Evidence map›Paper›PMID 42243707›Full record

ArticleBMC infectious diseases2026

Multicenter validation of a simple clinical risk score for early prediction of severe dengue among adults in Thailand.

Surangrat Pongpan, Patcharin Khamnuan, Pantitcha Thanatrakolsri, Supa Vittaporn, Punnaphat Daraswang

Abstract readMulticenter StudyValidation Study
In one paragraph

Article in BMC infectious diseases, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Surangrat PongpanFaculty of Public Health, Thammasat University, Lampang Campus, Lampang, 52190, Thailand.
Patcharin KhamnuanFaculty of Public Health, Thammasat University, Lampang Campus, Lampang, 52190, Thailand. patcharin.k@fph.tu.ac.th.
Pantitcha ThanatrakolsriFaculty of Public Health, Thammasat University, Lampang Campus, Lampang, 52190, Thailand.
Supa VittapornFaculty of Public Health, Thammasat University, Lampang Campus, Lampang, 52190, Thailand.
Punnaphat DaraswangBuriram Hospital, Mueang Buriram District, Buriram, 31000, Thailand.

Funding

The Thailand Science Research and Innovation Fundamental Fund in 2022 Contract No. TUFF 56/2565The Thammasat University Research Fund Contract No. TUFT-FF 45/2565
6 · The paper itself

Abstract

backgroundDengue remains a major public health challenge in Thailand. Although only a minority of patients progress to severe dengue, the condition is potentially life-threatening and requires early recognition. Simple clinical prediction tools may support early risk stratification in routine care, particularly in resource-limited settings. This study aimed to externally validate a simple clinical risk score for predicting severe dengue among adult patients using multicenter hospital data in Thailand.

methodsA retrospective multicenter validation study was conducted using clinical data from six hospitals in Thailand (2019-2022). Model discrimination was assessed using the area under the receiver operating characteristic curve (AuROC). Patients were categorized into three predefined risk groups. Likelihood ratios were calculated to evaluate clinical utility across risk strata. Calibration was assessed using calibration plots, slope, and intercept.

resultsThe model demonstrated good discriminative performance, with an AuROC of 0.83 (95% CI 0.77-0.90) in the validation cohort, compared with 0.88 in the development cohort (p-value = 0.249). Likelihood ratios indicated strong rule-in ability in the high-risk group (LR + = 52.02), while the low-risk group was associated with reduced probability of severe disease. Calibration was acceptable overall, although systematic underestimation was observed in higher-risk patients.

conclusionsThis simple clinical risk score demonstrated good and stable performance across diverse hospital settings. The model may support early in-hospital risk stratification and clinical monitoring decisions among adult dengue patients. Further prospective validation and recalibration studies are warranted. CLINICAL TRIAL NUMBER: Not applicable.

Indexed as

Severe DengueAdultFemaleHumansMaleMiddle AgedRetrospective StudiesRisk AssessmentRisk FactorsROC CurveThailandYoung AdultClinical prediction modelMulticenter external validationRisk stratificationSevere dengueThailand

Identifiers

PMID42243707
PMCPMC13455270

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.