Supplementary Material for: Neck circumference in polycystic ovary syndrome: a systematic review and bootstrapped meta-analysis with GRADE approach
Bibliographic record
Abstract
Introduction: Our aim was to perform a systematic review and meta-analysis for the association of neck circumference (NC) in polycystic ovary syndrome (PCOS) patients as compared to non-PCOS controls. Methods: Primarily the PubMed/MEDLINE database, and others such as SCOPUS, Google Scholar, Cochrane Library, up to November 15, 2023 for observational studies comparing NC in PCOS versus non-PCOS women. The mean and SD values of NC and other covariates in PCOS and control groups were extracted by two independent reviewers, and the quality and risk of bias assessment was done using Newcastle–Ottawa Scale of the studies. The meta-analysis employed combined standardized mean differences (SMD) with 95% confidence intervals (CI) to compare NC between PCOS patients and controls. The heterogeneity and validity were addressed by sub-group, meta-regression, and sensitivity analyses. We conducted a Bootstrapped meta-analysis using 1000 and 10000 simulations to test the accuracy of the obtained results. The certainty of evidence was assessed by GRADE approach. Results: Our meta-analysis included 9 observational studies. The PCOS patients showed a significantly higher NC values than the non-PCOS controls (SMD 0.66, 95% CI 0.41-0.91, p<0.0001). In the bootstrap meta-analysis, the accuracy of the observed findings was proved (SMD=0.66, CI=0.42 to 0.91) for the NC outcome. No publication bias was detected in the funnel plot analysis using Begg’s and Egger’s tests. The 95% prediction interval of 0.036 to 1.28, suggest that the true outcomes of the studies are generally in the same direction as the estimated average outcome. The sensitivity analysis provided the robustness of the outcome, and no single study was overly influential on the pooled estimate. Conclusion: This meta-analysis provides accurate evidence for significantly higher NC in PCOS as compared to non-PCOS controls. There is no sufficient evidence on the diagnostic accuracy measures for NC in PCOS. Hence, further research on its diagnostic utility in PCOS is needed.
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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 | 0.009 | 0.114 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.010 | 0.014 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.627 | 0.036 |
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".