Causal inference for planning randomised critical care trials:Protocol for a scoping review

BACKGROUND: Randomised clinical trials in critical care are prone to inconclusiveness owing, in part, to undue optimism about effect sizes and suboptimal accounting for heterogeneous treatment effects. Planned predictive enrichment based on secondary critical care data (often very rich with respect to both data types and temporal granularity) and causal inference methods may help overcome these challenges, but no overview exists about their use to this end. METHODS: We will conduct a scoping review to assess the extent and nature of the use of causal inference from secondary data for planned predictive enrichment of randomised clinical trials in critical care. We will systematically search 10 general and specialty journals for reports published on or after 1 January 2018, of randomised clinical trials enrolling adult critically ill patients. We will collect trial metadata (e.g., recruitment period and phase) and, when available, information pertaining to the focus of the review (predictive enrichment based on causal inference estimates from secondary data): causal inference methods, estimation techniques and software used; types of patient populations; data provenance, types and models; and the availability of the data (public or not). The results will be reported in a descriptive manner. DISCUSSION: The outlined scoping review aims to assess the use of causal inference methods and secondary data for planned predictive enrichment in randomised critical care trials. This will help guide methodological improvements to increase the utility, and facilitate the use, of causal inference estimates when planning such trials in the future

Vaccines to prevent COVID-19: A living systematic review with Trial Sequential Analysis and network meta-analysis of randomized clinical trials

Background COVID-19 is rapidly spreading causing extensive burdens across the world. Effective vaccines to prevent COVID-19 are urgently needed. Methods and findings Our objective was to assess the effectiveness and safety of COVID-19 vaccines through analyses of all currently available randomized clinical trials. We searched the databases CENTRAL, MEDLINE, Embase, and other sources from inception to June 17, 2021 for randomized clinical trials assessing vaccines for COVID-19. At least two independent reviewers screened studies, extracted data, and assessed risks of bias. We conducted meta-analyses, network meta-analyses, and Trial Sequential Analyses (TSA). Our primary outcomes included all-cause mortality, vaccine efficacy, and serious adverse events. We assessed the certainty of evidence with GRADE. We identified 46 trials; 35 trials randomizing 219 864 participants could be included in our analyses. Our meta-analyses showed that mRNA vaccines (efficacy, 95% [95% confidence interval (CI), 92% to 97%]; 71 514 participants; 3 trials; moderate certainty); inactivated vaccines (efficacy, 61% [95% CI, 52% to 68%]; 48 029 participants; 3 trials; moderate certainty); protein subunit vaccines (efficacy, 77% [95% CI, -5% to 95%]; 17 737 participants; 2 trials; low certainty); and viral vector vaccines (efficacy 68% [95% CI, 61% to 74%]; 71 401 participants; 5 trials; low certainty) prevented COVID- 19. Viral vector vaccines decreased mortality (risk ratio, 0.25 [95% CI 0.09 to 0.67]; 67 563 participants; 3 trials, low certainty), but comparable data on inactivated, mRNA, and protein subunit vaccines were imprecise. None of the vaccines showed evidence of a difference on serious adverse events, but observational evidence suggested rare serious adverse events. All the vaccines increased the risk of non-serious adverse events. Conclusions The evidence suggests that all the included vaccines are effective in preventing COVID-19. The mRNA vaccines seem most effective in preventing COVID-19, but viral vector vaccines seem most effective in reducing mortality. Further trials and longer follow-up are necessary to provide better insight into the safety profile of these vaccines.Fil: Korang, Steven Kwasi. Copenhagen University Hospital; DinamarcaFil: von Rohden, Elena. Copenhagen University Hospital; DinamarcaFil: Veroniki, Areti Angeliki. Imperial College London; Reino Unido. St. Michael’s Hospital; CanadáFil: Ong, Giok. John Radcliffe Hospital; Reino UnidoFil: Ngalamika, Owen. University of Zambia; ZambiaFil: Siddiqui, Faiza. Copenhagen University Hospital; DinamarcaFil: Juul, Sophie. Copenhagen University Hospital; DinamarcaFil: Nielsen, Emil Eik. Copenhagen University Hospital; DinamarcaFil: Feinberg, Joshua Buron. Copenhagen University Hospital; DinamarcaFil: Petersen, Johanne Juul. Copenhagen University Hospital; DinamarcaFil: Legart, Christian. Universidad de Copenhagen; Dinamarca. Copenhagen University Hospital; DinamarcaFil: Kokogho, Afoke. Henry M. Jackson Foundation Medical Research International; NigeriaFil: Maagaard, Mathias. Copenhagen University Hospital; Dinamarca. Zealand University Hospital; DinamarcaFil: Klingenberg, Sarah. Copenhagen University Hospital; DinamarcaFil: Thabane, Lehana. Mcmaster University; CanadáFil: Bardach, Ariel Esteban. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones en Epidemiología y Salud Pública. Instituto de Efectividad Clínica y Sanitaria. Centro de Investigaciones en Epidemiología y Salud Pública; Argentina. Instituto de Efectividad Clínica y Sanitaria; ArgentinaFil: Ciapponi, Agustín. Instituto de Efectividad Clínica y Sanitaria; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones en Epidemiología y Salud Pública. Instituto de Efectividad Clínica y Sanitaria. Centro de Investigaciones en Epidemiología y Salud Pública; ArgentinaFil: Thomsen, Allan Randrup. Universidad de Copenhagen; DinamarcaFil: Jakobsen, Janus C.. University of Southern Denmark; Dinamarca. Copenhagen University Hospital; DinamarcaFil: Gluud, Christian. Copenhagen University Hospital; Dinamarca. University of Southern Denmark; Dinamarc

A new tool to assess Clinical Diversity In Meta‐analyses (CDIM) of interventions

OBJECTIVE: To develop and validate Clinical Diversity In Meta-analyses (CDIM), a new tool for assessing clinical diversity between trials in meta-analyses of interventions.STUDY DESIGN AND SETTING: The development of CDIM was based on consensus work informed by empirical literature and expertise. We drafted the CDIM tool, refined it, and validated CDIM for interrater scale reliability and agreement in three groups.RESULTS: CDIM measures clinical diversity on a scale that includes four domains with 11 items overall: setting (time of conduct/country development status/units type); population (age, sex, patient inclusion criteria/baseline disease severity, comorbidities); interventions (intervention intensity/strength/duration of intervention, timing, control intervention, cointerventions); and outcome (definition of outcome, timing of outcome assessment). The CDIM is completed in two steps: first two authors independently assess clinical diversity in the four domains. Second, after agreeing upon scores of individual items a consensus score is achieved. Interrater scale reliability and agreement ranged from moderate to almost perfect depending on the type of raters.CONCLUSION: CDIM is the first tool developed for assessing clinical diversity in meta-analyses of interventions. We found CDIM to be a reliable tool for assessing clinical diversity among trials in meta-analysis.</p

Platform trials

Platform trials focus on the perpetual testing of many interventions in a disease or a setting. These trials have lasting organizational, administrative, data, analytic, and operational frameworks making them highly efficient. The use of adaptation often increases the probabilities of allocating participants to better interventions and obtaining conclusive results. The COVID-19 pandemic showed the potential of platform trials as a fast and valid way to improved treatments. This review gives an overview of key concepts and elements using the Intensive Care Platform Trial (INCEPT) as an example.</p

Statistical analysis plan for the ADJUNCT1 and ADJUNCT2 trials

Detailed statistical analysis plan for the ADJUNCT1 and ADJUNCT2 randomised clinical trials.</p

Primary outcomes and anticipated effect sizes in randomized controlled trials assessing adjuncts to ultrasound-guided peripheral nerve blocks: A Systematic Scoping Review

This is a protocol for a scoping review . The aim of the outlined review is to map the choices of primary outcomes and anticipated effect sizes in randomized controlled trials assessing adjuncts to ultrasound-guided peripheral nerve blocks in adult patients undergoing surgery