Development of a bedside score to predict dengue severity

BMC Infectious Diseases

Carole Forfait¹  Sylvie Laumond¹  Jean-Paul Grangeon¹  Daina Aubert¹  Anabelle Valiame¹  Myrielle Dupont-Rouzeyrol²  Catherine Inizan²  Arnaud Tarantola³  Cécile Cazorla⁴  Audrey Merlet⁴  Ingrid Marois⁴  Elodie Descloux⁴  Elise Klement-Frutos⁵  Emilie Barsac⁶  Ann-Claire Gourinat⁶ 

[1] Health Authorities (DASS), Noumea, New Caledonia;Institut Pasteur in New Caledonia, URE Dengue and Arboviruses, Institut Pasteur International Network, Noumea, New Caledonia;Institut Pasteur in New Caledonia, URE Epidemiology, Institut Pasteur International Network, Noumea, New Caledonia;Internal Medicine and Infectious Diseases Department, Territorial Hospital Center (CHT), Dumbea, New Caledonia;Internal Medicine and Infectious Diseases Department, Territorial Hospital Center (CHT), Dumbea, New Caledonia;Hôpitaux Universitaires Pitie Salpetriere-Charles Foix, Paris, France;Microbiology Laboratory, Territorial Hospital Center (CHT), Dumbea, New Caledonia;

关键词: Dengue;    Arboviruses;    Severity score;    Operational tool;    Hospital triage;    Pacific;   

DOI  :  10.1186/s12879-021-06146-z

来源: Springer

【 摘 要 】

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.

【 授权许可】

CC BY