METHOD: This is a retrospective cohort study of confirmed severe dengue patients that were admitted in 2014 to Hospital Kuala Lumpur. Data on baseline characteristics, clinical parameters, and laboratory findings at diagnosis of severe dengue were collected. The outcome of interest is death among patients diagnosed with severe dengue.
RESULTS: There were 199 patients with severe dengue included in the study. Multivariate analysis found lethargy, OR 3.84 (95% CI 1.23-12.03); bleeding, OR 8.88 (95% CI 2.91-27.15); pulse rate, OR 1.04 (95% CI 1.01-1.07); serum bicarbonate, OR 0.79 (95% CI 0.70-0.89) and serum lactate OR 1.27 (95% CI 1.09-1.47), to be statistically significant predictors of death. The regression equation to our model with the highest AUROC, 83.5 (95% CI 72.4-94.6), is: Log odds of death amongst severe dengue cases = - 1.021 - 0.220(Serum bicarbonate) + 0.001(ALT) + 0.067(Age) - 0.190(Gender).
CONCLUSION: This study showed that a large proportion of severe dengue occurred early, whilst patients were still febrile. The best prediction model to predict death at recognition of severe dengue is a model that incorporates serum bicarbonate and ALT levels.
METHODS: A national telephone survey was carried out with 2,512 individuals of the Malaysian public aged 18-60 years old. Individuals were contacted by random digit dialling covering the whole of Malaysia from February 2012 to June 2013.
RESULTS: From 2,512 participants, 6.1 % reported to have heard of the availability of the dengue home test kit and of these, 44.8 % expressed their intention to use the test kit if it was available. Multivariate logistic regressions indicated that participants with primary (OR: 0.65; 95 % CI: 0.43-0.89; p = 0.02, vs. tertiary educational level) and secondary educational levels (OR: 0.73; 95 % CI: 0.57-0.90; p = 0.01, vs. tertiary educational level) were less likely than participants with a tertiary educational level to use a home self-testing dengue kit for dengue if the kit was available. Participants with lower perceived barriers to dengue prevention (level of barriers 0-5) were less likely (OR: 0.67, 95 % CI: 0.53-0.85, p
METHODS: In-depth individual interviews with thematic saturation were conducted between May and July 2018. The data was analyzed using thematic analysis.
RESULTS: Based on expert opinion, diagnosis of severe dengue is challenging as it depends on astute clinical interpretation of non-dengue-specific clinical and laboratory findings. A specific test that detects impending manifestation of severe dengue could 1) overcome failure in identifying severe disease for referral or admission, 2) facilitate timely and appropriate management of plasma leakage and bleeding, 3) overcome the lack of clinical expertise and laboratory diagnosis in rural health settings. The most important feature of any diagnostics for severe dengue is the point-of-care (POC) format where it can be performed at or near the bedside.
CONCLUSION: The development of diagnostics to detect impending severe dengue is warranted to reduce the morbidity and mortality rates of dengue infection and it should be prioritized.
METHODS: This was a retrospective cohort study of confirmed dengue patients who were warded in Kuala Lumpur Hospital between December 2014 and January 2015. CK, AST, ALT, hematocrit, platelet count, WBC and serum albumin were taken upon ward admission and repeated at timed intervals. Composite indices based on admission AST and ALT were analyzed. Correlation coefficients and coefficients of determination were computed.
RESULTS: Among the 365 cases reviewed, twenty-two (6%) patients had severe dengue. AST and ALT were found to be good at identification of severe dengue. The AST2/ALT composite index was the most accurate (AUC 0.83; 95% CI 0.73 - 0.93). Optimal cutoff was 402 with a sensitivity of 59.1% (95% CI: 36.4 - 79.3%) and specificity of 92.4% (95% CI: 89.1 - 95.0%). Modified cutoff of 653 had a sensitivity of 40.9% (95% CI: 20.7 - 63.7%) and specificity of 97.4% (95% CI: 95.1 - 98.8%). Our analyses also suggested that several underlying biological processes represented by biomarkers tested were unrelated despite occurring in the same disease entity. Also, markers of plasma leakage were discordant and AST was likely hepatic in origin.
CONCLUSIONS: The composite index AST2/ALT may be used as a marker for identification of severe dengue based on admission AST and ALT, with two choices of cutoff values, 402 and 653. AST is most likely of liver origin and CK does not provide additional value.
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.
METHOD: Two hundred sixty eight serum specimens collected from patients that were diagnosed for dengue fever were confirmed for dengue virus serotyping by real-time polymerase chain reaction. Clinical, laboratory and demographic data were extracted from the hospital database to identify patients with confirmed leptospirosis infection among the dengue patients. Thus, frequency of co-infection was calculated and association of the dataset with dengue-leptospirosis co-infection was statistically determined.
RESULTS: The frequency of dengue co-infection with leptospirosis was 4.1%. Male has higher preponderance of developing the co-infection and end result of shock as clinical symptom is more likely present among co-infected cases. It is also noteworthy that, DENV 1 is the common dengue serotype among all cases identified as dengue-leptospirosis co-infection in this study.
CONCLUSION: The increasing incidence of leptospirosis among dengue infected patients has posed the need to precisely identify the presence of co-infection for the betterment of treatment without mistakenly ruling out either one of them. Thus, anticipating the possible clinical symptoms and laboratory results of dengue-leptospirosis co-infection is essential.