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Clinical risk-scoring algorithm to forecast scrub typhus severity

PURPOSE: 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 seve...

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Detalles Bibliográficos
Autores principales: Sriwongpan, Pamornsri, Krittigamas, Pornsuda, Tantipong, Hutsaya, Patumanond, Jayanton, Tawichasri, Chamaiporn, Namwongprom, Sirianong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove Medical Press 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3872011/
https://www.ncbi.nlm.nih.gov/pubmed/24379733
http://dx.doi.org/10.2147/RMHP.S55305
Descripción
Sumario:PURPOSE: 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.