Abstract 15580: The Impact of Sex and Gender-related Factors on Length-of-stay Following NSTEMI: A Multicountry Analysis
Bibliographic record
Abstract
Introduction: Gender refers to psycho-socio-cultural characteristics typically ascribed to men, women and gender-diverse individuals and has been shown to be associated with adverse clinical outcomes in AMI independent of sex. Substantial heterogeneity in hospital length of stay exists among patients admitted with NSTEMI. Whether sex and gender-based differences contribute to length-of-stay (LOS) among patients with NSTEMI remains unknown. Methods: To examine the relationship between sex, gender-related factors and LOS in adults hospitalized for NSTEMI, data from the GENESIS-PRAXY (n=1,210, Canada, U.S. and Switzerland), EVA (n=430, Italy) and VIRGO (n=3,572, U.S., Spain and Australia) studies of adults hospitalized for AMI were combined and analyzed. A best-fit linear regression model was selected through incremental analysis by stepwise addition of gender-related variables thought to be different in either impact or distribution between men and women. Results: Among the overall cohort (n=5,212), 2,218 participants with a diagnosis of NSTEMI were included in the final cohort (66% women, mean age 48.5 years, 67.8% U.S.). Half of the patients had a LOS of longer than 4 days (n=1,124) and were more likely to be white and have a clustering of cardiac risk factors in comparison to those with shorter LOS. No association between sex and LOS was observed in the bivariate analysis (p=0.87). In the multivariable model adjusted for sex, age, country of hospitalization, level of education, marital status, employment status, income, and social support, age (0.062 days/year, p=0.0002), being employed (-0.63 days in workers, p=0.01) and the treatment country relative to Canada (Italy=4.1 days; Spain=1.7 days; and the U.S.=-1.0 days, all p-value<0.001) were significant predictors of LOS. Conclusions: Employed individuals are more likely to experience a shorter LOS following NSTEMI. Variation in LOS exists across different countries and is likely due to institutional policy, resource allocation, and differences in cultural and psychosocial influences.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".