A preclinical systematic review and meta-analysis assessing the effect of biological sex in lipopolysaccharide-induced acute lung injury
Bibliographic record
Abstract
It is unclear what effect biological sex has on outcomes of acute lung injury (ALI). Clinical studies are confounded by their observational design. We addressed this knowledge gap with a preclinical systematic review of ALI animal studies. We searched MEDLINE and Embase for studies of intratracheal/intranasal/aerosolized lipopolysaccharide administration (the most common ALI model) that reported sex-stratified data. Screening and data extraction were conducted in duplicate. Our primary outcome was histological tissue injury and secondary outcomes included alveolar-capillary barrier alterations and inflammatory markers. We used a random-effects inverse variance meta-analysis, expressing data as standardized mean difference (SMD) with 95% confidence intervals (CIs). Risk of bias was assessed using the Systematic Review Centre for Laboratory Animal Experimentation (SYRCLE) tool. We identified six studies involving 132 animals across 11 independent experiments. A total of 41 outcomes were extracted, with the direction of effect suggesting greater severity in males than females in 26/41 outcomes (63%). One study reported on lung histology and found that male mice exhibited greater injury than females (SMD: 1.61, 95% CI: 0.53-2.69). Meta-analysis demonstrated significantly elevated albumin levels (SMD: 2.17, 95% CI: 0.63-3.70) and total cell counts (SMD: 0.80, 95% CI: 0.27-1.33) in bronchoalveolar lavage fluid from male mice compared with female mice. Most studies had an "unclear risk of bias." Our findings suggest sex-related differences in ALI severity. However, these conclusions are drawn from a small number of animals and studies. Further research is required to address the fundamental issue of biological sex differences in LPS-induced ALI.
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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 | 0.019 | 0.054 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.031 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".