Rashan Haniffa1, A Pubudu De Silva2, Prasad Weerathunga3, Mavuto Mukaka4, Priyantha Athapattu5, Sithum Munasinghe6, Buddhika Mahesh7, Palitha Mahipala8, Terrence De Silva9, Anuja Abayadeera10, Saroj Jayasinghe11, Nicolette de Keizer12, Arjen M Dondorp4. 1. National Intensive Care Surveillance, Quality Secretariat Building, Castle Street Hospital for Women, Colombo 08, Sri Lanka; Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, 3/F, 60th Anniversary Chalermprakiat Building, 420/6 Rajvithi Road, Bangkok 10400, Thailand; Department of Clinical Medicine, Faculty of Medicine, University of Colombo, No. 25, Kynsey Road, Colombo 08, Sri Lanka. Electronic address: rashan@nicslk.com. 2. National Intensive Care Surveillance, Quality Secretariat Building, Castle Street Hospital for Women, Colombo 08, Sri Lanka; Intensive Care National Audit & Research Centre, No. 24, High Holborn, London WC1V 6AZ, United Kingdom. 3. National Intensive Care Surveillance, Quality Secretariat Building, Castle Street Hospital for Women, Colombo 08, Sri Lanka; The Central Hospital, Asiri Group of Hospitals, No. 114, Norris Canal Road, Colombo 10, Sri Lanka. 4. Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, 3/F, 60th Anniversary Chalermprakiat Building, 420/6 Rajvithi Road, Bangkok 10400, Thailand. 5. National Intensive Care Surveillance, Quality Secretariat Building, Castle Street Hospital for Women, Colombo 08, Sri Lanka; Office of Medical Services, Ministry of Health, No. 385, Ven. Baddegama Wimalawansa Thero Mawatha, Colombo 10, Sri Lanka. 6. National Intensive Care Surveillance, Quality Secretariat Building, Castle Street Hospital for Women, Colombo 08, Sri Lanka. 7. Department of Community Medicine, Faculty of Medicine, University of Colombo, No. 25, Kynsey Road, Colombo 08, Sri Lanka. 8. National Intensive Care Surveillance, Quality Secretariat Building, Castle Street Hospital for Women, Colombo 08, Sri Lanka; Office of Director General of Health Services, Ministry of Health, No. 385, Ven. Baddegama Wimalawansa Thero Mawatha, Colombo 10, Sri Lanka. 9. Sri Lanka Medical Council, No. 31, Norris Canal Road, Colombo 10, Sri Lanka. 10. Department of Surgery, Faculty of Medicine, University of Colombo, No. 25, Kynsey Road, Colombo 08, Sri Lanka. 11. Department of Clinical Medicine, Faculty of Medicine, University of Colombo, No. 25, Kynsey Road, Colombo 08, Sri Lanka. 12. Academic Medical Center, University of Amsterdam, Meibergdreef 9, 1105 AZ Amsterdam-Zuidoost, Netherlands.
Abstract
PURPOSE: To determine the utility of APACHE II in a low-and middle-income (LMIC) setting and the implications of missing data. MATERIALS AND METHODS: Patients meeting APACHE II inclusion criteria admitted to 18 ICUs in Sri Lanka over three consecutive months had data necessary for the calculation of APACHE II, probabilities prospectively extracted from case notes. APACHE II physiology score (APS), probabilities, Standardised (ICU) Mortality Ratio (SMR), discrimination (AUROC), and calibration (C-statistic) were calculated, both by imputing missing measurements with normal values and by Multiple Imputation using Chained Equations (MICE). RESULTS: From a total of 995 patients admitted during the study period, 736 had APACHE II probabilities calculated. Data availability for APS calculation ranged from 70.6% to 88.4% for bedside observations and 18.7% to 63.4% for invasive measurements. SMR (95% CI) was 1.27 (1.17, 1.40) and 0.46 (0.44, 0.49), AUROC (95% CI) was 0.70 (0.65, 0.76) and 0.74 (0.68, 0.80), and C-statistic was 68.8 and 156.6 for normal value imputation and MICE, respectively. CONCLUSIONS: An incomplete dataset confounds interpretation of prognostic model performance in LMICs, wherein imputation using normal values is not a suitable strategy. Improving data availability, researching imputation methods and developing setting-adapted and simpler prognostic models are warranted.
PURPOSE: To determine the utility of APACHE II in a low-and middle-income (LMIC) setting and the implications of missing data. MATERIALS AND METHODS:Patients meeting APACHE II inclusion criteria admitted to 18 ICUs in Sri Lanka over three consecutive months had data necessary for the calculation of APACHE II, probabilities prospectively extracted from case notes. APACHE II physiology score (APS), probabilities, Standardised (ICU) Mortality Ratio (SMR), discrimination (AUROC), and calibration (C-statistic) were calculated, both by imputing missing measurements with normal values and by Multiple Imputation using Chained Equations (MICE). RESULTS: From a total of 995 patients admitted during the study period, 736 had APACHE II probabilities calculated. Data availability for APS calculation ranged from 70.6% to 88.4% for bedside observations and 18.7% to 63.4% for invasive measurements. SMR (95% CI) was 1.27 (1.17, 1.40) and 0.46 (0.44, 0.49), AUROC (95% CI) was 0.70 (0.65, 0.76) and 0.74 (0.68, 0.80), and C-statistic was 68.8 and 156.6 for normal value imputation and MICE, respectively. CONCLUSIONS: An incomplete dataset confounds interpretation of prognostic model performance in LMICs, wherein imputation using normal values is not a suitable strategy. Improving data availability, researching imputation methods and developing setting-adapted and simpler prognostic models are warranted.
Authors: Kris Salaveria; Simon Smith; Yu-Hsuan Liu; Richard Bagshaw; Markus Ott; Alexandra Stewart; Matthew Law; Angus Carter; Josh Hanson Journal: Am J Trop Med Hyg Date: 2021-10-18 Impact factor: 3.707
Authors: Rashan Haniffa; Ilhaam Isaam; A Pubudu De Silva; Arjen M Dondorp; Nicolette F De Keizer Journal: Crit Care Date: 2018-01-26 Impact factor: 9.097