ArticleRisk management and healthcare policy2014
Validation of a clinical risk-scoring algorithm for severe scrub typhus.
Article in Risk management and healthcare policy, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Revisiting doxycycline in pregnancy and early childhood--time to rebuild its reputation?Expert opinion on drug safety · 2016Pooled it
- A time-course comparative clinical and immune response evaluation study between the human pathogenic Orientia tsutsugamushi strains: Karp and Gilliam in a rhesus macaque (Macaca mulatta) model.PLoS neglected tropical diseases · 2022Article
- Validation of a Clinical Risk-scoring Algorithm for Scrub Typhus Severity in South India.Indian journal of critical care medicine : peer-reviewed, official publication of Indian Society of Critical Care Medicine · 2021Article
- Clinical and Laboratory Predictors associated with Complicated Scrub Typhus.Infection & chemotherapy · 2019Article
- Causes of acute undifferentiated fever and the utility of biomarkers in Chiangrai, northern Thailand.PLoS neglected tropical diseases · 2018Observational
- Scrub typhus: risks, diagnostic issues, and management challenges.Research and reports in tropical medicine · 2017Review
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveThe aim of the study reported here was to validate the risk-scoring algorithm for prognostication of scrub typhus severity.
methodsThe risk-scoring algorithm for prognostication of scrub typhus severity developed earlier from two general hospitals in Thailand was validated using an independent dataset of scrub typhus patients in one of the hospitals from a few years later. The predictive performances of the two datasets were compared by analysis of the area under the receiver-operating characteristic curve (AuROC). Classification of patients into non-severe, severe, and fatal cases was also compared.
resultsThe proportions of non-severe, severe, and fatal patients by operational definition were similar between the development and validation datasets. Patient, clinical, and laboratory profiles were also similar. Scores were similar in both datasets, both in terms of discriminating non-severe from severe and fatal patients (AuROC =88.74% versus 91.48%, P=0.324), and in discriminating fatal from severe and non-severe patients (AuROC =88.66% versus 91.22%, P=0.407). Over- and under-estimations were similar and were clinically acceptable.
conclusionThe previously developed risk-scoring algorithm for prognostication of scrub typhus severity performed similarly with the validation data and the first dataset. The scoring algorithm may help in the prognostication of patients according to their severity in routine clinical practice. Clinicians may use this scoring system to help make decisions about more intensive investigations and appropriate treatments.
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