Diagnostic accuracy and predictive value in differentiating the severity of dengue infection

Abstract

Objective To review the diagnostic test accuracy and predictive value of statistical models in differentiating the severity of dengue infection. Methods Electronic searches were conducted in the Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials, MEDLINE (complete), PubMed and Scopus. Eligible studies to be included in this review were cohort studies with participants confirmed by laboratory test for dengue infection and comparison among the different severity of dengue infection by using statistical models. The methodological quality of the paper was assessed by independent reviewers using QUADAS‐2. Results Twenty‐six studies published from 1994 to 2017 were included. Most diagnostic models produced an accuracy of 75% to 80% except one with 86%. Two models predicting severe dengue according to the WHO 2009 classification have 86% accuracy. Both of these logistic regression models were applied during the first three days of illness, and their sensitivity and specificity were 91–100% and 79.3–86%, respectively. Another model which evaluated the 30‐day mortality of dengue infection had an accuracy of 98.5%. Conclusion Although there are several potential predictive or diagnostic models for dengue infection, their limitations could affect their validity. It is recommended that these models be revalidated in other clinical settings and their methods be improved and standardised in future.

Vector-borne diseases in pregnancy

“…A systematic review of predictive tools found some have accuracy as high as 86% when applied to infection with symptom onset within 3 days and 98% for prediction of 30-day mortality. 41 Virus isolation using mammalian/mosquito cell lines or live mosquitos are definitive but labour intensive and time inefficient, and have largely been replaced by quicker, less expensive tests. 42 These novel investigations, like enzyme-linked immunosorbent assay (ELISA) against NS-1 antigen, real-time polymerase chain reaction (RT-PCR) and serology must be performed and interpreted in the context of clinical presentation, duration of symptoms, history of previous dengue infection and vaccination.…”

“…A systematic review of predictive tools found some have accuracy as high as 86% when applied to infection with symptom onset within 3 days and 98% for prediction of 30-day mortality. 41 …”

Improving dengue diagnosis and case confirmation in children by combining rapid diagnostic tests, clinical, and laboratory variables

“…Due to the shortcomings in implementing diagnostic tests in underdeveloped countries, recent studies in Asia and the Americas have focused on evaluating clinic variables and assigning scores depending on the frequency to establish the diagnosis (12, [21][22][23]47). Although this strategy has been helpful in improving patient care, the validation of these algorithms is a complex process due to the heterogeneity of the study population and the variability in clinical findings according to each stage of the disease (48)(49)(50)(51)(52)(53)(54)(55).…”

Improving dengue case confirmation by combining rapid diagnostic test, clinical, and laboratory variables

“…Due to the shortcomings in implementing laboratory tests in underdeveloped countries, in the last few years, many studies in Asia and the Americas have focused on the evaluation of clinical signs or symptoms and assigning scores depending on the frequency or severity to establish the final diagnosis [12,[21][22][23]51]. Although this strategy has been helpful in the early identification of cases and improving patient care and treatment, the validation of these clinical algorithms is difficult due to the heterogeneity of the study population, the variability in the clinical presentation between countries, and the differences in the signs or symptoms according to the disease stages [52][53][54][55][56][57][58][59].…”