Civilian Gunshot Wounds to the Head: Prognostic Factors Affecting Mortality: Meta-Analysis of 1774 Patients
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
Civilian gunshot wounds to the head (cGSWH) are devastating, but there is no consensus regarding prognosis and management. Therefore, we conducted a meta-analysis to identify prognostic factors associated with mortality. PubMed, EMBASE, Scopus, Web of Science, and Cochrane Library were queried for retrospective cohort studies of isolated cGSWH reporting mortality prognostic factors. Meta-Analysis Of Observational Studies in Epidemiology (MOOSE) guidelines were followed. Study quality was assessed using the Newcastle-Ottawa scale. Primary outcome was mortality. Pooled estimates of odds ratios (ORs) and 95% confidence intervals (CIs) were derived using random-effects models. Seventeen (17) observational studies (1774 patients) were identified and included. Factors associated with mortality were: age >40 years (OR, 3.44; 95% CI [1.71-6.91]), suicide attempt (5.78; [3.07-10.87]), Glasgow Coma Scale (GCS) 3-8 compared with 9-15 (38.02; [21.98-65.77]), GCS 3-5 versus 6-8 (15.38; [6.72-35.23], bilateral fixed and dilated pupils versus normal (67.12; [16.67-270.22]), and versus unilateral fixed and dilated pupil (25.35; [5.82-110.41]), dural penetration (29.07; [4.30-196.53]) and bihemispheric (4.23; [2.32-7.68]), and multi-lobar injuries (6.53; [1.99-21.42]). Selection for operative management, according to expert neurosurgical opinion, was protective (0.06; [0.01-0.22]). This is the first meta-analysis on cGSWH mortality prognostic factors. Increasing age, suicide attempt, lower GCS, bilateral mydriasis, dural penetration, and bihemispheric and multi-lobar injury are associated with increased mortality. This study can serve as a guide to clinicians and will provide directions for future research to develop evidence-based management algorithms.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.008 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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