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, 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 predictor

Validation of a clinical risk-scoring algorithm for severe scrub typhus

Pamornsri Sriwongpan,1,2 Jayanton Patumanond,3 Pornsuda Krittigamas,4 Hutsaya Tantipong,5 Chamaiporn Tawichasri,6 Sirianong Namwongprom1,7 1Clinical Epidemiology Program, Faculty of Medicine, Chiang Mai University, Chiang Mai, 2Department of Social Medicine, Chiangrai Prachanukroh Hospital, Chiang Rai, 3Clinical Epidemiology Program, Faculty of Medicine, Thammasat University, Bangkok, 4Department of General Pediatrics, Nakornping Hospital, Chiang Mai, 5Department of Medicine, Chonburi Hospital, Chonburi, 6Clinical Epidemiology Society at Chiang Mai, Chiang Mai, 7Department of Radiology, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand 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. Conclusion: 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. Keywords: severity, clinical prediction rule, algorithm, prognosis, Thailan

Effect of acetylsalicylic acid on thalassemia with pulmonary arterial hypertension

Nonlawan Chueamuangphan,1,2 Wattana Wongtheptian,2 Jayanton Patumanond,3 Apichard Sukonthasarn,4 Suporn Chuncharunee,5 Chamaiporn Tawichasri,6 Weerasak Nawarawong4 1Clinical Epidemiology Program, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand; 2Department of Medicine, Chiang Rai Hospital, Chiang Rai, Thailand; 3Clinical Epidemiology Program, Faculty of Medicine, Thammasat University, Bangkok, Thailand; 4Department of Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand; 5Department of Medicine, Faculty of Medicine, Ramathibodi Hospital, Mahidol University, Bangkok, Thailand; 6Clinical Epidemiology Society at Chiang Mai, Chiang Mai, Thailand Objective: To compare pulmonary artery systolic pressure (PASP) between thalassemic patients with pulmonary arterial hypertension (PAH) for whom acetylsalicylic acid (ASA) was and was not prescribed after 1 year. Methods: A retrospective cohort study was conducted at the hematological outpatient clinic at Chiang Rai Hospital, Chiang Rai, Thailand. All new cases of thalassemia with PAH from January 2007 to January 2012 were studied at the first month and at 12 months. The patients were classified into two groups. In one group, ASA 81 mg daily was prescribed for 1 year, whereas in another group no ASA was prescribed, due to its contraindications, which included bleeding, gastrointestinal side effects, and thrombocytopenia. PASP, estimated by a Doppler echocardiography, was measured by the same cardiologist. Propensity score adjustment was used to control confounding variables by indication and contraindication. Multivariable regression analysis was used to evaluate the effects of ASA. Results: Of the 63 thalassemia patients with PAH, there were 47 (74.6%) in the ASA group and 16 (25.4%) in the no ASA group. ASA, as compared with no ASA, did not significantly reduce PASP (adjusted difference -0.95; 95% confidence interval -16.99 to 15.10; P=0.906). Conclusion: Low-dose ASA may not have a beneficial effect on PASP after 1 year of treatment of PAH in thalassemia. Keywords: thalassemia, pulmonary arterial hypertension, acetylsalicylic aci