[Clinical characteristics and risk factors analysis of dengue fever incidence in Xishuangbanna, Yunnan Province in 2023].

Objective: To analyze the clinical characteristics of dengue fever patients, summarize the course and characteristics of the disease, and analyze the risk factors that affect the condition.

Methods: Retrospective collection of general information, clinical symptoms, medical history, laboratory tests, prognosis and other clinical data of dengue fever patients that admitted to Jinghong First People's Hospital and severe dengue fever patients at People's Hospital of Xishuangbanna Dai Autonomous Prefecture from June to December 2023 was conducted using a case report form (CRF). According to the diagnostic criteria of the World Health Organization (WHO), patients were divided into dengue fever group, dengue fever with warning signs group, and severe dengue fever group. The differences in clinical data between different groups of patients were analyzed and compared. Binary multiple factor Logistic regression analysis was used to explore the risk factors affecting the severity of dengue fever in patients. Receiver operator characteristic curve (ROC curve) was drawn to analyze the predictive value of prediction models constructed for various risk factors for severe dengue fever. Subgroup analysis was performed on the prognosis of severe dengue fever patients, and the differences in clinical data between two groups of patients with different prognoses were compared. Binary multivariate Logistic regression analysis was used to explore the risk factors affecting the prognosis of severe dengue fever patients. ROC curve was drawn to analyze the predictive value of prediction models constructed for various risk factors on the prognosis of severe dengue fever patients.

Results: A total of 2 264 patients were included, including 499 cases in the dengue fever group, 1 379 cases in the dengue fever with warning signs group, and 386 in the severe dengue fever group (43 deaths and 343 survivors). The most common symptom of dengue fever patients was fever (94.70%), followed by muscle soreness (70.54%), headache (63.12%), fatigue (58.92%), and chills (46.02%). Compared with the dengue fever group and the dengue fever with warning signs group, the ratio of thalassemia and the levels of cardiac troponin (cTnI, cTnT), MB isoenzyme of creatine kinase (CK-MB), and myoglobin were significantly increased in patients with severe dengue fever group, albumin (Alb) was significantly decreased in patients with severe dengue fever group. The levels of cTnT and myoglobin in patients with dengue fever with warning signs group were significantly higher than those in the dengue fever group, and the level of Alb in patients with dengue fever with warning signs group was significantly lower than that in the dengue fever group, the differences were statistically significant (all P < 0.05). Binary multivariate Logistic regression analysis showed that thalassemia [odds ratio (OR) = 6.214, 95% confidence interval (95%CI) was 2.337-16.524, P < 0.001], Alb ≤ 36 g/L (OR = 6.297, 95%CI was 4.270-9.286, P < 0.001), and cTnT levels (OR = 1.008, 95%CI was 1.002-1.015, P = 0.016) were risk factors for severe dengue fever. ROC curve analysis showed that the area under the ROC curve (AUC) for predicting severe dengue fever based on the prediction models constructed for the above risk factors was 0.856, with the best predictive value of 0.067, sensitivity of 67.1%, and specificity of 99.4%. In the subgroup analysis of patients with severe dengue fever, compared with the survival group, the levels of hematocrit (HCT), cTnT, and CK-MB in the death group patients were significantly increased, while the level of Alb was significantly decreased, and the differences were statistically significant. Binary multivariate Logistic regression analysis showed that Alb (OR = 0.839, 95%CI was 0.755-0.932, P = 0.001), HCT (OR = 1.086, 95%CI was 1.010-1.168, P = 0.025), elevated troponin level (OR = 10.119, 95%CI was 2.596-39.440, P < 0.001), and CK-MB (OR = 1.081, 95%CI was 1.032-1.133, P < 0.001) were risk factors for mortality in patients with severe dengue fever. ROC curve analysis showed that the AUC for predicting death in severe dengue fever patients based on the prediction models constructed for the above risk factors was 0.881, with the best predictive value of 0.113, sensitivity of 75.0%, and specificity of 88.9%.

Conclusions: Thalassemia, Alb ≤ 36 g/L, and cTnT level are risk factors for severe dengue fever, while HCT level, Alb level, CK-MB level, and elevated troponin level are risk factors for death in patients with severe dengue fever.