| Literature DB >> 30053833 |
Priscila Conrado Guerra Nunes1,2, Ana Maria Bispo de Filippis2, Monique Queiroz da Rocha Lima1, Nieli Rodrigues da Costa Faria2, Fernanda de Bruycker-Nogueira1, Jaqueline Bastos Santos2, Manoela Heringer1, Thaís Chouin-Carneiro1,3, Dinair Couto-Lima3, Bianca de Santis Gonçalves2, Simone Alves Sampaio2, Eliane Saraiva Machado de Araújo2, Juan Camilo Sánchez-Arcila1, Flávia Barreto Dos Santos4, Rita Maria Ribeiro Nogueira2.
Abstract
BACKGROUND: Dengue viruses (DENV) have emerged and reemerged in Brazil in the past 30 years causing explosive epidemics. The disease may range from clinically asymptomatic infections to severe and fatal outcomes. We aimed to describe the epidemiological, clinical and laboratorial aspects of the dengue fatal cases received by a Regional Reference Laboratory, Brazil in 30 years.Entities:
Keywords: Brazil; Dengue; Epidemiology; Fatal cases; Laboratorial diagnosis
Mesh:
Year: 2018 PMID: 30053833 PMCID: PMC6062978 DOI: 10.1186/s12879-018-3255-x
Source DB: PubMed Journal: BMC Infect Dis ISSN: 1471-2334 Impact factor: 3.090
Laboratorial diagnosis on dengue suspected fatal cases (n = 1047) confirmation in Brazil, 1986–2015
| Diagnostic test | Sample | Total (%) | |
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| Acute (< 7 days of illness) Positive/Tested (%) | Convalescent (≥7 days of illness) Positive/Tested (%) | ||
| Virus isolation | 46/768 (6.0) | Not done | 46/768 (6.0) |
| RT-PCR | 142/774 (18.3) | 11/112 (9.82) | 153/886 (17.3) |
| MAC-ELISA | 120/489 (24.5) | 42/113 (37.2) | 162/602 (26.9) |
| IgG-ELISA | 261/345 (75.6) | 57/73 (78.1) | 318/418 (76.0) |
| NS1-ELISA | 120/415 (28.9) | 24/93 (25.8) | 144/508 (28.3) |
Fig. 1Matrix layout representing all combination of laboratorial diagnostic methods performed to study dengue fatal cases. Vertical bars indicate the number of individuals who were tested using each combination of techniques sorted by size. In the bottom of bars, dark circles in the matrix indicate when a combination of techniques was done. The bar chart on the left indicates the frequency of each technique employed
Logistic models with logit links of epidemiological, virological and immunological variables influence on dengue mortality
| Variable (Factor vs.) | Factor | OR (95% CI) | ||
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| Gender |
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| 1.12 (0.88–1.44) | 0.42 |
| Female vs | ||||
| Serotypes |
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| DENV-1 vs. |
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| DENV-2 vs. |
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| Age (years old) |
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| 16–30 vs. |
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| 1.16 (0.79–1.71) | 0.522 |
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| 0–15 vs. |
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| 0.66 (0.43–1.04) | 0.07 |
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| 31–50 vs. |
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| Immune Responses |
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| 0.97 (0.71–1.34) | 0.89 |
| Primary | ||||
To calculate each logistic GLM, Death/Alive outcome was coded as binary variable. Odd ratios (COR), 95% confidence intervals (95%CI) and P-values were calculated using one GLM for each studied variable separately. Values highlighted in bold presented: COR > 1, values of OR contained into the 95%CI range and p-values < 0.05
Fig. 2Signs and symptoms associated with severe dengue reported in the fatal cases (n = 359) analyzed in this study
Logistic models with logit links of association between serotype and age leading to the evolution to a dengue fatal outcome
| Variable Factor (vs.) | Factor | OR (95% CI) |
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| Serotype (Age group compared) | Age (years old) | |||
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| 3.13 (0.95–11.59) | 0.122 |
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| 1.65 (0.50–6.10) | 0.495 | |
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| | 31–50 | 314 (05/309) | 0.53 (0.14–1.92) | 0.52 |
| 51–96 | 162 (7/155) | 1.47 (0.46–5.07) | 0.32 | |
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| | 51–96 | 162 (7/155) | 2.79 (0.88–9.56) | 0.08 |
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| 1.07 (0.56–2.12) | 0.864 | |
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| 0.85 (0.44–1.62) | 0.62 | |
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| 0.31 (0.11–0.73) | 0.037 |
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| 0.99 (0.56–1.77) | 0.997 | |
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| 1.66 (0.41–6.75) | 0.54 |
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| 1.46 (0.44–5.40) | 0.609 | |
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| 0.88 (0.21–4.34) | 0.86 |
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| 3.26 (0.97–14.78) | 0.08 | |
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To calculate each logistic GLM, Death/Alive outcome was coded as binary variable. Odd ratios (COR), 95% confidence intervals (95%CI) and p-values were calculated using one GLM for each studied variable separately. Values highlighted in bold presented: OR > 1, values of OR contained into the 95%CI range and p-values < 0.05
Fig. 3Dengue fatal cases (n = 222) immune response occurred during epidemics in Brazil
Logistic models with logit links of association of dengue serotype and Age with immune response that lead to the evolution to a dengue fatal outcome
| Variable Factor (vs.) | Factor | OR (95% CI) | ||
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| Serotype |
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| ‘n’ Primary Responses | ||||
| DENV-1 |
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| 0.38 (0.14–0.96) | 0.095 |
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| DENV-2 |
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| 0.83 (0.49–1.41) | 0.558 |
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| DENV-3 |
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| 1.04 (0.60–1.79) | 0.904 |
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| DENV-4 |
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| – | – |
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| Age |
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| (years old) ‘n’ Primary Responses | ||||
| 0–15 |
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| 16–30 |
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| 0.6 (0.28–1.26) | 0.267 |
| 31–50 |
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| 0.95 (0.52–1.76) | 0.89 |
| 51–96 |
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| 1.83 (0.89–3.83) | 0.172 |
To calculate each logistic GLM, Death/Alive outcome was coded as binary variable. Odd ratios (COR), 95% confidence intervals (95%CI) and p-values were calculated using one GLM for each studied variable separately. Values highlighted in bold presented: OR > 1, values of OR contained into the 95%CI range and p-values < 0.05
Fig. 4Dengue infecting serotypes identified in the fatal cases (n = 155) occurred during epidemics in Brazil
Fig. 5The relationship between age and immune response of dengue fatal cases (n = 205) analyzed in Brazil, 1986–2015
Fig. 6Age distribution of dengue fatal cases (n = 164) occurred during epidemics in Brazil