Abstract 254: The Canadian GENESIS Gender Index may be the Key to Understanding Differences in Health Status Outcomes in Acute Coronary Syndrome.
Bibliographic record
Abstract
Background: While it has been identified that gender (socially manufactured roles, behaviours, expressions and identities) plays a central role in men’s and women’s health, the distinction between gender and sex (biological attributes) has largely been ignored in health sciences research. One aspect of the GENESIS-PRAXY study was the development of a ‘gender index’ which measures gender and offers a pragmatic means to explore the relationship between sex, gender and health outcomes. The purpose of this study was to look at the unique contributions of sex, age and the GENESIS Gender Index (GGI) to baseline Seattle Angina Questionnaire (SAQ) dimensional scores in a cohort of patients undergoing cardiac catheterization for CAD. Methods: Questions that comprised the GGI were included in the follow-up questionnaire sent to patients in the APPROACH registry. For the purposes of these analyses, SAQ scores were dichotomized whereby respondents were given a score of 1 if they scored 100 (best possible score) on the SAQ scales, and 0 if less than 100. Logistic regression models were created including each of the SAQ dimensional scores as the dependent variables and sex, age and the GGI as the independent variables entered in unique blocks. The area under the curve (AUC) and resulting c statistics were calculated for each block. Results: GGI scores and baseline SAQ scores were calculated for 532 returned questionnaires sent between July 1st and August 31 st 2015 within one week of index catheterization. Men were more likely to report perfect SAQ dimensional scores compared to women and these relationships were significant in the Physical Limitation and Treatment Satisfaction scales (odds ratios 2.75 and 1.56 respectively). The inclusion of age into the models did not change the relationship between sex and the SAQ scales. However the inclusion of the GGI attenuated the relationship between sex and the SAQ scales whereby sex was no longer statistically independently predictive of SAQ scale scores. Furthermore c statistics indicated that including the GGI increased the discrimination of the models in all SAQ dimensional scales. Conclusions: This analyses adds to the literature that specifies that gender is a distinct constructs that can be measured by the GGI. More importantly, the increased predictive accuracy of the models that included the GGI suggests that the psychosocial variables included in the GGI provide more information in understanding the differences in outcomes between men and women undergoing catheterization for CAD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".