BackgroundTainan experienced the most severe dengue epidemic in Taiwan in 2015. This study investigates the association between the signs and symptoms at the time of reporting with the adverse dengue prognoses.MethodsA descriptive study was conducted using secondary data from the Dengue Disease Reporting System in Tainan, Taiwan, between January 1 and December 31, 2015. A multivariate stepwise logistic regression was used to identify the risk factors for the adverse prognoses: ICU admissions and mortality.ResultsThere were 22,777 laboratory-confirmed reported cases (mean age 45.6 ± 21.2 years), of which 3.7% were admitted to intensive care units (ICU), and 0.8% were fatal. The most common symptoms were fever (92.8%), myalgia (26.6%), and headache (22.4%). The prevalence of respiratory distress, altered consciousness, shock, bleeding, and thrombocytopenia increased with age. The multivariate analysis indicated that being in 65–89 years old age group [Adjusted Odds Ratio (aOR):4.95], or the 90 years old and above age group (aOR: 9.06), and presenting with shock (aOR: 8.90) and respiratory distress (aOR: 5.31) were significantly associated with the risk of ICU admission. While old age (aOR: 1.11), respiratory distress (aOR: 9.66), altered consciousness (aOR: 7.06), and thrombocytopenia (aOR: 2.55) were significantly associated with the risk of mortality.ConclusionsDengue patients older than 65 and those with severe and non-specific signs and symptoms at the time of reporting were at a higher risk of ICU admission and mortality. First-line healthcare providers need to be aware of the varied presentations between the different age groups to allow early diagnosis and in-time management, which would prevent ICU admissions and fatalities in dengue patients.

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BackgroundHepatic dysfunction and coagulopathy are common in acute dengue illness. We analyzed the trajectories of the above parameters in the survivors and fatal patients in the outbreak in Tainan, 2015.MethodsA retrospective study was conducted using data from a tertiary hospital between January and December 2015. Multilevel modeling (MLM) was used to identify the changes in aminotransferase (AST), alanine aminotransferase (ALT), activated partial thromboplastin time (aPTT), and platelet counts from Day 0 to Day 7 of the onset of dengue infection. The machine-learning algorithm was used by purity measure assumption to calculate the accuracy of serum transaminases and coagulation variables to discriminate between the fatal and survival groups.ResultsThere were 4,069 dengue patients, of which 0.9% died in one week after illness onset (i.e., early mortality). Case fatality rate was the highest for those aged ≥70 years. Both AST and ALT values of the fatal group were significantly higher than those of the survivor group from Day 3 (AST median, 624 U/L vs. 60 U/L, p < 0.001; ALT median, 116 U/L vs. 29 U/L, p = 0.01) of illness onset and peaked on Day 6 (AST median, 9805 U/L vs. 90 U/L, p < 0.001; ALT median, 1504 U/L vs. 49 U/L, p < 0.001). AST ≥ 203 U/L, ALT ≥ 55 U/L, AST2/ALT criteria ≥337.35, or AST/platelet count ratio index (APRI) ≥ 19.18 on Day 3 of dengue infection had a high true positive rate, 90%, 78%, 100%, or 100%, respectively, of early mortality. The platelet counts of the fatal group declined significantly than those of the survivor group since Day 3 of illness onset (median, 19 x103/μl vs. 91 x103/μl, p < 0.01), and aPTT values of the fatal group significantly prolonged longer since Day 5 (median, 68.7 seconds vs. 40.1 seconds, p < 0.001).ConclusionsAST, ALT, and platelet counts should be monitored closely from Day 0 to Day 3 of dengue infection, and aPTT be followed up on Day 5 of infection to identify the individuals at risk for early mortality.

Although dengue is currently not endemic in Taiwan, physicians need to be aware of the risk of transfusion-transmitted DENV infection. Our results suggest that screening measures to ensure blood safety should be evaluated and implemented during dengue epidemics even in nonendemic areas. Timely estimation of daily asymptomatic viremia prevalence by districts can help to select high-risk areas for such measures and to evaluate cost-effectiveness.

Background Variations in body temperature are highly informative during an illness. To date, there are not many adequate studies that have investigated the feasibility of a wearable wrist device for the continuous monitoring of body surface temperatures in humans. Objective The objective of this study was to validate the performance of HEARThermo, an innovative wearable device, which was developed to continuously monitor the body surface temperature in humans. Methods We implemented a multi-method research design in this study, which included 2 validation studies—one in the laboratory and one with human subjects. In validation study I, we evaluated the test-retest reliability of HEARThermo in the laboratory to measure the temperature and to correct the values recorded by each HEARThermo by using linear regression models. We conducted validation study II on human subjects who wore HEARThermo for the measurement of their body surface temperatures. Additionally, we compared the HEARThermo temperature recordings with those recorded by the infrared skin thermometer simultaneously. We used intraclass correlation coefficients (ICCs) and Bland-Altman plots to analyze the criterion validity and agreement between the 2 measurement tools. Results A total of 66 participants (age range, 10-77 years) were recruited, and 152,881 completed data were analyzed in this study. The 2 validation studies in the laboratory and on human skin indicated that HEARThermo showed a good test-retest reliability (ICC 0.96-0.98) and adequate criterion validity with the infrared skin thermometer at room temperatures of 20°C-27.9°C (ICC 0.72, P<.001). The corrected measurement bias averaged –0.02°C, which was calibrated using a water bath ranging in temperature from 16°C to 40°C. The values of each HEARThermo improved by the regression models were not significantly different from the temperature of the water bath (P=.19). Bland-Altman plots showed no visualized systematic bias. HEARThermo had a bias of 1.51°C with a 95% limit of agreement between –1.34°C and 4.35°C. Conclusions The findings of our study show the validation of HEARThermo for the continuous monitoring of body surface temperatures in humans.