Joelma Greicy Fernandes Lira, Ricardo Alves de Olinda, Gustavo Correia Basto da Silva, Luzibênia Leal de Oliveira, Raimunda Leite de Alencar Neta, Nívea Vilar Cardoso, Fernando Adami, Laércio da Silva Paiva
{"title":"巴西重症监护病房 COVID-19 患者的社会人口学特征和风险因素:一项横断面研究。","authors":"Joelma Greicy Fernandes Lira, Ricardo Alves de Olinda, Gustavo Correia Basto da Silva, Luzibênia Leal de Oliveira, Raimunda Leite de Alencar Neta, Nívea Vilar Cardoso, Fernando Adami, Laércio da Silva Paiva","doi":"10.1155/2024/2927407","DOIUrl":null,"url":null,"abstract":"<p><p>This is a cross-sectional study, with secondary data from Brazilian hospitals in the state of Paraíba, between January 2021 and January 2022. The evolution of clinical cases configured the dependent variable (cure or death), while the predictive variables were sociodemographic data, risk factors, use of ventilatory support, and vaccination against COVID-19. With the help of R software, the following tests were used: chi-square, Pearson's chi-square, and Fisher's exact adherence. Simple logistic regression models were constructed, and odds ratios (95% CI) were estimated using the LR test and Wald test. 7373 cases were reported, with a mean age of 58.1. Of the reported cases, 63.8% died. The most frequent sociodemographic profile included male people, of mixed race, with less than eight years of schooling. Chronic cardiovascular disease (OR 1.28; 95% CI: 1.13-1.45), diabetes (OR 1.41; 95% CI: 1.24-1.61), lung disease (OR 1.52; 95% CI: 1.11-2.09), and the use of invasive ventilatory support (OR 14.1; 95% CI: 10.56-18.59) were all associated with increased mortality. Nonvaccination was associated with a decreased risk of death (OR 0.74; 95% CI: 0.65-0.84). Male patients, nonwhite, and those with low education were more likely to have a worse clinical outcome. The risk factors studied were related to deaths, and those who did not require ventilatory support were related to cure.</p>","PeriodicalId":22985,"journal":{"name":"The Scientific World Journal","volume":"2024 ","pages":"2927407"},"PeriodicalIF":0.0000,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11262879/pdf/","citationCount":"0","resultStr":"{\"title\":\"Sociodemographic Profile and Risk Factors for the Evolution of Patients with COVID-19 in ICUs in Brazil: A Cross-Sectional Study.\",\"authors\":\"Joelma Greicy Fernandes Lira, Ricardo Alves de Olinda, Gustavo Correia Basto da Silva, Luzibênia Leal de Oliveira, Raimunda Leite de Alencar Neta, Nívea Vilar Cardoso, Fernando Adami, Laércio da Silva Paiva\",\"doi\":\"10.1155/2024/2927407\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>This is a cross-sectional study, with secondary data from Brazilian hospitals in the state of Paraíba, between January 2021 and January 2022. The evolution of clinical cases configured the dependent variable (cure or death), while the predictive variables were sociodemographic data, risk factors, use of ventilatory support, and vaccination against COVID-19. With the help of R software, the following tests were used: chi-square, Pearson's chi-square, and Fisher's exact adherence. Simple logistic regression models were constructed, and odds ratios (95% CI) were estimated using the LR test and Wald test. 7373 cases were reported, with a mean age of 58.1. Of the reported cases, 63.8% died. The most frequent sociodemographic profile included male people, of mixed race, with less than eight years of schooling. Chronic cardiovascular disease (OR 1.28; 95% CI: 1.13-1.45), diabetes (OR 1.41; 95% CI: 1.24-1.61), lung disease (OR 1.52; 95% CI: 1.11-2.09), and the use of invasive ventilatory support (OR 14.1; 95% CI: 10.56-18.59) were all associated with increased mortality. 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Sociodemographic Profile and Risk Factors for the Evolution of Patients with COVID-19 in ICUs in Brazil: A Cross-Sectional Study.
This is a cross-sectional study, with secondary data from Brazilian hospitals in the state of Paraíba, between January 2021 and January 2022. The evolution of clinical cases configured the dependent variable (cure or death), while the predictive variables were sociodemographic data, risk factors, use of ventilatory support, and vaccination against COVID-19. With the help of R software, the following tests were used: chi-square, Pearson's chi-square, and Fisher's exact adherence. Simple logistic regression models were constructed, and odds ratios (95% CI) were estimated using the LR test and Wald test. 7373 cases were reported, with a mean age of 58.1. Of the reported cases, 63.8% died. The most frequent sociodemographic profile included male people, of mixed race, with less than eight years of schooling. Chronic cardiovascular disease (OR 1.28; 95% CI: 1.13-1.45), diabetes (OR 1.41; 95% CI: 1.24-1.61), lung disease (OR 1.52; 95% CI: 1.11-2.09), and the use of invasive ventilatory support (OR 14.1; 95% CI: 10.56-18.59) were all associated with increased mortality. Nonvaccination was associated with a decreased risk of death (OR 0.74; 95% CI: 0.65-0.84). Male patients, nonwhite, and those with low education were more likely to have a worse clinical outcome. The risk factors studied were related to deaths, and those who did not require ventilatory support were related to cure.
期刊介绍:
The Scientific World Journal is a peer-reviewed, Open Access journal that publishes original research, reviews, and clinical studies covering a wide range of subjects in science, technology, and medicine. The journal is divided into 81 subject areas.