Comorbidities increase in-hospital mortality in dengue patients in Brazil

Werneck, Guilherme Loureiro; Macías, Alejandro E.; Mascareñas, César; Coudeville, Laurent; Morley, David; Recamier, Vincent; Guergova-Kuras, Mariana; Puentes-Rosas, Esteban; Baurin, Nicolas; Toh, Myew–Ling

doi:10.1590/0074-02760180082

Cited by 31 publications

(24 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Over the past few years, several lines of evidence have supported the notion that cardiovascular disease, stroke, diabetes, respiratory diseases and renal disorders may contribute, together with old age, to severe dengue disease [19–21]. Studies on West Nile virus [22], Japanese encephalitis virus [23] infections, and responses to Yellow fever virus vaccination [24], have also supported the pathogenic role of chronic comorbidities in the prognosis of infections.…”

Section: Discussionmentioning

confidence: 99%

Preexisting chronic conditions for fatal outcome among SFTS patients: An observational Cohort Study

et al. 2019

View full text Add to dashboard Cite

Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease that is caused by a novel bunyavirus SFTSV. Currently our knowledge of the host-related factors that influence the pathogenesis of disease is inadequate to allow prediction of fatal outcome. Here we conducted a prospective study of the largest database on the SFTS patients, to identify the presence of comorbidities in SFTS, and estimate their effect on the fatal outcome. Among 2096 patients eligible for inclusion, we identified nine kinds of comorbidities, from which hyperlipidemia (12.2%; 95% CI: 10.8%–13.6%), hypertension (11.0%; 95% CI: 9.6%–12.3%), chronic viral hepatitis (CVH) (9.3%; 95% CI: 8.1%–10.5%), and diabetes mellitus (DM) (6.8%; 95% CI: 5.7%–7.9%) were prevalent. Higher risk of death was found in patients with DM (adjusted OR = 2.304; 95% CI: 1.520–3.492; P<0.001), CVH (adjusted OR = 1.551; 95% CI: 1.053–2.285; P = 0.026) and chronic obstructive pulmonary diseases (COPD) (adjusted OR = 2.170; 95% CI: 1.215–3.872; P = 0.009) after adjusting for age, sex, delay from disease onset to admission and treatment regimens. When analyzing the comorbidities separately, we found that the high serum glucose could augment diseases severity. Compared to the group with max glucose < 7.0 mmol/L, patients with glucose between 7.0–11.1 mmol/L and glucose ≥11.1 mmol/L conferred higher death risk, with the adjusted OR to be 1.467 (95% CI: 1.081–1.989; P = 0.014) and 3.443 (95% CI: 2.427–4.884; P<0.001). Insulin therapy could effectively reduce the risk of severe outcome in DM patients with the adjusted OR 0.146 (95% CI: 0.058–0.365; P<0.001). For CVH patients, severe damage of liver and prolongation of blood coagulation time, as well as high prevalence of bleeding phenotype were observed. These data supported the provocative hypothesis that treating SFTS related complications can attain potentially beneficial effects on SFTS.

show abstract

Section: Discussionmentioning

confidence: 99%

Preexisting chronic conditions for fatal outcome among SFTS patients: An observational Cohort Study

et al. 2019

View full text Add to dashboard Cite

show abstract

“…6,28 While there are other studies on death in dengue, they examined the association with death in unselected dengue cases and were not prediction modelling studies. [39][40][41][42][43][44][45][46] Our study is the first modelling study, based on the latest and widely adopted WHO 2009 classification scheme, to model prediction of death in severe dengue cases. As mentioned above, there have been many studies that built models for identification of dengue and stratification of severity in dengue.…”

Section: Resultsmentioning

confidence: 99%

Multivariable prediction model for predicting deaths in severe dengue cases

Zaid

Leong

et al. 2019

Preprint

View full text Add to dashboard Cite

Background. Many predictive models have been developed to predict an outbreak, identify and stratify dengue but none has predicted death in severe dengue cases. To build a predictive model for deaths in severe dengue, a multicentre retrospective cohort study was conducted. Methods. Patients with severe dengue based on the World Health Organisation (WHO) 2009 classification were studied. Demographic, clinical and laboratory data were collected at diagnosis of severe dengue. Penalised regression was used for variable selection and model-building. Ten-fold cross-validation with 1000 repeats were performed for internal validation. Results. A cohort of 786 severe dengue cases, including 35 deaths, was analysed. Our model that predicts death in severe dengue cases comprises eight independent predictors: persistent diarrhoea, body mass index, respiratory rate, platelet count, aspartate transaminase, serum bicarbonate, serum lactate and serum albumin. The area under the receiver operating characteristic curve is 89·6% with a sensitivity of 99·6%, specificity of 23·6%, positive predictive value of 96·6%, negative predictive value of 71·1%, positive likelihood ratio 1·45 and negative likelihood ratio 0·01. We also found that the proportion of patients that were in the febrile phase at diagnosis of severe dengue for the overall cohort, decompensated and compensated shock were 74·3%, 73% and 75·4%, respectively. Conclusions. We developed a high-performance dengue death prediction model comprising clinical and laboratory data, and deployed an open-access web-based tool (www.saifulsafuan.com/REPROSED2017E2) for any centre to utilise for local validation. We additionally found that a large majority of patients developed severe dengue during the febrile phase. Keywords: Dengue; severe; model; predict; deaths; phase.

show abstract

“…Furthermore, there was a 1.7-fold higher prevalence of severe dengue associated with comorbidities (8.4%, p<0.001), compared to without comorbidities (4.8%). 16 The study by Chen et al, concluded that dengue patients with diabetes tended to have more severe thrombocytopenia and were more likely to have DHF/DSS. 17 Pang et al, found that ICU patients with severe Dengue were more likely to be diabetic(p=0.031)and similar findings are noted in other studies.…”

Section: Discussionmentioning

confidence: 99%

Effect of co morbidities on the clinical outcome of Dengue fever

2019

View full text Add to dashboard Cite

Background: Dengue is the most rapidly spreading mosquito-borne viral disease in the world. A number of Dengue Haemorrhagic Fever (DHF) risk factors had been suggested. However, these risk factors may not be generalized to all populations and epidemics for screening and clinical management of patients at risk of developing DHF/ Dengue shock syndrome (DSS).Methods: A hospital based prospective case control study was done by taking 40 cases each of dengue fever with diabetes mellitus, hypertension, diabetes and hypertension and 30 cases of dengue with asthma/COPD and these patients were compared with controls of 100 patients with dengue fever but no comorbidities. All patients had Dengue serology NS1 or IgM positive.Results: Patients admitted with dengue fever with comorbidities had increased duration of hospitalization with P value of 0.012. The clinical outcome of the 250 patients. In the subgroup of dengue fever patients with DM and Dengue fever with DM and HTN, they were noted to have a 2.69 and 3.06 times increased risk effect of DHF.Conclusions: Dengue fever with DM or DM with HTN have a higher risk of developing DHF when compared with patients with dengue fever with no comorbidities. This finding helps us in triaging patients with comorbidities who develop dengue fever for specialized care and closer clinical monitoring.

show abstract

Comorbidities increase in-hospital mortality in dengue patients in Brazil

Cited by 31 publications

References 22 publications

Preexisting chronic conditions for fatal outcome among SFTS patients: An observational Cohort Study

Preexisting chronic conditions for fatal outcome among SFTS patients: An observational Cohort Study

Multivariable prediction model for predicting deaths in severe dengue cases

Effect of co morbidities on the clinical outcome of Dengue fever

Contact Info

Product

Resources

About