Medicine
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This repository contains the published and unpublished research of the Faculty of Medicine by the staff members of the faculty
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Item Identification of dengue patients with high risk of severe disease, using early clinical and laboratory features, in a resource-limited setting(Springer-Verlag., 2020) Niriella, M.A.; Liyanage, I.K.; Udeshika, A.; Liyanapathirana, K.V.; de Silva, A.P.; de Silva, H.J.ABSTRACT: Only a minority of dengue infections lead to plasma leakage (critical phase [CP]). Early identification of the risk for CP is helpful for triage of patients. This study aimed to identify early clinical predictors of CP that will aid in patient triage during early illness. A retrospective, case-record-based analysis was performed on all microbiologically confirmed (NS1-antigen- or dengue-IgM-antibody-positive), dengue patients (n = 697), admitted to our unit from 01.01.2017 to 30.06.2017. Bivariate analysis was performed to identify clinical and laboratory parameters that predicted CP. Stepwise multivariate logistic regression with backward elimination (p < 0.05) was used to identify independent risk factors for CP. CP developed in 226 (32.4%) patients. Mortality was 1.0%. Predictors for CP (p < 0.05) within the first three days included age category 41-50 years (OR = 1.96), females (OR = 2.09), diabetes (OR = 1.30), persistent vomiting (OR = 2.18), platelet count < 120,000/mm-3 (OR = 1.91) and AST > 60 IU/L (OR = 3.72). On multivariate analysis, other variables except diabetes remained significant. Elevated transaminase levels remained the strongest independent predictor of CP (OR 2.83). The absence of all five risk factors excluded CP (negative predictive value: 97.2%). Age 41-50 years, female gender, persistent vomiting, thrombocytopenia, and elevated transaminases were early predictors of CP in dengue fever. The absence of these can be used to identify patients who may not require hospital admission. Elevated transaminase was the strongest predictor of CP during early illness.Item Early hepatitis is the strongest risk factor for the development of severe dengue infection: A points-based risk-score to predict critical disease in dengue fever(Sri Lanka Medical Association, 2018) Niriella, M.A.; Udeshika, A.K.M.A.; Liyanage, I.K.; de Silva, A.P.; de Silva, H.J.INTRODUCTION AND OBJECTIVES: Some dengue fever (DF) patients develop plasma leakage [critical-phase (CP)], which may progress to multi-organ failure. We attempted to identify early predictors ofCP in DF. METHODS: This was a retrospective, case-record-based study. Clinical, laboratory features in the first three-days (Dl-3) of illness was used to formulate a risk prediction model (RPM). Patients with serologically confirmed DF, admitted to the University Medical Unit, Teaching Hospital, Ragama, from 01.01.2017-30.06.2017 were included. Patients were randomly assigned to training (TD) and validation datasets (VD) of equal size. Stepwise multivariate logistic regression (p<0.05) was used to identify risk factors in TD. Versions of RPM were compared using Akaike criteria and McFadden's adjusted R2. Coefficients from the best RPM were used to derive weighted risk scores. Best RPM was validated in VD using C-statistic. RESULTS: 697 patients were included (mean-age:34.7±16.1 years, females-48.8%, TD=350, VD=346). CP developed inJ27 (32.6%). Mortality was I%. Risk predictors (p<0.05) were: female gender (OR=2.l), diabetes (OR=l.8), vomiting (OR=l.9), platelets60 IU/L (OR=3.3). In multivariate analysis, female gender (score=2), vomiting (score=3), platelets<120,000/mm-3 (score=3) and AST>60 IU/L 3 (score=4) were significant while diabetes was non-significant. Calculated RPM score ranged from 0-12. C-statistic for the TD was 0.78 and VD 0.77 (Hosmer-Lemeshow test: p=0.19 and 0.34 respectively). A cut-off of 5 was selected to maximise sensitivity (0.96), negative predictive value (0.95) with specificity of 0.44. CONCLUSION: This simple risk score seems useful in identifying those at risk ofCP within Dl-3 of the onset ofDF. The early presence of dengue hepatitis was the strongest predictor of CP.