589 Exploring Outcomes of Necrotising Fasciitis in Diabetic vs Non-Diabetic Patients: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Abstract Aim Necrotising fasciitis (NF) is a life-threatening soft tissue infection with significant morbidity and mortality. Diabetes mellitus is a key risk factor influencing the progression, outcome, and management of NF. Despite its importance, literature exploring the disparities between diabetic and non-diabetic NF patients remains limited. Perform a systematic review and meta-analysis comparing outcomes of NF in diabetic versus non-diabetic patients. Method A systematic review and meta-analysis were conducted following PRISMA guidelines. A search of the CENTRAL and PubMed identified all studies reporting outcomes in both cohorts. Nine studies involving over 1,200 patients were included. Primary outcome measures were amputation rates, mortality, admission length, debridement frequency, and microbial growth. Secondary outcomes included LRINEC scores, BMI, and renal disease. Odds ratios (OR) and mean differences (MD) with 95% confidence intervals (CI) were calculated using OpenMeta[Analyst] software. Heterogeneity was assessed via Cochran’s Q test and I² statistics. The Newcastle-Ottawa Scale evaluated study quality and bias risk. Results Diabetic patients had significantly higher amputation rates (OR 3.790, 95% CI:3.053–4.705; p<0.001) and incidence of polymicrobial infections (OR 2.475, 95% CI:1.475–4.155; p<0.001). Diabetics displayed higher mortality after sensitivity analysis (p=0.011). No significant differences were observed in admission duration or debridement frequency. Diabetic patients had significantly higher LRINEC scores (MD 2.024, 95% CI:1.332–2.716; p<0.001). Conclusions Diabetic NF patients experience worse outcomes, including higher amputation rates, mortality, and more severe infections. This meta-analysis underscores the need for early intervention, tailored management, and standardisation of diagnosis to improve outcomes in diabetic NF populations. Further high-quality prospective studies are warranted.
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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 | 0.015 | 0.032 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.045 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".