Beth Israel Deaconess Medical Center (BIDMC) between 2008 and 2012. We measured the correlation between the estimated sepsis risk and the estimated effect of sepsis on mortality using Spearman's correlation. We compared patients stratified by sepsis risk with patients stratified by sepsis risk and effect of sepsis on mortality.

RESULTS

The U-M and BIDMC cohorts included 7282 and 5942 ICU visits; 7.9% and 8.1% developed sepsis, respectively. Among visits with sepsis, 21.9% and 26.3% experienced mortality at U-M and BIDMC. The effect of sepsis on mortality was weakly correlated with sepsis risk (U-M: 0.35 [95% CI: 0.33-0.37], BIDMC: 0.31 [95% CI: 0.28-0.34]). High-risk patients identified by both stratification approaches overlapped by 66.8% and 52.8% at U-M and BIDMC, respectively. Accounting for risk of mortality identified an older population (U-M: age = 66.0 [interquartile range-IQR: 55.0-74.0] vs age = 63.0 [IQR: 51.0-72.0], BIDMC: age = 74.0 [IQR: 61.0-83.0] vs age = 68.0 [IQR: 59.0-78.0]).

DISCUSSION

Predictive models that guide selective interventions ignore the effect of disease on downstream outcomes. Reformulating patient stratification to account for the estimated effect of disease on downstream outcomes identifies a different population compared to stratification on disease risk alone.

CONCLUSION

Models that predict the risk of disease and ignore the effects of disease on downstream outcomes could be suboptimal for stratification.

Evaluating the feasibility, adoption, cost-effectiveness, and sustainability of telemedicine interventions in managing COVID-19 within low-and-middle-income countries (LMICs): A systematic review

COVID-19 has tragically taken the lives of more than 6.5 million people globally, significantly challenging healthcare systems and service delivery, especially in low-and middle-income countries (LMICs). This systematic review aims to: (1) evaluate the feasibility of telemedicine interventions for COVID-19 management; (2) assess the adoption of telemedicine interventions during the COVID-19 pandemic; (3) examine the cost-effectiveness of telemedicine implementation efforts and (4) analyze the sustainability of telemedicine interventions for COVID-19 disease management within LMIC service settings. We reviewed studies from selected public health and health science databases, focusing on those conducted in countries classified as low and middle-income by the World Bank, using telemedicine for confirmed COVID-19 cases, and adhering to Proctor's framework for implementation outcomes. Of the 766 articles identified and 642 screened, only 3 met all inclusion criteria. These studies showed reduced reliance on antibiotics, prescription drugs, and emergency department referrals among telemedicine patients. Statistical parity was observed in the length of stay, diagnostic test ordering rates, and International Classification of Diseases (ICD)-10 diagnoses between telemedicine and in-person visits. Telemedicine interventions designed for post-COVID physical rehabilitation demonstrated safety, sustainability, and enhanced quality of life for patients without requiring specialized equipment, proving adaptable across contexts with appropriate technology. These interventions were also economically sustainable and cost-effective for healthcare systems as a whole. Proposed strategies to bridge implementation gaps include community-level assessments, strategic planning, multisectoral partnerships of local hospital administration and lawmakers, legal consultations, and healthcare informatics improvements. Increased investment in telemedicine research focusing on infectious disease management is crucial for the continued development and refinement of effective strategies tailored to resource-constrained regions.

Pulmonary ultrasound in COVID-19 and non-COVID-19 pneumonia in South Africa: An observational study

Background

Pulmonary ultrasound techniques have historically been applied to acute lung diseases to describe lung lesions, particularly in critical care.

Objectives

To explore the role of lung ultrasound (LUS) in hospitalised patients with hypoxaemic pneumonia during the COVID-19 pandemic.

Methods

This was a single-centre prospective, observational study of two groups of adult patients with hypoxaemic pneumonia: those with COVID-19 pneumonia, and those with non-COVID-19 community-acquired pneumonia (CAP). A pulmonologist performed bedside LUS using the Bedside Lung Ultrasound in Emergency (BLUE) protocol, and the findings were verified by an independent study-blinded radiologist.

Results

We enrolled 48 patients with COVID-19 pneumonia and 24 with non-COVID CAP. The COVID-19 patients were significantly older than those with non-COVID CAP (median (interquartile range (IQR)) age 52 (42 - 62.5) years v. 42.5 (36 - 52.5) years, respectively; p=0.007), and had a lower prevalence of HIV infection (25% v. 54%, respectively; p=0.01) and higher prevalences of hypertension (54% v. 7%; p=0.002) and diabetes mellitus (19% v. 8%; p=0.04). In both groups, close to 30% of the patients had severe acute respiratory distress syndrome. A confluent B-line pattern in the right upper lobe was significantly associated with COVID-19 pneumonia compared with the C pattern (relative risk (RR) 3.8; 95% confidence interval (CI) 1.7 - 8.6). Bilateral changes on LUS rather than unilateral or no changes were associated with COVID-19 pneumonia (RR 1.55; 95% CI 1.004 - 2.387). There were no statistically significant differences in median (IQR) lung scores between patients with COVID-19 pneumonia and those with non-COVID CAP (8 (4 - 11.5) v. 7.5 (4.5 - 12.5), respectively). Patients with COVID-19 pneumonia had a higher than predicted mortality. Logistic regression analysis showed a higher Simplified Acute Physiology Score (SAPS II) (RR 1.11; 95% CI 1.02 - 1.21) and a lower total LUS score indicating B lines v. consolidation (RR 0.80; 95% CI 0.65 - 0.99) to be associated with mortality.

Conclusion

Patients with right upper zone consolidation were more likely to have non-COVID CAP than COVID-19 pneumonia. Finding a B pattern as opposed to consolidation was associated with mortality. The admission LUS score was unable to discriminate between COVID-19 and non-COVID CAP, and did not correlate with the ratio of partial pressure of oxygen to fractional inspired oxygen, clinical severity or mortality.

Study synopsis

What the study adds. During the COVID-19 pandemic, in a resource-limited, high-prevalence setting, lung ultrasound (LUS) patterns on admission to hospital were used to distinguish between COVID-19 and other causes in patients with hypoxaemic pneumonia. Patients with right upper zone consolidation were more likely to have non-COVID-19 community-acquired pneumonia (CAP) than COVID-19 pneumonia.Implications of the findings. The admission LUS score was unable to discriminate between COVID-19 pneumonia and non-COVID CAP, and did not correlate with the ratio of partial pressure of oxygen to fractional inspired oxygen, clinical severity or mortality. The pattern was more valuable than the total LUS score in understanding the disease process.

COVID-19 outbreak management in Western Sydney residential aged care homes: A mixed-methods Donabedian evaluation

Outbreaks of the novel respiratory viral disease, SARS-CoV-2 (COVID-19), have caused disproportionate morbidity and mortality for older people living in residential aged care homes. Between June 2021 and December 2022, the Delta and Omicron variants of COVID-19 were responsible for widespread outbreaks in homes across Western Sydney, New South Wales, Australia. To manage outbreaks in affected homes, a targeted response strategy was prepared and deployed in the form of outbreak management teams. This study utilised the Donabedian framework and a two-phase mixed methods design to evaluate the structures, processes and outcomes of the outbreak management teams at the level of the local health district. Phase 1 involved the descriptive analysis of outbreak data from Western Sydney aged care homes, created between June 2021 and December 2022. Phase 2 involved the completion of in-depth semi-structured interviews with 35 participants to explore the outbreak management team response from the perspective of its members and staff from residential aged care homes. Between June 2021 and December 2022, there were 281 outbreaks, 4113 resident cases, 346 hospitalisations and 127 deaths in residential aged care homes across Western Sydney. Structural factors that facilitated the outbreak management response and improved outcomes included smaller home sizes, the absence of shared rooms and bathrooms, adequate staffing and resources, suitable infrastructure, and the integration of the response with wider public health systems. Process facilitators included multi-disciplinary team membership, open communication channels, structured and streamlined procedures and roles, onsite infection control support and education, and long-term capability building. The lessons drawn from participants' experiences aim to improve the outcomes and sustainability of current and future outbreak management strategies.

Cost-Effectiveness of Nirmatrelvir/Ritonavir in COVID-19 Patients at High-Risk for Progression in Spain

The objective was to estimate the cost-effectiveness of nirmatrelvir/ritonavir (NMV/r) in treating adults with COVID-19 at high-risk of developing severe COVID-19 who do not require supplemental oxygen, compared to no treatment, from the Spanish National Health System (NHS) perspective. A decision-tree for the first year followed by a two-state Markov model with annual cycles for a lifetime horizon was developed. A cohort of 1000 high-risk, symptomatic COVID-19 patients entered the decision-tree for each comparator, divided into hospitalized patients, considering their level of care, and outpatients, for whom only symptom duration was considered. Vaccination status of patients and COVID-19-specific mortality for hospitalized patients were considered. NMV/r efficacy in reducing hospitalizations, deaths and symptom days was applied. Patient quality of life and costs were included (€2024). All the parameters and assumptions were validated by experts. The model reported outputs including costs, quality-adjusted life-years (QALYs) and cost per QALY gained. NMV/r was dominant compared to no treatment, with a decrease in cost per patient of €169.69 and an increase in QALYs of 0.05. NMV/r is a dominant option compared to no treatment in high-risk adult patients with symptomatic COVID-19 not requiring supplemental oxygen, from the Spanish NHS perspective.

Effect of Comorbidities on the Mortality of Patients With COVID-19: A Systematic Review of Reviews and Meta-Analyses

Studies with strong scientific evidence have demonstrated that comorbidities are associated with fatal outcomes in patients with SARS-CoV-2 infection. To aggregate the findings of these studies and assess the magnitude of the effect of different chronic diseases on COVID-19 mortality, we conducted a systematic review of reviews and meta-analysis. Six databases were searched to retrieve systematic reviews with meta-analysis published during the early years of the pandemic. Statistical analysis was performed using Stata v.12.0 software, and the risk ratio (RR) and odds ratio (OR), with a confidence interval of 95% (95% CI), were calculated. We selected 15 publications with 476 original articles and 2,135,888 patients. Our results indicated the following risk factors for COVID-19 mortality: diabetes mellitus (RR = 1.95; 95% CI:1.41-2.49); hypertension (RR = 1.88; 95% CI:1.51-2.26); cancer (RR = 1.84; 95% CI:1.24-2.43); cardiovascular (RR = 2.14; 95% CI:1.66-2.63), cerebrovascular (RR = 2.43; 95% CI:2.15-2.72), kidney (RR = 2.39; 95% CI:1.36-3.42), pulmonary (RR = 1.98; 95% CI:1.48-2.47) and liver diseases (OR = 1.56; 95% CI:1.18-1.94); obesity (OR = 1.15; 95% CI:1.04-1.26); smoking habits (OR = 1.18; 95% CI:1.13-1.22); and the male sex (OR = 1.69; 95% CI:1.65-1.73). Evidence has confirmed that underlying chronic conditions, which involve an imbalance in the immune response, significantly increase the risk of COVID-19 deaths.

The burden of COVID-19 mortality among solid organ transplant recipients in the United States

Solid organ transplant recipients (SOTRs) have a heightened risk of adverse coronavirus disease 2019 (COVID-19) outcomes because of immunosuppression and medical comorbidity. We quantified the burden of COVID-19 mortality in United States (US) SOTRs. A sample of deaths documented in the US solid organ transplant registry from June 2020 through December 2022 was linked to the National Death Index to identify COVID-19 deaths and weighted to represent all SOTR deaths during the study period. Among 505 757 SOTRs, 57 575 deaths occurred, and based on the linkage, 12 396 (21.5%) were due to COVID-19. COVID-19 mortality was higher in males (mortality rate ratio [MRR]: 1.13), SOTRs aged 65 years and older (MRR: 1.50 in ages 65-74 vs ages 55-64 years), and non-Hispanic Black and Hispanic SOTRs (MRRs: 1.55 and 1.79 vs non-Hispanic White SOTRs). Kidney and lung recipients had the highest COVID-19 mortality, followed by heart, and then liver recipients. COVID-19 mortality also varied over time and across US states. Overall, SOTRs had a 7-fold increased risk of COVID-19 death compared to the US general population. SOTRs comprised 0.13% of the US population but accounted for 1.46% of all US COVID-19 deaths. SOTRs experience greatly elevated COVID-19 mortality. Clinicians should continue to prioritize COVID-19 prevention and treatment in this high-risk population.

Mapping the viral battlefield: SARS-CoV-2 infection dynamics among healthcare workers in Brazil

BACKGROUND

Understanding the dynamics of SARS-CoV-2 viral infection and factors associated with in-hospital transmission rates among healthcare workers (HCW) is crucial for their protection. Brazil experienced high mortality rates due to COVID-19, and limited data are available on transmission of SARS-CoV-2 infection among HCW. This cohort study aimed to assess the dynamic of SARS-CoV-2 infections in HCW from two tertiary hospitals in central Brazil, one of them a Reference Hospital for COVID-19.

METHODS

From May 2020 to January 2021, 554 HCW directly involved with COVID-19 care were followed through 12 biweekly visits. During these visits, blood, nasal, and oropharyngeal samples were collected, and participants underwent interviews. SARS-CoV-2 detection was carried out using RT-qPCR, while the assessment of seroprevalence was based on IgG detection. Additionally, 35 positive samples underwent viral whole-genome sequencing.

RESULTS

The infection prevalence, as per RT-qPCR, was 28.5% (24.9-32.4), reflecting an overall attack rate ranging from 0.5% to 9.5%, marked by two peaks in August and December 2020. Oligosymptomatic and asymptomatic infections accounted for 14% of prevalent infections. The seroprevalence rate stood at 25.8%. The hospitalization rate was 8.2%, with a fatality rate of 1.3%. Risk factors associated with a positive diagnosis of COVID-19 included being male, working at the referral hospital, having a graduate-education level, and using hydroxychloroquine and zinc for prevention or treatment. One reinfection was identified. Absenteeism was 56.6%. The infection dynamics mirrored the pattern observed in the general population.

CONCLUSION

One-third of the professionals in the followed cohort were infected. Being male, working in a COVID-19 referral center, having a low level of education, and using medications for preventive treatment represented risk factors. Healthcare workers at the COVID-19 referral hospital exhibited a higher incidence rate compared to those at the non-referral hospital, increasing the plausibility that some of the infections occur in the hospital environment.

COVID-19 in the years 2020 to 2022 in Germany: effects of comorbidities and co-medications based on a large-scale database analysis

BACKGROUND

The SARS-CoV-2 pandemic was a challenge for health care systems worldwide. People with pre-existing chronic diseases have been identified as vulnerable patient groups. Furthermore, some of the drugs used for these chronic diseases such as antihypertensive drugs have been discussed as possible influencing factors on the progression of COVID-19. This study examines the effect of medication- and morbidity-associated risk factors suspected to moderate the disease course and progression of COVID-19.

METHODS

The study is based on claims data of the Techniker Krankenkasse, Germany's largest statutory health insurance. The data cover the years 2020 to 2022 and include insured persons with COVID-19 diagnosis from both the outpatient and inpatient sectors and a control of insured persons without COVID-19 diagnosis. We conducted a matched case-control study and matched each patient with an inpatient diagnosis of COVID-19 to (a) 10 control patients and (b) one patient with an outpatient diagnosis of COVID-19 to form two study cohorts. We performed a descriptive analysis to describe the proportion of patients in the two cohorts who were diagnosed with comorbidities or medication use known to influence the risk of COVID-19 progression. Multiple logistic regression models were used to identify risk factors for disease progression.

RESULTS

In the first study period the first study cohort comprised a total of 150,018 patients (13,638 cases hospitalised with COVID-19 and 136,380 control patients without a COVID-19 infection). Study cohort 2 included 27,238 patients (13,619 patients hospitalised with COVID-19 and 13,619 control patients with an outpatient COVID-19 diagnosis). Immunodeficiencies and use of immunosuppressives were strongest risk modifying factors for hospitalization in both study populations. Other comorbidities associated with hospitalization were diabetes, hypertension, and depression.

CONCLUSION

We have shown that hospitalisation with COVID-19 is associated with past medical history and medication use. Furthermore, we have demonstrated the ability of claims data as a timely available data source to identify risk factors for COVID-19 severity based on large numbers of patients. Given our results, claims data have the potential to be useful as part of a surveillance protocol allowing early-stage access to epidemiological data in future pandemics.

Real-world cost-effectiveness of nirmatrelvir-ritonavir as treatment for SARS-CoV-2 infection in the Belgian setting with omicron variant

Background

Nirmatrelvir-ritonavir is an oral treatment for SARS-CoV-2 infection in patients who are at high risk of developing severe COVID-19 disease. This antiviral has proven to significantly reduce the risk of hospitalization and death compared to no anti-SARS-CoV-2 treatment in this target population. This paper aims to assess the cost-effectiveness of nirmatrelvir-ritonavir in Belgium using real-world evidence.

Methods

A static decision tree model was developed to capture the health progression of patients infected with the SARS-CoV-2 virus. Outcomes were expressed in Quality Adjusted-Life Years (QALYs), hospitalizations, Intensive Care Unit (ICU) admissions, deaths and Long Covid cases, derived from epidemiological data over the first full year of the Omicron variant's circulation (2022). Costs were calculated for the year 2023 from the healthcare payer's perspective. Extensive sensitivity analyses were conducted to test the robustness of the cost-effectiveness results.

Results

In a cohort of 1,000 patients, treatment with nirmatrelvir-ritonavir is projected to save 95 QALYs and €82,658 compared to no anti-SARS-CoV-2 treatment over a lifetime horizon. These savings primarily stem from the reduction in hospitalizations among vulnerable patients who typically require a longer recovery time. The analysis also indicates 5 fewer ICU admissions and 8 fewer premature deaths per 1,000 infected patients.

Conclusion

In the context of Omicron SARS-CoV-2 infection, administering nirmatrelvir-ritonavir to patients at high risk of severe disease improves health outcomes and reduces costs. Nirmatrelvir-ritonavir is 100% likely to be cost-effective at a willingness to pay of €2,000 per QALY.

FIB-4 Index Can Predict Mortality in Hospitalized Patients with COVID-19 Infection, Independent of CT Severity Score

BACKGROUND

The fibrosis 4 (FIB-4) index is typically used in assessing liver fibrosis, and has shown potential in predicting the outcome in various diseases. This study aims to evaluate the predictive power of the FIB-4 index for mortality in COVID-19 patients admitted to a reference hospital in Tehran, Iran.

METHODS

In this prospective cohort study, 387 patients with COVID-19 without diabetes, were categorized into deceased and surviving groups. We compared anthropometric and demographic data, liver function tests, CT scores, and FIB-4 indices between the groups. Multivariate logistic regression assessed the independent association of FIB-4 with mortality.

RESULTS

Among the 387 patients, (all non-diabetics), 58 (15%) died, with a higher mortality rate observed in patients with a FIB-4 index≥2.6 (63.4%) compared to those with FIB-4<2.6 (29.7%). Deceased patients were considerably older and more likely to be hypertensive (P values<0.001). After adjustment of confounding factors, a FIB-4 index≥2.6 was found to be independently associated with increased mortality (OR: 13.511, 95% CI: 1.356-134.580, P=0.026).

CONCLUSION

The FIB-4 index, calculable by routine laboratory tests, may be a valuable prognostic factor for COVID-19 mortality. This easily obtainable marker could help identify high-risk patients early, potentially allowing for more rapid intervention and treatment prioritization.

Factors Associated with Self-reported COVID-19 Infection and Hospitalization among Patients Seeking Care at a Comprehensive Cancer Center

BACKGROUND

COVID-19 infection severity differs by race and ethnicity, but its long-term effect on cancer-related outcomes is unknown. Therefore, information on COVID-19 history is critical to ascertain among new cancer patients in order to advance research on its impact on cancer outcomes and potentially related health disparities.

METHODS

A cross-sectional study was conducted among 16,025 new patients seeking care at Moffitt Cancer Center (MCC) between 2021 and 2022. Patient self-reported histories of COVID-19 infection and other pre-existing health conditions were obtained from electronic questionnaires administered to all new MCC patients. Associations between demographics and COVID-19 infection and hospitalization were examined.

RESULTS

A total of 1,971 patients (12.3%) reported ever having COVID-19. Self-reported COVID-19 history was significantly more prevalent in Hispanic vs. non-Hispanic patients (OR = 1.24, 1.05-1.45) and less prevalent in Asian versus White patients (OR = 0.49, 95% 0.33-0.70). Among patients who ever had COVID-19, 10.6% reported a COVID-19-related hospitalization. Males had higher odds of a COVID-19 related hospitalization than females (OR = 1.50, 95% CI = 1.09-2.05), as did Black/African American patients (OR = 2.11, 95% CI = 1.18-3.60) and patients of races other than Black/African American and Asian (OR = 2.61, 95% CI = 1.43-4.54) compared to White patients. Hispanic patients also experienced higher odds of hospitalization (OR = 2.06, 95% CI-1.29- 3.23) compared with non-Hispanic patients of all races in a sensitivity analysis that combined race/ethnicity. Pre-existing lung and breathing problems were associated with higher odds of being hospitalized with COVID-19 (OR = 2.38, 95% CI = 1.61-3.48), but these and other health conditions did not explain the observed associations between race and COVID-19 hospitalization.

CONCLUSIONS

Higher rates of COVID-19 hospitalization were observed among patients identifying as Black/African American or Hispanic independent of pre-existing health conditions. Future studies evaluating long-term effects of COVID-19 should carefully examine potential racial/ethnic disparities in cancer outcomes.

Understanding excess mortality during COVID in Belgium: the influence of pre-existing health status and social factors

BACKGROUND

This study aims to investigate how pre-existing health status and social background contribute to excess mortality during the COVID-19 crisis in Belgium.

METHODS

The study population consists of almost 1.4 million adult members of Solidaris, the second largest health insurance fund in Belgium. Pre-existing health status was identified using health care reimbursement data, including medication use. Social characteristics included a proxy for low socio-economic status, nationality of origin, and living arrangement. Excess mortality during the COVID-19 crisis was measured by computing the relative difference between all-cause mortality in 2020 or 2021 and the average yearly mortality in 2015-2019. Directly Standardised Mortality Rates (DSMRs) were calculated to investigate absolute mortality inequalities. Mortality Rate Ratios (MRRs) were computed using Poisson regression analyses to investigate relative mortality inequalities.

RESULTS

DSMRs show that persons with no previous disease experienced significant excess mortality in 2020, like men with one, two or three diseases and women with various numbers of pre-existing diseases. Results by specific disease show heterogenous results. After adjusting for age, sex and social characteristics, persons with cancer experienced a significant mortality deficit of 17% in 2020 and of 9% in 2021. For persons with cancer and asthma or COPD, significant mortality deficits of 10% and  3% were observed in 2020 and 2021, respectively.

CONCLUSION

The study provides insights into the complex dynamics of mortality during the COVID-19 crisis, emphasising the need to consider individual-level information on pre-existing health and social background jointly.

Predictors of developing severe COVID-19 among hospitalized patients: a retrospective study

Background

COVID-19 poses a significant threat to global public health. As the severity of SARS-CoV-2 infection varies among individuals, elucidating risk factors for severe COVID-19 is important for predicting and preventing illness progression, as well as lowering case fatality rates. This work aimed to explore risk factors for developing severe COVID-19 to enhance the quality of care provided to patients and to prevent complications.

Methods

A retrospective study was conducted in Saudi Arabia's eastern province, including all COVID-19 patients aged 18 years or older who were hospitalized at Prince Saud Bin Jalawi Hospital in July 2020. Comparative tests as well as both univariate and multivariate logistic regression analyses were performed to identify risk factors for developing severe COVID-19 and poor outcomes.

Results

Based on the comparative statistical tests patients with severe COVID-19 were statistically significantly associated with older age and had higher respiratory rate, longer hospital stay, and higher prevalence of diabetes than non-severe cases. They also exhibited statistically significant association with high levels of potassium, urea, creatinine, lactate dehydrogenase (LDH), D-dimer, and aspartate aminotransferase (AST). The univariate analysis shows that having diabetes, having high severe acute respiratory infection chest X-ray scores, old age, prolong hospitalization, high potassium and lactate dehydrogenase, as well as using insulin, heparin, corticosteroids, favipiravir or azithromycin were all statistically significant associated with severe COVID-19. However, after adjustments in the multivariate analysis, the sole predictor was serum LDH (p = 0.002; OR 1.005; 95% CI 1.002-1.009). In addition, severe COVID-19 patients had higher odds of being prescribed azithromycin than non-severe patients (p = 0.001; OR 13.725; 95% CI 3.620-52.043). Regarding the outcomes, the median hospital stay duration was statistically significantly associated with death, intensive care unit admission (ICU), and mechanical ventilation. On the other hand, using insulin, azithromycin, beta-agonists, corticosteroids, or favipiravir were statistically significantly associated with reduced mortality, ICU admission, and need of mechanical ventilation.

Conclusion

This study sheds light on numerous parameters that may be utilized to construct a prediction model for evaluating the risk of severe COVID-19. However, no protective factors were included in this prediction model.

The relationship between anxiety, depression, and COVID-19 diagnosis in term pregnancy: a hospital-based Romanian study

Background and aim

There are few published data on the mental health problems of women with pregnancy complicated by SARS-CoV-2 infection. Our study aimed to evaluate anxiety and depression related to a COVID-19 diagnosis in women who gave birth in a Romanian tertiary maternity.

Methods

A hospital-based cross-sectional study was conducted between September 2020 and October 2021 on 105 women admitted for term delivery; 51 women were diagnosed with SARS-CoV-2 infection just before delivery, and 54 without infection. Participants were assessed during the first 72 hours postpartum (T1) and the following two weeks postpartum (T2). Hospital Anxiety and Depression Scale (HADS) was used for anxiety and depression assessment at T1. The COVID-19 Pandemic Mental Health Questionnaire (CoPaQ) was applied at T2 only in the COVID-positive cases identified at T1.

Results

Postnatal anxiety levels were higher in COVID-positive women compared to COVID-negative women (p = .004), but there were no differences in the postnatal depression level between the groups. Psychological manifestations related to the pandemic, such as contamination anxiety, posttraumatic stress disorder (PTSD), and obsessive-compulsive disorder (OCD) symptoms, were positively related to HADS anxiety scores, while maintaining social relationships were negatively associated with the scale. The COVID-19 diagnosis was found to be a significant predictor for adverse pregnancy outcomes (APOs), with COVID-positive women having a 4.72-fold higher risk of developing them than those who tested COVID-negative (OR=4.72, 95% CI [2.05; 10.86]). The multivariate analysis using anxiety and depression as dependent variables indicated a significant effect for COVID-19 diagnosis, Wilks' Lambda = 0.940, p = 0.048.

Conclusion

Increased levels of anxiety, PTSD, and obsessive-compulsive symptoms were associated with the postpartum period in pregnant women with COVID-19 infection during delivery. Maintaining social interaction proved to be a protective factor against the increased anxiety reported by COVID-19-infected women.

Association between demographic, clinical characteristics and severe complications by SARS-CoV-2 infection in a community-based healthcare network in Chile

BACKGROUND

Most of the evidence on risk factors for COVID-19 complications comes from North America or Europe with very little research from Latin-America. We aimed to evaluate the association between sociodemographic, clinical factors and the risk of COVID-19 complications among adults in Chile, the fifth Latin-American country with more COVID-19 reported cases since de beginning of the Pandemic.

METHODS

A retrospective population-based cohort study using data from electronic health records from a large Primary Care Network, linked to national hospital, immunization, Covid-19 PCR surveillance, mortality and birth records. We included people 18+ years old enrolled in the Primary Care Network between 1st January 2020 and 31st December 2021. Using Multivariate Cox proportional hazard models, we evaluate the association between sociodemographic, clinical characteristics with three COVID-19 complications: (1) a hospital admission, (2) an ICU admission, and (3) death due to a COVID-19 infection that occurred between the 1st January 2020 and the 31st December 2021.

RESULTS

44,674 people were included. The mean age was 44.30 (sd 17.31), 55.6% were female, 15.9% had a type of healthcare insurance for people from the lowest category of income, 11.6% and 9.4% had a record of hypertension or diabetes mellitus diagnosis. Among the 44,674 people, 455 (1.02%) had a hospital admission due to a COVID-19 infection and 216(0.48%) of them also had an ICU admission. Among the 44,674 people,148(0.33%) died due to COVID-19 infection. Older age and male sex were consistently associated with a higher risk of the three COVID-19 complications. Hypertension and diabetes were associated with a higher risk of a hospital admission and death, but not with an ICU admissions due to COVID-19 infection. Having two or more COVID-19 vaccine doses compared with no doses was associated with a lower risk of any hospital admission (HR 0.81; 95% CI 0.77-0.84), an ICU admission (HR 0.60; 95% CI 0.57-0.63) and death (HR 0.50; 95% CI 0.46-0.54). Pregnant or puerperal women were more likely to be admitted to hospital (HR 2.89; 95% CI 1.41-5.89) or ICU (HR 3.04; 95% CI 1.01-9.14).

CONCLUSIONS

Sociodemographic and clinical factors associated with COVID-19 complications such as age, sex and pre-existing conditions were comparable to those reported in similar studies from higher-income countries, and can be used to predict severity in COVID-19 patients.

SARS-CoV-2 risk factors among symptomatic vaccinated adults attending community testing locations in the Netherlands from June 2021 till February 2022

INTRODUCTION

Most studies on risk factors for a SARS-CoV-2 infection were conducted in the pre-vaccination era with many non-pharmaceutical prevention measures in place. We investigated risk factors for symptomatic SARS-CoV-2 infections in vaccinated persons in a period with a varying degree of prevention measures.

METHODS

In a test-negative case control study among vaccinated adults attending community COVID-19 testing locations between June 1st 2021 till February 28th 2022, we compared symptomatic cases with symptomatic controls (to study risk factors specific for SARS-CoV-2) and with asymptomatic controls (to study risk factors that could apply to respiratory infections in general). We examined potential risk factors including household composition and mitigation behaviour by logistic regression, adjusting for age, sex, and week of testing.

RESULTS

Risk factors for a positive SARS-CoV-2 test when symptomatic cases were compared to symptomatic controls were: having a household size of more than 4 (adjusted odds ratio: 1.47; 95% CI 1.14-1.92), being a healthcare worker (1.27;1.18-1.47), and visiting busy locations outside (1.49;1.19-1.87). When symptomatic cases were compared to asymptomatic controls, a household size of more than 4 members (1.71;1.25-2.33), living with children aged 0-12 (1.59;1.12-2.26), visiting busy locations outside (1.64;1.24-2.17) were independent risk factors for a positive SARS-CoV-2 test. Risk factors for separate periods and waves differed from the study period as a whole.

CONCLUSION

This study was conducted in a period with a varying degree of prevention measures. Among vaccinated individuals, we identified several SARS-CoV-2 specific risk factors and SARS-CoV-2 risk factors that could be more general for respiratory infections. For SARS-CoV-2 transmission more attention could be given to visiting busy outdoor locations, having a household size that consists of more than 4 persons, being a healthcare worker, and living with children aged 0-12. Risk factors varied with different phases in the pandemic, emphasizing the importance of repeated assessment of risk factors.

Predictors of high-flow nasal cannula (HFNC) failure in severe community-acquired pneumonia or COVID-19

The aim was to identify predictors for early identification of HFNC failure risk in patients with severe community-acquired (CAP) pneumonia or COVID-19. Data from adult critically ill patients admitted with CAP or COVID-19 and the need for ventilatory support were retrospectively analysed. HFNC failure was defined as the need for invasive ventilation or death before intubation. 60 patients with CAP and 185 with COVID-19 were included. 27 (45%) patients with CAP and 69 (37.3%) patients with COVID-19 showed HFNC failure. Lower oxygenation index, lower respiratory oxygenation (ROX) index, and higher respiratory rate at the start of HFNC were significantly associated with HFNC failure. ROC-analysis identified a respiratory rate of 27/min as the optimal cut-off for predicting HFNC failure, with a specificity of 59% and a sensitivity of 75%, and an oxygenation index after HFNC initiation of 99.6 (specificity 81%, sensitivity 74%). In COVID-19, an elevated CRB65-score at hospital admission and at HFNC-initiation was significantly associated with HFNC failure. In CAP and COVID patients an oxygenation index < 99.6, a respiratory rate > 27/min and a ROX index < 4.88 were predictors for HFNC failure whereas a CRB65 score > 3 at hospital admission and > 2 at HFNC start was predictive for HFNC failure in COVID-19.

Follow-up of patients with chronic conditions within primary care practices during COVID-19: Results from 7 Central and Eastern-European countries from the cross-sectional PRICOV-19 study

BACKGROUND

The COVID-19 pandemic posed severe challenges to delivery of services at Primary Care level and for achieving follow-up of patients with chronic diseases.

OBJECTIVES

We analysed data from the PRICOV-19 study to explore determinants of active follow-up for chronic disease patients in seven Central and Eastern European (CEE) countries during the pandemic.

METHODS

Pricov-19 was a cross-sectional study conducted within PC (Primary Care) practices in 37 European countries. We analysed data from 7 CEE countries (Bulgaria, Czech Republic, Hungary, Poland, Moldova, Romania, Ukraine) collected between November 2020 and December 2021. Practices were recruited through random or convenience sampling and participation of practices was voluntary. We performed descriptive statistics to identify the level of follow-up of chronic disease and what health system and practice-specific factors were associated with better follow-up. We used logistic regression and meta-analysis techniques to explore associations and heterogeneity between countries.

RESULTS

67.8% out of 978 practices reported actively following up chronic patients. Positive associations were found between active follow-up and such as having more GPs (aOR = 1.18, p-value = 0.005), an above-average chronic patient population (aOR = 3.13, p-value = 0.006), adequate government support (aOR = 2.35, p-value = 0.001), and GPs having time for guideline reading (aOR = 0.008, p-value = 1.71).

CONCLUSIONS

Patient follow-up, was influenced by different health system and practice-specific factors. The implications suggest the need for government support to enhance PC practice organisation during crises and solutions to decrease GP workload and provide tailored care for patients with chronic disease.

The role of perceived risk on dishonest decision making during a pandemic

The COVID-19 pandemic presented serious risks to the health and financial wellbeing of millions of people across the world. While many individuals adapted to these challenges through a variety of prosocial and protective behaviors (e.g., social distancing, working from home), many others also engaged in dishonest behaviors (e.g., lying to obtain vaccines or furlough payments). Hence, the COVID-19 pandemic provided a unique context in which to obtain a better understanding of the relationship between risk and dishonesty. Across three preregistered studies, we assessed whether objective risk and perceived risk influenced the decision to behave dishonestly in order to gain access to vaccines and furlough payments during a pandemic. We also assessed the extent to which such dishonesty was deterred by the probability of the dishonesty being detected. We found that heightened health risk perceptions were positively related with lying to obtain a vaccine (Studies 1 and 2), but found no evidence of the same relationship between financial risk perceptions and lying to access furlough payments (Study 2). We also found that the probability of dishonesty being detected had a negative relationship with dishonest behavior (Study 3). In addition, across the three studies, we found that (i) dishonesty was consistently evident in approximately one-third of all of our samples, and (ii) greater dishonesty was associated with older age. We discuss how our findings could be utilized by policy makers to better deter and detect dishonest behaviors during future similar crises.

Variation in the Impact of New York on Pause on Traffic Congestion by Racialized Economic Segregation and Environmental Burden

During the 2019 coronavirus pandemic, stay-at-home policies such as New York's (NY) NY on Pause dramatically reduced traffic congestion. Despite high traffic burden in NY's environmental justice communities, this reduction has not been evaluated through an environmental justice lens-our objective in this analysis. We obtained census tract-level traffic congestion data from Google traffic maps hourly for 2018-2020. We defined congestion as the percent of streets in a census tract with heavy traffic (red- or maroon-color). We used the Index of Concentration at the Extremes (ICE) to measure racialized economic segregation and the CDC's Environmental Justice Index (EJI) as a measure of combined environmental, social, and chronic disease burden. We divided census tracts into quintiles of ICE and EJI and used linear mixed models stratified by ICE and EJI quintile in an interrupted time series design. Prior to NY on Pause, less marginalized and burdened census tracts (Q5) tended to have higher levels of traffic congestion; during NY on Pause, this trend reversed. For both ICE and EJI, more marginalized and burdened (Q1-Q2 vs. Q4-Q5) tracts had smaller absolute decreases in percent traffic congestion. For example, percent traffic congestion in ICE Q5 decreased by 7.8% (% change: -36.6%), but in Q1, it decreased by 4.2% (% change: -51.7%). NY on Pause, while protecting residents during COVID-19, may have resulted in inequitable reductions in traffic congestion. It is critical that such inequities are measured and acknowledged so that future policies to reduce traffic congestion and respond to pandemics can enhance equity.

Susceptibility to and severity of SARS-CoV-2 infection according to prescription drug use-an observational study of 46,506 Danish healthcare workers

It is not well investigated whether exposure to specific drug classes is associated with COVID-19. We investigated the risk of SARS-CoV-2 infection and severe COVID-19 among healthcare workers according to prescription drug use. We conducted an observational study among Danish healthcare workers. SARS-CoV-2 positivity was defined as a positive PCR/ELISA test throughout 2020 and severe COVID-19 as any above 48-hour hospitalization within 14 days after infection. Patient characteristics came from online surveys while data on SARS-CoV-2, drugs and hospitalizations came from Danish Health Registers. Infected individuals were matched with uninfected controls based on age, sex, and chronic diseases. Drug exposure was defined as any prescription redemption in the past six and one month(s) before infection for each drug class. Models assessing the risk of infection (conditional logistic regression) and severe COVID-19 (logistic regressions) versus drug usage were adjusted for BMI, smoking, alcohol, education, region, and patient contact when possible. We matched 5,710 SARS-CoV-2-infected cases with 57,021 controls. The odds of infection were reduced by calcium channel blocker (adjusted odds ratio (aOR) 0.81, 95% Confidence Interval (CI): 0.66-1.00) and vasoprotective drug (aOR 0.77, CI: 0.62-0.95) usage during the six months before infection compared to no usage. Exposure to antibacterials in the past month increased the odds of infection (aOR 1.27, CI: 1.09-1.48). Among infected participants, the odds of severe COVID-19 were higher with usage of almost any investigated drug, especially, diuretics (crude odds radio (OR) 4.82, CI:2.15-10.83), obstructive airway disease drugs (OR 4.49, CI: 2.49-8.08), and antibacterials (OR 2.74 CI:1.62-4.61). In conclusion, antibacterials were associated with more SARS-CoV-2 infections and calcium channel blockers with less. Once infected, users of prescription drugs had higher odds of developing severe COVID-19. These findings suggest a need for studies to clarify interactions between specific drug groups, behaviour, known risk factors, and disease susceptibility/severity.

Unravelling demographic and socioeconomic patterns of COVID-19 death and other causes of death: results of an individual-level analysis of exhaustive cause of death data in Belgium, 2020

BACKGROUND

The COVID-19 pandemic led to significant excess mortality in 2020 in Belgium. By using microlevel cause-specific mortality data for the total adult population in Belgium in 2020, three outcomes were considered in this study aiming at predicting sociodemographic (SD) and socioeconomic (SE) patterns of (1) COVID-19 specific death compared to survival; (2) all other causes of death (OCOD) compared to survival; and (3) COVID-19 specific death compared to all OCOD.

METHODS

Two complementary statistical methods were used. First, multivariable logistic regression models providing odds ratios and 95% confidence intervals were fitted for the three study outcomes. In addition, we computed conditional inference tree (CIT) algorithms, a non-parametric class of classification trees, to identify and rank by significance level the strongest predictors of the three study outcomes.

RESULTS

Older individuals, males, individuals living in collectivities, first-generation migrants, and deprived SE groups experienced higher odds of dying from COVID-19 compared to survival; living in collectivities was identified by the CIT as the strongest predictor followed by age and sex. Education emerged as one of the strongest predictors for individuals not living in collectivities. Overall, similar patterns were observed for all OCOD except for first- and second-generation migrants having lower odds of all OCOD compared to survival; age group was identified by the CIT as the strongest predictor. Older individuals, males, individuals living in collectivities, first- and second-generation migrants, and individuals with lower levels of education had higher odds of COVID-19 death compared to all OCOD; living in collectivities was identified by the CIT as the strongest predictor followed by age, sex, and migration background. Education and income emerged as among the strongest predictors among individuals not living in collectivities.

CONCLUSIONS

This study identified important SD and SE disparities in COVID-19 mortality, with living in collectivities highlighted as the strongest predictor. This underlines the importance of implementing preventive measures, particularly within the most vulnerable populations, in infectious disease pandemic preparedness to reduce virus circulation and the resulting lethality.

Sex Differences in Long-Term Cardiovascular Outcomes and Mortality After COVID-19 Hospitalization During Alpha, Delta and Omicron Waves

Background: Increased mortality and occurrence of cardiovascular (CV) outcomes during hospitalization and in short-term follow-up for moderate to severe SARS-CoV-2 infection have been associated with male sex, yet data regarding long-term outcomes by sex and COVID-19 variant (Alpha, Delta, and Omicron) are limited. Methods: This prospective study of 4882 patients examines potential differences by sex in the occurrence of primary combined cardiovascular outcomes (CV death, CV hospitalization, myocardial infarction (MI), stroke, pulmonary embolism) as well as secondary outcomes (CV death, cardiovascular hospitalizations, myocardial infarction, stroke, pulmonary embolism) at 18-month follow-up after urgent hospitalization for SARS-CoV-2-associated pneumonia, as well as evaluating for differences during the three COVID-19 waves. Survival rate was analyzed for the entire cohort by sex and SARS-CoV-2 variant and adjusted for age using the multiple Kaplan-Meier method. To compare survival in groups of men and women for each wave, the Gehan-Wilcoxon test was applied with significance p < 0.05. Univariate Cox proportional hazards models were used to search for potential risk factors of CV death at 18-months follow-up separately for men and women in each COVID-19 wave. Results: Men had significantly higher 18-month CV mortality compared to women in the Delta wave (6.13% men vs. 3.62% women, p = 0.017). Although men had higher percentages of all other CV endpoints (excepting pulmonary embolism) at follow-up during the Delta wave, none were significant compared with women, except for the combined CV endpoint (16.87% men vs. 12.61% women, p = 0.017). No significant differences by sex in CV outcomes were seen during the Alpha and Omicron variants. Discrepancies in CV outcomes in demographical data and concomitant disease between the COVID-19 variants of concern existed. Conclusions: Higher male mortality and higher but non-significant incidences of CV outcomes occurred during the Delta wave of the COVID-19 pandemic, with the lowest incidence of CV outcomes observed during the Omicron variant.

Association of chronic opioid therapy and opioid use disorder with COVID-19-related hospitalization and mortality: Evidence from three health systems in the United States

Objective

Chronic opioid use can lead to detrimental effects on the immune and various organ systems that put individuals prescribed chronic opioid therapy (COT) for pain and those with an opioid use disorder (OUD) at risk for severe COVID-19 disease. We assessed the association of COT and OUD with COVID-19-related hospitalization and death to inform targeted interventions to improve clinical outcomes in COVID-19 patients who use opioids.

Methods

We conducted a retrospective cohort study of adults ages ≥ 18 with laboratory-confirmed SARS-CoV-2 infection in 2020 and 2021 from three US health systems. We used Cox proportional hazards regression to estimate the 30-day risk of COVID-19-related hospitalization and death associated with two opioid exposures (COT and OUD) following an infection.

Results

The study cohort included 53,123 patients with SARS-CoV-2 infection and a mean (SD) age of 45.1 (16.5), of whom 1,059 (2.0 %) were exposed to COT and 269 (0.5 %) had an OUD diagnosis in the year prior to infection. There were 2,270 observed COVID-19-related hospitalizations or deaths (1.6 per 1,000 person-days, 95 % CI 1.5-1.7). In the fully adjusted model, COT was not associated with increased risk (HR 1.19; 95 % CI, 0.98-1.43), while past-year OUD was independently associated with severe COVID-19 disease (HR 1.82; 95 % CI, 1.18-2.80). Past-year OUD remained associated with increased risk in post-hoc analysis with COVID-19-related hospitalization alone as the outcome (HR 2.00; 95 % CI, 1.30-3.08).

Conclusions

Past-year OUD is a potential independent risk factor for severe COVID-19 disease that warrants monitoring to improve the prognosis of patients with COVID-19.

The association between excess weight and COVID-19 outcomes: An umbrella review

This umbrella review assessed the association between excess weight and COVID-19 outcomes. MEDLINE, PsycINFO, and CINAHL were systematically searched for reviews that assessed the association between excess weight and COVID-19 outcomes. A second-order meta-analysis was conducted on the available data for intensive care unit admission, invasive mechanical ventilation administration, disease severity, hospitalization, and mortality. The quality of included reviews was assessed using the AMSTAR-2 appraisal tool. In total, 52 systematic reviews were included, 49 of which included meta-analyses. The risk of severe outcomes (OR = 1.86; 95% CI: 1.70 to 2.05), intensive care unit admission (OR = 1.58; 95% CI: 1.45 to 1.72), invasive mechanical ventilation administration (OR = 1.70; 95% CI: 1.57 to 1.83), hospitalization (OR = 1.82; 95% CI: 1.61 to 2.05), and mortality (OR = 1.35; 95% CI: 1.24 to 1.48) following COVID-19 infection was significantly higher in individuals living with excess weight compared with those with a healthy weight. There was limited evidence available in the included reviews regarding the influence of moderating factors such as ethnicity, and the majority of included reviews were of poor quality. Obesity appears to represent an important modifiable pre-infection risk factor for severe COVID-19 outcomes, including death.

Clinical characteristics and predictors of complications and mortality in hospitalized octogenarian patients with COVID-19: an ambispective study

OBJECTIVE

This study aimed to describe the clinical presentation of COVID-19 in hospitalized patients aged 80 or above and to identify predictors for death and complications throughout the epidemic waves of the disease.

METHODS

This was an observational, multicenter, ambispective study conducted between March 2020 and August 2021 using data collected in five centers from southern metropolitan area of Barcelona (COVID-MetroSud cohort). Patients were grouped based on the pandemic waves of inclusion in the registry. We conducted a descriptive analysis, followed by bivariate and multivariate analyses (binary logistic regression) to identify predictors of risk for death or complications.

RESULTS

A total of 1192 patients (mean [SD] age 85.7 [4.22] years and 46.8% female) were included. The most frequently reported symptoms in all waves were fever (63.1%), cough (56.5%), dyspnea (48.2%), and asthenia (27.5%). Laboratory and radiological findings consistently showed abnormal bilateral chest X-ray results (72.5% of patients) and elevated inflammatory markers such as lactate dehydrogenase (mean [SD] 335 [188] U/L), C-reactive protein (CRP) (mean [SD] 110 [88.4] U/L), and ferritin (mean [SD] 842 [1561] U/L). Acute respiratory distress syndrome (43.7%), renal failure (19.2%), and delirium (17.5%) were the most frequent complications. The overall mortality rate was 41.4% and declined across the epidemic waves. Age, diabetes mellitus, heart failure, dyspnea, and higher baseline levels of creatinine were identified as risk factors for complications, while a higher Barthel index and presence of cough were found to be protective. Age, dyspnea, abnormal bilateral chest X-ray, CRP, and sodium were identified as risk factors for death.

CONCLUSIONS

This study demonstrates the clinical presentation of COVID-19 (fever, cough, dyspnea, and asthenia) and the different risk factors for mortality and complications in octogenarian hospitalized patients throughout the pandemic. These findings could be highly valuable for managing future virus pandemics.

Cholesterol and Cholesterol-Lowering Medications in COVID-19-An Unresolved Matter

Infections with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) cause coronavirus disease 2019 (COVID-19), a disease with very heterogeneous symptoms. Dyslipidaemia is prevalent in at least 20% of Europeans, and dyslipidaemia before SARS-CoV-2 infection increases the risk for severe COVID-19 and mortality by 139%. Many reports described reduced serum cholesterol levels in virus-infected patients, in particular in those with severe disease. The liver is the major organ for lipid homeostasis and hepatic dysfunction appears to occur in one in five patients infected with SARS-CoV-2. Thus, SARS-CoV-2 infection, COVID-19 disease severity and liver injury may be related to impaired cholesterol homeostasis. These observations prompted efforts to assess the therapeutic opportunities of cholesterol-lowering medications to reduce COVID-19 severity. The majority of studies implicate statins to have beneficial effects on disease severity and outcome in COVID-19. Proprotein convertase subtilisin/kexin type 9 (PCSK9) antibodies have also shown potential to protect against COVID-19. This review describes the relationship between systemic cholesterol levels, liver injury and COVID-19 disease severity. The potential effects of statins and PCSK9 in COVID-19 are summarised. Finally, the relationship between cholesterol and lung function, the first organ to be affected by SARS-CoV-2, is described.

Challenges in Diagnosis of COVID-19 Pneumonia under Ocrelizumab and De-Risking Strategies in Multiple Sclerosis-The Elephant Is (Still) in the Room

Severe SARS-CoV-2 infections may still be observed in people bearing risk factors, such as the use of anti-CD20 monoclonal antibodies (mAbs), which are adopted in several autoimmune disorders including multiple sclerosis (MS). COVID-19 diagnosis is routinely based on nasopharyngeal swab testing, but suboptimal sensitivity for SARS-CoV-2 detection compared to bronchoalveolar lavage (BAL) may lead to misdiagnosis in some cases. Such diagnostic issues were described in a few MS patients receiving anti-CD20 mAbs, including middle-aged people and lacking information on subsequent MS therapeutic management, a debated topic as no evidence-based guidance on de-risking strategies is currently available. Here, we report the case of a young MS patient who developed severe COVID-19 pneumonia under treatment with the anti-CD20 mAb ocrelizumab, and who was finally diagnosed with SARS-CoV-2 by BAL despite repeatedly negative nasopharyngeal swabs. Ocrelizumab was then discontinued, and treatment with a sphingosine-1 phosphate receptor modulator was started, followed by maintenance of clinical and radiological MS stability. Challenges in diagnosing COVID-19 pneumonia in people without risk factors other than immunomodulatory treatment are hence discussed, as well as potential strategies for de-risking MS therapies. The latter topic is increasingly debated based on raising concerns for potential long-term safety issues of high-efficacy treatments, including anti-CD20 mAbs.

GWAS and polygenic risk score of severe COVID-19 in Eastern Europe

Background

COVID-19 disease has infected more than 772 million people, leading to 7 million deaths. Although the severe course of COVID-19 can be prevented using appropriate treatments, effective interventions require a thorough research of the genetic factors involved in its pathogenesis.

Methods

We conducted a genome-wide association study (GWAS) on 7,124 individuals (comprising 6,400 controls who had mild to moderate COVID-19 and 724 cases with severe COVID-19). The inclusion criteria were acute respiratory distress syndrome (ARDS), acute respiratory failure (ARF) requiring respiratory support, or CT scans indicative of severe COVID-19 infection without any competing diseases. We also developed a polygenic risk score (PRS) model to identify individuals at high risk.

Results

We identified two genome-wide significant loci (P-value <5 × 10-8) and one locus with approximately genome-wide significance (P-value = 5.92 × 10-8-6.15 × 10-8). The most genome-wide significant variants were located in the leucine zipper transcription factor like 1 (LZTFL1) gene, which has been highlighted in several previous GWAS studies. Our PRS model results indicated that individuals in the top 10% group of the PRS had twice the risk of severe course of the disease compared to those at median risk [odds ratio = 2.18 (1.66, 2.86), P-value = 8.9 × 10-9].

Conclusion

We conducted one of the largest studies to date on the genetics of severe COVID-19 in an Eastern European cohort. Our results are consistent with previous research and will guide further epidemiologic studies on host genetics, as well as for the development of targeted treatments.

Lessons from the COVID-19 pandemic to strengthen NCD care and policy in humanitarian settings: a mixed methods study exploring humanitarian actors' experiences

BACKGROUND

The COVID-19 pandemic and response severely impacted people living with non-communicable diseases (PLWNCDs) globally. It exacerbated pre-existing health inequalities, severely disrupted access to care, and worsened clinical outcomes for PLWNCDs, who were at higher risk of morbidity and mortality from the virus. The pandemic's effects were likely magnified in humanitarian settings, where there were pre-existing gaps in continuity of care for non-communicable diseases (NCDs). We sought to explore factors affecting implementation of NCD care in crisis settings during the COVID-19 pandemic and the adaptations made to support implementation.

METHODS

Guided by the Consolidated Framework for Implementation Research, we undertook an online survey of 98 humanitarian actors from multiple regions and organization types (March-July 2021), followed by in-depth interviews with 13 purposively selected survey respondents (October-December 2021). Survey data were analysed using descriptive statistics, while interview data were analysed thematically, using both deductive and inductive approaches.

RESULTS

Initially, humanitarian actors faced challenges influenced by external actors' priorities, such as de-prioritisation of NCD care by governments, travel restrictions and supply chain interruptions. With each infection wave and lockdown, humanitarian actors were better able to adapt and maintain NCD services. The availability of COVID-19 vaccines was a positive turning point, especially for the risk management of people with NCDs and protection of health workers. Key findings include that, despite pre-existing challenges, humanitarian actors largely continued NCD services during the crisis. Enabling factors that supported continuity of NCD services included the ability to quickly pivot to remote means of communication with PLWNCDs, flexibility in medicine dispensing, and successful advocacy to prioritize NCD management within health systems. Key lessons learned included the importance of partnerships and cooperation with other health actors, and the mobilisation or repurposing of community health workers/volunteer networks.

CONCLUSIONS

The COVID-19 experience should prompt national and global health stakeholders to strengthen inclusion of NCDs in emergency preparedness, response, and resilience planning. Key lessons were learned around remote care provision, including adapting to NCD severity, integrating community health workers, providing context-adapted patient information, combating misinformation, and strengthening cross-sectoral partnerships.

A Brighton Collaboration standardized template with key considerations for a benefit-risk assessment for the Comirnaty COVID-19 mRNA vaccine

The Brighton Collaboration Benefit-Risk Assessment of VAccines by TechnolOgy (BRAVATO) Working Group evaluates the safety and other key features of new platform technology vaccines, including nucleic acid (RNA and DNA) vaccines. This manuscript uses the BRAVATO template to report the key considerations for a benefit-risk assessment of the coronavirus disease 2019 (COVID-19) mRNA-based vaccine BNT162b2 (Comirnaty®, or Pfizer-BioNTech COVID-19 vaccine) including the subsequent Original/Omicron BA.1, Original/Omicron BA.4-5 and Omicron XBB.1.5 variant-adapted vaccines developed by BioNTech and Pfizer to protect against COVID-19 caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Initial Emergency Use Authorizations or conditional Marketing Authorizations for the original BNT162b2 vaccine were granted based upon a favorable benefit-risk assessment taking into account clinical safety, immunogenicity, and efficacy data, which was subsequently reconfirmed for younger age groups, and by real world evidence data. In addition, the favorable benefit-risk assessment was maintained for the bivalent vaccines, developed against newly arising SARS-CoV-2 variants, with accumulating clinical trial data.

Messenger Use and Video Calls as Correlates of Depressive and Anxiety Symptoms: Results From the Corona Health App Study of German Adults During the COVID-19 Pandemic

BACKGROUND

Specialized studies have shown that smartphone-based social interaction data are predictors of depressive and anxiety symptoms. Moreover, at times during the COVID-19 pandemic, social interaction took place primarily remotely. To appropriately test these objective data for their added value for epidemiological research during the pandemic, it is necessary to include established predictors.

OBJECTIVE

Using a comprehensive model, we investigated the extent to which smartphone-based social interaction data contribute to the prediction of depressive and anxiety symptoms, while also taking into account well-established predictors and relevant pandemic-specific factors.

METHODS

We developed the Corona Health App and obtained participation from 490 Android smartphone users who agreed to allow us to collect smartphone-based social interaction data between July 2020 and February 2021. Using a cross-sectional design, we automatically collected data concerning average app use in terms of the categories video calls and telephony, messenger use, social media use, and SMS text messaging use, as well as pandemic-specific predictors and sociodemographic covariates. We statistically predicted depressive and anxiety symptoms using elastic net regression. To exclude overfitting, we used 10-fold cross-validation.

RESULTS

The amount of variance explained (R2) was 0.61 for the prediction of depressive symptoms and 0.57 for the prediction of anxiety symptoms. Of the smartphone-based social interaction data included, only messenger use proved to be a significant negative predictor of depressive and anxiety symptoms. Video calls were negative predictors only for depressive symptoms, and SMS text messaging use was a negative predictor only for anxiety symptoms.

CONCLUSIONS

The results show the relevance of smartphone-based social interaction data in predicting depressive and anxiety symptoms. However, even taken together in the context of a comprehensive model with well-established predictors, the data only add a small amount of value.

Chemerin Levels in COVID-19 Are More Affected by Underlying Diseases than by the Virus Infection Itself

BACKGROUND/OBJECTIVES

Chemerin is an adipokine involved in inflammatory and metabolic diseases, and its circulating levels have been associated with inflammatory parameters in various patient cohorts. Severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) infection, which causes COVID-19, triggers inflammatory pathways. However, the association between serum chemerin levels and COVID-19 disease severity and outcomes has not been definitively established.

METHODS

In this study, serum chemerin levels were analyzed in 64 patients with moderate COVID-19 and 60 patients with severe disease.

RESULTS

The results showed that serum chemerin levels were comparable between these two groups and slightly higher than in healthy controls. Notably, COVID-19 patients with hypertension exhibited elevated serum chemerin levels, while those with liver cirrhosis had lower levels. When patients with these comorbidities were excluded from the analyses, serum chemerin levels in COVID-19 patients were similar to those in healthy controls. Positive correlations were observed between serum chemerin levels and markers such as alkaline phosphatase, C-reactive protein, eosinophils, and lymphocytes in the entire cohort, as well as in the subgroup excluding patients with hypertension and cirrhosis. Additionally, urinary chemerin levels were comparable between COVID-19 patients and controls, and neither hypertension nor dialysis significantly affected urinary chemerin levels. Both survivors and non-survivors had similar serum and urinary chemerin levels.

CONCLUSIONS

In conclusion, this study suggests that comorbidities such as arterial hypertension and liver cirrhosis do have a more significant impact on serum chemerin levels than SARS-CoV-2 infection itself.

Clinical profiles and mortality predictors of hospitalized patients with COVID-19 in Ethiopia

BACKGROUND

Studying the characteristics of hospitalized Coronavirus Disease 2019 (COVID-19) patients is vital for understanding the disease and preparing for future outbreaks. The aim of this study was to analyze and describe the clinical profiles and factors associated with mortality among COVID-19 patients admitted to Jimma Medical Center COVID-19 Treatment Center (JMC CTC) in Ethiopia.

METHODS

All confirmed COVID-19 patients admitted to JMC CTC between 17 April 2020 and 05 March 2022 were included in this study. Socio-demographic data, clinical information, and outcome variables were collected retrospectively from medical records and COVID-19 database at the hospital. Bivariable and multivariable analyses were performed to determine factors associated with COVID-19 severity and mortality. A P-value < 0.05 was considered statistically significant.

RESULTS

A total of 542 confirmed COVID-19 patients were admitted to JMC CTC, of which 322 (59.4%) were male. Their median age was 48 years (IQR 32-64). About 51% (n = 277) of them had severe COVID-19 upon admission. Patients with hypertension [AOR: 2.8 (95% CI: 1.02-7.7, p = 0.046)], diabetes [AOR: 8.8 (95% CI: 1.2-17.3, p = 0.039)], and underlying respiratory diseases [AOR: 18.8 (95% CI: 2.06-71.51, p = 0.009)] were more likely to present with severe COVID-19 cases. Overall, 129 (23.8%) died in the hospital. Death rate was higher among patients admitted with severe disease [AHR = 5.5 (3.07-9.9) p < 0.001)] and those with comorbidities such as hypertension [AHR = 3.5 (2.28-5.41), p < 0.001], underlying respiratory disease [AHR = 3.4 (1.97-5.94), p < 0.001], cardiovascular disease (CVDs) [AHR = 2.8 (1.73-4.55), p < 0.001], and kidney diseases [AHR = 3.7 (2.3-5.96), p < 0.001].

CONCLUSION

About half of COVID-19 cases admitted to the hospital had severe disease upon admission. Comorbidities such as hypertension, diabetes, and respiratory diseases were linked to severe illness. COVID-19 admissions were associated with high inpatient mortality, particularly among those with severe disease and comorbidities.

Falls in focus: an analysis of the rate of falls in 25 Australian residential aged care facilities from 2019 to 2021, pre- and during COVID-19 lockdowns

INTRODUCTION

During 2020-2021 Australia maintained comparatively low rates of COVID-19 in the community and residential aged care facilities (RAC) due to stringent public health measures such as lockdowns. However, the public health measures implemented may have had unintended impacts on critical RAC resident health outcomes, such as falls, due to routine care disruptions and aged care resident isolation. We utilised a longitudinal data to assess the association between COVID-19 lockdowns and the rate of falls in RAC settings.

METHODS

A longitudinal cohort study was conduct using routinely collected data from 25 RAC facilities from one non-profit aged care provider in Sydney, Australia. The study included 2,996 long term residents between March 2019 and March 2021. The outcome measures were all falls, injurious falls, and falls assessed as requiring hospitalisation. Generalised estimating equations (GEE) were applied to determine the association between COVID-19 lockdown periods and fall-related outcomes while adjusting for confounders and seasonality.

RESULTS

During the study period 11,658 falls were recorded. Residents frequently experienced at least one fall during the study period (median: 1, interquartile range: 0-4). During Lockdown 1 (March-June 2020) the rate of all falls increased 32% (IRR 1.32, 95% CI 1.19-1.46, p < 0.01) and the rate of injurious falls increased by 28% (IRR 1.28, 95% CI 1.12-1.46, p < 0.01) compared to pre-pandemic rates. The rate of falls assessed as requiring hospitalisation remained unchanged during Lockdown 1 (IRR 1.07, 95% CI 0.86-1.32, p = 0.519). During Lockdown 2 (Dec 2020-Jan 2021) the rate of all falls, injurious falls, and falls assessed as requiring hospitalisation did not change significantly compared to pre-pandemic rates.

CONCLUSION

These findings suggest that the consequences of stringent COVID-19 restrictions, as seen in Lockdown 1, produced changes in residents' care which contributed to more falls and associated harm. The subsequent lockdown, which were less restrictive and occurred after staff had gained experience, was associated with no significant increase in falls rate. The nature and extent of lockdowns implemented for infection control in RAC need to balance multiple potential adverse effects. Factors which facilitated resilience during this period require exploration in future research.

Surveillance strategies for the detection of new pathogen variants across epidemiological contexts

Surveillance systems that monitor pathogen genome sequences are critical for rapidly detecting the introduction and emergence of pathogen variants. To evaluate how interactions between surveillance capacity, variant properties, and the epidemiological context influence the timeliness of pathogen variant detection, we developed a geographically explicit stochastic compartmental model to simulate the transmission of a novel SARS-CoV-2 variant in New York City. We measured the impact of (1) testing and sequencing volume, (2) geographic targeting of testing, (3) the timing and location of variant emergence, and (4) the relative variant transmissibility on detection speed and on the undetected disease burden. Improvements in detection times and reduction of undetected infections were driven primarily by increases in the number of sequenced samples. The relative transmissibility of the new variant and the epidemic context of variant emergence also influenced detection times, showing that individual surveillance strategies can result in a wide range of detection outcomes, depending on the underlying dynamics of the circulating variants. These findings help contextualize the design, interpretation, and trade-offs of genomic surveillance strategies of pandemic respiratory pathogens.

Improving effective coverage of medical-oxygen services for neonates and children in health facilities in Uganda: a before-after intervention study

BACKGROUND

Medical oxygen services are essential for the care of acutely unwell patients. We aimed to assess the effects of a multilevel, multicomponent health-system intervention on hypoxaemia detection, oxygen therapy, and mortality among neonates and children attending level IV health centres and hospitals in Uganda.

METHODS

For this before-after intervention study, we included children who attended paediatric or neonatal wards of 24 level IV health centres and seven general or regional referral hospitals in the Busoga and North Buganda regions of Uganda between June 1, 2020, and June 30, 2022. All neonates younger than 1 month and children aged 1 month to 14 years were eligible for inclusion. We excluded neonates who were not sick but stayed in the maternity ward for routine postnatal care. The intervention involved clinical training, mentorship, and supportive supervision; provision of pulse oximeters and cylinder-based oxygen sources; biomedical-capacity support; and support to develop and disseminate oxygen supply strategies, oxygen therapy guidelines, and lists of essential oxygen supplies. Trained research assistants extracted individual patient data from case notes using a standardised electronic data collection form. Data were collected on health-facility details, age, sex, clinical signs and symptoms, admission diagnoses, pulse oximetry readings, oxygen therapy details, and final patient outcome. The primary outcome was the proportion of admitted neonates and children with a pulse oximetry oxygen saturation reading documented in their patient case notes on day 1 of health-facility admission (ie, pulse oximetry coverage). We used mixed-effects logistic regression to evaluate the effect of the intervention.

FINDINGS

We obtained data on 71 997 eligible neonates and children admitted to 31 participating health facilities; the primary analysis included 10 001 patients in the pre-intervention period (ie, June 1 to Oct 30, 2020) and 51 329 patients in the post-intervention period (ie, March 1, 2021, to June 30, 2022). Because 1356 patients had missing data for sex, 4365 (46·7%) of 9347 in the pre-intervention group and 22 831 (46·2%) of 49 410 in the post-intervention group were female; 4982 (53·3%) in the pre-intervention group and 26 579 (53·8%) in the post-intervention group were male. The proportion of neonates and children with pulse oximetry at admission increased from 2365 (23·7%) of 10 001 in the pre-intervention period to 45 029 (87·7%) of 51 328 in the post-intervention period. Adjusted analysis indicated greater likelihood of a patient receiving pulse oximetry during the post-intervention period compared with the pre-intervention period (adjusted odds ratio 40·10, 95% CI 37·38-42·93; p<0·0001).

INTERPRETATION

Large-scale improvements in hospital oxygen services are achievable and have the potential to improve clinical outcomes. Governments should be encouraged to develop national oxygen plans and focus investment on interventions that have been shown to be effective, including the introduction of pulse oximetry into routine hospital care and clinical and biomedical mentoring and support.

FUNDING

Bill & Melinda Gates Foundation and ELMA Philanthropies.

TRANSLATIONS

For the Luganda and Lusoga translations of the abstract see Supplementary Materials section.

Perceptions and acceptance of COVID-19 vaccine among pregnant and lactating women in Singapore: a pre-vaccine rollout cross-sectional study

INTRODUCTION

Vaccination is critical in controlling the coronavirus disease 2019 (COVID-19) pandemic. However, vaccine perception and acceptance among pregnant and lactating women is unknown in Singapore. We aimed to determine the acceptance of COVID-19 vaccination among these two groups of women in Singapore and the factors associated with vaccine acceptance.

METHODS

We conducted an anonymous, online survey on the perceptions of the COVID-19 vaccine and its acceptance by pregnant and lactating women at a tertiary maternal and child hospital in Singapore from 1 March to 31 May 2021. Information on their demographics and knowledge was collected. These factors were assessed for their relationship with vaccine acceptance.

RESULTS

A total of 201 pregnant and 207 lactating women participated. Vaccine acceptance rates in pregnant and lactating women were 30.3% and 16.9%, respectively. Pregnant women who were unsure or unwilling to take the vaccine cited concerns about safety of the vaccine during pregnancy (92.9%), while lactating women were concerned about its potential long-term negative effects on the breastfeeding child (75.6%). Factors that were positively associated with vaccine acceptance included a lower monthly household income or education level, appropriate knowledge regarding vaccine mechanism and higher perceived maternal risk of COVID-19. Most pregnant (70.0%) and lactating women (83.7%) were willing to take the vaccine only when more safety data during pregnancy and breastfeeding were available.

CONCLUSION

COVID-19 vaccine acceptance was low among pregnant and lactating women in Singapore. Addressing the safety concerns when more data are available and education on the mechanism of vaccine action will likely improve acceptance among these women.

Predictors of mortality in severe pneumonia patients: a systematic review and meta-analysis

BACKGROUND

Severe pneumonia has consistently been associated with high mortality. We sought to identify risk factors for the mortality of severe pneumonia to assist in reducing mortality for medical treatment.

METHODS

Electronic databases including PubMed, Web of Science, EMBASE, Cochrane Library, and Scopus were systematically searched till June 1, 2023. All human research were incorporated into the analysis, regardless of language, publication date, or geographical location. To pool the estimate, a mixed-effect model was used. The Newcastle-Ottawa Scale (NOS) was employed for assessing the quality of included studies that were included in the analysis.

RESULTS

In total, 22 studies with a total of 3655 severe pneumonia patients and 1107 cases (30.29%) of death were included in the current meta-analysis. Significant associations were found between age [5.76 years, 95% confidence interval [CI] (3.43, 8.09), P < 0.00001], male gender [odds ratio (OR) = 1.47, 95% CI (1.07, 2.02), P = 0.02], and risk of death from severe pneumonia. The comorbidity of neoplasm [OR = 3.37, 95% CI (1.07, 10.57), P = 0.04], besides the presence of complications such as diastolic hypotension [OR = 2.60, 95% CI (1.45, 4.67), P = 0.001], ALI/ARDS [OR = 3.63, 95% CI (1.78, 7.39), P = 0.0004], septic shock [OR = 9.43, 95% CI (4.39, 20.28), P < 0.00001], MOF [OR = 4.34, 95% CI (2.36, 7.95), P < 0.00001], acute kidney injury [OR = 2.45, 95% CI (1.14, 5.26), P = 0.02], and metabolic acidosis [OR = 5.88, 95% CI (1.51, 22.88), P = 0.01] were associated with significantly higher risk of death among patients with severe pneumonia. Those who died, compared with those who survived, differed on multiple biomarkers on admission including serum creatinine [Scr: + 67.77 mmol/L, 95% CI (47.21, 88.34), P < 0.00001], blood urea nitrogen [BUN: + 6.26 mmol/L, 95% CI (1.49, 11.03), P = 0.01], C-reactive protein [CRP: + 33.09 mg/L, 95% CI (3.01, 63.18), P = 0.03], leukopenia [OR = 2.63, 95% CI (1.34, 5.18), P = 0.005], sodium < 136 mEq/L [OR = 2.63, 95% CI (1.34, 5.18), P = 0.005], albumin [- 5.17 g/L, 95% CI (- 7.09, - 3.25), P < 0.00001], PaO2/FiO2 [- 55.05 mmHg, 95% CI (- 60.11, - 50.00), P < 0.00001], arterial blood PH [- 0.09, 95% CI (- 0.15, - 0.04), P = 0.0005], gram-negative microorganism [OR = 2.56, 95% CI (1.17, 5.62), P = 0.02], and multilobar or bilateral involvement [OR = 3.65, 95% CI (2.70, 4.93), P < 0.00001].

CONCLUSIONS

Older age and male gender might face a greater risk of death in severe pneumonia individuals. The mortality of severe pneumonia may also be significantly impacted by complications such diastolic hypotension, ALI/ARDS, septic shock, MOF, acute kidney injury, and metabolic acidosis, as well as the comorbidity of neoplasm, and laboratory indicators involving Scr, BUN, CRP, leukopenia, sodium, albumin, PaO2/FiO2, arterial blood PH, gram-negative microorganism, and multilobar or bilateral involvement.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO Protocol Number: CRD 42023430684.

Early-Life Disease Exposure and Its Heterogeneous Effects on Mortality Throughout Life: Sweden, 1905-2016

Exposure to infectious diseases in early life has been linked to increased mortality risk in later life in high-disease settings, such as eighteenth- and nineteenth-century Europe. Less is known about the long-term effects of early-life disease exposure in milder disease environments. This study estimates heterogeneous effects from disease exposure in infancy on later-life mortality in twentieth-century Sweden, by socioeconomic status at birth and sex. Using historical population data for southern Sweden, we study 11,515 individuals who were born in 1905-1929 from age 1 until age 85. We measure exposure to disease using the local post-early neonatal mortality rate in the first 12 months after birth and apply flexible parametric survival models. For females, we find a negative effect on life expectancy (scarring) at ages 1-85 following high disease exposure in infancy, particularly for those born to unskilled workers. For males, we find no negative effect on later-life survival, likely because stronger mortality selection in infancy outweighs scarring. Thus, even as the incidence of infectious diseases declined at the start of the twentieth century, early-life disease exposure generated long-lasting negative but heterogeneous population health effects.

Individual risk factors associated with SARS-CoV-2 infection during Alpha variant in high-income countries: a systematic review and meta-analysis

Objectives

This study aimed to systematically appraise risk factors associated with SARS-CoV-2 infection in high-income countries during the period of predominance of the Alpha variant (January 2020 to April 2021).

Methods

Four electronic databases were used to search observational studies. Literature search, study screening, data extraction and quality assessment were conducted by two authors independently. Meta-analyses were conducted for each risk factor, when appropriate.

Results

From 12,094 studies, 27 were included. The larger sample size was 17,288,532 participants, more women were included, and the age range was 18-117 years old. Meta-analyses identified men [Odds Ratio (OR): 1.23, 95% Confidence Interval (CI): 1.97-1.42], non-white ethnicity (OR: 1.63, 95% CI: 1.39-1.91), household number (OR: 1.08, 95% CI: 1.06-1.10), diabetes (OR: 1.22, 95% CI: 1.08-1.37), cancer (OR: 0.82, 95% CI: 0.68-0.98), cardiovascular diseases (OR: 0.92, 95% CI: 0.84-1.00), asthma (OR: 0.83, 95% CI: 0.75-0.92) and ischemic heart disease (OR: 0.82, 95% CI: 0.74-0.91) as associated with SARS-CoV-2 infection.

Conclusion

This study indicated several risk factors for SARS-CoV-2 infection. Due to the heterogeneity of the studies included, more studies are needed to understand the factors that increase the risk for SARS-CoV-2 infection.

Systematic review registration

https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021244148, PROSPERO registration number, CRD42021244148.

UKB.COVID19: an R package for UK Biobank COVID-19 data processing and analysis

COVID-19 caused by SARS-CoV-2 has resulted in a global pandemic with a rapidly developing global health and economic crisis. Variations in the disease have been observed and have been associated with the genomic sequence of either the human host or the pathogen. Worldwide scientists scrambled initially to recruit patient cohorts to try and identify risk factors. A resource that presented itself early on was the UK Biobank (UKBB), which is investigating the respective contributions of genetic predisposition and environmental exposure to the development of disease. To enable COVID-19 studies, UKBB is now receiving COVID-19 test data for their participants every two weeks. In addition, UKBB is delivering more frequent updates of death and hospital inpatient data (including critical care admissions) on the UKBB Data Portal. This frequently changing dataset requires a tool that can rapidly process and analyse up-to-date data. We developed an R package specifically for the UKBB COVID-19 data, which summarises COVID-19 test results, performs association tests between COVID-19 susceptibility/severity and potential risk factors such as age, sex, blood type, comorbidities and generates input files for genome-wide association studies (GWAS). By applying the R package to data released in April 2021, we found that age, body mass index, socioeconomic status and smoking are positively associated with COVID-19 susceptibility, severity, and mortality. Males are at a higher risk of COVID-19 infection than females. People staying in aged care homes have a higher chance of being exposed to SARS-CoV-2. By performing GWAS, we replicated the 3p21.31 genetic finding for COVID-19 susceptibility and severity. The ability to iteratively perform such analyses is highly relevant since the UKBB data is updated frequently. As a caveat, users must arrange their own access to the UKBB data to use the R package.

The association of sociodemographic characteristics and comorbidities with post-acute sequelae of SARS-CoV-2 in a Medicaid managed care population with and without HIV

Understanding how post-acute sequelae of SARS-CoV-2 infection (PASC) affects communities disproportionately affected by HIV is critically needed. This study aimed to identify the prevalence of PASC symptoms among Medicaid enrollees at risk for or living with HIV. Through a web survey, we received 138 valid responses from Medicaid-managed plan members who had received a COVID diagnosis. Participants' mean age was 45.4 years (SD = 11.9) and most were non-Hispanic Black (43.5%) or Hispanic (39.1%). Almost thirty-two percent reported inadequate incomes and 77.5% were HIV-positive. In the overall population, the frequently reported symptoms included neck/back/low back pain, brain fog/difficulty concentrating, bone/joint pain, muscle aches, and fatigue. Findings indicate that there is no statistically significant difference in the prevalence and intensity of PASC symptoms lasting 6 months or more between individuals living with and without HIV. Multiple regression analysis found that the number of PASC symptoms 6 months or longer was independently associated with inadequate incomes and comorbidities (cardiac problems, cancer, fibromyalgia) (R2 = .34). Those with inadequate incomes and comorbidities have more numerous PASC symptoms. Implications for health care delivery and long-term COVID services will be discussed.

Complex patterns of multimorbidity associated with severe COVID-19 and long COVID

BACKGROUND

Early evidence that patients with (multiple) pre-existing diseases are at highest risk for severe COVID-19 has been instrumental in the pandemic to allocate critical care resources and later vaccination schemes. However, systematic studies exploring the breadth of medical diagnoses are scarce but may help to understand severe COVID-19 among patients at supposedly low risk.

METHODS

We systematically harmonized >12 million primary care and hospitalisation health records from ~500,000 UK Biobank participants into 1448 collated disease terms to systematically identify diseases predisposing to severe COVID-19 (requiring hospitalisation or death) and its post-acute sequalae, Long COVID.

RESULTS

Here we identify 679 diseases associated with an increased risk for severe COVID-19 (n = 672) and/or Long COVID (n = 72) that span almost all clinical specialties and are strongly enriched in clusters of cardio-respiratory and endocrine-renal diseases. For 57 diseases, we establish consistent evidence to predispose to severe COVID-19 based on survival and genetic susceptibility analyses. This includes a possible role of symptoms of malaise and fatigue as a so far largely overlooked risk factor for severe COVID-19. We finally observe partially opposing risk estimates at known risk loci for severe COVID-19 for etiologically related diseases, such as post-inflammatory pulmonary fibrosis or rheumatoid arthritis, possibly indicating a segregation of disease mechanisms.

CONCLUSIONS

Our results provide a unique reference that demonstrates how 1) complex co-occurrence of multiple - including non-fatal - conditions predispose to increased COVID-19 severity and 2) how incorporating the whole breadth of medical diagnosis can guide the interpretation of genetic risk loci.

Pre-Existing Atrial Fibrillation in Hospitalized Patients with COVID-19: Insights from the CARDIO COVID 19-20 Registry

Pre-existing (chronic) atrial fibrillation (AF) has been identified as a risk factor for cardiovascular complications and mortality in patients with COVID-19; however, evidence in Latin America (LATAM) is scarce. This prospective and multicenter study from the CARDIO COVID 19-20 database includes hospitalized adults with COVID-19 from 14 countries in LATAM. A parsimonious logistic regression model was used to identify the main factors associated with mortality in a simulated case-control setting comparing patients with a history of AF to those without. In total, 3260 patients were included, of which 115 had AF. The AF group was older, had a higher prevalence of comorbidities, and had greater use of cardiovascular medications. In the model, AF, chronic kidney disease, and a respiratory rate > 25 at admission were associated with higher in-hospital mortality. The use of corticosteroids did not reach statistical significance; however, an effect was seen through the confidence interval. Thus, pre-existing AF increases mortality risk irrespective of other concomitant factors. Chronic kidney disease and a high respiratory rate at admission are also key factors for in-hospital mortality. These findings highlight the importance of comorbidities and regional characteristics in COVID-19 outcomes, in this instance, enhancing the evidence for patients from LATAM.

The digital divide between primary and secondary care: An analysis using SARS-CoV-2 hospital admissions

Using data from two ED. departments of 773 patients admitted with SARS-CoV-2, ICD-10 codes derived from the General Practitioner - Summary Care Record (GP-SCR) and Emergency Department (ED.) records were analysed for code discrepancies and whether this related to increased mortality. The average number of ICD-10 codes in both GP-SCR and ED. records was higher for patients who died than patients who survived (all p < .0001). Pre-existing GP digital data provides a better prediction of mortality than data collected manually during admission clerking in the ED. Up to 78.47% of GP-SCR codes were missed in the ED. records and up to 45.49% of the ED. record codes were not in the GP-SCR. A subset of missed ICD-10 codes were identified as being able to predict outcome; a trend towards increasing death rate as the proportion of missed codes increases. Initiatives to make the GP-SCR available to the wider healthcare community should improve patient care and reduce bias during development of machine learning based algorithms.

Complex patterns of multimorbidity associated with severe COVID-19 and Long COVID

Early evidence that patients with (multiple) pre-existing diseases are at highest risk for severe COVID-19 has been instrumental in the pandemic to allocate critical care resources and later vaccination schemes. However, systematic studies exploring the breadth of medical diagnoses, including common, but non-fatal diseases are scarce, but may help to understand severe COVID-19 among patients at supposedly low risk. Here, we systematically harmonized >12 million primary care and hospitalisation health records from ~500,000 UK Biobank participants into 1448 collated disease terms to systematically identify diseases predisposing to severe COVID-19 (requiring hospitalisation or death) and its post-acute sequalae, Long COVID. We identified a total of 679 diseases associated with an increased risk for severe COVID-19 (n=672) and/or Long COVID (n=72) that spanned almost all clinical specialties and were strongly enriched in clusters of cardio-respiratory and endocrine-renal diseases. For 57 diseases, we established consistent evidence to predispose to severe COVID-19 based on survival and genetic susceptibility analyses. This included a possible role of symptoms of malaise and fatigue as a so far largely overlooked risk factor for severe COVID-19. We finally observed partially opposing risk estimates at known risk loci for severe COVID-19 for etiologically related diseases, such as post-inflammatory pulmonary fibrosis (e.g., MUC5B, NPNT, and PSMD3) or rheumatoid arthritis (e.g., TYK2), possibly indicating a segregation of disease mechanisms. Our results provide a unique reference that demonstrates how 1) complex co-occurrence of multiple - including non-fatal - conditions predispose to increased COVID-19 severity and 2) how incorporating the whole breadth of medical diagnosis can guide the interpretation of genetic risk loci.