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- Gerdin, M., et al.
(författare)
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Predicting Early Mortality in Adult Trauma Patients Admitted to Three Public University Hospitals in Urban India: A Prospective Multicentre Cohort Study
- 2014
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Ingår i: Plos One. - : Public Library of Science (PLoS). - 1932-6203. ; 9:9
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Tidskriftsartikel (refereegranskat)abstract
- Background: 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. 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. Methods: We 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. Results: A 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. Conclusion: This 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.
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- Gerdin, M., et al.
(författare)
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Early Hospital Mortality among Adult Trauma Patients Significantly Declined between 1998-2011: Three Single-Centre Cohorts from Mumbai, India
- 2014
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Ingår i: Plos One. - : Public Library of Science (PLoS). - 1932-6203. ; 9:3
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Tidskriftsartikel (refereegranskat)abstract
- Background: Traumatic injury causes more than five million deaths each year of which about 90% occur in low-and middle-income countries (LMIC). Hospital trauma mortality has been significantly reduced in high-income countries, but to what extent similar results have been achieved in LMIC has not been studied in detail. Here, we assessed if early hospital mortality in patients with trauma has changed over time in an urban lower middle-income setting. Methods: We conducted a retrospective study of patients admitted due to trauma in 1998, 2002, and 2011 to a large public hospital in Mumbai, India. Our outcome measure was early hospital mortality, defined as death between admission and 24-hours. We used multivariate logistic regression to assess the association between time and early hospital mortality, adjusting for patient case-mix. Injury severity was quantified using International Classification of Diseases-derived Injury Severity Score (ICISS). Major trauma was defined as ICISS, 0.90. Results: We analysed data on 4189 patients out of which 86.5% were males. A majority of patients were between 15 and 55 years old and 36.5% had major trauma. Overall early hospital mortality was 8.9% in 1998, 6.0% in 2002, and 8.1% in 2011. Among major trauma patients, early hospital mortality was 13.4%, in 1998, 11.3% in 2002, and 10.9% in 2011. Compared to trauma patients admitted in 1998, those admitted in 2011 had lower odds for early hospital mortality (OR = 0.56, 95% CI = 0.41-0.76) including those with major trauma (OR = 0.57, 95% CI = 0.41-0.78). Conclusions: We observed a significant reduction in early hospital mortality among patients with major trauma between 1998 and 2011. Improved survival was evident only after we adjusted for patient case-mix. This finding highlights the importance of risk-adjustment when studying longitudinal mortality trends.
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