Civilian Gunshot Wounds to the Head: Prognostic Factors Affecting Mortality:Meta-Analysis of 1774 Patients.

Maragkos, Georgios A, Efstathios Papavassiliou, Martina Stippler, and Aristotelis S Filippidis. 2018. “Civilian Gunshot Wounds to the Head: Prognostic Factors Affecting Mortality:Meta-Analysis of 1774 Patients.”. Journal of Neurotrauma 35 (22): 2605-14.

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.
Last updated on 07/07/2024