Statins and risk of thromboembolism:A meta-regression to disentangle the efficacy-to-effectiveness gap using observational and trial evidence

Background and aims Meta-analyses of randomised controlled trials (RCTs) and observational studies indicate a lower risk of venous thromboembolism (VTE) associated with statin treatment. We aimed to compare the effect of statin therapy in these two settings and to identify and quantify potential factors to explain statin efficacy and effectiveness. Methods and results We electronically searched on December 11th, 2018, articles reporting on first VTE events in RCTs (statin vs placebo) and in observational studies (participants exposed vs non-exposed to statin). We performed Knapp-Hartung random-effect meta-analyses to calculate pooled relative risks (RRs) of VTE events associated with statin treatment, separately for RCTs and observational studies; and estimated the ratio of the relative risk (RRR) comparing RCTs and observational studies using meta-regressions, progressively adjusted for study-level characteristics. Twenty-one RCTs (115,107 participants; 959 events) and 8 observational studies (2,898,096 participants; 19,671 events) were included. Pooled RRs for RCTs and observational studies were 0.82 (95% confidence interval (CI): 0.67–1.00; I2 19.2%) and 0.60 (95% CI: 0.42–0.86; I2 86.3%), respectively. In meta-regressions, the unadjusted RRR indicated a nonsignificant 23% smaller benefit in RCTs (RRR 0.77; 95% CI: 0.52–1.13); accounting for age, sex, geographical region, and duration of follow-up, there was a sensible change of the RRR which resulted 0.30 (95% CI: 0.13–0.68). Conclusion Differences in the characteristics between patients included in RCTs and those in observational studies may account for the differential effect of statins in preventing VTE in the two settings

Ethnic minority representation in UK COVID-19 trials: systematic review and meta-analysis

Background The COVID-19 pandemic has highlighted health disparities affecting ethnic minority communities. There is growing concern about the lack of diversity in clinical trials. This study aimed to assess the representation of ethnic groups in UK-based COVID-19 randomised controlled trials (RCTs). Methods A systematic review and meta-analysis were undertaken. A search strategy was developed for MEDLINE (Ovid) and Google Scholar (1st January 2020–4th May 2022). Prospective COVID-19 RCTs for vaccines or therapeutics that reported UK data separately with a minimum of 50 participants were eligible. Search results were independently screened, and data extracted into proforma. Percentage of ethnic groups at all trial stages was mapped against Office of National Statistics (ONS) statistics. Post hoc DerSimonian-Laird random-effects meta-analysis of percentages and a meta-regression assessing recruitment over time were conducted. Due to the nature of the review question, risk of bias was not assessed. Data analysis was conducted in Stata v17.0. A protocol was registered (PROSPERO CRD42021244185). Results In total, 5319 articles were identified; 30 studies were included, with 118,912 participants. Enrolment to trials was the only stage consistently reported (17 trials). Meta-analysis showed significant heterogeneity across studies, in relation to census-expected proportions at study enrolment. All ethnic groups, apart from Other (1.7% [95% CI 1.1–2.8%] vs ONS 1%) were represented to a lesser extent than ONS statistics, most marked in Black (1% [0.6–1.5%] vs 3.3%) and Asian (5.8% [4.4–7.6%] vs 7.5%) groups, but also apparent in White (84.8% [81.6–87.5%] vs 86%) and Mixed 1.6% [1.2–2.1%] vs 2.2%) groups. Meta-regression showed recruitment of Black participants increased over time (p = 0.009). Conclusions Asian, Black and Mixed ethnic groups are under-represented or incorrectly classified in UK COVID-19 RCTs. Reporting by ethnicity lacks consistency and transparency. Under-representation in clinical trials occurs at multiple levels and requires complex solutions, which should be considered throughout trial conduct. These findings may not apply outside of the UK setting

Employment outcomes of people with Long Covid symptoms:community-based cohort study

Background: Evidence on the long-term employment consequences of SARS-CoV-2 infection is lacking. We used data from a large, community-based sample in the UK to estimate associations between Long Covid and employment outcomes.Methods: This was an observational, longitudinal study using a pre-post design. We included survey participants from 3 February 2021 to 30 September 2022 when they were aged 16-64 years and not in education. Using conditional logit modelling, we explored the time-varying relationship between Long Covid status ≥12 weeks after a first test-confirmed SARS-CoV-2 infection (reference: pre-infection) and labour market inactivity (neither working nor looking for work) or workplace absence lasting ≥4 weeks.Results: Of 206,299 participants (mean age 45 years, 54% female, 92% white), 15% were ever labour market inactive and 10% were ever long-term absent during follow-up. Compared with pre-infection, inactivity was higher in participants reporting Long Covid 30 to <40 weeks (adjusted odds ratio [aOR]: 1.45; 95% CI: 1.17 to 1.81) or 40 to <52 weeks (aOR: 1.34; 95% CI: 1.05 to 1.72) post-infection. Combining with official statistics on Long Covid prevalence, and assuming a correct statistical model, our estimates translate to 27,000 (95% CI: 6,000 to 47,000) working-age adults in the UK being inactive because of Long Covid in July 2022.Conclusions: Long Covid is likely to have contributed to reduced participation in the UK labour market, though it is unlikely to be the sole driver. Further research is required to quantify the contribution of other factors, such as indirect health effects of the pandemic

Kidney Function and Long-Term Risk of End-Stage Kidney Disease and Mortality in a Multiethnic Population

Introduction: Contemporary differences between South Asian and White ethnicities in the incidence of end-stage kidney disease (ESKD) and mortality are poorly described. Methods: Data for all South Asian patients who had an estimated glomerular filtration rate (eGFR) measure after January 1, 2006, and 1 million randomly selected participants of other ethnicities were extracted from the Clinical Practice Research Datalink (CPRD). All participants were followed-up with from index date until ESKD, all-cause mortality, or end of study. All-cause mortality rate and ESKD incidence rate by age were described among Whites and South Asians, and adjusted hazard ratios (HRs) of these 2 outcomes by baseline eGFR estimated using Cox proportional hazard model. Results: A total of 40,888 South Asians and 236,634 Whites were followed for a median of 5.3 and 9.4 years for ESKD incidence and mortality outcomes, respectively. All-cause mortality rates were higher among Whites than South Asians; South Asian women aged between 70 and 85 years had a slightly higher ESKD incidence rate compared to their White counterparts. Compared to Whites with a baseline eGFR of 90 ml/min per 1.73 m2, adjusted HRs for all-cause mortality were significantly lower among South Asians than Whites; however, adjusted HRs for ESKD incidence by baseline eGFR were similar in both ethnicities. Calculating South Asian eGFRs using an ethnicity-specific equation had no impact on the results. Conclusions: South Asians experience lower mortality than Whites but not substantially higher rates of ESKD. Further research is warranted to better understand the reasons for these ethnic differences and possible impacts on chronic kidney disease (CKD) service delivery and patient outcomes

Changes in the trajectory of Long Covid symptoms following COVID-19 vaccination: community-based cohort study

OBJECTIVE: To estimate associations between COVID-19 vaccination and Long Covid symptoms in adults who were infected with SARS-CoV-2 prior to vaccination. DESIGN: Observational cohort study using individual-level interrupted time series analysis. SETTING: Random sample from the community population of the UK. PARTICIPANTS: 28,356 COVID-19 Infection Survey participants (mean age 46 years, 56% female, 89% white) aged 18 to 69 years who received at least their first vaccination after test-confirmed infection. MAIN OUTCOME MEASURES: Presence of Long Covid symptoms at least 12 weeks after infection over the follow-up period 3 February to 5 September 2021. RESULTS: Median follow-up was 141 days from first vaccination (among all participants) and 67 days from second vaccination (84% of participants). First vaccination was associated with an initial 12.8% decrease (95% confidence interval: -18.6% to -6.6%, p<0.001) in the odds of Long Covid, with the data being compatible with both increases and decreases in the trajectory (+0.3% per week, 95% CI: -0.6% to +1.2% per week, p=0.51) after this. Second vaccination was associated with an 8.8% decrease (95% CI: -14.1% to -3.1%, p=0.003) in the odds of Long Covid, with the odds subsequently decreasing by 0.8% (-1.2% to -0.4%, p<0.001) per week. There was no statistical evidence of heterogeneity in associations between vaccination and Long Covid by socio-demographic characteristics, health status, whether hospitalised with acute COVID-19, vaccine type (adenovirus vector or mRNA), or duration from infection to vaccination. CONCLUSIONS: : The likelihood of Long Covid symptoms reduced after COVID-19 vaccination, and there was evidence of a sustained improvement after the second dose, at least over the median follow-up time of 67 days. Vaccination may contribute to a reduction in the population health burden of Long Covid, though longer follow-up time is needed

Glycosylated haemoglobin and prognosis in 10,536 people with cancer and pre-existing diabetes: a meta-analysis with dose-response analysis

AIMS: To assess whether glycaemic control is associated with prognosis in people with cancer and pre-existing diabetes. METHODS: In this pre-registered systematic review (PROSPERO: CRD42020223956), PubMed and Web of Science were searched on 25th Nov 2021 for studies investigating associations between glycosylated haemoglobin (HbA1c) and prognosis in people with diabetes and cancer. Summary relative risks (RRs) and 95% Confidence Intervals (CIs) for associations between poorly controlled HbA1c or per 1-unit HbA1c increment and cancer outcomes were estimated using a random-effects meta-analysis. We also investigated the impact of potential small-study effects using the trim-and-fill method and potential sources of heterogeneity using subgroup analyses. RESULTS: Fifteen eligible observational studies, reporting data on 10,536 patients with cancer and pre-existing diabetes, were included. Random-effects meta-analyses indicated that HbA1c ≥ 7% (53 mmol/mol) was associated with increased risks of: all-cause mortality (14 studies; RR: 1.14 [95% CI: 1.03-1.27]; p-value: 0.012), cancer-specific mortality (5; 1.68 [1.13-2.49]; p-value: 0.011) and cancer recurrence (8; 1.68 [1.18-2.38; p-value: 0.004]), with moderate to high heterogeneity. Dose-response meta-analyses indicated that 1-unit increment of HbA1c (%) was associated with increased risks of all-cause mortality (13 studies; 1.04 [1.01-1.08]; p-value: 0.016) and cancer-specific mortality (4; 1.11 [1.04-1.20]; p-value: 0.003). All RRs were attenuated in trim-and-fill analyses. CONCLUSIONS: Our findings suggested that glycaemic control might be a modifiable risk factor for mortality and cancer recurrence in people with cancer and pre-existing diabetes. High-quality studies with a larger sample size are warranted to confirm these findings due to heterogeneity and potential small-study effects. In the interim, it makes clinical sense to recommend continued optimal glycaemic control

Prediction of diabetic foot ulceration: The value of using microclimate sensor arrays

Background: Accurately predicting the risk of diabetic foot ulceration (DFU) could dramatically reduce the enormous burden of chronic wound management and amputation. Yet, current prognostic models are unable to precisely predict DFU events. Typically, efforts have focused on individual factors like temperature, pressure or shear rather than the overall foot microclimate. Method: A systematic review was conducted by searching PubMed reports with no restrictions on start date covering literature published until 20 February 2019 using relevant keywords, including temperature, pressure, shear and relative humidity. We review the use of these variables as predictors of DFU, highlighting gaps in our current understanding and suggesting which specific features should be combined to develop a real-time microclimate prognostic model. Results: Current prognostic models rely either solely on contralateral temperature, pressure or shear measurement; these parameters, however, rarely reach 50% specificity in relation to DFU. There is also considerable variation in methodological investigation, anatomical sensor configuration and resting time prior to temperature measurements (5-20 minutes). Few studies have considered relative humidity and mean skin resistance. Conclusions: Very limited evidence supports the use of single clinical parameters in predicting the risk of DFU. We suggest the microclimate as a whole should be considered to predict DFU more effectively and suggest nine specific features which appear to be implicated for further investigation. Technology supports real-time inshoe data collection and wireless transmission, providing a potentially rich source of data to better predict risk of DFU