Cardiogenic shock—sex-specific risk factors and outcome differences
Bibliographic record
Abstract
Cardiogenic shock (CS) remains a high-mortality condition despite technological and therapeutic advances. One key to potentially improving CS prognosis is understanding patient heterogeneity and which patients may benefit most from different treatment options, a key element of which is sex differences. While cardiovascular diseases (CVDs) have historically been considered a male-dominant condition, the field is increasingly aware that females are also a substantial portion of the patient population. While estrogen has been implicated in protective roles against CVD and tissue hypoxia, its role in CS remains unclear. Clinically, female CS patients tend to be older, have more severe comorbidities and are more likely to have non-acute myocardial infarction etiologies with preserved ejection fractions. Female CS patients are more likely to receive pharmacotherapy while less likely to receive mechanical circulatory support. There is increased short-term mortality in females, although long-term mortality is similar between the sexes. More sex-specific and age-stratified research needs to be done to fully understand the relevant pathophysiological differences in CS, to better recognize and manage CS patients and reduce its mortality.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".