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. 2022 Mar 11:9:100066.
doi: 10.1016/j.sipas.2022.100066. eCollection 2022 Jun.

Weather and prehospital predictors of trauma patient mortality in a rural American state

Obieze C Nwanna-Nzewunwa  1 , Carolyne Falank  1 , Sean A Francois  1 , Julianne Ontengco  1 , Bruce Chung  1 , Damien W Carter  1
Affiliations

Weather and prehospital predictors of trauma patient mortality in a rural American state

Obieze C Nwanna-Nzewunwa et al. Surg Pract Sci. .

Abstract

Introduction: In rural settings, factors like weather and location can significantly impact total prehospital time and survival after injury. We sought to determine what prehospital conditions affect mortality and morbidity in severely injured patients.

Materials and methods: We retrospectively evaluated adult trauma patients that were admitted to our level 1 trauma center with Glasgow Coma Score (GCS≤ 9), hypotension (SBP≤ 90 mmHg), or both. Weather and prehospital conditions on patient outcomes were evaluated. Weather data was extracted from the National Oceanographic and Atmospheric Administration public database. Prediction models were done using bivariate and multivariate logistic regression analysis.

Results: A total of 442 subjects were captured, Median time on the scene was 15 min [IQR =10, 20.5], with median time to definitive care 129 min [IQR= 61, 247]. Hypotension in the field was the greatest predictor of ED mortality (OR=11, P = 0.004), and field hypoxia (OR=3, P = 0.007) was a predictor of in-hospital mortality. Patients with field GCS ≤ 9 had higher odds of ICU admission (OR=2, P = 0.029). Among transfers, increasing prehospital time correlated with ED mortality while injury during warmer weather showed lower odds (OR =0.94, P = 0.019) of mortality. No weather condition predicted mortality for patients that presented directly from the field.

Conclusion: Among severely injured patients being injured during cold weather was associated with higher in-hospital mortality among trauma transfer patients. Prehospital hypotension, hypoxia, and GCS≤9 are also independent predictors of mortality. Future analysis will explore factors impacting transport and field time in order to improve outcomes.

Keywords: Injury; Mortality; Prehospital; Trauma; Weather.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Fig. 1
Fig. 1
Distribution of injury mechanisms among all trauma patients encountered (n = 442).
Fig. 2
Fig. 2
Heat map showing the geographic distribution of injured patients at MMC (New England view).
Fig. 3
Fig. 3
Heat map showing the geographic distribution of injured patients at MMC (Maine view).
See this image and copyright information in PMC

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