Predicting early mortality in adult trauma patients admitted to three public university hospitals in urban India: a prospective multicentre cohort study.

Martin Gerdin,Vineet Kumar,Li Felländer-Tsai,Max Petzold,Monty Khajanchi,Sanjeev Bhoi,Makhan Lal Saha,Satish Dharap,Nobhojit Roy,Johan Von Schreeb,Chiara Lazzeri

doi:10.1371/journal.pone.0105606

Abstract

BackgroundIn India alone, more than one million people die yearly due to trauma. Identification of patients at risk of early mortality is crucial to guide clinical management and explain prognosis. Prediction models can support clinical judgement, but existing models have methodological limitations. The aim of this study was to derive a vital sign based prediction model for early mortality among adult trauma patients admitted to three public university hospitals in urban India.MethodsWe conducted a prospective cohort study of adult trauma patients admitted to three urban university hospitals in India between October 2013 and January 2014. The outcome measure was mortality within 24 hours. We used logistic regression with restricted cubic splines to derive our model. We assessed model performance in terms of discrimination, calibration, and optimism.ResultsA total of 1629 patients were included. Median age was 35, 80% were males. Mortality between admission and 24 hours was 6%. Our final model included systolic blood pressure, heart rate, and Glasgow coma scale. Our model displayed good discrimination, with an area under the receiver operating characteristics curve (AUROCC) of 0.85. Predicted mortality corresponded well with observed mortality, indicating good calibration.ConclusionThis study showed that routinely recorded systolic blood pressure, heart rate, and Glasgow coma scale predicted early hospital mortality in trauma patients admitted to three public university hospitals in urban India. Our model needs to be externally validated before it can be applied in the clinical setting.

Highlights

In India alone, more than one million people die yearly due to trauma
We have recently shown that early trauma mortality is a problem in the Indian hospital setting [25], indicating the need for urgent intervention
In variables with missing values the fraction of missing data ranged from 6% for time from injury to arrival to the study centres to 20% for systolic blood pressure

Summary

Introduction

In India alone, more than one million people die yearly due to trauma. Identification of patients at risk of early mortality is crucial to guide clinical management and explain prognosis. The aim of this study was to derive a vital sign based prediction model for early mortality among adult trauma patients admitted to three public university hospitals in urban India. Of the more than five million annual trauma deaths, over 90% occur in low and middle-income countries [3]. A lower middle-income country, accounts for almost 20% of global trauma mortality [6]. A significant proportion of India’s trauma mortality occurs in urban areas [7], where pre-hospital care is limited [8,9]. About 50% of India’s trauma mortality has been reported to occur in hospitals [10], potentially due to poorly developed emergency care and limited critical care capabilities [11,12]. Many hospitals lack formalised triage systems to rapidly identify patients at risk of mortality [13]

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