title: Validation of a novel prediction model for early mortality in adult trauma patients in three public university hospitals in urban India.
abstract: BACKGROUND
  Trauma is one of the top threats to population health globally. Several prediction models have been developed to supplement clinical judgment in trauma care. Whereas most models have been developed in high-income countries the majority of trauma deaths occur in low- and middle-income countries. Almost 20 % of all global trauma deaths occur in India alone. The aim of this study was to validate a basic clinical prediction model for use in urban Indian university hospitals, and to compare it with existing models for use in early trauma care.
  
  
  METHODS
  We conducted a prospective cohort study in three hospitals across urban India. The model we aimed to validate included systolic blood pressure and Glasgow coma scale. We compared this model with three additional models, which all have been designed for use in bedside trauma care, and two single variable models based on systolic blood pressure and Glasgow coma scale respectively. The outcome was early mortality, defined as death within 24 h from the time when vital signs were first measured. We compared the models in terms of discrimination, calibration, and potential clinical consequences using decision curve analysis. Multiple imputation was used to handle missing data. Performance measures are reported using their median and inter-quartile range (IQR) across imputed datasets.
  
  
  RESULTS
  We analysed 4440 patients, out of which 1629 were used as an updating sample and 2811 as a validation sample. We found no evidence that the basic model that included only systolic blood pressure and Glasgow coma scale had worse discrimination or potential clinical consequences compared to the other models. A model that also included heart had better calibration. For the model with systolic blood pressure and Glasgow coma scale the discrimination in terms of area under the receiver operating characteristics curve was 0.846 (IQR 0.841-0.849). Calibration measured by estimating a calibration slope was 1.183 (IQR 1.168-1.202). Decision curve analysis revealed that using this model could potentially result in 45 fewer unnecessary surveys per 100 patients.
  
  
  CONCLUSIONS
  A basic clinical prediction model with only two parameters may prove to be a feasible alternative to more complex models in contexts such as the Indian public university hospitals studied here. We present a colour-coded chart to further simplify the decision making in early trauma care.
authors.affiliation: Health Systems and Policy, Department of Public Health Sciences, Karolinska Institutet, Tomtebodavägen 18A, Solna, 171 65, Stockholm, Sweden. martin.gerdin@ki.se.
authors.forename: Martin
authors.initials: M
authors.lastname: Gerdin
authors.affiliation: Health Systems and Policy, Department of Public Health Sciences, Karolinska Institutet, Tomtebodavägen 18A, Solna, 171 65, Stockholm, Sweden. nobhojit.roy@ki.se.|Department of Surgery, Bhabha Atomic Research Centre Hospital, Mumbai, India. nobhojit.roy@ki.se.|Tata Institute of Social Sciences, School of Habitat, Mumbai, India. nobhojit.roy@ki.se.
authors.forename: Nobhojit
authors.initials: N
authors.lastname: Roy
authors.affiliation: General Surgery, Seth GS Medical College & King Edward Memorial Hospital, Mumbai, India. monta32@gmail.com.
authors.forename: Monty
authors.initials: M
authors.lastname: Khajanchi
authors.affiliation: Department of Surgery, Lokmanya Tilak Municipal Medical College and General Hospital, Mumbai, India. drvineetkumar@hotmail.com.
authors.forename: Vineet
authors.initials: V
authors.lastname: Kumar
authors.affiliation: Department of Clinical Science Intervention and Technology, Division of Orthopedics and Biotechnology, Karolinska Institutet, Stockholm, Sweden. li.tsai@ki.se.
authors.forename: Li
authors.initials: L
authors.lastname: Felländer-Tsai
authors.affiliation: Centre for Applied Biostatistics, Occupational and Environmental Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden. max.petzold@gu.se.|Faculty of Health Sciences, School of Public Health, University of the Witwatersrand, Johannesburg, South Africa. max.petzold@gu.se.
authors.forename: Max
authors.initials: M
authors.lastname: Petzold
authors.affiliation: Health Systems and Policy, Department of Public Health Sciences, Karolinska Institutet, Tomtebodavägen 18A, Solna, 171 65, Stockholm, Sweden. goran.tomson@ki.se.|Department of Learning, Informatics, Management and Ethics, Karolinska Institutet, Stockholm, Sweden. goran.tomson@ki.se.
authors.forename: Göran
authors.initials: G
authors.lastname: Tomson
authors.affiliation: Health Systems and Policy, Department of Public Health Sciences, Karolinska Institutet, Tomtebodavägen 18A, Solna, 171 65, Stockholm, Sweden. johan.von.schreeb@ki.se.
authors.forename: Johan
authors.initials: J
authors.lastname: von Schreeb
mesh_terms: D000328:Adult; D005260:Female; D005544:Forecasting; D006779:Hospitals, Public; D006785:Hospitals, University; D006801:Humans; D007194:India; D008297:Male; D008875:Middle Aged; D008962:Models, Theoretical; D061213:Mortality, Premature / Q000639:trends*; D011446:Prospective Studies; D014505:Urban Population; D014947:Wounds and Injuries / Q000628:therapy*; D055815:Young Adult