Sex-based analysis of treatment responses in animal models of sepsis: a preclinical systematic review protocol
Bibliographic record
Abstract
BACKGROUND: The importance of investigating sex- and gender-dependent differences has been recently emphasized by major funding agencies. Notably, the influence of biological sex on clinical outcomes in sepsis is unclear, and observational studies suffer from the effect of confounding factors. The controlled experimental environment afforded by preclinical studies allows for clarification and mechanistic evaluation of sex-dependent differences. We propose a systematic review to assess the impact of biological sex on baseline responses to disease induction as well as treatment responses in animal models of sepsis. Given the lack of guidance surrounding sex-based analyses in preclinical systematic reviews, careful consideration of various factors is needed to understand how best to conduct analyses and communicate findings. METHODS: MEDLINE and Embase will be searched (2011-present) to identify preclinical studies of sepsis in which any intervention was administered and sex-stratified data reported. The primary outcome will be mortality. Secondary outcomes will include organ dysfunction, bacterial load, and IL-6 levels. Study selection will be conducted independently and in duplicate by two reviewers. Data extraction will be conducted by one reviewer and audited by a second independent reviewer. Data extracted from included studies will be pooled, and meta-analysis will be conducted using random effects modeling. Primary analyses will be stratified by animal age and will assess the impact of sex at the following time points: pre-intervention, in response to treatment, and post-intervention. Risk of bias will be assessed using the SYRCLE's risk-of-bias tool. Illustrative examples of potential methods to analyze sex-based differences are provided in this protocol. DISCUSSION: Our systematic review will summarize the current state of knowledge on sex-dependent differences in sepsis. This will identify current knowledge gaps that future studies can address. Finally, this review will provide a framework for sex-based analysis in future preclinical systematic reviews. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42022367726.
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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 | 0.118 | 0.126 |
| Meta-epidemiology (narrow) | 0.006 | 0.004 |
| Meta-epidemiology (broad) | 0.019 | 0.021 |
| Bibliometrics | 0.015 | 0.012 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.009 | 0.005 |
| Insufficient payload (model declined to judge) | 0.047 | 0.007 |
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".