Abstract P070: Risk of All-cause Mortality in Women versus Men With Type 2 Diabetes: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
Introduction: Previous studies have shown sex differences in the all cause mortality rate associated with type 2 diabetes. Hypothesis: We did a meta-analysis to provide reliable and comprehensive estimates of type 2 diabetes on risk of all-cause mortality in women versus men. Methods: We systematically searched PubMed, Embase, and Web of science for studies published from their starting dates to October 10, 2017. Studies were selected only if they reported sex-specific estimates of the standardized mortality ratio (SMR) or hazard ratios associated with type 2 diabetes for all-cause mortality. We used random effects meta-analyses with inverse-variance weighting to obtain sex-specific SMRs and their pooled ratio (women to men) for all-cause mortality. Study quality was assessed using the Newcastle–Ottawa scale. Results: Data from 30 studies including 2,307,694 individuals and 252,491 deaths occurred were included. The pooled women-to-men ratio of the SMR for all-cause mortality was 1·14 (95% CI 1.09-1.19, p<0.001; I 2 =81.6%). Compared with healthy counterparts, the pooled SMR for all-cause mortality in patients with T2D was 2.30(95%CI 1.97-2.68) in women, and 1.94(95%CI 1.73-2.18) in men, respectively. Sensitivity analysis with omission of one study at a time did not change the results of this meta-analysis. Conclusions: Women with type 2 diabetes have a roughly 14% greater excess risk of all-cause mortality compared with men counterparts. This meta-analysis was registered at the International Prospective Register of Systematic Reviews (Prospero) ( http://www.crd.york.ac.uk/PROSPERO ; registration number: CRD42017074187). Figure 1 .Pooled women-to-men ratios of SMRs for all-cause mortality, comparing people with type 2 diabetes versus healthy counterparts.
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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 | 0.015 | 0.040 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.033 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".