Body composition and risk of heart failure: protocol for a systematic review and meta-analysis
Bibliographic record
Abstract
Introduction Although there is strong evidence of an association between general adiposity and incidence of heart failure, previous systematic reviews and meta-analyses have not reliably assessed the association of heart failure risk with other aspects of body composition (such as body fat distribution or lean mass), or between body composition and risk of heart failure subtypes. We aim to conduct a systematic review and meta-analysis of prospective studies to address these uncertainties, and inform efforts to prevent and treat heart failure. Methods and analysis The Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Protocols statement was used as a template for this protocol. A systematic search of Medline, Embase and Global Health from database inception to present will be conducted to identify prospective studies reporting on the associations between major measures of body composition (body mass index, waist circumference, waist–hip ratio, total body fat, visceral adiposity tissue and lean mass) and risk of heart failure. Article screening and selection will be performed by two reviewers independently, and disagreements will be adjudicated by consensus or by a third reviewer. Data from eligible articles will be extracted, and article quality will be assessed using the Newcastle-Ottawa Scale. Relative risks (and 95% CIs) will be pooled in a fixed effect meta-analysis, if there is no prohibitive heterogeneity of studies as assessed using the Cochrane Q statistic and I2 statistic. Subgroup analyses will be by age, sex, ethnicity and heart failure subtypes. Publication bias in the meta-analysis will be assessed using Egger’s test and funnel plots. Ethics and dissemination This work is secondary analyses on published data and ethical approval is not required. We plan to publish results in an open-access peer-reviewed journal, present it at international and national conferences, and share the findings on social media. PROSPERO registration number CRD42020224584.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.089 | 0.150 |
| Meta-epidemiology (narrow) | 0.009 | 0.007 |
| Meta-epidemiology (broad) | 0.025 | 0.037 |
| Bibliometrics | 0.012 | 0.013 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.007 | 0.006 |
| Research integrity | 0.009 | 0.011 |
| Insufficient payload (model declined to judge) | 0.076 | 0.008 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".