国际公共卫生与安全杂志

Dengue Severity Risk Factors in New Caledonia - Design of Predictive Tool Usable By Doctors during the First Consultation

Abstract

Forfait C*, Marois I, Aubert D, Valiame A, Gourinat AC, Descloux E, Hartmann E and Laumond S

Objectives: In New Caledonia (NC), Dengue circulation was detected every year since last decade. The 2017 epidemic have affected 4,379 people with 11.5% of hospital admission and 15 deaths. The aim of this work is to study the risk factors of severe dengue during the 2017 outbreak and to develop a predictive tool, based on a model, usable by doctors during the first consultation to early assess the risk for a dengue patient to progress to a severe form.

Study design: This is a non-interventional retrospective study in which a cohort of hospitalized and non-hospitalized cases, positive for dengue virus infection by qRTPCR was documented.

Methods: Patients were classified in severe or non-severe dengue. We explored the association of dengue severity to patients’ characteristics, symptoms at the first consultation, dengue serotype and previous Zika and dengue infection. A predictive model of the severity usable at first consultation was built using a multivariate analysis and a cross-validation procedure.

Results: A total of 771 dengue cases were studied, with 134 patients who developed severe dengue fever. The dengue serotype does not appear to influence the severity of the infection, whereas, an anterior dengue seems to be significantly related to a severe form. We created two predictive models based on patient characteristics and clinical signs, one for "women" and one for "men" because of the sex and age class interaction. For both models, the variables were: age, selfdeclared ethnicity, alert signs (mucosal bleedizg, clinical liquid accumulation, abdominal pain, lethargy or anxiety) and for women model added variables were arterial hypertension, platelet aggregation inhibitor and anticoagulants treatments. The average and median AUC values for both models are > 0.80 which shows a fairly good model quality; moreover high negative predictive values (> 95%) indicate that models are quite protective.

Conclusion: This study described severity and risk factors for both hospitalized and non-hospitalized patients. The developed models can be used at the first consultation and doctors will be able to early assess the risk for dengue patient to progress to a severe form and increased surveillance with possible hospitalization.