scholarly journals Clinical decision-making for spinal manipulation for persistent spinal pain following lumbar surgery: a protocol for a systematic review and meta-analysis of individual participant data

BMJ Open ◽  
2021 ◽  
Vol 11 (12) ◽  
pp. e054070
Author(s):  
Robert James Trager ◽  
Clinton J Daniels ◽  
Kevin W Meyer ◽  
Amber C Stout ◽  
Jeffery A Dusek
Keyword(s):  
Clinical Decision Making ◽  
Case Reports ◽  
Grey Literature ◽  
Spinal Manipulative Therapy ◽  
Pain Syndrome ◽  
Spinal Pain ◽  
Lumbar Spine Surgery ◽  
Individual Participant Data ◽  
University Hospitals ◽  
Individual Participant

IntroductionThere are limited available research and guidance regarding the use of spinal manipulative therapy (SMT) in patients with low back-related symptoms following lumbar spine surgery, a condition called persistent spinal pain syndrome type 2 (PSPS-2). This publication outlines a review protocol to identify and synthesise individual participant data (IPD) to examine associations between patient, clinical and surgical variables and SMT application in adults with PSPS-2.Methods and analysisPubMed, OVID, Web of Science, Scopus, PEDro, Index to Chiropractic Literature and KoreaMed will be searched from inception to 1 January 2022 without language restrictions. Case reports, series, observational studies and cases from grey literature of adults receiving SMT for PSPS-2 will be included. Two investigators will independently screen citations, abstracts and full-text articles. A risk-of-bias assessment will be performed in duplicate to rate cases according to exposure and outcome ascertainment and data completeness. Data extraction will be performed in duplicate and missing IPD will be requested from corresponding authors. Multiple binary logistic regression will be used to identify independent predictors of the use of lumbar–SMT, lumbar–manual-thrust SMT and SMT within 1-year postsurgery. Patient, clinical and surgical variables will be summarised using descriptive statistics, while SMT-related outcomes (lumbar–SMT, lumbar–manual-thrust SMT and 1-year surgery-to-SMT interval) will be described using adjusted ORs with 95% CIs.Ethics and disseminationThis study was deemed not human subjects research by the University Hospitals’ institutional review board. The results of this review will be disseminated at conferences and/or published in a peer-reviewed journal.PROSPERO registration numberCRD42021250039.

scholarly journals A heart failure phenotype stratified model for predicting 1-year mortality in patients admitted with acute heart failure: results from an individual participant data meta-analysis of four prospective European cohorts

BMC Medicine ◽  
2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Yuntao Chen ◽  
Adriaan A. Voors ◽  
Tiny Jaarsma ◽  
Chim C. Lang ◽  
Iziah E. Sama ◽  
...  
Keyword(s):  
Heart Failure ◽  
Clinical Decision Making ◽  
Cox Model ◽  
Meta Analysis ◽  
Prognostic Index ◽  
Individual Participant Data ◽  
Mortality Risks ◽  
Baseline Mortality ◽  
Individual Participant ◽  
Stratified Model

Abstract Background Prognostic models developed in general cohorts with a mixture of heart failure (HF) phenotypes, though more widely applicable, are also likely to yield larger prediction errors in settings where the HF phenotypes have substantially different baseline mortality rates or different predictor-outcome associations. This study sought to use individual participant data meta-analysis to develop an HF phenotype stratified model for predicting 1-year mortality in patients admitted with acute HF. Methods Four prospective European cohorts were used to develop an HF phenotype stratified model. Cox model with two rounds of backward elimination was used to derive the prognostic index. Weibull model was used to obtain the baseline hazard functions. The internal-external cross-validation (IECV) approach was used to evaluate the generalizability of the developed model in terms of discrimination and calibration. Results 3577 acute HF patients were included, of which 2368 were classified as having HF with reduced ejection fraction (EF) (HFrEF; EF < 40%), 588 as having HF with midrange EF (HFmrEF; EF 40–49%), and 621 as having HF with preserved EF (HFpEF; EF ≥ 50%). A total of 11 readily available variables built up the prognostic index. For four of these predictor variables, namely systolic blood pressure, serum creatinine, myocardial infarction, and diabetes, the effect differed across the three HF phenotypes. With a weighted IECV-adjusted AUC of 0.79 (0.74–0.83) for HFrEF, 0.74 (0.70–0.79) for HFmrEF, and 0.74 (0.71–0.77) for HFpEF, the model showed excellent discrimination. Moreover, there was a good agreement between the average observed and predicted 1-year mortality risks, especially after recalibration of the baseline mortality risks. Conclusions Our HF phenotype stratified model showed excellent generalizability across four European cohorts and may provide a useful tool in HF phenotype-specific clinical decision-making.

scholarly journals Socioeconomic inequalities in reach, compliance and effectiveness of lifestyle interventions among workers: protocol for an individual participant data meta-analysis and equity-specific reanalysis

BMJ Open ◽  
2019 ◽  
Vol 9 (2) ◽  
pp. e025463 ◽  
Author(s):  
Karen M Oude Hengel ◽  
Pieter Coenen ◽  
Suzan J W Robroek ◽  
Cecile R L Boot ◽  
Allard J van der Beek ◽  
...  
Keyword(s):  
Human Subjects ◽  
Meta Analysis ◽  
Grey Literature ◽  
Study Data ◽  
Population Characteristics ◽  
Socioeconomic Differences ◽  
Individual Participant Data ◽  
Occupational Setting ◽  
Individual Participant ◽  
Socioeconomic Equity

IntroductionObesity and unhealthy behaviour are more prevalent among workers with a low compared with a high socioeconomic position (SEP), and thus contribute to socioeconomic health inequalities. The occupational setting is considered an important setting to address unhealthy behaviours due to the possibility to efficiently reach a large group of adults through worksite health promotion. This paper describes the rationale and design for an individual participant data (IPD) meta-analysis and a socioeconomic equity-specific reanalysis aiming to: (1) investigate socioeconomic differences in the effectiveness of interventions aimed at promoting healthy behaviour and preventing obesity, (2) examine socioeconomic differences in reach and compliance and (3) to investigate underlying factors affecting possible socioeconomic differences.Methods and analysisA systematic search was conducted in electronic databases including Embase, Medline Ovid, Web of Science, Cochrane Central and Google Scholar as well as in grey literature and trial registries. Two researchers have independently selected a total of 34 relevant studies (from 88 articles). Responsible researchers of these eligible studies were asked to provide their study data and an assessment of the methodological criteria was done. The data of the intervention studies will be pooled for the IPD meta-analysis, whereas the socioeconomic equity-specific reanalysis will focus on each study separately, stratified for SEP. Both methods will be conducted to investigate socioeconomic differences in effectiveness, reach and compliance (research aims 1 and 2). For research aim 3, different factors, such as population characteristics, organisational work environment and intervention characteristics, will be investigated as possible moderators in the associations between SEP and effectiveness, reach and compliance.Ethics and disseminationThe Medical Ethical Committee of Erasmus MC declared that the Medical Research Involving Human Subjects Act does not apply to the meta-analyses. The findings will be disseminated through peer-reviewed publications and (inter)national conference presentations.Trial registration numberCRD42018099878.

scholarly journals Which patients benefit specifically from short-term psychodynamic psychotherapy (STPP) for depression? Study protocol of a systematic review and meta-analysis of individual participant data

BMJ Open ◽  
2018 ◽  
Vol 8 (2) ◽  
pp. e018900 ◽  
Author(s):  
Ellen Driessen ◽  
Allan A Abbass ◽  
Jacques P Barber ◽  
Mary Beth Connolly Gibbons ◽  
Jack J M Dekker ◽  
...  
Keyword(s):  
Systematic Review ◽  
Psychodynamic Psychotherapy ◽  
Meta Analysis ◽  
Grey Literature ◽  
Prospective Trial ◽  
Individual Participant Data ◽  
Short Term ◽  
Link Type ◽  
Individual Participant ◽  
Meta Analyses

IntroductionShort-term psychodynamic psychotherapy (STPP) is an empirically supported treatment that is often used to treat depression. However, it is largely unclear if certain subgroups of depressed patients can benefit specifically from this treatment method. We describe the protocol for a systematic review and meta-analysis of individual participant data (IPD) aimed at identifying predictors and moderators of STPP for depression efficacy.Method and analysisWe will conduct a systematic literature search in multiple bibliographic databases (PubMed, PsycINFO, Embase.com, Web of Science and Cochrane’s Central Register of Controlled Trials), ‘grey literature’ databases (GLIN and UMI ProQuest) and a prospective trial register (http://www.controlled-trials.com). We will include studies reporting (a) outcomes on standardised measures of (b) depressed (c) adult patients (d) receiving STPP. We will next invite the authors of these studies to share the participant-level data of their trials and combine these data to conduct IPD meta-analyses. The primary outcome for this study is post-treatment efficacy as assessed by a continuous depression measure. Potential predictors and moderators include all sociodemographic variables, clinical variables and psychological patient characteristics that are measured before the start of treatment and are assessed consistently across studies. One-stage IPD meta-analyses will be conducted using mixed-effects models.Ethics and disseminationInstitutional review board approval is not required for this study. We intend to submit reports of the outcomes of this study for publication to international peer-reviewed journals in the fields of psychiatry or clinical psychology. We also intend to present the outcomes at international scientific conferences aimed at psychotherapy researchers and clinicians. The findings of this study can have important clinical implications, as they can inform expectations of STPP efficacy for individual patients, and help to make an informed choice concerning the best treatment option for a given patient.PROSPERO registration numberCRD42017056029.

scholarly journals External validation of prognostic models predicting pre-eclampsia: individual participant data meta-analysis

BMC Medicine ◽  
2020 ◽  
Vol 18 (1) ◽  
Author(s):  
Kym I. E. Snell ◽  
◽  
John Allotey ◽  
Melanie Smuk ◽  
Richard Hooper ◽  
...  
Keyword(s):  
Clinical Decision Making ◽  
Prediction Models ◽  
Meta Analysis ◽  
External Validation ◽  
Predictive Performance ◽  
Prognostic Models ◽  
Individual Participant Data ◽  
Net Benefit ◽  
Mortality And Morbidity ◽  
Individual Participant

Abstract Background Pre-eclampsia is a leading cause of maternal and perinatal mortality and morbidity. Early identification of women at risk during pregnancy is required to plan management. Although there are many published prediction models for pre-eclampsia, few have been validated in external data. Our objective was to externally validate published prediction models for pre-eclampsia using individual participant data (IPD) from UK studies, to evaluate whether any of the models can accurately predict the condition when used within the UK healthcare setting. Methods IPD from 11 UK cohort studies (217,415 pregnant women) within the International Prediction of Pregnancy Complications (IPPIC) pre-eclampsia network contributed to external validation of published prediction models, identified by systematic review. Cohorts that measured all predictor variables in at least one of the identified models and reported pre-eclampsia as an outcome were included for validation. We reported the model predictive performance as discrimination (C-statistic), calibration (calibration plots, calibration slope, calibration-in-the-large), and net benefit. Performance measures were estimated separately in each available study and then, where possible, combined across studies in a random-effects meta-analysis. Results Of 131 published models, 67 provided the full model equation and 24 could be validated in 11 UK cohorts. Most of the models showed modest discrimination with summary C-statistics between 0.6 and 0.7. The calibration of the predicted compared to observed risk was generally poor for most models with observed calibration slopes less than 1, indicating that predictions were generally too extreme, although confidence intervals were wide. There was large between-study heterogeneity in each model’s calibration-in-the-large, suggesting poor calibration of the predicted overall risk across populations. In a subset of models, the net benefit of using the models to inform clinical decisions appeared small and limited to probability thresholds between 5 and 7%. Conclusions The evaluated models had modest predictive performance, with key limitations such as poor calibration (likely due to overfitting in the original development datasets), substantial heterogeneity, and small net benefit across settings. The evidence to support the use of these prediction models for pre-eclampsia in clinical decision-making is limited. Any models that we could not validate should be examined in terms of their predictive performance, net benefit, and heterogeneity across multiple UK settings before consideration for use in practice. Trial registration PROSPERO ID: CRD42015029349.

How do academics assess the results of multiple experiments?

2018 ◽  
Author(s):  
Olmo Van den Akker ◽  
Linda Dominguez Alvarez ◽  
Marjan Bakker ◽  
Jelte M. Wicherts ◽  
Marcel A. L. M. van Assen
Keyword(s):  
Bayesian Inference ◽  
Secondary Analysis ◽  
Individual Participant Data ◽  
Additional Experiment ◽  
Underlying Theory ◽  
Individual Participant ◽  
Vote Counting

We studied how academics assess the results of a set of four experiments that all test a given theory. We found that participants’ belief in the theory increases with the number of significant results, and that direct replications were considered to be more important than conceptual replications. We found no difference between authors and reviewers in their propensity to submit or recommend to publish sets of results, but we did find that authors are generally more likely to desire an additional experiment. In a preregistered secondary analysis of individual participant data, we examined the heuristics academics use to assess the results of four experiments. Only 6 out of 312 (1.9%) participants we analyzed used the normative method of Bayesian inference, whereas the majority of participants used vote counting approaches that tend to undervalue the evidence for the underlying theory if two or more results are statistically significant.

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