Systematically missing confounders in individual participant data meta-analysis of observational cohort studies.

One difficulty in performing meta-analyses of observational cohort studies is that the availability of confounders may vary between cohorts, so that some cohorts provide fully adjusted analyses while others only provide partially adjusted analyses. Commonly, analyses of the association between an exposure and disease either are restricted to cohorts with full confounder information, or use all cohorts but do not fully adjust for confounding. We propose using a bivariate random-effects meta-analysis model to use information from all available cohorts while still adjusting for all the potential confounders. Our method uses both the fully adjusted and the partially adjusted estimated effects in the cohorts with full confounder information, together with an estimate of their within-cohort correlation. The method is applied to estimate the association between fibrinogen level and coronary heart disease incidence using data from 154,012 participants in 31 cohort

Predictors of loss to follow up among patients with type 2 diabetes mellitus attending a private not for profit urban diabetes clinic in Uganda : a descriptive retrospective study

BACKGROUND: Although the prevalence of type 2 diabetes mellitus is increasing in Uganda, data on loss to follow up (LTFU) of patients in care is scanty. We aimed to estimate proportions of patients LTFU and document associated factors among patients attending a private not for profit urban diabetes clinic in Uganda. METHODS: We conducted a descriptive retrospective study between March and May 2017. We reviewed 1818 out-patient medical records of adults diagnosed with type 2 diabetes mellitus registered between July 2003 and September 2016 at St. Francis Hospital - Nsambya Diabetes clinic in Uganda. Data was extracted on: patients' registration dates, demographics, socioeconomic status, smoking, glycaemic control, type of treatment, diabetes mellitus complications and last follow-up clinic visit. LTFU was defined as missing collecting medication for six months or more from the date of last clinic visit, excluding situations of death or referral to another clinic. We used Kaplan-Meier technique to estimate time to defaulting medical care after initial registration, log-rank test to test the significance of observed differences between groups. Cox proportional hazards regression model was used to determine predictors of patients' LTFU rates in hazard ratios (HRs). RESULTS: Between July 2003 and September 2016, one thousand eight hundred eighteen patients with type 2 diabetes mellitus were followed for 4847.1 person-years. Majority of patients were female 1066/1818 (59%) and 1317/1818 (72%) had poor glycaemic control. Over the 13 years, 1690/1818 (93%) patients were LTFU, giving a LTFU rate of 34.9 patients per 100 person-years (95%CI: 33.2-36.6). LTFU was significantly higher among males, younger patients (< 45 years), smokers, patients on dual therapy, lower socioeconomic status, and those with diabetes complications like neuropathy and nephropathy. CONCLUSION: We found high proportions of patients LTFU in this diabetes clinic which warrants intervention studies targeting the identified risk factors and strengthening follow up of patients

Individualised therapy of angiotensin converting enzyme (ACE) inhibitors in stable coronary artery disease: overview of the primary results of the PERindopril GENEtic association (PERGENE) study

In patients with stable coronary artery disease (CAD) without overt heart failure, ACE inhibitors are among the most commonly used drugs as these agents have been proven effective in reducing the risk of cardiovascular events. Considerable individual variations in the blood pressure response to ACE inhibitors are observed and as such heterogeneity in clinical treatment effect would be likely as well. Assessing the consistency of treatment benefit is essential for the rational and cost-effective prescription of ACE inhibitors. Information on heterogeneities in treatment effect between subgroups of patients could be used to develop an evidence-based guidance for the installation of ACE-inhibitor therapy. Obviously, therapy should only be applied in those patients who most likely will benefit. Attempts to develop such treatment guidance by using clinical characteristics have been unsuccessful. No heterogeneity in risk reduction by ACE inhibitors has been observed in relation to relevant clinical characteristics. A new approach to such ‘guided-therapy’ could be to integrate more patient-specific characteristics such as the patients’ genetic information. If proven feasible, pharmacogenetic profiling could optimise patients’ benefit of treatment and reduce unnecessary treatment of patients. Cardiovascular pharmacogenetic research of ACE inhibitors in coronary artery disease patients is in a formative stage and studies are limited. The PERGENE study is a large pharmacogenetic substudy of the EUROPA trial, aimed to assess the achievability of pharmacogenetic profiling. We provide an overview of the main results of the PERGENE study in terms of the genetic determinants of treatment benefit and blood pressure response. The main results of the PERGENE study show a pharmacogenetic profile related to the treatment benefit of perindopril identifying responders and non-responders to treatment

Comparison of the impact of atrial fibrillation on the risk of early death after stroke in women versus men

BACKGROUND: Atrial fibrillation (AF) is considered a predictive factor of poor clinical outcome in patients with an ischemic stroke (IS). This study addressed whether the impact of AF on the in-hospital mortality after first ever IS is different according to the patient’s gender. METHODS: We prospectively studied 1678 patients with first ever IS consecutively admitted to two University Hospitals. We recorded demographic data, vascular risk factors, and the stroke severity (NIHSS) at admission analyzing their impact on the in-hospital mortality and on the combined mortality-dependency at discharge using a Cox proportional hazards model. Two variable interactions between those factors independently related to in-hospital mortality and combined mortality-dependency at discharge were tested. RESULTS: Overall in-hospital mortality was 11.3%. Cox proportional hazards model showed that NIHSS at admission (HR: 1.178 [95% CI 1.149–1.207]), age (HR: 1.044 [95% CI 1.026–1.061]), AF (HR: 1.416 [95% CI 1.048–1.913]), male gender (HR: 1.853 [95% CI 1.323–2.192) and ischemic heart disease (HR: 1.527 [95% CI 1.063–2.192]) were independent predictors of in-hospital mortality. A significant interaction between gender and AF was found (p = 0.017). Data were stratified by gender, showing that AF was an independent predictor of poor outcome just for woman (HR: 2.183 [95% CI 1.403–3.396]; p < 0.001). The independent predictors of combined mortality-disability at discharge were NIHSS at admission (HR: 1.052 [95% CI 1.041–1.063]), age (HR: 1.011 [95% CI 1.004–1.018]), AF (HR: 1.197 [95% CI 1.031–1.390]), ischemic heart disease (HR: 1.222 [95% CI 1.004–1.488]), and smoking (HR: 1.262 [95% CI 1.033–1.541]). CONCLUSIONS: The impact of AF is different in the twogenders and appears as a specific ischemic stroke predictor of in-hospital mortality just for women

Markers of Dysglycaemia and Risk of Coronary Heart Disease in People without Diabetes: Reykjavik Prospective Study and Systematic Review

BACKGROUND: Associations between circulating markers of dysglycaemia and coronary heart disease (CHD) risk in people without diabetes have not been reliably characterised. We report new data from a prospective study and a systematic review to help quantify these associations. METHODS AND FINDINGS: Fasting and post-load glucose levels were measured in 18,569 participants in the population-based Reykjavik study, yielding 4,664 incident CHD outcomes during 23.5 y of mean follow-up. In people with no known history of diabetes at the baseline survey, the hazard ratio (HR) for CHD, adjusted for several conventional risk factors, was 2.37 (95% CI 1.79-3.14) in individuals with fasting glucose > or = 7.0 mmol/l compared to those or = 7 mmol/l at baseline were excluded, relative risks for CHD, adjusted for several conventional risk factors, were: 1.06 (1.00-1.12) per 1 mmol/l higher fasting glucose (23 cohorts, 10,808 cases, 255,171 participants); 1.05 (1.03-1.07) per 1 mmol/l higher post-load glucose (15 cohorts, 12,652 cases, 102,382 participants); and 1.20 (1.10-1.31) per 1% higher HbA(1c) (9 cohorts, 1639 cases, 49,099 participants). CONCLUSIONS: In the Reykjavik Study and a meta-analysis of other Western prospective studies, fasting and post-load glucose levels were modestly associated with CHD risk in people without diabetes. The meta-analysis suggested a somewhat stronger association between HbA(1c) levels and CHD risk

Pre-hospital ECG for acute coronary syndrome in urban India: A cost-effectiveness analysis

<p>Abstract</p> <p>Background</p> <p>Patients with acute coronary syndrome (ACS) in India have increased pre-hospital delay and low rates of thrombolytic reperfusion. Use of ECG could reduce pre-hospital delay among patients who first present to a general practitioner (GP). We assessed whether performing ECG on patients with acute chest pain would improve long-term outcomes and be cost-effective.</p> <p>Methods</p> <p>We created a Markov model of urban Indian patients presenting to a GP with acute chest pain to compare a GP's performing an ECG versus not performing one. Variables describing the accuracy of a GP's referral decision in chest pain and ACS, ACS treatment patterns, the effectiveness of thrombolytic reperfusion, and costs were derived from Indian data where available and other developed world studies. The model was used to estimate the incremental cost-effectiveness ratio (ICER) of the intervention in 2007 US dollars per quality adjusted life years (QALY) gained.</p> <p>Results</p> <p>Under baseline assumptions, the ECG strategy cost an additional $12.65 per QALY gained compared to no ECG. Sensitivity analyses around the cost of the ECG, cost of thrombolytic, and referral accuracy of the GP yielded ICERs for the ECG strategy ranging between cost-saving and$1124/QALY. All results indicated the intervention is cost-effective under current World Health Organization recommendations.</p> <p>Conclusions</p> <p>While direct presentation to the hospital with acute chest pain is preferable, in urban Indian patients presenting first to a GP, an ECG performed by the GP is a cost-effective strategy to reduce disability and mortality. This strategy should be clinically studied and considered until improved emergency transport services are available.</p

Is bioelectrical impedance accurate for use in large epidemiological studies?

Percentage of body fat is strongly associated with the risk of several chronic diseases but its accurate measurement is difficult. Bioelectrical impedance analysis (BIA) is a relatively simple, quick and non-invasive technique, to measure body composition. It measures body fat accurately in controlled clinical conditions but its performance in the field is inconsistent. In large epidemiologic studies simpler surrogate techniques such as body mass index (BMI), waist circumference, and waist-hip ratio are frequently used instead of BIA to measure body fatness. We reviewed the rationale, theory, and technique of recently developed systems such as foot (or hand)-to-foot BIA measurement, and the elements that could influence its results in large epidemiologic studies. BIA results are influenced by factors such as the environment, ethnicity, phase of menstrual cycle, and underlying medical conditions. We concluded that BIA measurements validated for specific ethnic groups, populations and conditions can accurately measure body fat in those populations, but not others and suggest that for large epdiemiological studies with diverse populations BIA may not be the appropriate choice for body composition measurement unless specific calibration equations are developed for different groups participating in the study

Genome-Wide Identification of Susceptibility Alleles for Viral Infections through a Population Genetics Approach

Viruses have exerted a constant and potent selective pressure on human genes throughout evolution. We utilized the marks left by selection on allele frequency to identify viral infection-associated allelic variants. Virus diversity (the number of different viruses in a geographic region) was used to measure virus-driven selective pressure. Results showed an excess of variants correlated with virus diversity in genes involved in immune response and in the biosynthesis of glycan structures functioning as viral receptors; a significantly higher than expected number of variants was also seen in genes encoding proteins that directly interact with viral components. Genome-wide analyses identified 441 variants significantly associated with virus-diversity; these are more frequently located within gene regions than expected, and they map to 139 human genes. Analysis of functional relationships among genes subjected to virus-driven selective pressure identified a complex network enriched in viral products-interacting proteins. The novel approach to the study of infectious disease epidemiology presented herein may represent an alternative to classic genome-wide association studies and provides a large set of candidate susceptibility variants for viral infections

Life expectancy associated with different ages at diagnosis of type 2 diabetes in high-income countries: 23 million person-years of observation

Background: The prevalence of type 2 diabetes is increasing rapidly, particularly among younger age groups. Estimates suggest that people with diabetes die, on average, 6 years earlier than people without diabetes. We aimed to provide reliable estimates of the associations between age at diagnosis of diabetes and all-cause mortality, cause-specific mortality, and reductions in life expectancy. Methods: For this observational study, we conducted a combined analysis of individual-participant data from 19 high-income countries using two large-scale data sources: the Emerging Risk Factors Collaboration (96 cohorts, median baseline years 1961–2007, median latest follow-up years 1980–2013) and the UK Biobank (median baseline year 2006, median latest follow-up year 2020). We calculated age-adjusted and sex-adjusted hazard ratios (HRs) for all-cause mortality according to age at diagnosis of diabetes using data from 1 515 718 participants, in whom deaths were recorded during 23·1 million person-years of follow-up. We estimated cumulative survival by applying age-specific HRs to age-specific death rates from 2015 for the USA and the EU. Findings: For participants with diabetes, we observed a linear dose–response association between earlier age at diagnosis and higher risk of all-cause mortality compared with participants without diabetes. HRs were 2·69 (95% CI 2·43–2·97) when diagnosed at 30–39 years, 2·26 (2·08–2·45) at 40–49 years, 1·84 (1·72–1·97) at 50–59 years, 1·57 (1·47–1·67) at 60–69 years, and 1·39 (1·29–1·51) at 70 years and older. HRs per decade of earlier diagnosis were similar for men and women. Using death rates from the USA, a 50-year-old individual with diabetes died on average 14 years earlier when diagnosed aged 30 years, 10 years earlier when diagnosed aged 40 years, or 6 years earlier when diagnosed aged 50 years than an individual without diabetes. Using EU death rates, the corresponding estimates were 13, 9, or 5 years earlier. Interpretation: Every decade of earlier diagnosis of diabetes was associated with about 3–4 years of lower life expectancy, highlighting the need to develop and implement interventions that prevent or delay the onset of diabetes and to intensify the treatment of risk factors among young adults diagnosed with diabetes. Funding: British Heart Foundation, Medical Research Council, National Institute for Health and Care Research, and Health Data Research UK