Martin Gerdin1, Nobhojit Roy2, Li Felländer-Tsai3, Göran Tomson4, Johan von Schreeb5, Max Petzold6, Amit Gupta7, Ashish Jhakal7, Debojit Basak8, Deen Mohamed Ismail9, Dusu Yabo7, K Jegadeesan10, Jyoti Kamble11, Makhan Lal Saha12, Mangesh Nitnaware13, Monty Khajanchi14, Ranganathan Jothi15, Samarendra Nath Ghosh16, Sanjeev Bhoi7, Santosh Mahindrakar7, Satish Dharap17, Shilpa Rao18, Veera Kamal10, Vineet Kumar17, Santosh Tirlotkar19. 1. Health Systems and Policy, Department of Public Health Sciences, Karolinska Institutet, SE-171 77 Stockholm, Sweden. Electronic address: martin.gerdin@ki.se. 2. Health Systems and Policy, Department of Public Health Sciences, Karolinska Institutet, SE-171 77 Stockholm, Sweden; Department of Surgery, Bhabha Atomic Research Centre Hospital, Mumbai, Maharashtra 400085, India; School of Habitat, Tata Institute of Social Sciences, Chembur, Mumbai, Maharashtra 400088, India. 3. Division of Orthopedics and Biotechnology, Department of Clinical Science Intervention and Technology, Karolinska Institutet, Alfred Nobels allé 8, SE-141 52 Huddinge, Sweden. 4. Health Systems and Policy, Department of Public Health Sciences, Karolinska Institutet, SE-171 77 Stockholm, Sweden; Department of Learning, Informatics, Management and Ethics, Karolinska Institutet, SE-171 77 Stockholm, Sweden. 5. Health Systems and Policy, Department of Public Health Sciences, Karolinska Institutet, SE-171 77 Stockholm, Sweden. 6. Centre for Applied Biostatistics, Occupational and Environmental Medicine, Sahlgrenska Academy, University of Gothenburg, PO Box 414, SE-405 30 Gothenburg, Sweden; School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, 7 York Rd, Johannesburg 2193, South Africa. 7. Jai Prakash Narayan Apex Trauma Center, All India Institute of Medical Sciences, New Delhi, Delhi 110029, India. 8. Institute of Post-Graduate Medical Education and Research and Seth Sukhlal Karnani Memorial Hospital, Harish Mukherjee Rd, Bhowanipore, Kolkata, India. 9. Department of Orthopedics, Madras Medical College, Chennai, Tamil Nadu 600003, India. 10. Madras Medical College, Chennai, Tamil Nadu 600003, India. 11. King Edward Memorial Hospital, Mumbai, Maharashtra 400012, India. 12. Department of Surgery, Institute of Post-Graduate Medical Education and Research and Seth Sukhlal Karnani Memorial Hospital, Harish Mukherjee Rd, Bhowanipore, Kolkata, India. 13. Lokmanya Tilak Municipal Medical College and General Hospital, Mumbai, Maharashtra 400022, India. 14. General Surgery, Seth GS Medical College & King Edward Memorial Hospital, Mumbai, Maharashtra 400012, India. 15. Department of Neurosurgery, Madras Medical College, Chennai, Tamil Nadu 600003, India. 16. Department of Neurosurgery, Institute of Post-Graduate Medical Education and Research and Seth Sukhlal Karnani Memorial Hospital, Harish Mukherjee Rd, Bhowanipore, Kolkata, India. 17. Department of Surgery, Lokmanya Tilak Municipal Medical College and General Hospital, Mumbai, Maharashtra 400022, India. 18. Department of Surgery, King Edward Memorial Hospital, Mumbai, Maharashtra 400012, India. 19. School of Habitat, Tata Institute of Social Sciences, Chembur, Mumbai, Maharashtra 400088, India.
Abstract
OBJECTIVE: We evaluated the transferability of prediction models between trauma care contexts in India and the United States and explored updating methods to adjust such models for new contexts. STUDY DESIGN AND SETTINGS: Using a combination of prospective cohort and registry data from 3,728 patients of Towards Improved Trauma Care Outcomes in India (TITCO) and from 18,756 patients of the US National Trauma Data Bank (NTDB), we derived models in one context and validated them in the other, assessing them for discrimination and calibration using systolic blood pressure, heart rate, and Glasgow coma scale as candidate predictors. RESULTS: Early mortality was 8% in the TITCO and 1-2% in the NTDB samples. Both models discriminated well, but the TITCO model overestimated the risk of mortality in NTDB patients, and the NTDB model underestimated the risk in TITCO patients. CONCLUSION: Transferability was good in terms of discrimination but poor in terms of calibration. It was possible to improve this miscalibration by updating the models' intercept. This updating method could be used in samples with as few as 25 events.
OBJECTIVE: We evaluated the transferability of prediction models between trauma care contexts in India and the United States and explored updating methods to adjust such models for new contexts. STUDY DESIGN AND SETTINGS: Using a combination of prospective cohort and registry data from 3,728 patients of Towards Improved Trauma Care Outcomes in India (TITCO) and from 18,756 patients of the US National Trauma Data Bank (NTDB), we derived models in one context and validated them in the other, assessing them for discrimination and calibration using systolic blood pressure, heart rate, and Glasgow coma scale as candidate predictors. RESULTS: Early mortality was 8% in the TITCO and 1-2% in the NTDB samples. Both models discriminated well, but the TITCO model overestimated the risk of mortality in NTDBpatients, and the NTDB model underestimated the risk in TITCO patients. CONCLUSION: Transferability was good in terms of discrimination but poor in terms of calibration. It was possible to improve this miscalibration by updating the models' intercept. This updating method could be used in samples with as few as 25 events.