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VOLUME 25 , ISSUE 5 ( May, 2021 ) > List of Articles

ORIGINAL RESEARCH

Validation of a Clinical Risk-scoring Algorithm for Scrub Typhus Severity in South India

Shivali Gulati, Kiran Chunduru, Mridula Madiyal, Maninder S Setia

Citation Information : Gulati S, Chunduru K, Madiyal M, Setia MS. Validation of a Clinical Risk-scoring Algorithm for Scrub Typhus Severity in South India. Indian J Crit Care Med 2021; 25 (5):551-556.

DOI: 10.5005/jp-journals-10071-23828

License: CC BY-NC 4.0

Published Online: 01-05-2021

Copyright Statement:  Copyright © 2021; The Author(s).


Abstract

Background: A clinical risk-scoring algorithm (CRSA) to forecast the scrub typhus severity was developed from two general hospitals in Thailand where patients were classified into three groups—nonsevere, severe, and fatal. In this study, an attempt was made to validate the risk-scoring algorithm for prognostication of scrub typhus severity in India. Materials and methods: This prospective study was conducted at a hospital in South India between November 2017 and March 2019. Patients of scrub typhus were categorized into nonsevere, severe, and fatal according to the CRSA. The patients were also grouped into severe and nonsevere according to the definition of severe scrub typhus which was used as a gold standard. The obtained CRSA score was validated against the classification based on the definition of severe scrub typhus. Receiver operating characteristics (ROC) curve for the scores was plotted and the Youden's index for optimal cutoff was used. Results: A total of 198 confirmed cases of scrub typhus were included in the study. According to the ROC curve, at a severity score ≥7, an optimal combination of sensitivity of 75.9% and specificity of 77.5% was achieved. It correctly predicted 76.77% (152 of 198) of patients as severe, with an underestimation of 10.61% (21 patients) and an overestimation of 12.63% (25 patients). Conclusion: In the present study setting, a cutoff of ≥7 for severity prediction provides an optimum combination of sensitivity and specificity. These findings need to be validated in further studies.

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