A score for predicting risk of death from cardiovascular disease in adults with raised blood pressure, based on individual patient data from randomised controlled trials

Estimating individualized treatment effects using an individual participant data meta-analysis

BACKGROUND

One key aspect of personalized medicine is to identify individuals who benefit from an intervention. Some approaches have been developed to estimate individualized treatment effects (ITE) with a single randomized control trial (RCT) or observational data, but they are often underpowered for the ITE estimation. Using individual participant data meta-analyses (IPD-MA) might solve this problem. Few studies have investigated how to develop risk prediction models with IPD-MA, and it remains unclear how to combine those methods with approaches used for ITE estimation. In this article, we compared different approaches using both simulated and real data with binary and time-to-event outcomes to estimate the individualized treatment effects from an IPD-MA in a one-stage approach.

METHODS

We compared five one-stage models: naive model (NA), random intercept (RI), stratified intercept (SI), rank-1 (R1), and fully stratified (FS), built with two different strategies, the S-learner and the T-learner constructed with a Monte Carlo simulation study in which we explored different scenarios with a binary or a time-to-event outcome. To evaluate the performance of the models, we used the c-statistic for benefit, the calibration of predictions, and the mean squared error. The different models were also used on the INDANA IPD-MA, comparing an anti-hypertensive treatment to no treatment or placebo ( N = 40 237 , 836 events).

RESULTS

Simulation results showed that using the S-learner led to better ITE estimation performances for both binary and time-to-event outcomes. None of the risk models stand out and had significantly better results. For the INDANA dataset with a binary outcome, the naive and the random intercept models had the best performances.

CONCLUSIONS

For the choice of the strategy, using interactions with treatment (the S-learner) is preferable. For the choice of the method, no approach is better than the other.

Cost-Effectiveness of Pharmacist Prescribing for Managing Hypertension in the United States

Importance

Pharmacist-led interventions can significantly improve blood pressure (BP) control. The long-term cost-effectiveness of pharmacist-prescribing interventions implemented on a large scale in the US remains unclear.

Objective

To estimate the cost-effectiveness of implementing a pharmacist-prescribing intervention to improve BP control in the US.

Design, Setting, and Participants

This economic evaluation included a 5-state Markov model based on the pharmacist-prescribing intervention used in The Alberta Clinical Trial in Optimizing Hypertension (or RxACTION) (2009 to 2013). In the trial, control group patients received an active intervention, including a BP wallet card, education, and usual care. Data were analyzed from January to June 2023.

Main Outcomes and Measures

Cardiovascular (CV) events, end-stage kidney disease events, life years, quality-adjusted life years (QALYs), lifetime costs, and lifetime incremental cost-effectiveness ratio (ICER). CV risk was calculated using Framingham risk equations. Costs were based on the reimbursement rate for level 1 encounters, medication costs from published literature, and event costs from national surveys and pricing data sets. Quality of life was determined using a published catalog of EQ-5D utility values. One-way sensitivity analyses were used to assess alternative reimbursement values, a reduced time horizon of 5 years, alternative assumptions for BP reduction, and the assumption of no benefit to the intervention after 10 years. The model was expanded to the US population to estimate population-level cost and health impacts.

Results

Assumed demographics were mean (SD) age, 64 (12.5) years, 121 (49%) male, and a mean (SD) baseline BP of 150/84 (13.9/11.5) mm Hg. Over a 30-year time horizon, the pharmacist-prescribing intervention yielded 2100 fewer cases of CV disease and 8 fewer cases of kidney disease per 10 000 patients. The intervention was also associated with 0.34 (2.5th-97.5th percentiles, 0.23-0.45) additional life years and 0.62 (2.5th-97.5th percentiles, 0.53-0.73) additional QALYs. The cost savings were $10 162 (2.5th-97.5th percentiles, $6636-$13 581) per person due to fewer CV events with the pharmacist-prescribing intervention, even after the cost of the visits and medication adjustments. The intervention continued to produce benefits in more conservative analyses despite increased costs as the ICER ranged from $2093 to $24 076. At the population level, a 50% intervention uptake was associated with a $1.137 trillion in cost savings and would save an estimated 30.2 million life years over 30 years.

Conclusion and Relevance

These findings suggest that a pharmacist-prescribing intervention to improve BP control may provide high economic value. The necessary tools and resources are readily available to implement pharmacist-prescribing interventions across the US; however, reimbursement limitations remain a barrier.

Vall d'Hebron Risk Score II for myocardial infarction and cardiac death

OBJECTIVES

The aim of this study was to create a new Vall d'Hebron Risk Score-II (VH-RS-II) for non-fatal myocardial infarction (MI) and/or cardiac death (CD), excluding patients with coronary revascularisation (CR) during the follow-up.

METHODS

We analysed 5215 consecutive patients underwent gated single photon emission CT (SPECT); 2960 patients (age 64.2±11, male 58.1%) had no previous MI and/or CR, and 2255 patients (age 63.3±11, male 81.9%) had previous MI and/or CR. During a follow-up of 4.3±2.6 years, the cardiac event (MI and CD) was evaluated. This study was reviewed and approved by the ethics committee of our institution (number form trial register, PR(AG)168.2012). To obtain the predictor model, multivariate Cox regression analysis and multivariate logistic regression analysis were used. RS-VH-II was validated with 679 patients.

RESULTS

In patients without previous MI and/or CR, age (HR: 1.01; p<0.001), diabetes (HR: 2.1, p=0.001), metabolic equivalent (METs) (HR: 0.89, p=0.038), ST segment depression (HR: 1.4, p=0.011), ejection fraction (EF) (HR: 0.97, p<0.001) and summed stress score (HR: 1.2, p<0.001) were the independent predictors of CE (C-statistic: 0.8). In patients with previous MI and/or CR, age (HR: 1.06, p<0.001), male (HR: 1.9, p=0.047), smoker (HR: 1.5, p=0.047), METs (HR: 0.8, p<0.001), ST segment depression (HR: 1.4, p=0.002), EF (HR: 0.96; p<0.001) and summed difference score (HR: 1.03, p=0.06) were the independent predictors of CE (C-statistic:0.8).

CONCLUSION

The VH-RS-II obtained from different clinical exercise and gated SPECT variables allow the risk stratification for MI and CD in patients with or without previous MI and/or CR in due form.

Disease burden among Ukrainians forcibly displaced by the 2022 Russian invasion

The Russian invasion of Ukraine on February 24, 2022, has displaced more than a quarter of the population. Assessing disease burdens among displaced people is instrumental in informing global public health and humanitarian aid efforts. We estimated the disease burden in Ukrainians displaced both within Ukraine and to other countries by combining a spatiotemporal model of forcible displacement with age- and gender-specific estimates of cardiovascular disease (CVD), diabetes, cancer, HIV, and tuberculosis (TB) in each of Ukraine's 629 raions (i.e., districts). Among displaced Ukrainians as of May 13, we estimated that more than 2.63 million have CVDs, at least 615,000 have diabetes, and over 98,500 have cancer. In addition, more than 86,000 forcibly displaced individuals are living with HIV, and approximately 13,500 have TB. We estimated that the disease prevalence among refugees was lower than the national disease prevalence before the invasion. Accounting for internal displacement and healthcare facilities impacted by the conflict, we estimated that the number of people per hospital has increased by more than two-fold in some areas. As regional healthcare systems come under increasing strain, these estimates can inform the allocation of critical resources under shifting disease burdens.

Extremely Low Activity of Serum Alanine Aminotransferase Is Associated with Long-Term Overall-Cause Mortality in the Elderly Patients Undergoing Percutaneous Coronary Intervention after Acute Coronary Syndrome

Background and Objectives: Recent studies revealed that the extremely low activity of serum alanine aminotransferase (ALT) is associated with frailty and contributes to increased mortality after acute physical stress. We aimed to investigate whether the extremely low activity of serum ALT (<10 U/L) at the time of diagnosis can be used to predict overall-cause mortality in elderly patients that underwent percutaneous coronary intervention (PCI) after acute coronary syndrome (ACS) diagnosis. Materials and Methods: A retrospective medical record review was performed on 1597 patients diagnosed with ACS who underwent PCI at a single university hospital from February 2014 to March 2020. The associations between the extremely low activity of serum ALT and mortality were assessed using a stepwise Cox regression (forward: conditional). Results: A total of 210 elderly patients were analyzed in this study. The number of deaths was 64 (30.5%), the mean survival time was 25.0 ± 18.9 months, and the mean age was 76.9 ± 7.6 years. The mean door-to-PCI time was 74.0 ± 20.9 min. The results of stepwise Cox regression analysis showed that the extremely low activity of serum ALT (adjusted hazard ratio: 5.157, 95% confidence interval: 3.001-8.862, p < 0.001) was the independent risk factor for long-term overall-cause mortality in the elderly who underwent PCI after ACS diagnosis. Conclusions: The extremely low activity of serum ALT at ACS diagnosis is a significant risk factor for increased long-term overall-cause mortality in the elderly who underwent PCI after ACS diagnosis. It is noteworthy that a simple laboratory test at the time of diagnosis was found to be a significant risk factor for mortality.

Score-based prediction model for severe vitamin D deficiency in patients with critical illness: development and validation

BACKGROUND

Severe vitamin D deficiency (SVDD) dramatically increases the risks of mortality, infections, and many other diseases. Studies have reported higher prevalence of vitamin D deficiency in patients with critical illness than general population. This multicenter retrospective cohort study develops and validates a score-based model for predicting SVDD in patients with critical illness.

METHODS

A total of 662 patients with critical illness were enrolled between October 2017 and July 2020. SVDD was defined as a serum 25(OH)D level of < 12 ng/mL (or 30 nmol/L). The data were divided into a derivation cohort and a validation cohort on the basis of date of enrollment. Multivariable logistic regression (MLR) was performed on the derivation cohort to generate a predictive model for SVDD. Additionally, a score-based calculator (the SVDD score) was designed on the basis of the MLR model. The model's performance and calibration were tested using the validation cohort.

RESULTS

The prevalence of SVDD was 16.3% and 21.7% in the derivation and validation cohorts, respectively. The MLR model consisted of eight predictors that were then included in the SVDD score. The SVDD score had an area under the receiver operating characteristic curve of 0.848 [95% confidence interval (CI) 0.781-0.914] and an area under the precision recall curve of 0.619 (95% CI 0.577-0.669) in the validation cohort.

CONCLUSIONS

This study developed a simple score-based model for predicting SVDD in patients with critical illness.

TRIAL REGISTRATION

ClinicalTrials.gov protocol registration ID: NCT03639584. Date of registration: May 12, 2022.

The Cardiovascular Literature-Based Risk Algorithm (CALIBRA): Predicting Cardiovascular Events in Patients With Non-Dialysis Dependent Chronic Kidney Disease

Background and Objectives

Cardiovascular (CV) disease is the main cause of morbidity and mortality in patients suffering from chronic kidney disease (CKD). Although it is widely recognized that CV risk assessment represents an essential prerequisite for clinical management, existing prognostic models appear not to be entirely adequate for CKD patients. We derived a literature-based, naïve-bayes model predicting the yearly risk of CV hospitalizations among patients suffering from CKD, referred as the CArdiovascular, LIterature-Based, Risk Algorithm (CALIBRA).

Methods

CALIBRA incorporates 31 variables including traditional and CKD-specific risk factors. It was validated in two independent CKD populations: the FMC NephroCare cohort (European Clinical Database, EuCliD®) and the German Chronic Kidney Disease (GCKD) study prospective cohort. CALIBRA performance was evaluated by c-statistics and calibration charts. In addition, CALIBRA discrimination was compared with that of three validated tools currently used for CV prediction in CKD, namely the Framingham Heart Study (FHS) risk score, the atherosclerotic cardiovascular disease risk score (ASCVD), and the Individual Data Analysis of Antihypertensive Intervention Trials (INDANA) calculator. Superiority was defined as a ΔAUC>0.05.

Results

CALIBRA showed good discrimination in both the EuCliD® medical registry (AUC 0.79, 95%CI 0.76-0.81) and the GCKD cohort (AUC 0.73, 95%CI 0.70-0.76). CALIBRA demonstrated improved accuracy compared to the benchmark models in EuCliD® (FHS: ΔAUC=-0.22, p<0.001; ASCVD: ΔAUC=-0.17, p<0.001; INDANA: ΔAUC=-0.14, p<0.001) and GCKD (FHS: ΔAUC=-0.16, p<0.001; ASCVD: ΔAUC=-0.12, p<0.001; INDANA: ΔAUC=-0.04, p<0.001) populations. Accuracy of the CALIBRA score was stable also for patients showing missing variables.

Conclusion

CALIBRA provides accurate and robust stratification of CKD patients according to CV risk and allows score calculations with improved accuracy compared to established CV risk scores also in real-world clinical cohorts with considerable missingness rates. Our results support the generalizability of CALIBRA across different CKD populations and clinical settings.

Development, validation, and visualization of a web-based nomogram to predict 5-year mortality risk in older adults with hypertension

Background

Hypertension-related mortality has been increasing in older adults, resulting in serious burden to society and individual. However, how to identify older adults with hypertension at high-risk mortality remains a great challenge. The purpose of this study is to develop and validate the prediction nomogram for 5-year all-cause mortality in older adults with hypertension.

Methods

Data were extracted from National Health and Nutrition Examination Survey (NHANES). We recruited 2691 participants aged 65 years and over with hypertension in the NHANES 1999-2006 cycles (training cohort) and 1737 participants in the NHANES 2007-2010 cycles (validation cohort). The cohorts were selected to provide at least 5 years follow-up for evaluating all-cause mortality by linking National Death Index through December 31, 2015. We developed a web-based dynamic nomogram for predicting 5-year risk of all-cause mortality based on a logistic regression model in training cohort. We conducted internal validation by 1000 bootstrapping resamples and external validation in validation cohort. The discrimination and calibration of nomogram were evaluated using concordance index (C-index) and calibration curves.

Results

The final model included eleven independent predictors: age, sex, diabetes, cardiovascular disease, body mass index, smoking, lipid-lowering drugs, systolic blood pressure, hemoglobin, albumin, and blood urea nitrogen. The C-index of model in training and validation cohort were 0.759 (bootstrap-corrected C-index 0.750) and 0.740, respectively. The calibration curves also indicated that the model had satisfactory consistence in two cohorts. A web-based nomogram was established (https://hrzhang1993.shinyapps.io/dynnomapp).

Conclusions

The novel developed nomogram is a useful tool to accurately predict 5-year all-cause mortality in older adults with hypertension, and can provide valuable information to make individualized intervention.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12877-022-03087-3.

Dementia Risk Score for a Population in Southern Europe Calculated Using Competing Risk Models

Background:

Dementia prevention can be addressed if the intervention is applied early.

Objective:

The objective of this study was to develop and validate competing risk models to predict the late risk of dementia based on variables assessed in middle age in a southern European population.

Methods:

We conducted a prospective observational study of the EPIC-Spain cohort that included 25,015 participants. Dementia cases were identified from electronic health records and validated by neurologists. Data were gathered on sociodemographic characteristics and cardiovascular risk factors. To stratify dementia risk, Fine and Gray competing risk prediction models were constructed for the entire sample and for over-55-year-olds. Risk scores were calculated for low (the 30% of the sample with the lowest risk), moderate (> 30% –60%), and high (> 60% –100%) risk.

Results:

The 755 cases of dementia identified represented a cumulative incidence of 3.1% throughout the study period. The AUC of the model for over-55-year-olds was much higher (80.8%) than the overall AUC (68.5%) in the first 15 years of follow-up and remained that way in the subsequent follow-up. The weight of the competing risk of death was greater than that of dementia and especially when the entire population was included.

Conclusion:

This study presents the first dementia risk score calculated in a southern European population in mid-life and followed up for 20 years. The score makes it feasible to achieve the early identification of individuals in a southern European population who could be targeted for the prevention of dementia based on the intensive control of risk factors.

Contemporary Review of Risk Scores in Prediction of Coronary and Cardiovascular Deaths

PURPOSE OF REVIEW

Explore the current literature supporting risk stratification scores for prediction of coronary and cardiovascular disease deaths.

RECENT FINDINGS

Accurate risk prediction remains the foundation of management choice in primary prevention. When applied to new populations, the calibration of a predictive model will deteriorate, although discrimination changes minimally. One of the approaches with better performance and validation is the initial use of pooled cohort equation to identify low and high-risk patients, followed by coronary artery calcium scoring in those with borderline to intermediate risk. It is important to utilize a risk stratification tool that has been validated in a patient population that resembles the one used to develop the original tool to maintain adequate calibration. It is likely that the future of mortality risk prediction will develop in combined clinical risk predictors and cardiovascular imaging, such coronary artery calcium (CAC) scoring that renders the highest predictive accuracy.

Absolute Cardiovascular Disease Risk Assessed in Old Age Predicts Disability and Mortality: A Retrospective Cohort Study of Community-Dwelling Older Adults

Background

Evidence is limited on the predictive validity of absolute cardiovascular disease (CVD) risk, estimated by multivariable assessments in old age, for disability and mortality. We aimed to examine the longitudinal associations of absolute CVD risk assessed using region‐specific risk estimation charts with disability and mortality among community‐dwelling people aged ≥65 years.

Methods and Results

This retrospective cohort study included 7456 community‐dwelling people aged ≥65 years (mean age, 73.7 years) without CVD and functional decline at baseline. They lived in either Obu City or Midori Ward of Nagoya City, Aichi Prefecture, Japan. We estimated absolute CVD risk using the revised World Health Organization CVD risk estimation charts and stratified risk levels into 3 categories: low (<10%), mid (10% to <20%), and high (≥20%). We followed up the functional disability incidence and all‐cause mortality monthly for 5 years. The prevalence of each CVD risk level based on the laboratory‐based model was as follows: low CVD risk, 1096 (14.7%); mid CVD risk, 5510 (73.9%); and high CVD risk, 850 (11.4%). During follow‐up, the incidence rates of disability and mortality were 33.4 per 1000 and 12.4 per 1000 person‐years, respectively. Cox regression analysis showed that the adjusted hazard ratios (95% CIs) for disability incidence were 1.32 (1.13–1.56) and 1.44 (1.18–1.77) in mid and high CVD risk levels, respectively (reference: low CVD risk level); for mortality incidence, they were 1.53 (1.16–2.01) and 2.02 (1.45–2.80) in mid and high CVD risk levels, respectively (reference: low CVD risk level).

Conclusions

Absolute CVD risk was associated with both disability and mortality in people aged ≥65 years. Estimated CVD risk levels may be useful surrogate markers for disability and mortality risks even when assessed in old age.

Latin-American Ambulatory Blood Pressure Registry (MAPA-LATAM): An urgent need

Hypertension (HT) is one of the main risk factors for cardiovascular disease (CVD). Although it is a global problem, independently of economic situation, region, race or culture, the data available on Latin America are limited. Clinical guidelines emphasise the importance of obtaining reliable blood pressure readings. For this reason, the use of ambulatory blood pressure monitoring (ABPM) is recommended. This improves precision and reproducibility, resulting in better diagnosing and therapeutic decision-making, and constitutes a better estimation of prognosis than office measurements. Unfortunately, there is no global prospective ABPM registry for all of Latin America that analyses HT prevalence, the level of knowledge about it, treatment percentage and the degree of control. Consequently, the authors of this article consider its implementation a priority.

Developing a cognitive dysfunction risk score for use with opioid-dependent persons in drug treatment

BACKGROUND

Cognitive dysfunction is common in persons seeking medication for opioid use disorder (MOUD) and may hinder many addiction-related services. Brief but accurate screening measures are needed to efficiently assess cognitive dysfunction in these resource-limited settings. The study aimed to develop a brief predictive risk score tailored for use among patients in drug treatment.

METHODS

The present study examined predictors of mild cognitive impairment (MCI), objectively assessed via the NIH Toolbox, among 173 patients receiving methadone as MOUD at an urban New England drug treatment facility. Predictors of MCI were identified in one subsample using demographic characteristics, medical chart data, and selected items from the Brief Inventory of Neuro-Cognitive Impairment (BINI). Predictors were cross-validated in a second subsample using logistic regression. Receiver operating curve (ROC) analyses determined an optimal cut-off score for detecting MCI.

RESULTS

A cognitive dysfunction risk score (CDRS) was calculated from patient demographics (age 50+, non-White ethnicity, less than high school education), medical and substance use chart data (history of head injury, overdose, psychiatric diagnosis, past year polysubstance use), and selected self-report items (BINI). The CDRS discriminated acceptably well, with a ROC curve area of 70.6 %, and correctly identified 78 % of MCI cases (sensitivity = 87.5 %; specificity = 55.6 %).

CONCLUSIONS

The CDRS identified patients with cognitive challenges at a level likely to impede treatment engagement and/or key outcomes. The CDRS may assist in efficiently identifying patients with cognitive dysfunction while requiring minimal training and resources. Larger validation studies are needed in other clinical settings.

Prognostic value of ambulatory blood pressure values in elderly patients with heart failure. Results of the DICUMAP study

INTRODUCTION

Ambulatory blood pressure monitoring (ABPM) has demonstrated value in the prognostic assessment of hypertensive patients with heart failure (HF) with or without other cardiovascular diseases. The objective of this study was to evaluate whether ABPM can identify subjects with HF with a worse prognosis.

METHODS AND RESULTS

Prospective multicenter study that included clinically stable outpatients with HF. All patients underwent ABPM. A total of 154 patients from 17 centers were included. Their mean age was 76.8 years (± 8.3) and 55.2% were female. In total, 23.7% had HF with a reduced ejection fraction (HFrEF), 68.2% were in NYHA functional class II, and 19.5% were in NYHA functional class III. At one year of follow up, there were 13 (8.4%) deaths, of which 10 were attributed to HF. Twenty-nine patients required hospitalization, of which 19 were due to HF. The presence of a non-dipper BP pattern was associated with an increased risk for readmission or death at one year of follow-up (25% vs. 5%; p=.024). According to a Cox regression analysis, more advanced NYHA functional class (hazard ratio 3.51; 95% CI 1.70-7.26; p=.001; for NYHA class III vs. II) and a higher proportional nocturnal reduction in diastolic BP (hazard ratio 0.961; 95%CI 0.926-0.997; p=.032 per 1% diastolic BP reduction) were independently associated with death or readmission at one year.

CONCLUSION

In older patients with chronic HF, a non-dipper BP pattern measured by ABPM was associated with a higher risk of hospitalization and death due to HF.

Impact of the Uncoupling Protein 1 on Cardiovascular Risk in Patients with Rheumatoid Arthritis

Adiposity is strongly associated with cardiovascular (CV) morbidity. Uncoupling protein 1 (UCP1) increases energy expenditure in adipocytes and may counteract adiposity. Our objective was to investigate a connection between UCP1 expression and cardiovascular health in patients with rheumatoid arthritis (RA) in a longitudinal observational study. Transcription of UCP1 was measured by qPCR in the subcutaneous adipose tissue of 125 female RA patients and analyzed with respect to clinical parameters and the estimated CV risk. Development of new CV events and diabetes mellitus was followed for five years. Transcription of UCP1 was identified in 89 (71%) patients. UCP1 positive patients had often active RA disease (p = 0.017), high serum levels of IL6 (p = 0.0025) and were frequently overweight (p = 0.015). IL-6^hiBMI^hi patients and patients treated with IL6 receptor inhibitor tocilizumab had significantly higher levels of UCP1 compared to other RA patients (p < 0.0001, p = 0.032, respectively). Both UCP1^hi groups displayed unfavorable metabolic profiles with high plasma glucose levels and high triglyceride-to-HDL ratios, which indicated insulin resistance. Prospective follow-up revealed no significant difference in the incidence of new CV and metabolic events in the UCP1^hi groups and remaining RA patients. The study shows that high transcription of UCP1 in adipose tissue is related to IL6-driven processes and reflects primarily metabolic CV risk in female RA patients.

SCORE underestimates cardiovascular mortality in hypertension: insight from the OLD-HTA and NEW-HTA Lyon cohorts

AIMS

Current European guidelines recommend the SCORE to estimate 10-year cardiovascular mortality in patients with moderate/low cardiovascular risk. SCORE was derived from the general population. The objective of this study was to investigate the estimated 10-year cardiovascular mortality according to the SCORE in a historic and a contemporary cohort of hypertensive patients.

METHODS AND RESULTS

After exclusion of secondary prevention and diabetes, 3086 patients were analysed in the OLD-HTA (1969-90) and 1081 in the NEW-HTA (1997-2014) Lyon cohorts. SCORE was calculated using the low and high cardiovascular risk equations and charts, and patients classified as being at low (0%), moderate (1-4%), high (5-9%), and very high (≥10%) risk. In the OLD-HTA cohort, 10-year cardiovascular mortality was higher (1.2%, 5.5%, 17.7%, and 27.0%) than that predicted by the low-risk equation (0%, 1.7%, 6.4%, and 14.8%). In the NEW-HTA cohort, similar results were observed (1.1%, 4.7%, 15.1%, and 15.2% vs. 0%, 1.9%, 6.2%, and 11.7%, respectively). Using the high-risk equation, mortality was underestimated in both cohorts, but the difference was smaller. The diagnostic performance of the high-risk equation was lower than the low-risk equation in both cohorts, considering the SCORE as a continuous or a categorical variable (Likelihood ratio test P < 0.05 for all comparisons in OLD-HTA). Similar results were obtained using SCORE charts.

CONCLUSION

SCORE underestimates the 10-year cardiovascular mortality risk in hypertensive patients in a historic cohort and in a contemporary one. The algorithm to predict cardiovascular mortality in hypertensive patients needs an update given new information since its creation.

Predicting dementia diagnosis from cognitive footprints in electronic health records: a case-control study protocol

INTRODUCTION

Dementia is a group of disabling disorders that can be devastating for persons living with it and for their families. Data-informed decision-making strategies to identify individuals at high risk of dementia are essential to facilitate large-scale prevention and early intervention. This population-based case-control study aims to develop and validate a clinical algorithm for predicting dementia diagnosis, based on the cognitive footprint in personal and medical history.

METHODS AND ANALYSIS

We will use territory-wide electronic health records from the Clinical Data Analysis and Reporting System (CDARS) in Hong Kong between 1 January 2001 and 31 December 2018. All individuals who were at least 65 years old by the end of 2018 will be identified from CDARS. A random sample of control individuals who did not receive any diagnosis of dementia will be matched with those who did receive such a diagnosis by age, gender and index date with 1:1 ratio. Exposure to potential protective/risk factors will be included in both conventional logistic regression and machine-learning models. Established risk factors of interest will include diabetes mellitus, midlife hypertension, midlife obesity, depression, head injuries and low education. Exploratory risk factors will include vascular disease, infectious disease and medication. The prediction accuracy of several state-of-the-art machine-learning algorithms will be compared.

ETHICS AND DISSEMINATION

This study was approved by Institutional Review Board of The University of Hong Kong/Hospital Authority Hong Kong West Cluster (UW 18-225). Patients' records are anonymised to protect privacy. Study results will be disseminated through peer-reviewed publications. Codes of the resulted dementia risk prediction algorithm will be made publicly available at the website of the Tools to Inform Policy: Chinese Communities' Action in Response to Dementia project (https://www.tip-card.hku.hk/).

Myocardial Infarction after Kidney Transplantation: A Risk and Specific Profile Analysis from a Nationwide French Medical Information Database

Introduction: Renal transplant recipients have a high peri-operative risk for cardiovascular events. The post-transplantation period also carries a risk of myocardial infarction (MI). Coronary artery disease (CAD) is a leading cause of death in these patients. We aimed to assess the risk of MI, the specific morbidity profile of MI after transplantation as well as the long-term prognosis after MI in renal transplantation (RT) patients regarding cardiovascular (CV) death and all-cause death. Methods: From a French national medical information database, all of the patients seen in French hospitals in 2013 with at least 5-years follow-up were retrospectively identified and patients without transplantation but with previous dialysis at baseline were excluded. There were 17,526 patients with RT and 3,288,857 with no RT. Results: Among these patients, 1020 in the RT group (5.8%), and 93,320 in the non-RT group (2.8%) suffered acute MI during a median follow-up of 5.4 years. After multivariable adjustment, risk of MI was higher in RT patients than in non-RT patients (HR 1.45, IC 95% 1.35–1.55). The mean age was 59.5 years for transplant patients with MI, and 70.6 years for the reference population with MI (p < 0.0001). MI patients with RT (vs. non RT patients) were more likely to have hypertension, diabetes dyslipidemia, and peripheral artery disease (76.0% vs. 48.1%, 38.7% vs. 25.2%, 33.2% vs. 23.2%, and 31.2% vs. 17.3%, respectively, p < 0.0001). Incidence of non ST-elevation MI (NSTEMI) was higher in RT patients while incidence of ST-elevation MI (STEMI) was higher in patients without RT. In unadjusted analysis, risk of all-cause death and CV death within the first month after MI were higher in patients without RT (18% vs. 11.1% p < 0.0001 and 12.3% vs. 7.8%, p < 0.0001, respectively). However, multivariable analysis indicated that risk of all-cause death was higher in patients with RT than in those with no RT (adjusted HR 1.15 IC 95% 1.03–1.28). Conclusions: MI is not an uncommon complication after RT (incidence of around 5.8% after 5 years). RT is independently associated with a 45% higher risk of MI than in patients without RT, with a predominance of NSTEMI. MI in patients with RT is independently associated with a 15% higher risk of all-cause death than that in patients with MI and no RT.

Development of a Synthetic Population Model for Assessing Excess Risk for Cardiovascular Disease Death

Importance

Evaluating the association of social determinants of health with chronic diseases at the population level requires access to individual-level factors associated with disease, which are rarely available for large populations. Synthetic populations are a possible alternative for this purpose.

Objective

To construct and validate a synthetic population that statistically mimics the characteristics and spatial disease distribution of a real population, using real and synthetic data.

Design, Setting, and Participants

This population-based decision analytical model used data for Allegheny County, Pennsylvania, collected from January 2015 to December 2016, to build a semisynthetic population based on the synthetic population used by the modeling and simulation platform FRED (A Framework for Reconstructing Epidemiological Dynamics). Disease status was assigned to this population using health insurer claims data from the 3 major insurance providers in the county or from the National Health and Nutrition Examination Survey. Biological, social, and other variables were also obtained from the National Health Interview Survey, Allegheny County, and public databases. Data analysis was performed from November 2016 to February 2020.

Exposures

Risk of cardiovascular disease (CVD) death.

Main Outcomes and Measures

Difference between expected and observed CVD death risk. A validated risk equation was used to estimate CVD death risk.

Results

The synthetic population comprised 1 188 112 individuals with demographic characteristics similar to those of the 2010 census population in the same county. In the synthetic population, the mean (SD) age was 40.6 (23.3) years, and 622 997 were female individuals (52.4%). Mean (SD) observed 4-year rate of excess CVD death risk at the census tract level was -40 (523) per 100 000 persons. The correlation of social determinant data with difference between expected and observed CVD death risk indicated that income- and education-based social determinants were associated with risk. Estimating improved social determinants of health and biological factors associated with disease did not entirely remove the excess in CVD death rates. That is, a 20% improvement in the most significant determinants still resulted in 105 census tracts with excess CVD death risk, which represented 24% of the county population.

Conclusions and Relevance

The results of this study suggest that creating a geographically explicit synthetic population from real and synthetic data is feasible and that synthetic populations are useful for modeling disease in large populations and for estimating the outcome of interventions.

Risk Prediction Tool for Assessing the Probability of Death or Myocardial Infarction in Patients With Stable Coronary Artery Disease

Several risk scores in acute coronary syndromes are available, but few models exist for stable coronary artery disease to guide decision-making and prognosis. A multivariate model was developed using 23 baseline candidate variables from the Clinical Outcomes Utilizing Revascularization and Aggressive Drug Therapy EvaluationTrial (n = 2,287 patients). Discrimination of the model was evaluated by the concordance c-index. The procedure was validated using 100 random half samples. We identified 9 independent predictors of death or myocardial infarction (MI) during a 5-year follow-up. The following predictors and points contributing to the risk score were: heart failure (3), number of diseased coronary arteries (1 for each vessel), diabetes (1), age (1 for each 15 years ≥ age 45), previous revascularization (1), current smoking (1), female (1), previous MI (1), and high-density lipoprotein cholesterol (1: 31 to 40 mg/dL; 2: <30 mg/dL). The risk tool had a potential range from 0 to 15, corresponding to 5-year event rates of 5.8% to 56%. C-indices ranged from 0.67 for the full data set to 0.62 for the validating subsamples. Respective observed versus predicted 5-year event rates for 3 predefined risk strata revealed: 30% had a low-risk score of 0 to 3 (9.3% vs 9.3%, or 1.9%/year); 59% had an intermediate-risk score of 4-6 (18.0% vs 18.1%, or 3.6%/year); and 11% had a high-risk score of 7-11 (36% vs 36.5%, or 7.2%/year). This stable coronary artery disease risk score permitted a prognostic assessment of 5-year probability of death or MI with an approximate 4-fold range in event rates from the lowest (9.3%) to the highest (36%) terciles, thus enabling better clinical practice decisions that allow physicians to tailor the intensity of treatment to the level of risk.

Cardiometabolic risk prediction algorithms for young people with psychosis: a systematic review and exploratory analysis

OBJECTIVE

Cardiometabolic risk prediction algorithms are common in clinical practice. Young people with psychosis are at high risk for developing cardiometabolic disorders. We aimed to examine whether existing cardiometabolic risk prediction algorithms are suitable for young people with psychosis.

METHODS

We conducted a systematic review and narrative synthesis of studies reporting the development and validation of cardiometabolic risk prediction algorithms for general or psychiatric populations. Furthermore, we used data from 505 participants with or at risk of psychosis at age 18 years in the ALSPAC birth cohort, to explore the performance of three algorithms (QDiabetes, QRISK3 and PRIMROSE) highlighted as potentially suitable. We repeated analyses after artificially increasing participant age to the mean age of the original algorithm studies to examine the impact of age on predictive performance.

RESULTS

We screened 7820 results, including 110 studies. All algorithms were developed in relatively older participants, and most were at high risk of bias. Three studies (QDiabetes, QRISK3 and PRIMROSE) featured psychiatric predictors. Age was more strongly weighted than other risk factors in each algorithm. In our exploratory analysis, calibration plots for all three algorithms implied a consistent systematic underprediction of cardiometabolic risk in the younger sample. After increasing participant age, calibration plots were markedly improved.

CONCLUSION

Existing cardiometabolic risk prediction algorithms cannot be recommended for young people with or at risk of psychosis. Existing algorithms may underpredict risk in young people, even in the face of other high-risk features. Recalibration of existing algorithms or a new tailored algorithm for the population is required.

Prediction models for cardiovascular disease risk in the hypertensive population: a systematic review

OBJECTIVE

The aim of this study was to identify, describe, and evaluate the available cardiovascular disease risk prediction models developed or validated in the hypertensive population.

METHODS

MEDLINE and the Web of Science were searched from database inception to March 2019, and all reference lists of included articles were reviewed.

RESULTS

A total of 4766 references were screened, of which 18 articles were included in the review, presenting 17 prediction models specifically developed for hypertensive populations and 25 external validations. Among the 17 prediction models, most were constructed based on randomized trials in Europe or North America to predict the risk of fatal or nonfatal cardiovascular events. The most common predictors were classic cardiovascular risk factors such as age, diabetes, sex, smoking, and SBP. Of the 17 models, only one model was externally validated. Among the 25 external validations, C-statistics ranged from 0.58 to 0.83, 0.56 to 0.75, and 0.64 to 0.78 for models developed in the hypertensive population, the general population and other specific populations, respectively. Most of the development studies and validation studies had an overall high risk of bias according to PROBAST.

CONCLUSION

There are a certain number of cardiovascular risk prediction models in patients with hypertension. The risk of bias assessment showed several shortcomings in the methodological quality and reporting in both the development and validation studies. Most models developed in the hypertensive population have not been externally validated. Compared with models developed for the general population and other specific populations, models developed for the hypertensive population do not display a better performance when validated among patients with hypertension. Research is needed to validate and improve the existing cardiovascular disease risk prediction models in hypertensive populations rather than developing completely new models.

A novel clinical risk prediction model for myocardial infarction, coronary revascularization, and cardiac death according to clinical, exercise, and gated SPECT variables (VH-RS)

AIMS

To create a risk score for cardiac events (CE) according to clinical, exercise, and gated SPECT variables.

METHODS AND RESULTS

We analysed 5707 consecutive patients; 3181 patients (age 64.2 ± 11 years, male 59.6%) with suspected coronary artery disease (CAD) [without previous myocardial infarction (MI) or coronary revascularization (CR)] and 2526 patients (age 63.3 ± 11 years, male 81.7%) with established CAD (with previous MI or CR). To create the Vall d'Hebron Risk Score (VH-RS), first we analyse the predictors of CE (non-fatal MI, CR, and/or cardiac death), then the probability of CE for every patient according to the predictive variables. According to risk we stratified patients into four risk levels: very low risk (VLR), low risk (LR), moderate risk (MR), and high risk (HRi) using Multiple Cox Regression analysis models. Finally, we validate the VH-RS in another prospective cohort of 734 patients. In patients with suspected CAD; age (P < 0.001); gender (P = 0.001); hyperlipidaemia (P < 0.001); nitrates (P = 0.04); ejection fraction (EF) (P = 0.001); summed stress score (P < 0.001); METs (P < 0.001); exercise angina (P = 0.006); and mm of ST segment depression (P = 0.004) were the independent predictors of CE (C-statistic: 0.8; P < 0.001). In patients with established CAD, EF (P < 0.001); summed difference score (P = 0.001); age (P < 0.001); smoker (P = 0.002); nitrates (P = 0.003); exercise angina (P = 0.001); METs (P < 0.001); and mm of ST segment depression (P = 0.011) were the independent predictors of CE (C-statistic: 0.7; P < 0.001). The risk score obtained from these variables allows the stratification of patients into four risk levels: VLR, LR, MR, and HRi.

CONCLUSIONS

The cardiac risk stratification by mean of clinical, exercise, and gated SPECT variables is an objective aid to assessing an individual's cardiac risk.

Can risk be predicted? An umbrella systematic review of current risk prediction models for cardiovascular diseases, diabetes and hypertension

OBJECTIVE

To provide an overview of the currently available risk prediction models (RPMs) for cardiovascular diseases (CVDs), diabetes and hypertension, and to compare their effectiveness in proper recognition of patients at risk of developing these diseases.

DESIGN

Umbrella systematic review.

DATA SOURCES

PubMed, Scopus, Cochrane Library.

ELIGIBILITY CRITERIA

Systematic reviews or meta-analysis examining and comparing performances of RPMs for CVDs, hypertension or diabetes in healthy adult (18-65 years old) population, published in English language.

DATA EXTRACTION AND SYNTHESIS

Data were extracted according to the following parameters: number of studies included, intervention (RPMs applied/assessed), comparison, performance, validation and outcomes. A narrative synthesis was performed. Data were reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.

STUDY SELECTION

3612 studies were identified. After title/abstract screening and removal of duplicate articles, 37 studies met the eligibility criteria. After reading the full text, 13 were deemed relevant for inclusion. Three further papers from the reference lists of these articles were then added.

STUDY APPRAISAL

The methodological quality of the included studies was assessed using the AMSTAR tool.

RISK OF BIAS IN INDIVIDUAL STUDIES

Risk of Bias evaluation was carried out using the ROBIS tool.

RESULTS

Sixteen studies met the inclusion criteria: six focused on diabetes, two on hypertension and eight on CVDs. Globally, prediction models for diabetes and hypertension showed no significant difference in effectiveness. Conversely, some promising differences among prediction tools were highlighted for CVDs. The Ankle-Brachial Index, in association with the Framingham tool, and QRISK scores provided some evidence of a certain superiority compared with Framingham alone.

LIMITATIONS

Due to the significant heterogeneity of the studies, it was not possible to perform a meta-analysis. The electronic search was limited to studies in English and to three major international databases (MEDLINE/PubMed, Scopus and Cochrane Library), with additional works derived from the reference list of other studies; grey literature with unpublished documents was not included in the search. Furthermore, no assessment of potential adverse effects of RPMs was carried out.

CONCLUSIONS

Consistent evidence is available only for CVD prediction: the Framingham score, alone or in combination with the Ankle-Brachial Index, and the QRISK score can be confirmed as the gold standard. Further efforts should not be concentrated on creating new scores, but rather on performing external validation of the existing ones, in particular on high-risk groups. Benefits could be further improved by supplementing existing models with information on lifestyle, personal habits, family and employment history, social network relationships, income and education.

PROSPERO REGISTRATION NUMBER

CRD42018088012.

Eligibility of patients with type 2 diabetes for sodium-glucose co-transporter-2 inhibitor cardiovascular outcomes trials: An assessment using the Diabetes Collaborative Registry

Generalizability of findings from cardiovascular outcomes trials (CVOTs) to patients with type 2 diabetes (T2D) in clinical practice is unknown. We assessed the proportions of patients in the Diabetes Collaborative Registry who would have met enrolment criteria for pivotal CVOTs of sodium-glucose co-transporter-2 inhibitors (SGLT-2is): EMPA-REG OUTCOME, CANVAS, DECLARE and VERTIS CV. In 172 643 patients, mean [standard deviation (SD)] age and HbA1c were 68.1 (11.8) years and 7.8% (2.2), respectively; 56.8% of patients were men and SGLT-2i use was 4.4%. Atherosclerotic cardiovascular disease (ASCVD) prevalence was 64.3% and mean 10-year ASCVD risk was 28.6% in patients without ASCVD. Proportions of patients eligible for CVOTs ranged from 26% (EMPA-REG OUTCOME) to 44% (DECLARE); 48% of patients were ineligible for all CVOTs. Mean (SD) ASCVD risk was 25.4% (22.6), 32.1% (20.6) and 37.7% (19.4) in patients eligible for no, one or two CVOTs, respectively. SGLT-2i use was low in patients eligible for no CVOTs (3.5%) and at least one CVOT (5.2%). In conclusion, applicability of CVOT results to patients with T2D in clinical practice varies based on trial eligibility criteria.

Pharmacist prescribing and care improves cardiovascular risk, but is it cost-effective? A cost-effectiveness analysis of the RxEACH study

Background

The R_xEACH randomized trial demonstrated that community pharmacist prescribing and care reduced the risk for cardiovascular (CV) events by 21% compared to usual care.

Objective

To evaluate the economic impact of pharmacist prescribing and care for CV risk reduction in a Canadian setting.

Methods

A Markov cost-effectiveness model was developed to extrapolate potential differences in long-term CV outcomes, using different risk assessment equations. The mean change in CV risk for the 2 groups of R_xEACH was extrapolated over 30 years, with costs and health outcomes discounted at 1.5% per year. The model incorporated health outcomes, costs and quality of life to estimate overall cost-effectiveness. It was assumed that the intervention would be 50% effective after 10 years. Individual-level results were scaled up to population level based on published statistics (29.2% of Canadian adults are at high risk for CV events). Costs considered included direct medical costs as well as the costs associated with implementing the pharmacist intervention. Uncertainty was explored via probabilistic sensitivity analysis.

Results

It is estimated that the Canadian health care system would save more than $4.4 billion over 30 years if the pharmacist intervention were delivered to 15% of the eligible population. Pharmacist care would be associated with a gain of 576,689 quality-adjusted life years and avoid more than 8.9 million CV events. The intervention is economically dominant (i.e., it is both more effective and reduces costs when compared to usual care).

Conclusion

Across a range of 1-way and probabilistic sensitivity analyses of key parameters and assumptions, pharmacist prescribing and care are both more effective and cost-saving compared to usual care. Canadians need and deserve such care.

A cardiovascular risk score for hypertensive patients previously admitted to hospital

BACKGROUND

Cardiovascular risk scales in hypertensive populations have limitations for clinical practice.

AIMS

To develop and internally validate a predictive model to estimate one-year cardiovascular risk for hypertensive patients admitted to hospital.

METHODS

Cohort study of 303 hypertensive patients admitted through the Emergency Department in a Spanish region in 2015-2017. The main variable was the onset of cardiovascular disease during follow-up. The secondary variables were: gender, age, educational level, family history of cardiovascular disease, Charlson score and its individual conditions, living alone, quality of life, smoking, blood pressure, physical activity and adherence to the Mediterranean diet. A Cox regression model was constructed to predict cardiovascular disease one year after admission. This was then adapted to a points system, externally validated by bootstrapping (discrimination and calibration) and implemented in a mobile application for Android.

RESULTS

A total of 93 patients developed cardiovascular disease (30.7%) over a mean period of 1.68 years. The predictors in the points system were: gender, age, myocardial infarction, heart failure, peripheral arterial disease and daily activity (quality of life). The internal validation by bootstrapping was satisfactory.

CONCLUSION

A novel points system was developed to predict short-term cardiovascular disease in hypertensive patients after hospital admission. External validation studies are needed to corroborate the results obtained.

Real-world opportunity of empagliflozin to improve blood pressure control in African American patients with type 2 diabetes: A National Cardiovascular Data Registry "research-to-practice" project from the diabetes collaborative registry

The 1245.29 Trial recently showed that empaglifozin improved both blood pressure and glucose control in African American (AA) patients with type 2 diabetes (T2D) and hypertension. Using the Diabetes Collaborative Registry, a large-scale US registry of outpatients with diabetes recruited from primary care, cardiology and endocrinology practices, we sought to understand the potential impact of these observations in routine clinical practice. Among 74 290 AA patients with T2D from 368 US clinics, 60.4% had hypertension, of whom 34.5% had systolic blood pressure ≥ 140 mm Hg (20.8% of the total AA T2D population). Only 1.7% of this eligible population had been prescribed a sodium-glucose co-transporter two inhibitor. The mean estimated 5-year risk of cardiovascular death was 7.7%, which could be reduced to 6.2% when modelling the antihypertensive effect of empagliflozin across the eligible population (based on an 8-mm Hg blood pressure reduction). These findings may represent a potential opportunity for better management of cardiovascular risk factors and improved outcomes in this vulnerable cohort.

A one-year risk score to predict all-cause mortality in hypertensive inpatients

The aim of this study was to construct and internally validate a scoring system to estimate the probability of death in hypertensive inpatients. Existing predictive models do not meet all the indications for clinical application because they were constructed in patients enrolled in clinical trials and did not use the recommended statistical methodology. This cohort study comprised 302 hypertensive patients hospitalized between 2015 and 2017 in Spain. The main variable was time-to-death (all-cause mortality). Secondary variables (potential predictors of the model) were: age, gender, smoking, blood pressure, Charlson Comorbidity Index (CCI), physical activity, diet and quality of life. A Cox model was constructed and adapted to a points system to predict mortality one year from admission. The model was internally validated by bootstrapping, assessing both discrimination and calibration. The system was integrated into a mobile application for Android. During the study, 63 patients died (20.9%). The points system prognostic variables were: gender, CCI, personal care and daily activities. Internal validation showed good discrimination (mean C statistic of 0.76) and calibration (observed probabilities adjusted to predicted probabilities). In conclusion, a points system was developed to determine the one-year mortality risk for hypertensive inpatients. This system is very simple to use and has been internally validated. Clinically, we could monitor more closely those patients with a higher risk of mortality to improve their prognosis and quality of life. However, the system must be externally validated to be applied in other geographic areas.

Registry report on prediction by Pocock cardiovascular score of cerebral microemboli acutely following carotid endarterectomy

Background

Cerebral microemboli may lead to ischaemic neurological complications after carotid endarterectomy (CEA). The association between classical cardiovascular risk factors and acute cerebral microemboli following carotid surgery has not been studied. The aim of this study was to explore whether an established cardiovascular risk score (Pocock score) predicts the presence of cerebral microemboli acutely after CEA.

Subjects and methods

Pocock scores were assessed for the 670 patients from the Carotid Surgery Registry (age 71±1 (SEM) years, 474 (71%) male, 652 (97%) Caucasian) managed from January 2002 to December 2012 in the Regional Vascular Centre at University Hospitals Coventry and Warwickshire NHS Trust, which serves a population of 950 000. CEA was undertaken in 474 (71%) patients for symptomatic carotid stenosis and in 196 (25%) asymptomatic patients during the same period. 74% of patients were hypertensive, 71% were smokers and 49% had hypercholesterolaemia.

Results

A high Pocock score (≥2.3%) was significantly associated with evidence of cerebral microemboli acutely following CEA (P=0.039, Mann-Whitney (MW) test). A Pocock score (≥2.3%) did not predict patients who required additional antiplatelet therapy (microemboli signal (MES) rate >50 hour^-1: P=0.164, MW test). Receiver operating characteristic analysis also showed that the Pocock score predicts acute postoperative microemboli (area under the curve (AUC) 0.546, 95% CI 0.502 to 0.590, P=0.039) but not a high rate of postoperative microemboli (MES >50 hour⁻¹: AUC 0.546, 95% CI 0.482 to 0.610, P=0.164). A Pocock score ≥2.3% showed a sensitivity of 74% for the presence of acute postoperative cerebral microemboli. A Pocock score ≥2.3% also showed a sensitivity of 77% and a negative predictive value of 90% for patients who developed a high microembolic rate >50 hour⁻¹ after carotid surgery.

Conclusion

These findings demonstrate that the Pocock score could be used as a clinical tool to identify patients at high risk of developing acute postoperative microemboli.

Association between serum uric acid and carotid disease in patients with atherosclerotic acute ischemic stroke

Aim

The role of serum uric acid in ischemic stroke is controversial. On the one hand, it has a role as neuroprotectant in acute phase, but on the other hand, it may promote atherosclerosis in carotid arteries. Our aim is to investigate the association of serum uric acid levels at admission of acute ischemic stroke patients with carotid disease.

Methods

Cross-sectional study of patients admitted due to acute ischemic stroke. Clinical and laboratory variables were recorded. The carotid disease was defined based on the findings of carotid echography intima to media thickness and stenosis. Patients were grouped according to these findings. Robust statistical methods were applied into analysis.

Results

A total of 245 patients were recruited through a stroke registry. Their values of serum uric acid were related to both carotid intima to media thickness and stenosis showing a positive relationship between serum uric acid levels and intima to media thickness by Pearson correlation ( p < 0.05). Similarly, after adjusting for all potential confounders, eGFR, glucose, age and serum uric acid levels, (OR 1.26 (95% CI 1.04 −1.52, p¼0.01), were identified as independent predictors for having a intima to media thickness ≥1 mm. Similarly, by grouping patients in tertiles of the serum uric acid distribution, we found a predominantly greater carotid disease in the tertile with the highest levels of serum uric acid ( p < 0.005).

Conclusion

Our study supports the hypotheses that serum uric acid levels have different roles in the case of ischemic stroke. Its effects on the vascular wall contribute to the development of atherosclerosis and carotid disease.

Development of clinical risk models for diabetic cardiovascular autonomic neuropathy in a Chinese population using logistic regression analysis

Background: We developed clinical risk models for predicting diabetic cardiovascular autonomic neuropathy (DCAN) in Chinese diabetic patients.

Methods: A Chinese cohort of 455 diabetic participants underwent a short heart rate variability (HRV) test which was recruited between 2011 and 2013. Clinical risk models were developed that included independent and significant risk factors by using multiple variable stepwise regressions. These clinical risk models were tested in another independent cohort of Chinese individuals.

Results: The clinical risk models included age, fasting plasma glucose, 2-h plasma blood glucose, triglycerides, resting HRs, and duration of diabetes mellitus. The area under the receiver-operating characteristic (ROC) curve of the study group was 0.794. In the model with the continuous variables, the area under the ROC curve was 0.810. A cutoff score of 12.54 which produced the optimal sensitivity (68.20%) and specificity (76.80%) and identified the percentage (35.77%) of the population that required subsequent testing.

Conclusions: The clinical risk models showed high sensitivity and specificity for the prediction of DCAN in Chinese diabetic patients.

Predicting individual responses to the electroconvulsive therapy with hippocampal subfield volumes in major depression disorder

Electroconvulsive therapy (ECT) is one of the most effective treatments for major depression disorder (MDD). ECT can induce neurogenesis and synaptogenesis in hippocampus, which contains distinct subfields, e.g., the cornu ammonis (CA) subfields, a granule cell layer (GCL), a molecular layer (ML), and the subiculum. It is unclear which subfields are affected by ECT and whether we predict the future treatment response to ECT by using volumetric information of hippocampal subfields at baseline? In this study, 24 patients with severe MDD received the ECT and their structural brain images were acquired with magnetic resonance imaging before and after ECT. A state-of-the-art hippocampal segmentation algorithm from Freesurfer 6.0 was used. We found that ECT induced volume increases in CA subfields, GCL, ML and subiculum. We applied a machine learning algorithm to the hippocampal subfield volumes at baseline and were able to predict the change in depressive symptoms (r = 0.81; within remitters, r = 0.93). Receiver operating characteristic analysis also showed robust prediction of remission with an area under the curve of 0.90. Our findings provide evidence for particular hippocampal subfields having specific roles in the response to ECT. We also provide an analytic approach for generating predictions about clinical outcomes for ECT in MDD.

Cardiovascular risk reduction in referrals to outpatient vascular clinics

Introduction

Patients with peripheral arterial disease (PAD), aneurysmal disease (AD) or carotid atherosclerosis are at high cardiovascular risk, necessitating secondary cardiovascular protection. The aim of this study was to determine compliance with cardiovascular risk reduction guidelines in new patients referred to vascular clinics.

Methods

A multicentre collaborative national observational audit of new patients referred to eight tertiary general vascular clinics over a three-month period in England and Wales was conducted by the Vascular and Endovascular Research Network (VERN). Referral letters, case notes and investigations were reviewed by local investigators, and data analysed by VERN.

Results

A total of 656 patients were included in the study: 73.2% had PAD, 23.2% had AD and 3.7% had carotid atherosclerosis. A third (37.5%) were current smokers, two-thirds (61.7%) were on antiplatelet therapy and two-thirds (61.5%) were on statin therapy. Smoking was more prevalent in the PAD cohort (PAD 41.4%, AD 27.5%, p =0.003). However, more PAD patients were on antiplatelet therapy (PAD 63.9%, AD 53.3%, p =0.024). Both antiplatelet and statin prescription significantly increased with the number of cardiovascular risk factors. Patients with a previous cardiac or cerebrovascular history were more likely to have stopped smoking, and to be on antiplatelet and statin therapy (p <0.0001 for each). Overall, 47.3% of patients were on both antiplatelet and statin therapy, and 28.9% were on antiplatelet and statin therapy and not smoking.

Conclusions

This study highlights deficiencies in cardiovascular risk minimisation in patients with established vascular disease. Patients with concomitant cardiac or cerebrovascular disease were more likely to be on best medical therapy.

Lipid profile, cardiovascular disease and mortality in a Mediterranean high-risk population: The ESCARVAL-RISK study

INTRODUCTION

The potential impact of targeting different components of an adverse lipid profile in populations with multiple cardiovascular risk factors is not completely clear. This study aims to assess the association between different components of the standard lipid profile with all-cause mortality and hospitalization due to cardiovascular events in a high-risk population.

METHODS

This prospective registry included high risk adults over 30 years old free of cardiovascular disease (2008-2012). Diagnosis of hypertension, dyslipidemia or diabetes mellitus was inclusion criterion. Lipid biomarkers were evaluated. Primary endpoints were all-cause mortality and hospital admission due to coronary heart disease or stroke. We estimated adjusted rate ratios (aRR), absolute risk differences and population attributable risk associated with adverse lipid profiles.

RESULTS

51,462 subjects were included with a mean age of 62.6 years (47.6% men). During an average follow-up of 3.2 years, 919 deaths, 1666 hospitalizations for coronary heart disease and 1510 hospitalizations for stroke were recorded. The parameters that showed an increased rate for total mortality, coronary heart disease and stroke hospitalization were, respectively, low HDL-Cholesterol: aRR 1.25, 1.29 and 1.23; high Total/HDL-Cholesterol: aRR 1.22, 1.38 and 1.25; and high Triglycerides/HDL-Cholesterol: aRR 1.21, 1.30, 1.09. The parameters that showed highest population attributable risk (%) were, respectively, low HDL-Cholesterol: 7.70, 11.42, 8.40; high Total/HDL-Cholesterol: 6.55, 12.47, 8.73; and high Triglycerides/HDL-Cholesterol: 8.94, 15.09, 6.92.

CONCLUSIONS

In a population with cardiovascular risk factors, HDL-cholesterol, Total/HDL-cholesterol and triglycerides/HDL-cholesterol ratios were associated with a higher population attributable risk for cardiovascular disease compared to other common biomarkers.

Annual progression of endothelial dysfunction in patients with COPD

BACKGROUND

The risk to die from cardiovascular disease is particularly high in patients with COPD. This longitudinal study aims to evaluate changes of endothelial function over time and identify underlying mechanisms in COPD patients.

METHODS

In stable COPD patients we performed annual assessments of endothelial function by flow-mediated dilatation (FMD), lung function, systemic inflammation and cholesterol, sympathetic activation, oxygenation, physical activity and exercise capacity. Associations between annual changes of potential predictors and FMD were investigated in mixed analysis.

RESULTS

76 patients (41% GOLD stage 1/2, 30% 3, 29% 4) were included. Endothelial function significantly decreased annually by -0.14% (95%CI -0.25/-0.04), equal to a relative decrease of -5.6%. Yearly change in 6-min walking distance was significantly associated with FMD in univariable analysis (Coef. -0.00, p = 0.045). Progressive airway obstruction and increase in level of total cholesterol were borderline significant with a greater decrease in FMD (Coeff. -0.02, p = 0.097 and Coeff. -0.16, p = 0.080, respectively). In multivariable analysis a greater annual decline in FEV1 tends to be independently associated with a decrease in FMD (p = 0.085).

CONCLUSION

The findings of this study demonstrated that COPD patients experience a significant decrease in endothelial function over time. A greater annual decline in lung function tends to be associated with greater decrease in FMD. However, no other independent predictors for endothelial dysfunction could be identified.

CLINICAL TRIAL REGISTRATION

www.ClinicalTrials.gov, NCT01527773.

A sudden death risk score specifically for hypertension: based on 25 648 individual patient data from six randomized controlled trials

OBJECTIVE

To construct a sudden death risk score specifically for hypertension (HYSUD) patients with or without cardiovascular history.

METHODS

Data were collected from six randomized controlled trials of antihypertensive treatments with 8044 women and 17 604 men differing in age ranges and blood pressure eligibility criteria. In total, 345 sudden deaths (1.35%) occurred during a mean follow-up of 5.16 years. Risk factors of sudden death were examined using a multivariable Cox proportional hazards model adjusted on trials. The model was transformed to an integer system, with points added for each factor according to its association with sudden death risk.

RESULTS

Antihypertensive treatment was not associated with a reduction of the sudden death risk and had no interaction with other factors, allowing model development on both treatment and placebo groups. A risk score of sudden death in 5 years was built with seven significant risk factors: age, sex, SBP, serum total cholesterol, cigarette smoking, diabetes, and history of myocardial infarction. In terms of discrimination performance, HYSUD model was adequate with areas under the receiver operating characteristic curve of 77.74% (confidence interval 95%, 74.13-81.35) for the derivation set, of 77.46% (74.09-80.83) for the validation set, and of 79.17% (75.94-82.40) for the whole population.

CONCLUSION

Our work provides a simple risk-scoring system for sudden death prediction in hypertension, using individual data from six randomized controlled trials of antihypertensive treatments. HYSUD score could help assessing a hypertensive individual's risk of sudden death and optimizing preventive therapeutic strategies for these patients.

Why do authors derive new cardiovascular clinical prediction rules in the presence of existing rules? A mixed methods study

Background

Researchers should examine existing evidence to determine the need for a new study. It is unknown whether developers evaluate existing evidence to justify new cardiovascular clinical prediction rules (CPRs).

Objective

We aimed to assess whether authors of cardiovascular CPRs cited existing CPRs, why some authors did not cite existing CPRs, and why they thought existing CPRs were insufficient.

Method

Derivation studies of cardiovascular CPRs from the International Register of Clinical Prediction Rules for Primary Care were evaluated. We reviewed the introduction sections to determine whether existing CPRs were cited. Using thematic content analysis, the stated reasons for determining existing cardiovascular CPRs insufficient were explored. Study authors were surveyed via e-mail and post. We asked whether they were aware of any existing cardiovascular CPRs at the time of derivation, how they searched for existing CPRs, and whether they thought it was important to cite existing CPRs.

Results

Of 85 derivation studies included, 48 (56.5%) cited existing CPRs, 33 (38.8%) did not cite any CPR, and four (4.7%) declared there was none to cite. Content analysis identified five categories of existing CPRs insufficiency related to: (1) derivation (5 studies; 11.4% of 44), (2) construct (31 studies; 70.5%), (3) performance (10 studies; 22.7%), (4) transferability (13 studies; 29.5%), and (5) evidence (8 studies; 18.2%). Authors of 54 derivation studies (71.1% of 76 authors contacted) responded to the survey. Twenty-five authors (46.3%) reported they were aware of existing CPR at the time of derivation. Twenty-nine authors (53.7%) declared they conducted a systematic search to identify existing CPRs. Most authors (90.7%) indicated citing existing CPRs was important.

Conclusion

Cardiovascular CPRs are often developed without citing existing CPRs although most authors agree it is important. Common justifications for new CPRs concerned construct, including choice of predictor variables or relevance of outcomes. Developers should clearly justify why new CPRs are needed with reference to existing CPRs to avoid unnecessary duplication.

Cost-effectiveness of pharmacist care for managing hypertension in Canada

Background:

More than half of all heart disease and stroke are attributable to hypertension, which is associated with approximately 10% of direct medical costs globally. Clinical trial evidence has demonstrated that the benefits of pharmacist intervention, including education, consultation and/or prescribing, can help to reduce blood pressure; a recent Canadian trial found an 18.3 mmHg reduction in systolic blood pressure associated with pharmacist care and prescribing. The objective of this study was to evaluate the economic impact of such an intervention in a Canadian setting.

Methods:

A Markov cost-effectiveness model was developed to extrapolate potential differences in long-term cardiovascular and renal disease outcomes, using Framingham risk equations and other published risk equations. A range of values for systolic blood pressure reduction was considered (7.6-18.3 mmHg) to reflect the range of potential interventions and available evidence. The model incorporated health outcomes, costs and quality of life to estimate an overall incremental cost-effectiveness ratio. Costs considered included direct medical costs as well as the costs associated with implementing the pharmacist intervention strategy.

Results:

For a systolic blood pressure reduction of 18.3 mmHg, the estimated impact is 0.21 fewer cardiovascular events per person and, discounted at 5% per year, 0.3 additional life-years, 0.4 additional quality-adjusted life-years and $6,364 cost savings over a lifetime. Thus, the intervention is economically dominant, being both more effective and cost-saving relative to usual care.

Discussion:

Across a range of one-way and probabilistic sensitivity analyses of key parameters and assumptions, pharmacist intervention remained both effective and cost-saving.

Conclusion:

Comprehensive pharmacist care of hypertension, including patient education and prescribing, has the potential to offer both health benefits and cost savings to Canadians and, as such, has important public health implications.

Stroke Risk Factors, Genetics, and Prevention

Stroke is a heterogeneous syndrome, and determining risk factors and treatment depends on the specific pathogenesis of stroke. Risk factors for stroke can be categorized as modifiable and nonmodifiable. Age, sex, and race/ethnicity are nonmodifiable risk factors for both ischemic and hemorrhagic stroke, while hypertension, smoking, diet, and physical inactivity are among some of the more commonly reported modifiable risk factors. More recently described risk factors and triggers of stroke include inflammatory disorders, infection, pollution, and cardiac atrial disorders independent of atrial fibrillation. Single-gene disorders may cause rare, hereditary disorders for which stroke is a primary manifestation. Recent research also suggests that common and rare genetic polymorphisms can influence risk of more common causes of stroke, due to both other risk factors and specific stroke mechanisms, such as atrial fibrillation. Genetic factors, particularly those with environmental interactions, may be more modifiable than previously recognized. Stroke prevention has generally focused on modifiable risk factors. Lifestyle and behavioral modification, such as dietary changes or smoking cessation, not only reduces stroke risk, but also reduces the risk of other cardiovascular diseases. Other prevention strategies include identifying and treating medical conditions, such as hypertension and diabetes, that increase stroke risk. Recent research into risk factors and genetics of stroke has not only identified those at risk for stroke but also identified ways to target at-risk populations for stroke prevention.

Quantifying the impact of different approaches for handling continuous predictors on the performance of a prognostic model

Continuous predictors are routinely encountered when developing a prognostic model. Investigators, who are often non-statisticians, must decide how to handle continuous predictors in their models. Categorising continuous measurements into two or more categories has been widely discredited, yet is still frequently done because of its simplicity, investigator ignorance of the potential impact and of suitable alternatives, or to facilitate model uptake. We examine three broad approaches for handling continuous predictors on the performance of a prognostic model, including various methods of categorising predictors, modelling a linear relationship between the predictor and outcome and modelling a nonlinear relationship using fractional polynomials or restricted cubic splines. We compare the performance (measured by the c-index, calibration and net benefit) of prognostic models built using each approach, evaluating them using separate data from that used to build them. We show that categorising continuous predictors produces models with poor predictive performance and poor clinical usefulness. Categorising continuous predictors is unnecessary, biologically implausible and inefficient and should not be used in prognostic model development. © 2016 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.

Cohort profile: Women's Healthy Ageing Project (WHAP) - a longitudinal prospective study of Australian women since 1990

Background

The cohort was commenced to examine women’s health from midlife (45–55 years) before the menopausal transition and into ageing.

Methods

Randomised selection and assessment of 2,001 women living in the Melbourne metropolitan area was conducted by the Roy Morgan Centre in 1990/91. Of the 779 women who met the entry criteria for the longitudinal follow-up (aged 45–55 years, menstruating, having a uterus and at least one ovary and not taking hormone therapy) 438 agreed to be seen annually across the menopausal transition from 1992 to 1999. Longitudinal prospective follow-up since 2000 has continued intermittently (2002/03, 2004/05, 2012/13, 2014/15). Data collection has included fasting biomarkers in each year since 1992, clinical assessment, lifestyle and quality of life data, physical measures and validated questionnaire data. Participants have consented to data linkage and, to date, mammogram and BioGrid data have been accessed. Biobank storage including serum, deoxyribonucleic acid (DNA) storage and PAXgene tubes are maintained.

Discussion

The WHAP has contributed to over 200 published research findings, several books, and book chapters in a variety of areas, including: health and wellbeing; mental and cognitive health; bone health; lifestyle, vascular risk and prevention; women’s health and hormonal transition; and cross-cultural research.

With all participants now aged over 70 years, the cohort is ideally placed to answer key questions of healthy ageing in women. With more than 25 years of longitudinal prospective follow-up this Australian dataset is unique in its duration, breadth and detail of measures including clinical review and specialized disease-specific testing and biomarkers. Ongoing follow-up into older ages for this long-running cohort will enable the association between mid to late-life factors and healthy ageing to be determined. This is particularly valuable for the examination of chronic diseases which have a 20–30 year prodrome and to provide knowledge on multiple morbidities. The dataset has a unique opportunity to improve our understanding of temporal relationships and the interactions between risk factors and comorbidities.

Electronic supplementary material

The online version of this article (doi:10.1186/s40695-016-0018-y) contains supplementary material, which is available to authorized users.

The application of information theory for the research of aging and aging-related diseases

This article reviews the application of information-theoretical analysis, employing measures of entropy and mutual information, for the study of aging and aging-related diseases. The research of aging and aging-related diseases is particularly suitable for the application of information theory methods, as aging processes and related diseases are multi-parametric, with continuous parameters coexisting alongside discrete parameters, and with the relations between the parameters being as a rule non-linear. Information theory provides unique analytical capabilities for the solution of such problems, with unique advantages over common linear biostatistics. Among the age-related diseases, information theory has been used in the study of neurodegenerative diseases (particularly using EEG time series for diagnosis and prediction), cancer (particularly for establishing individual and combined cancer biomarkers), diabetes (mainly utilizing mutual information to characterize the diseased and aging states), and heart disease (mainly for the analysis of heart rate variability). Few works have employed information theory for the analysis of general aging processes and frailty, as underlying determinants and possible early preclinical diagnostic measures for aging-related diseases. Generally, the use of information-theoretical analysis permits not only establishing the (non-linear) correlations between diagnostic or therapeutic parameters of interest, but may also provide a theoretical insight into the nature of aging and related diseases by establishing the measures of variability, adaptation, regulation or homeostasis, within a system of interest. It may be hoped that the increased use of such measures in research may considerably increase diagnostic and therapeutic capabilities and the fundamental theoretical mathematical understanding of aging and disease.

ECG risk markers for atrial fibrillation and sudden cardiac death in minimally symptomatic obstructive sleep apnoea: the MOSAIC randomised trial

OBJECTIVE

Obstructive sleep apnoea (OSA), atrial fibrillation (AF) and sudden cardiac death (SCD) may occur concomitantly, and are of considerable epidemiological interest, potentially leading to morbidity and mortality. Effective treatment of OSA with continuous positive airway pressure (CPAP) could prevent progression and/or recurrence of AF and factors leading to SCD. Recently, a randomised controlled trial showed a statistically and clinically significant prolongation of measures of cardiac repolarisation after CPAP withdrawal in symptomatic patients with moderate to severe OSA. Whether or not CPAP therapy improves ECG risk markers of AF and SCD in patients with minimally symptomatic OSA as well, is unknown.

METHODS

3 centres taking part in the MOSAIC (Multicentre Obstructive Sleep Apnoea Interventional Cardiovascular) trial randomised 303 patients with minimally symptomatic OSA to receive either CPAP or standard care for 6 months. Treatment effects of CPAP on P-wave duration, P-wave dispersion, QT interval, QT dispersion, Tpeak-to-Tend (TpTe) and TpTe/QT ratio were analysed.

RESULTS

Participants were primarily men (83%). Mean age was 57.8 (7.2) and mean ODI (Oxygen Desaturation Index) at baseline was 13.1/h (12.3). Full 12-lead ECG data was available in 250 patients. Mean (SD) baseline intervals of P-wave duration, P-wave dispersion, QTc interval, QT dispersion, TpTe and TpTe/QT ratio in ms were 87.4 (8.3), 42.3 (11.9), 397.8 (22.7), 43.1 (16.7), 73.5 (13.7) and 0.19 (0.0), respectively. No treatment effect of CPAP on risk markers for AF and SCD was found.

CONCLUSIONS

There seems to be no effect of CPAP on ECG measures of arrhythmia risk in patients with minimally symptomatic OSA.

TRIAL REGISTRATION NUMBER

ISRCTN34164388; Post-results.

Effect of CPAP on Cardiac Function in Minimally Symptomatic Patients with OSA: Results from a Subset of the MOSAIC Randomized Trial

STUDY OBJECTIVES

Minimally symptomatic obstructive sleep apnea (OSA) is highly prevalent, and the effects of continuous positive airway pressure (CPAP) on myocardial function in these patients are unknown. The MOSAIC randomized, controlled trial of CPAP for minimally symptomatic OSA assessed the effect of CPAP on myocardial function in a subset of patients.

METHODS

Two centers taking part in the MOSAIC trial randomized 238 patients in parallel to 6 months of CPAP (120) or standard care (118). Of these, 168 patients had echocardiograms, and 68 patients had a cardiac magnetic resonance scan (CMR). A larger group (314) from 4 centers had brain natriuretic peptide (BNP) measured.

RESULTS

Mean (SD) baseline oxygen desaturation index (ODI) and Epworth sleepiness score (ESS) were 13.5 (13.2), and 8.4 (4.0), respectively. CPAP significantly reduced ESS and ODI. Baseline LV ejection fraction (LVEF) was well preserved (60.4%). CPAP had no significant effect on echo-derived left atrial (LA) area (-1.0 cm2, 95% CI -2.6 to +0.6, p = 0.23) or early to late left ventricular filling velocity (E/A) ratio (-0.01, 95% CI -0.07 to +0.05, p = 0.79). There was a small change in echo-derived LV end diastolic volume (EDV) with CPAP (-5.9 mL, 95% CI -10.6 to -1.2, p = 0.015). No significant changes were detected by CMR on LV mass index (+1.1 g/m(2), 95% CI -5.9 to +8.0, p = 0.76) or LVEF (+0.8%, 95% CI -1.2 to +2.8, p = 0.41). CPAP did not affect BNP levels (p = 0.16).

CONCLUSIONS

Six months of CPAP therapy does not change cardiac functional or structural parameters measured by echocardiogram or CMR in patients with minimally symptomatic mild-to-moderate OSA.

CLINICAL TRIAL REGISTRATION

ISRCTN 34164388 (http://isrctn.org).