Prevalence of left ventricular systolic dysfunction and heart failure with reduced ejection fraction in men and women with type 2 diabetes

Background: Type 2 diabetes mellitus (T2D) is associated with the development of left ventricular systolic dysfunction (LVSD) and heart failure with reduced ejection fraction (HFrEF). T2D patients with LVSD are at higher risk of mortality and morbidity than patients without LVSD, while progression of LVSD can be delayed or halted by the use of proven therapies. As estimates of the prevalence are scarce and vary considerably, the aim of this study was to retrieve summary estimates of the prevalence of LVSD/HFrEF in T2D and to see if there were any sex differences. Methods: A systematic search of Medline and Embase was performed to extract the prevalence of LVSD/HFrEF in T2D (17 studies, mean age 50.1 ± 6.3 to 71.5 ± 7.5), which were pooled using random-effects meta-analysis. Results: The pooled prevalence of LVSD was higher in hospital populations (13 studies, n = 5835, 18% [95% CI 17-19%]), than in the general population (4 studies, n = 1707, 2% [95% CI 2-3%]). Seven studies in total reported sex-stratified prevalence estimates (men: 7% [95% CI 5-8%] vs. women: 1.3% [95% CI 0.0.2.2%]). The prevalence of HFrEF was available in one general population study (5.8% [95% CI 3.7.6%], men: 6.8% vs. women: 3.0%). Conclusions: The summary prevalence of LVSD is higher among T2D patients from a hospital setting compared with from the general population, with a higher prevalence in men than in women in both settings. The prevalence of HFrEF among T2D in the population was only assessed in a single study and again was higher among men than women

Cardiac imaging to detect coronary artery disease in athletes aged 35 years and older. A scoping review.

Sudden cardiac death (SCD) is a devastating event in athletes. Screening efforts that were first directed at athletes younger than 35 years, are now focusing on the rapidly growing group of older sportspersons. Athletes aged ≥35 years have a 10-fold increased risk of exercise-related cardiac arrest, mostly due to coronary artery disease (CAD). Although cardiac imaging is pivotal in identifying CAD, the role of imaging modalities in screening asymptomatic older sportspersons remains unclear. We performed a scoping review to identify the role of cardiac imaging to detect CAD in older sportspersons and to identify gaps in the existing literature. We searched Medline, Embase and the Cochrane library for studies reporting data on cardiac imaging of CAD in sportspersons ≥35 years. The systematic search yielded 1737 articles and 14 were included in this scoping review. Imaging modalities included 2 echocardiography, 1 unenhanced Computed Tomography (CT) for coronary artery calcium scoring (CACS), 3 CACS and contrast-enhanced CT angiography (CCTA), 2 CACS and Cardiac Magnetic Resonance (CMR), 1 CCTA with CMR and echocardiography, 2 CCTA, 2 CMR, and 1 myocardial perfusion imaging article. The low number of relevant articles and the selection bias introduced by studying specific groups, like veteran marathon runners, indicate the need for future research. Cardiac CT (CACS and CCTA) probably has the highest potential for pre-participation screening, with high diagnostic value to detect CAD and low radiation dose. However, currently there is insufficient evidence for incorporating routine cardiac imaging in the pre-participation screening of asymptomatic sportspersons over 35 years

Calculating the sample size required for developing a clinical prediction model.

Clinical prediction models aim to predict outcomes in individuals, to inform diagnosis or prognosis in healthcare. Hundreds of prediction models are published in the medical literature each year, yet many are developed using a dataset that is too small for the total number of participants or outcome events. This leads to inaccurate predictions and consequently incorrect healthcare decisions for some individuals. In this article, the authors provide guidance on how to calculate the sample size required to develop a clinical prediction model

STARD for Abstracts: Essential items for reporting diagnostic accuracy studies in journal or conference abstracts

Many abstracts of diagnostic accuracy studies are currently insufficiently informative. We extended the STARD (Standards for Reporting Diagnostic Accuracy) statement by developing a list of essential items that authors should consider when reporting diagnostic accuracy studies in journal or conference abstracts. After a literature review of published guidance for reporting biomedical studies, we identified 39 items potentially relevant to report in an abstract. We then selected essential items through a two round web based survey among the 85 members of the STARD Group, followed by discussions within an executive committee. Seventy three STARD Group members responded (86%), with 100% completion rate. STARD for Abstracts is a list of 11 quintessential items, to be reported in every abstract of a diagnostic accuracy study. We provide examples of complete reporting, and developed template text for writing informative abstract

Transparent reporting of multivariable prediction models developed or validated using clustered data (TRIPOD-Cluster): explanation and elaboration.

The TRIPOD-Cluster (transparent reporting of multivariable prediction models developed or validated using clustered data) statement comprises a 19 item checklist, which aims to improve the reporting of studies developing or validating a prediction model in clustered data, such as individual participant data meta-analyses (clustering by study) and electronic health records (clustering by practice or hospital). This explanation and elaboration document describes the rationale; clarifies the meaning of each item; and discusses why transparent reporting is important, with a view to assessing risk of bias and clinical usefulness of the prediction model. Each checklist item of the TRIPOD-Cluster statement is explained in detail and accompanied by published examples of good reporting. The document also serves as a reference of factors to consider when designing, conducting, and analysing prediction model development or validation studies in clustered data. To aid the editorial process and help peer reviewers and, ultimately, readers and systematic reviewers of prediction model studies, authors are recommended to include a completed checklist in their submission

The assessment of the quality of reporting of meta-analyses in diagnostic research: a systematic review

<p>Abstract</p> <p>Background</p> <p>Over the last decade there have been a number of guidelines published, aimed at improving the quality of reporting in published studies and reviews. In systematic reviews this may be measured by their compliance with the PRISMA statement. This review aims to evaluate the quality of reporting in published meta-analyses of diagnostic tests, using the PRISMA statement and establish whether there has been a measurable improvement over time.</p> <p>Methods</p> <p>Eight databases were searched for reviews published prior to 31^stDecember 2008. Studies were selected if they evaluated a diagnostic test, measured performance, searched two or more databases, stated the search terms and inclusion criteria, and used a statistical method to summarise a test's performance. Data were extracted on the review characteristics and items of the PRISMA statement. To measure the change in the quality of reporting over time, PRISMA items for two periods of equal duration were compared.</p> <p>Results</p> <p>Compliance with the PRISMA statement was generally poor: none of the reviews completely adhered to all 27 checklist items. Of the 236 meta-analyses included following selection: only 2(1%) reported the study protocol; 59(25%) reported the searches used; 76(32%) reported the results of a risk of bias assessment; and 82(35%) reported the abstract as a structured summary. Only 11 studies were published before 2000. Thus, the impact of QUOROM on the quality of reporting was not evaluated. However, the periods 2001-2004 and 2005-2008 (covering 93% of studies) were compared using relative risks (RR). There was an increase in the proportion of reviews reporting on five PRISMA items: eligibility criteria (RR 1.13, 95% CI 1.00 - 1.27); risk of bias across studies (methods) (RR 1.81, 95% CI 1.34 - 2.44); study selection results (RR 1.48, 95% CI 1.05 - 2.09); results of individual studies (RR 1.37, 95% CI 1.09 - 1.72); risk of bias across studies (results) (RR 1.65, 95% CI 1.20 - 2.25).</p> <p>Conclusion</p> <p>Although there has been an improvement in the quality of meta-analyses in diagnostic research, there are still many deficiencies in the reporting which future reviewers need to address if readers are to trust the validity of the reported findings.</p

A tutorial on individualized treatment effect prediction from randomized trials with a binary endpoint.

Randomized trials typically estimate average relative treatment effects, but decisions on the benefit of a treatment are possibly better informed by more individualized predictions of the absolute treatment effect. In case of a binary outcome, these predictions of absolute individualized treatment effect require knowledge of the individual's risk without treatment and incorporation of a possibly differential treatment effect (ie, varying with patient characteristics). In this article, we lay out the causal structure of individualized treatment effect in terms of potential outcomes and describe the required assumptions that underlie a causal interpretation of its prediction. Subsequently, we describe regression models and model estimation techniques that can be used to move from average to more individualized treatment effect predictions. We focus mainly on logistic regression-based methods that are both well-known and naturally provide the required probabilistic estimates. We incorporate key components from both causal inference and prediction research to arrive at individualized treatment effect predictions. While the separate components are well known, their successful amalgamation is very much an ongoing field of research. We cut the problem down to its essentials in the setting of a randomized trial, discuss the importance of a clear definition of the estimand of interest, provide insight into the required assumptions, and give guidance with respect to modeling and estimation options. Simulated data illustrate the potential of different modeling options across scenarios that vary both average treatment effect and treatment effect heterogeneity. Two applied examples illustrate individualized treatment effect prediction in randomized trial data

Acute myocardial infarction incidence and hospital mortality: routinely collected national data versus linkage of national registers

Background and Objective To compare levels of and trends in incidence and hospital mortality of first acute myocardial infarction (AMI) based on routinely collected hospital morbidity data and on linked registers. Cases taken from routine hospital data are a mix of patients with recurrent and first events, and double counting occurs when cases are admitted for an event several times during 1 year. By linkage of registers, recurrent events and double counts can be excluded. Study Design and Setting In 1995 and 2000, 28,733 and 25,864 admissions for AMI were registered in the Dutch national hospital discharge register. Linkage with the population register yielded 21,565 patients with a first AMI in 1995 and 20,414 in 2000. Results In 1995 and 2000, the incidence based on the hospital register was higher than based on the linked registers in men (22% and 23% higher) and women (18% and 20% higher). In both years, hospital mortality based on the hospital register and on linked registers was similar. The decline in incidence between 1995 and 2000 was comparable whether based on standard hospital register data or linked data (18% and 20% in men, 15% and 17% in women). Similarly, the decline in hospital mortality was comparable using either approach (11% and 9% in both men and women). Conclusion Although the incidence based on routine hospital data overestimates the actual incidence of first AMI based on linked registers, hospital mortality and trends in incidence and hospital mortality are not changed by excluding recurrent events and double counts. Since trends in incidence and hospital mortality of AMI are often based on national routinely collected data, it is reassuring that our results indicate that findings from such studies are indeed valid and not biased because of recurrent events and double counts

Evaluation of Xpert® MTB/RIF and ustar easyNAT™ TB IAD for diagnosis of tuberculous lymphadenitis of children in Tanzania : a prospective descriptive study

Fine needle aspiration biopsy has become a standard approach for diagnosis of peripheral tuberculous lymphadenitis. The aim of this study was to compare the performance of Xpert MTB/RIF and Ustar EasyNAT TB IAD nucleic acid amplification assays, against acid-fast bacilli microscopy, cytology and mycobacterial culture for the diagnosis of TB lymphadenitis in children from a TB-endemic setting in Tanzania.; Children of 8 weeks to 16 years of age, suspected of having TB lymphadenitis, were recruited at a district hospital in Tanzania. Fine needle aspirates of lymph nodes were analysed using acid-fast bacilli microscopy, liquid TB culture, cytology, Xpert MTB/RIF and EasyNAT. Latent class analysis and comparison against a composite reference standard comprising "culture and/or cytology" was done, to assess the performance of Xpert MTB/RIF and EasyNAT for the diagnosis of TB lymphadenitis.; Seventy-nine children were recruited; 4 were excluded from analysis. Against a composite reference standard of culture and/or cytology, Xpert MTB/RIF and EasyNAT had a sensitivity and specificity of 58 % and 93 %; and 19 % and 100 % respectively. Relative to latent class definitions, cytology had a sensitivity of 100 % and specificity of 94.7 %.; Combining clinical assessment, cytology and Xpert MTB/RIF may allow for a rapid and accurate diagnosis of childhood TB lymphadenitis. Larger diagnostic evaluation studies are recommended to validate these findings and on Xpert MTB/RIF to assess its use as a solitary initial test for TB lymphadenitis in children