Demographic characteristics, clinical symptoms, biochemical markers and probability of occurrence of severe dengue: A multicenter hospital-based study in Bangladesh

Abstract

Establishing reliable early warning models for severe dengue cases is a high priority to facilitate triage in dengue-endemic areas and optimal use of limited resources. However, few studies have identified the complex interactive relationship between potential risk factors and severe dengue. This research aimed to assess the potential risk factors and detect their high-order combinative effects on severe dengue. A structured questionnaire was used to collect detailed dengue outbreak data from eight representative hospitals in Dhaka, Bangladesh, in 2019. Logistic regression and machine learning models were used to examine the complex effects of demographic characteristics, clinical symptoms, and biochemical markers on severe dengue. A total of 1,090 dengue cases (158 severe and 932 non-severe) were included in this study. Dyspnoea (Odds Ratio [OR] = 2.87, 95% Confidence Interval [CI]: 1.72 to 4.77), plasma leakage (OR = 3.61, 95% CI: 2.12 to 6.15), and hemorrhage (OR = 2.33, 95% CI: 1.46 to 3.73) were positively and significantly associated with the occurrence of severe dengue. Classification and regression tree models showed that the probability of occurrence of severe dengue cases ranged from 7% (age >12.5 years without plasma leakage) to 92.9% (age ≤12.5 years with dyspnoea and plasma leakage). The random forest model indicated that age was the most important factor in predicting severe dengue, followed by education, plasma leakage, platelet, and dyspnoea. The research provides new evidence to identify key risk factors contributing to severe dengue cases, which could be beneficial to clinical doctors to identify and predict the severity of dengue early.

Twenty-two years of dengue outbreaks in Bangladesh: epidemiology, clinical spectrum, serotypes, and future disease risks

“…Moreover, in this work, for generating spatial Maps, publicly available data on dengue cases were obtained from the Directorate GGeneral of Health Services, Bangladesh [ 10 ] and secondary data on dengue cases from outside of Dhaka without travel history (this study was ethically approved by Biomedical Research Foundation, Bangladesh) [ 11 ] and mosquito-related data (this study was ethically approved by icddr,b Bangladesh) [ 12 ] were collected from previous studies.…”

Using Computational Simulations Based on Fuzzy Cognitive Maps to Detect Dengue Complications

“…Several studies have used AI techniques to explore dengue, performing prediction processes [ 17 ], disease classification [ 18 ], outbreak control [ 19 ], and risk factor verification [ 20 ]. Some studies report the use of AI techniques to predict the development of dengue severity using genetic data.…”

“…For example, Hoyos et al [ 24 ] combined artificial neural networks and support vector machines to classify the patient based on dengue severity, achieving 98% accuracy. Yang et al [ 20 ] developed a classification model to find key risk factors in severe dengue cases; the results showed that the probability of the occurrence of severe dengue cases ranged from 7% (age > 12.5 years, without plasma leakage) to 92.9% (age ≤ 12.5 years, with dyspnea and plasma leakage). Chowdhury et al [ 25 ] used the XGBoost classifier with a Shapley dependency plot, finding that low platelet count and elevated hematocrit concentration have greater influences on whether the patient will suffer dengue shock.…”

INFECTION OF HUMAN MACROPHAGES BY Angomonas deanei (Crithidia deanei) AND Herpertomonas roitmani

“…La identificación temprana del dengue grave podría ser beneficiosos para que los médicos clínicos tomen oportunamente las medidas pertinentes y disminuir o anular el mayor riesgo de muerte de los casos graves que no se manejan adecuadamente; los factores más importantes para predecir el dengue grave son: la edad, seguido de la educación, la fuga de plasma, las plaquetas y la disnea. Por lo tanto, encontrar biomarcadores que puedan predecir de manera confiable el desarrollo de dengue grave en individuos sintomáticos es uno de los principales enfoques de los esfuerzos de investigación actuales (YANG et al, 2023). (Butantan-DV) (ORELLANO et al, 2016;ORELLANO et al, 2023;ESPAÑA et al, 2021).…”