Clinical risk-scoring algorithm to forecast scrub typhus severity

Pamornsri Sriwongpan,1,2 Pornsuda Krittigamas,3 Hutsaya Tantipong,4 Jayanton Patumanond,5 Chamaiporn Tawichasri,6 Sirianong Namwongprom1,71Clinical Epidemiology Program, Chiang Mai University, Chiang Mai, Thailand; 2Department of Social Medicine, Chiangrai Prachanukroh Hospital, Chiang Rai, Thailan...

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Main Authors: Sriwongpan P, Krittigamas P, Tantipong H, Patumanond J, Tawichasri C, Namwongprom S
Format: Article
Language:English
Published: Dove Medical Press 2013-12-01
Series:Risk Management and Healthcare Policy
Online Access:http://www.dovepress.com/clinical-risk-scoring-algorithm-to-forecast-scrub-typhus-severity-a15299
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spelling doaj-c9a577f7454b456d9a26da13c84296d72020-11-24T22:51:25ZengDove Medical PressRisk Management and Healthcare Policy1179-15942013-12-012014default111715299Clinical risk-scoring algorithm to forecast scrub typhus severitySriwongpan PKrittigamas PTantipong HPatumanond JTawichasri CNamwongprom S Pamornsri Sriwongpan,1,2 Pornsuda Krittigamas,3 Hutsaya Tantipong,4 Jayanton Patumanond,5 Chamaiporn Tawichasri,6 Sirianong Namwongprom1,71Clinical Epidemiology Program, Chiang Mai University, Chiang Mai, Thailand; 2Department of Social Medicine, Chiangrai Prachanukroh Hospital, Chiang Rai, Thailand; 3Department of General Pediatrics, Nakornping Hospital, Chiang Mai, Thailand; 4Department of Medicine, Chonburi Hospital, Chonburi, Thailand; 5Clinical Epidemiology Program, Thammasat University, Bangkok, Thailand; 6Clinical Epidemiology Society at Chiang Mai, Chiang Mai, Thailand; 7Department of Radiology, Chiang Mai University, Chiang Mai, ThailandPurpose: To develop a simple risk-scoring system to forecast scrub typhus severity.Patients and methods: Seven years' retrospective data of patients diagnosed with scrub typhus from two university-affiliated hospitals in the north of Thailand were analyzed. Patients were categorized into three severity groups: nonsevere, severe, and dead. Predictors for severity were analyzed under multivariable ordinal continuation ratio logistic regression. Significant coefficients were transformed into item score and summed to total scores.Results: Predictors of scrub typhus severity were age >15 years, (odds ratio [OR] =4.09), pulse rate >100/minute (OR 3.19), crepitation (OR 2.97), serum aspartate aminotransferase >160 IU/L (OR 2.89), serum albumin ≤3.0 g/dL (OR 4.69), and serum creatinine >1.4 mg/dL (OR 8.19). The scores which ranged from 0 to 16, classified patients into three risk levels: non-severe (score ≤5, n=278, 52.8%), severe (score 6–9, n=143, 27.2%), and fatal (score ≥10, n=105, 20.0%). Exact severity classification was obtained in 68.3% of cases. Underestimations of 5.9% and overestimations of 25.8% were clinically acceptable.Conclusion: The derived scrub typhus severity score classified patients into their severity levels with high levels of prediction, with clinically acceptable under- and overestimations. This classification may assist clinicians in patient prognostication, investigation, and management. The scoring algorithm should be validated by independent data before adoption into routine clinical practice.Keywords: severe scrub typhus, risk-scoring system, clinical prediction rule, prognostic predictorshttp://www.dovepress.com/clinical-risk-scoring-algorithm-to-forecast-scrub-typhus-severity-a15299
collection DOAJ
language English
format Article
sources DOAJ
author Sriwongpan P
Krittigamas P
Tantipong H
Patumanond J
Tawichasri C
Namwongprom S
spellingShingle Sriwongpan P
Krittigamas P
Tantipong H
Patumanond J
Tawichasri C
Namwongprom S
Clinical risk-scoring algorithm to forecast scrub typhus severity
Risk Management and Healthcare Policy
author_facet Sriwongpan P
Krittigamas P
Tantipong H
Patumanond J
Tawichasri C
Namwongprom S
author_sort Sriwongpan P
title Clinical risk-scoring algorithm to forecast scrub typhus severity
title_short Clinical risk-scoring algorithm to forecast scrub typhus severity
title_full Clinical risk-scoring algorithm to forecast scrub typhus severity
title_fullStr Clinical risk-scoring algorithm to forecast scrub typhus severity
title_full_unstemmed Clinical risk-scoring algorithm to forecast scrub typhus severity
title_sort clinical risk-scoring algorithm to forecast scrub typhus severity
publisher Dove Medical Press
series Risk Management and Healthcare Policy
issn 1179-1594
publishDate 2013-12-01
description Pamornsri Sriwongpan,1,2 Pornsuda Krittigamas,3 Hutsaya Tantipong,4 Jayanton Patumanond,5 Chamaiporn Tawichasri,6 Sirianong Namwongprom1,71Clinical Epidemiology Program, Chiang Mai University, Chiang Mai, Thailand; 2Department of Social Medicine, Chiangrai Prachanukroh Hospital, Chiang Rai, Thailand; 3Department of General Pediatrics, Nakornping Hospital, Chiang Mai, Thailand; 4Department of Medicine, Chonburi Hospital, Chonburi, Thailand; 5Clinical Epidemiology Program, Thammasat University, Bangkok, Thailand; 6Clinical Epidemiology Society at Chiang Mai, Chiang Mai, Thailand; 7Department of Radiology, Chiang Mai University, Chiang Mai, ThailandPurpose: To develop a simple risk-scoring system to forecast scrub typhus severity.Patients and methods: Seven years' retrospective data of patients diagnosed with scrub typhus from two university-affiliated hospitals in the north of Thailand were analyzed. Patients were categorized into three severity groups: nonsevere, severe, and dead. Predictors for severity were analyzed under multivariable ordinal continuation ratio logistic regression. Significant coefficients were transformed into item score and summed to total scores.Results: Predictors of scrub typhus severity were age >15 years, (odds ratio [OR] =4.09), pulse rate >100/minute (OR 3.19), crepitation (OR 2.97), serum aspartate aminotransferase >160 IU/L (OR 2.89), serum albumin ≤3.0 g/dL (OR 4.69), and serum creatinine >1.4 mg/dL (OR 8.19). The scores which ranged from 0 to 16, classified patients into three risk levels: non-severe (score ≤5, n=278, 52.8%), severe (score 6–9, n=143, 27.2%), and fatal (score ≥10, n=105, 20.0%). Exact severity classification was obtained in 68.3% of cases. Underestimations of 5.9% and overestimations of 25.8% were clinically acceptable.Conclusion: The derived scrub typhus severity score classified patients into their severity levels with high levels of prediction, with clinically acceptable under- and overestimations. This classification may assist clinicians in patient prognostication, investigation, and management. The scoring algorithm should be validated by independent data before adoption into routine clinical practice.Keywords: severe scrub typhus, risk-scoring system, clinical prediction rule, prognostic predictors
url http://www.dovepress.com/clinical-risk-scoring-algorithm-to-forecast-scrub-typhus-severity-a15299
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