The Effects of Biological Sex on Sepsis Treatments in Animal Models: A Systematic Review and a Narrative Elaboration on Sex- and Gender-Dependent Differences in Sepsis
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Bibliographic record
Abstract
Preclinical studies provide an opportunity to evaluate the relationship between sex and sepsis, and investigate underlying mechanisms in a controlled experimental environment. The objective of our systematic review was to assess the impact of biological sex on treatment response to fluid and antibiotic therapy in animal models of sepsis. Furthermore, we provide a narrative elaboration of sex-dependent differences in preclinical models of sepsis. DATA SOURCES: MEDLINE and Embase were searched from inception to March 16, 2020. STUDY SELECTION: All studies reporting sex-stratified data comparing antibiotics and/or fluid resuscitation with a placebo or no treatment arm in an in vivo model of sepsis were included. DATA EXTRACTION: Outcomes of interest were mortality (primary) and organ dysfunction (secondary). Risk of bias was assessed. Study selection and data extraction were conducted independently and in duplicate. DATA SYNTHESIS: The systematic search returned 2,649 unique studies, and two met inclusion criteria. Both studies used cecal ligation and puncture models with imipenem/cilastatin antibiotics. No eligible studies investigated fluids. In one study, antibiotic therapy significantly reduced mortality in male, but not female, animals. The other study reported no sex differences in organ dysfunction. Both studies were deemed to be at a high overall risk of bias. CONCLUSIONS: There is a remarkable and concerning paucity of data investigating sex-dependent differences in fluid and antibiotic therapy for the treatment of sepsis in animal models. This may reflect poor awareness of the importance of investigating sex-dependent differences. Our discussion therefore expands on general concepts of sex and gender in biomedical research and sex-dependent differences in key areas of sepsis research such as the cardiovascular system, immunometabolism, the microbiome, and epigenetics. Finally, we discuss current clinical knowledge, the potential for reverse translation, and directions for future studies. REGISTRATION: PROSPERO CRD42020192738.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 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 it