Predictors of Short-Term Trauma Laparotomy Outcomes in an Integrated Military-Civilian Health System: A 23-Year Retrospective Cohort Study.
Sami GendlerShaul GelikasTomer TalmyRoy NadlerAvishai Michael TsurIrina RadomislenskyMoran BodasElon GlassbergOfer AlmogAvi BenovJacob ChenPublished in: Journal of clinical medicine (2024)
Background : Trauma laparotomy (TL) remains a cornerstone of trauma care. We aimed to investigate prehospital measures associated with in-hospital mortality among casualties subsequently undergoing TLs in civilian hospitals. Methods : This retrospective cohort study cross-referenced the prehospital and hospitalization data of casualties treated by Israel Defense Forces-Medical Corps teams who later underwent TLs in civilian hospitals between 1997 and 2020. Results : Overall, we identified 217 casualties treated by IDF-MC teams that subsequently underwent a TL, with a mortality rate of 15.2% (33/217). The main mechanism of injury was documented as penetrating for 121/217 (55.8%). The median heart rate and blood pressure were within the normal limit for the entire cohort, with a low blood pressure predicting mortality (65 vs. 127, p < 0.001). In a multivariate analysis, prehospital endotracheal intubation (ETI), emergency department Glasgow coma scores of 3-8, and the need for a thoracotomy or bowel-related procedures were significantly associated with mortality (OR 6.8, p < 0.001, OR = 48.5, p < 0.001, and OR = 4.61, p = 0.002, respectively). Conclusions : Prehospital interventions introduced throughout the study period did not lead to an improvement in survival. Survival was negatively influenced by prehospital ETI, reinforcing previous observations of the potential deleterious effects of definitive airways on hemorrhaging trauma casualties. While a low blood pressure was a predictor of mortality, the median systolic blood pressure for even the sickest patients (ISS > 16) was within normal limits, highlighting the challenges in triage and risk stratification for trauma casualties.
Keyphrases
- blood pressure
- trauma patients
- heart rate
- cardiac arrest
- emergency department
- hypertensive patients
- healthcare
- cardiovascular events
- heart rate variability
- emergency medical
- risk factors
- newly diagnosed
- heart failure
- cardiovascular disease
- palliative care
- cystic fibrosis
- risk assessment
- blood glucose
- type diabetes
- data analysis
- machine learning
- radiation therapy
- big data
- left ventricular
- coronary artery disease
- electronic health record
- artificial intelligence
- rectal cancer
- human health
- atrial fibrillation