Beč kao formativni prostor Branka Gavelle

Model used for data simulation. The Hussey and Hughes [8] mixed model and a simplified version corresponding to the parameters chosen for our data simulations. (DOCX 13 kb

Analysis of the Modified Rankin Scale in Randomised Controlled Trials of Acute Ischaemic Stroke: A Systematic Review

Background: Historically, most acute stroke clinical trials were neutral statistically, with trials typically dichotomising ordinal scales, such as the modified Rankin Scale. Studies published before 2007 have shown that preserving the ordinal nature of these scales increased statistical power. A systematic review of trials published since 2007 was conducted to re-evaluate statistical methods used and to assess whether practice has changed. Methods: A search of electronic databases identified RCTs published between Jan 2007 and July 2014 in acute ischaemic stroke using an ordinal dependency scale as the primary outcome. Findings: Forty-two RCTs were identified. The majority used a dichotomous analysis (25, 59.5%), eight (21.4%) retained the ordinal scale and nine (19.0%) used another type of analysis. Conclusions: Trials published since 2007 still favoured dichotomous analyses over ordinal. Stroke trials, where appropriate, should consider retaining the ordinal nature of dependency scales

Unequal cluster sizes in stepped-wedge cluster randomised trials: a systematic review

OBJECTIVES: To investigate the extent to which cluster sizes vary in stepped-wedge cluster randomised trials (SW-CRT) and whether any variability is accounted for during the sample size calculation and analysis of these trials. SETTING: Any, not limited to healthcare settings. PARTICIPANTS: Any taking part in an SW-CRT published up to March 2016. PRIMARY AND SECONDARY OUTCOME MEASURES: The primary outcome is the variability in cluster sizes, measured by the coefficient of variation (CV) in cluster size. Secondary outcomes include the difference between the cluster sizes assumed during the sample size calculation and those observed during the trial, any reported variability in cluster sizes and whether the methods of sample size calculation and methods of analysis accounted for any variability in cluster sizes. RESULTS: Of the 101 included SW-CRTs, 48% mentioned that the included clusters were known to vary in size, yet only 13% of these accounted for this during the calculation of the sample size. However, 69% of the trials did use a method of analysis appropriate for when clusters vary in size. Full trial reports were available for 53 trials. The CV was calculated for 23 of these: the median CV was 0.41 (IQR: 0.22-0.52). Actual cluster sizes could be compared with those assumed during the sample size calculation for 14 (26%) of the trial reports; the cluster sizes were between 29% and 480% of that which had been assumed. CONCLUSIONS: Cluster sizes often vary in SW-CRTs. Reporting of SW-CRTs also remains suboptimal. The effect of unequal cluster sizes on the statistical power of SW-CRTs needs further exploration and methods appropriate to studies with unequal cluster sizes need to be employed

Prevalence of Co-Morbidities by Ethnicity in a UK Primary Care CKD Cohort

Background Cardiovascular (CV) and endstage renal disease events in CKD are more common in non-white ethnicities compared to white ethnicities. The prevalence of co-morbidities in CKD in Black and South Asian ethnicities outside of North America is poorly studies but may account for these higher renal and CV event rates. Methods We analysed cross-sectional data from the PSP-CKD study (ClinicalTrials.gov NCT01688141). Individuals were analysed if they had a baseline EPI eGFR <60 ml/min/1.73m2 and an ethnicity code. The groups’ baseline characteristics between ethnicities were compared using t-tests and Chi2 . Results 18,058 (78.1%) individuals out of 23,129 had ethnicity recorded. Of these, 17,264 (95.6%) were White, 263 (1.5%) Black and 243 (1.4%) were South Asian. Individuals of Black and South Asian ethnicities were more likely to be male and younger. Mean EPI eGFRs were similar across ethnicities but South Asians had higher mean ACR in both those with and without diabetes mellitus (DM). In Black individuals a diagnosis of hypertension (HTN) was less common but both systolic and diastolic blood pressures had higher mean values. DM was more prevalent in South Asians and HbA1c was higher too. Both Black and South Asian groups had lower rates of CV disease. Conclusion In South Asians with CKD, DM was present in more than 40% and glycaemic control was worse. A HTN diagnosis was less common in Black individuals but blood pressure was more poorly controlled. Both groups had lower rates of previous CV events. Targeted management of these co-morbidities in South Asian and Black populations with CKD may be warranted

Mortality and Co-Morbidities in South Asian Individuals with CKD Compared to White Ethnicities

Background The epidemiology of CKD in South Asian (SA) populations in high-income countries is poorly studied. The Leicester City and County Chronic Kidney Disease (LCC-CKD) cohort has been developed to study this population in comparison to other ethnic groups. To our knowledge no study has compared all-cause mortality in SA subpopulations with CKD compared to other ethnicities. Methods Data was collected for LCC-CKD from primary care electronic records. The cohort has 5 years of completed follow-up from 2011 to 2016. Comparison was made between individuals of SA and Whites ethnicities. The groups’ baseline characteristics were compared using t-tests and Chi2 . Unadjusted and adjusted Cox proportional hazards models were used for comparison of allcause mortality. Results 3,887 of 6,133 (63.4%) individuals in the LCC-CKD cohort have an ethnicity code of whom 268 are of SA ethnicity (6.9%). Gender proportions were similar, but mean age and EPI eGFR were lower and ACR higher for SA compared to White ethnicities. diabetes mellitus was more common in SA but clinical cardiovascular disease was less common (see table). Unadjusted all-cause survival analysis suggested all-causes mortality was 39% lower (HR 0.61, 95% CI 0.46-0.80, p<0.0001) in SA. However, in an adjusted model using the variables listed in the table, SA had similar risk to the White population (HR 0.97, 95% CI 0.71-1.33, p=0.85). Conclusion Compared to the White population, SA with CKD are younger with more advanced CKD and more likely to have diabetes. Adjusted all-cause mortality was similar between ethnicity groups. These factors may explain why SA individuals are more likely to progress to endstage renal disease

A systematic review of simulation studies which compare existing statistical methods to account for non-compliance in randomised controlled trials

Introduction Non-compliance is a common challenge for researchers and may reduce the power of an intention-to-treat analysis. Whilst a per protocol approach attempts to deal with this issue, it can result in biased estimates. Several methods to resolve this issue have been identified in previous reviews, but there is limited evidence supporting their use. This review aimed to identify simulation studies which compare such methods, assess the extent to which certain methods have been investigated and determine their performance under various scenarios. Methods A systematic search of several electronic databases including MEDLINE and Scopus was carried out from conception to 30th November 2022. Included papers were published in a peer-reviewed journal, readily available in the English language and focused on comparing relevant methods in a superiority randomised controlled trial under a simulation study. Articles were screened using these criteria and a predetermined extraction form used to identify relevant information. A quality assessment appraised the risk of bias in individual studies. Extracted data was synthesised using tables, figures and a narrative summary. Both screening and data extraction were performed by two independent reviewers with disagreements resolved by consensus. Results Of 2325 papers identified, 267 full texts were screened and 17 studies finally included. Twelve methods were identified across papers. Instrumental variable methods were commonly considered, but many authors found them to be biased in some settings. Non-compliance was generally assumed to be all-or-nothing and only occurring in the intervention group, although some methods considered it as time-varying. Simulation studies commonly varied the level and type of non-compliance and factors such as effect size and strength of confounding. The quality of papers was generally good, although some lacked detail and justification. Therefore, their conclusions were deemed to be less reliable. Conclusions It is common for papers to consider instrumental variable methods but more studies are needed that consider G-methods and compare a wide range of methods in realistic scenarios. It is difficult to make conclusions about the best method to deal with non-compliance due to a limited body of evidence and the difficulty in combining results from independent simulation studies.</p

Leg Ischaemia Management Collaboration (LIMb) Statistical Analysis Plan

The Statistical Analysis Plan (SAP) to define the methods in determinig the primary outcome of the data collected from the Leg Ischaemia Managament Collaboration (LIMb) study.</p

Health impacts of seated arm ergometry training in patients with a diabetic foot ulcer: protocol for a randomised controlled trial.

INTRODUCTION:Once diagnosed with a diabetic foot ulcer (DFU), patients are advised to offload, keeping pressure off the foot in order to facilitate ulcer healing. An increase in offloading is often accompanied by reductions in physical activity which can worsen the overall health of patients.While unable to perform traditional forms of upright activity, one mode of exercise that would allow patients to be physically active while adhering to offloading instruction is seated arm ergometry. The merits of tailored aerobic exercise in DFU remain unexplored. METHODS AND ANALYSIS:This is a prospective open-label randomised controlled trial. Participants will be randomised to one of two groups, an exercise intervention group or control. The intervention group are required to undertake arm ergometry training at a moderate intensity (65%-75% HRpeak), three times per week for 12 weeks as individually prescribed by an exercise physiologist, while the control group will continue to receive standard care alone. Assessment of outcome measures will occur at baseline and after the intervention period, these will include: a seated VO2 peak test, a blood sample, a short physical performance battery, a dual-energy X-ray absorptiometry scan and completing a range of health-based questionnaires. The above will be used to determine: cardiorespiratory fitness, metabolic health, physical function, body composition and quality of life, respectively. Ulcer area will also be measured as an approximate marker of ulcer healing. ETHICS AND DISSEMINATION:This trial has been approved by 'Yorkshire & The Humber-Leeds West Research Ethics Committee' (19/YH/0269). Trial results will be published in peer-reviewed journals and through conference presentations. TRIAL REGISTRATION NUMBER:ISRCTN16000053. Registered in accordance with WHO Trial Registration Data Set (version 1.3.1)

Long-term mortality following acute myocardial infarction among those with and without diabetes: A systematic review and meta-analysis of studies in the post reperfusion era.

Aims: Considerable medical advances have seen an improved survival following an acute myocardial infarction (AMI), whether these benefits extend to those with diabetes remains less clear. This systematic review and meta-analysis aim to provide robust estimates of the association between diabetes and long-term mortality (≥one year) following AMI. Material and Methods: Medline, Embase and Web of Science databases were searched (January 1985 - July 2016) for terms related to long-term mortality, diabetes and AMI. Two authors independently abstracted the data. Hazard ratios (HR) comparing mortality in people with and without diabetes were pooled across studies using Bayesian random effects metaanalysis. Results: Ten randomised controlled trials and 56 cohort studies, including 714,780 patients, reported an estimated total of 202,411 deaths over the median follow-up of 2.0 years (range 1 to 20). The risk of death over time was significantly higher among those with diabetes compared to those without (unadjusted Hazard Ratio (HR) 1.82; 95% Credible Interval (CrI) 1.73 to 1.91). Mortality remained higher in the analysis restricted to 23/64 cohorts which had adjusted for confounders (adjusted HR 1.48 (1.43 to 1.53)). The excess long-term mortality in diabetes was evident irrespective of the phenotype and modern treatment of AMI, and persisted in early survivors (unadjusted HR 1.82 (1.70 to 1.95)). Conclusions: Despite medical advances, individuals with diabetes have a 50% increased long-term mortality compared to those without. Further research to understand the determinants of this excess risk are important for public health, given the predicted rise in global diabetes prevalence

Double-counting of populations in evidence synthesis in public health: a call for awareness and future methodological development

Background There is a growing interest in the inclusion of real-world and observational studies in evidence synthesis such as meta-analysis and network meta-analysis in public health. While this approach offers great epidemiological opportunities, use of such studies often introduce a significant issue of double-counting of participants and databases in a single analysis. Therefore, this study aims to introduce and illustrate the nuances of double-counting of individuals in evidence synthesis including real-world and observational data with a focus on public health. Methods The issues associated with double-counting of individuals in evidence synthesis are highlighted with a number of case studies. Further, double-counting of information in varying scenarios is discussed with potential solutions highlighted. Results Use of studies of real-world data and/or established cohort studies, for example studies evaluating the effectiveness of therapies using health record data, often introduce a significant issue of double-counting of individuals and databases. This refers to the inclusion of the same individuals multiple times in a single analysis. Double-counting can occur in a number of manners, such as, when multiple studies utilise the same database, when there is overlapping timeframes of analysis or common treatment arms across studies. Some common practices to address this include synthesis of data only from peer-reviewed studies, utilising the study that provides the greatest information (e.g. largest, newest, greater outcomes reported) or analysing outcomes at different time points. Conclusions While common practices currently used can mitigate some of the impact of double-counting of participants in evidence synthesis including real-world and observational studies, there is a clear need for methodological and guideline development to address this increasingly significant issue.</p