ABSTRACT
Introduction: The AST/platelet ratio index (APRI) is a well-researched indicator of liver fibrosis. Some studies have shown that APRI can be used as a predictor of severe dengue, but the data is limited. As dengue epidemics are common in our country with limited healthcare resources, we believe APRI can help emergency physicians/primary physicians in predicting the severity of dengue and plan for the appropriate use of limited healthcare resources. Objective: 1) To determine the utility of APRI as a predictor of severe dengue. 2) To determine the association of APRI with length of hospital stay and platelet requirement. Materials and Methods: A retrospective cross-sectional study was done on patients presented to the Emergency Medicine department at Travancore Medicity Medical College with a positive Dengue NS1 antigen or IgM antibody. Results: We found from the univariate analysis results that ALT > 74.5 IU/L has a sensitivity of 59.6 and a specificity of 76.3 (AUC: 0.696; 95% CI: 0.606-0.786), AST > 160.5 IU/L has a sensitivity of 42.3 and a specificity of 93.7 (AUC: 0.747; 95% CI: 0.665-0.829), and APRI > 3.2 has a sensitivity of 69.2 and a specificity of 84.2 (AUC: 0.806; 95% CI: 0.72-0.884) to predict severe dengue. Patients with an APRI of >3.2 required a mean hospital stay of 5.47 days (P = 0.005); 27 (81.8%) requiring platelet transfusion had an APRI of > 3.2 (P = 0.00). Conclusion: APRI is a straightforward index that can be easily derived from AST and platelet values. APRI values of >3.2 can predict severe dengue with a sensitivity of 69.2 and a specificity of 84.2. APRI values of >3.2 are also associated with the length of hospital stay and requirement of platelet transfusion.
ABSTRACT
Background: As India was slowly coming out of shock from the second wave wrecked by the Delta strain, the world population is now struck once again with a new strain of coronavirus disease 2019 (COVID-19), designated as B.1.1.529, named as OMICRON. Though several international studies have evaluated the role of computed tomography (CT) in diagnosis, predicting prognosis, and monitoring the progression of disease, to our best knowledge, there are no Indian studies published in this context. Objective: (1) To determine the use of chest CT severity score as predictor of mortality in COVID-19 patients. (2) To determine the prognosis based on length of hospital stay. Materials and Methods: A observational cohort study was done at Travancore Medical College Hospital. A retrospective analysis of patients who presented to the Emergency Medicine Department with a positive COVID antigen or reverse transcriptase-polymerase chain reaction (RT-PCR) results and those who underwent a CT chest at the time of presentation was conducted. Data was analyzed by using Statistical Package for Social Sciences (SPSS) version 16. Descriptive statistics such as mean, frequency, and percentages were calculated. Chi-square test was used to find the statistical significance. The Kaplan-Meier method was used to evaluate the relationship between CT score and mortality, which was compared with the log-rank test. Results: A total of 252 patients with positive COVID antigen or RT-PCR who underwent CT chest were included in our study. Our study population was composed of 139 (55.2%) males and 113 (44.8%) females. Only one patient with mild CT severity score required >14 days of ICU stay, whereas two (2%) and five (9.6%) patients with moderate and severe CT severity score, respectively, required ICU stay for >14 days. The P value was 0.001, which again is statistically significant. In our study, out of 44 patients categorized under mild CT severity score, only two (4.5%) patients had expired. Out of 98 patients categorized under moderate CT severity score, 14 (14.3%) patients had expired, whereas out of 52 patients categorized under severe CT severity score at the time of admission, 25 (48.1%) patients had expired. The P value was 0.001, which is statistically significant. Conclusion: Our study could prove that patients with CT severity score ≥15 had high risk of mortality and required prolonged ICU stay of >5 days. CT severity score helps the primary care physicians to predict probable outcome and length of hospital stay at the time of admission itself and allocate the limited resources appropriately.
