Abstract
BackgroundIn 2017, New Caledonia experienced an outbreak of severe dengue causing high hospital burden (4379 cases, 416 hospital admissions, 15 deaths). We decided to build a local operational model predictive of dengue severity, which was needed to ease the healthcare circuit.MethodsWe retrospectively analyzed clinical and biological parameters associated with severe dengue in the cohort of patients hospitalized at the Territorial Hospital between January and July 2017 with confirmed dengue, in order to elaborate a comprehensive patient’s score. Patients were compared in univariate and multivariate analyses. Predictive models for severity were built using a descending step-wise method.ResultsOut of 383 included patients, 130 (34%) developed severe dengue and 13 (3.4%) died. Major risk factors identified in univariate analysis were: age, comorbidities, presence of at least one alert sign, platelets count < 30 × 109/L, prothrombin time < 60%, AST and/or ALT > 10 N, and previous dengue infection. Severity was not influenced by the infecting dengue serotype nor by previous Zika infection.Two models to predict dengue severity were built according to sex. Best models for females and males had respectively a median Area Under the Curve = 0.80 and 0.88, a sensitivity = 84.5 and 84.5%, a specificity = 78.6 and 95.5%, a positive predictive value = 63.3 and 92.9%, a negative predictive value = 92.8 and 91.3%. Models were secondarily validated on 130 patients hospitalized for dengue in 2018.ConclusionWe built robust and efficient models to calculate a bedside score able to predict dengue severity in our setting. We propose the spreadsheet for dengue severity score calculations to health practitioners facing dengue outbreaks of enhanced severity in order to improve patients’ medical management and hospitalization flow.
Highlights
In 2017, New Caledonia experienced an outbreak of severe dengue causing high hospital burden (4379 cases, 416 hospital admissions, 15 deaths)
We confirm that the World Health Organization (WHO) 2009 criteria to evaluate the severity of dengue infection are applicable in New Caledonia (NC), with a Positive Predictive Value for the presence of at least one warning sign of 93% and a Negative Predictive Value (NPV) of 89.3% on our 2017 dataset
The criteria of our models rely on demographic, behavioral or biomedical (AST, platelet count) data or data linked to a preexisting medical condition, which are available early in the development of dengue, as soon as hospital admission
Summary
In 2017, New Caledonia experienced an outbreak of severe dengue causing high hospital burden (4379 cases, 416 hospital admissions, 15 deaths). Dengue fever is the most prevalent human arbovirosis and a major public health issue in tropical and subtropical countries with epidemic outbreaks [1, 2]. There is a lack of specific treatments, vector control measures regularly fail to prevent epidemics and safe preventive dengue vaccines are not widely available [3,4,5]. Dengue has a wide spectrum of clinical presentations usually starting by an abrupt onset of fever, malaise, skin rash, headache, anorexia/vomiting, diarrhea, and abdominal pain, often with unpredictable clinical evolution. Warning signs of severe dengue include persisting vomiting, abdominal pain, lethargy/anxiety, mucosal bleeding, liquid accumulation, hepatomegaly, and rapid hematocrit increase concurrent with a platelet count drop [4]
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