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      Comorbidities and in-hospital death of viral pneumonia adults admitted to SUS (2002–2015)

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          ABSTRACT

          OBJECTIVE

          To identify demographic and clinical characteristics of adult patients hospitalized in the Brazilian Unified Health System (SUS) due to viral pneumonia and investigate the association between some comorbidities and death during hospitalization.

          METHODS

          This retrospective cohort study was conducted with secondary data of adults admitted to SUS due to viral pneumonia between 2002 and 2015. Patient profile was characterized based on demographic and clinical variables. The association between the ten Elixhauser comorbidities and in-hospital death was investigated using Poisson regression models with robust standard errors. Results were quantified as incidence rate ratio (IRR) with 95% confidence intervals (CI), and we built five models using successive inclusion of variables blocks.

          RESULTS

          Hospital admissions for viral pneumonias decreased throughout the study period, and it was observed that 5.8% of hospitalized patients had an in-hospital death. We observed significant differences in demographic and clinical characteristics by comparing individuals who died during hospitalization with those who did not, with the occurrence of one or more comorbidities being more expressive among patients who died. Although not considered risk factors for in-hospital death, chronic pulmonary disease and congestive heart failure were the most common comorbidities. Conversely, IRR for in-hospital death increased with other neurological disorders, diabetes, cancer, obesity, and especially with HIV/AIDS.

          CONCLUSIONS

          Individuals presenting with pulmonary and cardiovascular diseases require proper attention during hospitalization, as well as those with other neurological diseases, diabetes, cancer, obesity, and especially HIV/AIDS. Understanding the influence of chronic diseases on viral infections may support the healthcare system in achieving better outcomes.

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          Most cited references36

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          Prevalence of comorbidities and its effects in patients infected with SARS-CoV-2: a systematic review and meta-analysis

          Highlights • COVID -19 cases are now confirmed in multiple countries. • Assessed the prevalence of comorbidities in infected patients. • Comorbidities are risk factors for severe compared with non-severe patients. • Help the health sector guide vulnerable populations and assess the risk of deterioration.
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            Comorbidity Measures for Use with Administrative Data

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              Alternatives for logistic regression in cross-sectional studies: an empirical comparison of models that directly estimate the prevalence ratio

              Background Cross-sectional studies with binary outcomes analyzed by logistic regression are frequent in the epidemiological literature. However, the odds ratio can importantly overestimate the prevalence ratio, the measure of choice in these studies. Also, controlling for confounding is not equivalent for the two measures. In this paper we explore alternatives for modeling data of such studies with techniques that directly estimate the prevalence ratio. Methods We compared Cox regression with constant time at risk, Poisson regression and log-binomial regression against the standard Mantel-Haenszel estimators. Models with robust variance estimators in Cox and Poisson regressions and variance corrected by the scale parameter in Poisson regression were also evaluated. Results Three outcomes, from a cross-sectional study carried out in Pelotas, Brazil, with different levels of prevalence were explored: weight-for-age deficit (4%), asthma (31%) and mother in a paid job (52%). Unadjusted Cox/Poisson regression and Poisson regression with scale parameter adjusted by deviance performed worst in terms of interval estimates. Poisson regression with scale parameter adjusted by χ2 showed variable performance depending on the outcome prevalence. Cox/Poisson regression with robust variance, and log-binomial regression performed equally well when the model was correctly specified. Conclusions Cox or Poisson regression with robust variance and log-binomial regression provide correct estimates and are a better alternative for the analysis of cross-sectional studies with binary outcomes than logistic regression, since the prevalence ratio is more interpretable and easier to communicate to non-specialists than the odds ratio. However, precautions are needed to avoid estimation problems in specific situations.
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                Author and article information

                Journal
                Rev Saude Publica
                Rev Saude Publica
                rsp
                Revista de Saúde Pública
                Faculdade de Saúde Pública da Universidade de São Paulo
                0034-8910
                1518-8787
                05 July 2021
                2021
                : 55
                : e43
                Affiliations
                [I ] orgnameUniversidade Federal de Minas Gerais orgdiv1Faculdade de Medicina orgdiv2Programa de Pós-Graduação em Saúde Pública Belo Horizonte MG Brasil originalUniversidade Federal de Minas Gerais. Faculdade de Medicina. Programa de Pós-Graduação em Saúde Pública. Belo Horizonte, MG, Brasil
                [II ] orgnameUniversidade Federal de Minas Gerais orgdiv1Instituto de Ciências Exatas orgdiv2Departamento de Estatística Belo Horizonte MG Brasil originalUniversidade Federal de Minas Gerais. Instituto de Ciências Exatas. Departamento de Estatística. Belo Horizonte, MG, Brasil
                [III ] orgnameUniversidade Federal de Minas Gerais orgdiv1Faculdade de Farmácia orgdiv2Departamento de Farmácia Social Belo Horizonte MG Brasil originalUniversidade Federal de Minas Gerais. Faculdade de Farmácia. Departamento de Farmácia Social. Belo Horizonte, MG, Brasil
                [IV ] orgnameUniversidade Federal de Minas Gerais orgdiv1Faculdade de Medicina orgdiv2Departamento de Medicina Preventiva e Social Belo Horizonte MG Brasil originalUniversidade Federal de Minas Gerais. Faculdade de Medicina. Departamento de Medicina Preventiva e Social. Belo Horizonte, MG, Brasil
                Author notes
                Correspondence: Thais Piazza Av. Professor Alfredo Balena, 190 30130-100 - Santa Efigênia Belo Horizonte, MG, Brasil E-mail: piazzathais@ 123456gmail.com

                Authors’ Contributions: Study design and planning: TP, DPM, HAR, IAR, MLC. Data collection: DPM, HAR, APL. Data analysis and interpretation: TP, DPM, HAR, APL, IAR, MACS, MLC. Manuscript drafting: TP, DPM. Manuscript review: HAR, APL, IAR, MAAC, AGG, MLC. Approval of the final version: TP, DPM, HAR, APL, IAR, MACS, AAG, MLC. Public responsibility for the content of the article: TP, DPM, HAR, APL, IAR, MACS, AAG, MLC.

                Conflict of Interests: The authors declare no conflict of interest.

                Author information
                https://orcid.org/0000-0001-9385-7609
                https://orcid.org/0000-0002-3109-1342
                https://orcid.org/0000-0001-6433-0568
                https://orcid.org/0000-0001-7654-1063
                https://orcid.org/0000-0001-7199-8590
                https://orcid.org/0000-0002-5228-8822
                https://orcid.org/0000-0001-5256-0577
                https://orcid.org/0000-0001-5622-567X
                Article
                00236
                10.11606/s1518-8787.2021055003109
                8275093
                34259785
                abd24eb0-ce8d-4537-83b1-5d6ad4a17027

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 2 September 2020
                : 11 November 2020
                Page count
                Figures: 1, Tables: 3, Equations: 0, References: 30
                Funding
                Funded by: Conselho Nacional de Desenvolvimento Científico e Tecnológico
                Award ID: 306030/2018-7
                Funded by: Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
                Award ID: 001
                Funded by: Fundação de Amparo à Pesquisa do Estado de Minas Gerais
                Award ID: CDS - PPM-00369-17
                Funding: This study was funded by Conselho Nacional de Desenvolvimento Científico e Tecnológico – CNPq [National Council of Technological and Scientific Development], Brazil (http://www.cnpq. br/web/guest/geral), Grant Number: 306030/2018-7; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (Capes) - Finance code 001; and Fundação de Amparo à Pesquisa do Estado de Minas Gerais – FAPEMIG [The Minas Gerais State Research Foundation], Brazil (http://www.fapemig.br/), Grant Number: (CDS - PPM-00369-17).
                Categories
                Original Article

                pneumonia, viral, epidemiology,risk factors,comorbidity,hospitalization,hospital mortality

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