title: Validation of a clinical risk-scoring algorithm for severe scrub typhus.
abstract: OBJECTIVE
  The aim of the study reported here was to validate the risk-scoring algorithm for prognostication of scrub typhus severity.
  
  
  METHODS
  The 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.
  
  
  RESULTS
  The 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.
  
  
  CONCLUSIONS
  The 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.
authors.affiliation: Clinical Epidemiology Program, Faculty of Medicine, Chiang Mai University, Chiang Mai ; Department of Social Medicine, Chiangrai Prachanukroh Hospital, Chiang Rai.
authors.forename: Pamornsri
authors.initials: P
authors.lastname: Sriwongpan
authors.affiliation: Clinical Epidemiology Program, Faculty of Medicine, Thammasat University, Bangkok.
authors.forename: Jayanton
authors.initials: J
authors.lastname: Patumanond
authors.affiliation: Department of General Pediatrics, Nakornping Hospital, Chiang Mai.
authors.forename: Pornsuda
authors.initials: P
authors.lastname: Krittigamas
authors.affiliation: Department of Medicine, Chonburi Hospital, Chonburi.
authors.forename: Hutsaya
authors.initials: H
authors.lastname: Tantipong
authors.affiliation: Clinical Epidemiology Society at Chiang Mai, Chiang Mai.
authors.forename: Chamaiporn
authors.initials: C
authors.lastname: Tawichasri
authors.affiliation: Clinical Epidemiology Program, Faculty of Medicine, Chiang Mai University, Chiang Mai ; Department of Radiology, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand.
authors.forename: Sirianong
authors.initials: S
authors.lastname: Namwongprom
keywords: Thailand; algorithm; clinical prediction rule; prognosis; severity