Sex and gender differences in intensive care medicine
Bibliographic record
Abstract
Despite significant advancements in critical care medicine, limited attention has been given to sex and gender disparities in management and outcomes of patients admitted to the intensive care unit (ICU). While "sex" pertains to biological and physiological characteristics, such as reproductive organs, chromosomes and sex hormones, "gender" refers more to sociocultural roles and human behavior. Unfortunately, data on gender-related topics in the ICU are lacking. Consequently, data on sex and gender-related differences in admission to the ICU, clinical course, length of stay, mortality, and post-ICU burdens, are often inconsistent. Moreover, when examining specific diagnoses in the ICU, variations can be observed in epidemiology, pathophysiology, presentation, severity, and treatment response due to the distinct impact of sex hormones on the immune and cardiovascular systems. In this narrative review, we highlight the influence of sex and gender on the clinical course, management, and outcomes of the most encountered intensive care conditions, in addition to the potential co-existence of unconscious biases which may also impact critical illness. Diagnoses with a known sex predilection will be discussed within the context of underlying sex differences in physiology, anatomy, and pharmacology with the goal of identifying areas where clinical improvement is needed. To optimize patient care and outcomes, it is crucial to comprehend and address sex and gender differences in the ICU setting and personalize management accordingly to ensure equitable, patient-centered care. Future research should focus on elucidating the underlying mechanisms driving sex and gender disparities, as well as exploring targeted interventions to mitigate these disparities and improve outcomes for all critically ill patients.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".