A novel scoring system to predict the requirement for surgical intervention in victims of motor vehicle crashes: Development and validation using independent cohorts

一种预测机动车事故受害者是否需要手术干预的新型评分系统:基于独立队列的开发和验证

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Abstract

BACKGROUND: Given that there are still considerable number of facilities which lack surgical specialists round the clock across the world, the ability to estimate the requirement for emergency surgery in victims of motor vehicle crashes (MVCs) can ensure appropriate resource allocation. In this study, a surgical intervention in victims of MVC (SIM) score was developed and validated, using independent patient cohorts. METHODS: We retrospectively identified MVC victims in a nationwide trauma registry (2004-2016). Adults ≥ 15 years who presented with palpable pulse were included. Patients with missing data on the type/date of surgery were excluded. Patient were allocated to development or validation cohorts based on the date of injury. After missing values were imputed, predictors of the need for emergency thoracotomy and/or laparotomy were identified with multivariate logistic regression, and scores were then assigned using odds ratios. The SIM score was validated with area under the receiver operating characteristic curve (AUROC) and calibration plots of SIM score-derived probability and observed rates of emergency surgery. RESULTS: We assigned 13,328 and 12,348 patients to the development and validation cohorts, respectively. Age, motor vehicle collision and vital signs on hospital arrival were identified as independent predictors for emergency thoracotomy and/or laparotomy, and SIM score was developed as 0-9 scales. The score has a good discriminatory power (AUROC = 0.79; 95% confidence interval = 0.77-0.81), and both estimated and observed rates of emergency surgery increased stepwise from 1% at a score ≤ 1 to almost 40% at a score ≥ 8 with linear calibration plots. CONCLUSIONS: The SIM score was developed and validated to accurately estimate the need for emergent thoracotomy and/or laparotomy in MVC victims.

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