Validation of a simplified risk prediction model using a cloud based critical care registry in a lower-middle income country
Bharath Kumar Tirupakuzhi Vijayaraghavan,
Dilanthi Priyadarshini,
Aasiyah Rashan,
Abi Beane,
Ramesh Venkataraman,
Nagarajan Ramakrishnan,
Rashan Haniffa and
the Indian Registry of IntenSive care(IRIS) Collaborators
PLOS ONE, 2020, vol. 15, issue 12, 1-9
Abstract:
Background: The use of severity of illness scoring systems such as the Acute Physiology and Chronic Health Evaluation in lower-middle income settings comes with important limitations, primarily due to data burden, missingness of key variables and lack of resources. To overcome these challenges, in Asia, a simplified model, designated as e-TropICS was previously developed. We sought to externally validate this model using data from a multi-centre critical care registry in India. Methods: Seven ICUs from the Indian Registry of IntenSive care(IRIS) contributed data to this study. Patients > 18 years of age with an ICU length of stay > 6 hours were included. Data including age, gender, co-morbidity, diagnostic category, type of admission, vital signs, laboratory measurements and outcomes were collected for all admissions. e-TropICS was calculated as per original methods. The area under the receiver operator characteristic curve was used to express the model’s power to discriminate between survivors and non-survivors. For all tests of significance, a 2-sided P less than or equal to 0.05 was considered to be significant. AUROC values were considered poor when ≤ to 0.70, adequate between 0.71 to 0.80, good between 0.81 to 0.90, and excellent at 0.91 or higher. Calibration was assessed using Hosmer-Lemeshow C -statistic. Results: We included data from 2062 consecutive patient episodes. The median age of the cohort was 60 and predominantly male (n = 1350, 65.47%). Mechanical Ventilation and vasopressors were administered at admission in 504 (24.44%) and 423 (20.51%) patients respectively. Overall, mortality at ICU discharge was 10.28% (n = 212). Discrimination (AUC) for the e-TropICS model was 0.83 (95% CI 0.812–0.839) with an HL C statistic p value of
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0244989
DOI: 10.1371/journal.pone.0244989
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