Sex and gender differences in intensive care medicine
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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 it