How Does HbA1c Predict Mortality and Readmission in Patients with Heart Failure? A Protocol for Systematic Review and Meta-analysis
Bibliographic record
Abstract
Abstract BackgroundAccumulating evidence suggests that HbA1c levels, a common clinical indicator of chronic glucose metabolism over the preceding 2-3 months, are independent risk factor for cardiovascular disease, including heart failure. The aim of this protocol is to conduct a systematic review and meta-analysis to assess the possible predictive value of HbA1c on mortality and readmission in patients with heart failure.MethodsA systematic and comprehensive search will be performed using PubMed, Embase, Central and other databases before August 2021 to identify relevant trials. All-cause mortality is the pre-specified primary endpoint. Cardiovascular death and heart failure readmission are secondary interested endpoints. We will only include prospective and retrospective cohort trials and place no restrictions on the language, race, region and publication period. The Newcastle-Ottawa Scale will be used to assess the quality of each trial included. If there are sufficient trials, we will conduct meta-analysis with pooled relative risks and corresponding 95% confidence interval to evaluate the possible predictive value of HbA1c on mortality and readmission. Otherwise, we will undertake a narrative synthesis. Heterogeneity and publication bias will be assessed. If heterogeneity is significant among included trails, a sensitivity analysis or subgroup analysis will be used to explore the source of heterogeneity, such as diverse types of heart failure or patients with diabetes and non-diabetes. Also, we will conduct meta-regression to examine the time-effect and treatment-effect modifiers on all-cause mortality compared between different quantile of HbA1c levels. Finally, a restricted cubic spline model may be used to explore the dose-response relationship between HbA1c and adverse outcomes.DiscussionThis planned analysis is anticipated to identify the predictive value of HbA1c on mortality and readmission in patients with heart failure. Improved understanding of different HbA1c levels and their specific effect on diverse types of heart failure or patients with diabetes and non-diabetes is expected to be figured out. Also, a dose-response relationship or optimal range of HbA1c will be determined to instruct clinicians and patients.PROSPERO registration detailsCRD42021276067
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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 | 0.079 | 0.139 |
| Meta-epidemiology (narrow) | 0.006 | 0.004 |
| Meta-epidemiology (broad) | 0.023 | 0.041 |
| Bibliometrics | 0.012 | 0.011 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.048 | 0.005 |
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".