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Correlation between hospitalized patients' demographics, symptoms, comorbidities, and COVID-19 pandemic in Bahia, Brazil.

ABSTRACT: In this paper, we provide a retrospective cohort study with patients that have been hospitalized for general or intensive care unit admission due to COVID-19, between March 3 and July 29, 2020, in the state of Bahia, Brazil. We aim to correlate those patients' demographics, symptoms and comorbidities, with the risk of mortality from COVID-19, length of hospital stay, and time from diagnosis to definitive outcome. On the basis of a dataset provided by the Health Secretary of the State of Bahia, we selected 3,896 hospitalized patients from a total of 154,868 COVID-19 patients that included non-hospitalized patients and patients with invalid registration in the dataset. Then, we statistically analyzed whether there was a significant correlation between the patient record data and the COVID-19 pandemic, and our main findings reinforced by the use of a multivariable logistic regression were that older age (Odds Ratio [OR] = 1.03, 95% Confidence Interval [CI] = 1.03-1.04, p-value (p) <0.001), an initial symptom of shortness of breath (OR = 1.88, 95% CI = 1.60-2.20, p < 0.001), and the presence of comorbidities, mainly chronic kidney disease (OR = 2.41, 95% CI = 1.67-3.48, p < 0.001) are related to an increased risk of mortality from COVID-19. On the other hand, sore throat (OR = 0.74, 95% CI = 0.58-0.95, p = 0.02) and length of hospital stay (OR = 0.96, 95% CI = 0.58-0.95, p < 0.001) are more related to a reduced risk of mortality from COVID-19. Moreover, a multivariable linear regression conducted with statistically significant variables (p < 0.05) showed that age (OR = 0.97, 95% CI = 0.95-0.98, p < 0.001) and time from diagnosis to definitive outcome (OR = 1.67, 95% CI = 1.64-1.71, p < 0.001) are associated with the length of hospital stay.

SUBMITTER: Macedo MCF

PROVIDER: S-EPMC7735911 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Correlation between hospitalized patients' demographics, symptoms, comorbidities, and COVID-19 pandemic in Bahia, Brazil.

Macedo Márcio C F MCF Pinheiro Isabelle M IM Carvalho Caio J L CJL Fraga Hilda C J R HCJR Araujo Isaac P C IPC Montes Simone S SS Araujo Otávio A C OAC Alves Lucas A LA Saba Hugo H Araújo Márcio L V MLV Queiroz Ivonete T L ITL Sampaio Romilson L RL Souza Márcia S P L MSPL da Silva Ana Claudia F N ACFN Souza Antonio C S ACS

PloS one 20201214 12

In this paper, we provide a retrospective cohort study with patients that have been hospitalized for general or intensive care unit admission due to COVID-19, between March 3 and July 29, 2020, in the state of Bahia, Brazil. We aim to correlate those patients' demographics, symptoms and comorbidities, with the risk of mortality from COVID-19, length of hospital stay, and time from diagnosis to definitive outcome. On the basis of a dataset provided by the Health Secretary of the State of Bahia, w ...[more]

PMID: 33318711

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Project description:BackgroundCOVID-19 pandemic is disaster to public health worldwide. Better perspective on COVID's features early in its course-prior to the development of vaccines and widespread variants-may prove useful in the understanding of future pandemics. Ontology provides a standardized integrative method for knowledge modeling and computer-assisted reasoning. In this study, we systematically extracted and analyzed clinical phenotypes and comorbidities in COVID-19 patients found at different countries and regions during the early pandemic using an ontology-based bioinformatics approach, with the aim to identify new insights and hidden patterns of the COVID-19 symptoms.ResultsA total of 48 research articles reporting analysis of first-hand clinical data from over 40,000 COVID-19 patients were surveyed. The patients studied therein were diagnosed with COVID-19 before May 2020. A total of 18 commonly-occurring phenotypes in these COVID-19 patients were first identified and then classified into different hierarchical groups based on the Human Phenotype Ontology (HPO). This meta-analytic approach revealed that fever, cough, and the loss of smell and taste were ranked as the most commonly-occurring phenotype in China, the US, and Italy, respectively. We also found that the patients from Europe and the US appeared to have more frequent occurrence of many nervous and abdominal symptom phenotypes (e.g., loss of smell, loss of taste, and diarrhea) than patients from China during the early pandemic. A total of 22 comorbidities, such as diabetes and kidney failure, were found to commonly exist in COVID-19 patients and positively correlated with the severity of the disease. The knowledge learned from the study was further modeled and represented in the Coronavirus Infectious Disease Ontology (CIDO), supporting semantic queries and analysis. Furthermore, also considering the symptoms caused by new viral variants at the later stages, a spiral model hypothesis was proposed to address the changes of specific symptoms during different stages of the pandemic.ConclusionsDifferential patterns of symptoms in COVID-19 patients were found given different locations, time, and comorbidity types during the early pandemic. The ontology-based informatics provides a unique approach to systematically model, represent, and analyze COVID-19 symptoms, comorbidities, and the factors that influence the disease outcomes.

Project description:BackgroundStudies of previous pandemics indicate that healthcare workers have a high risk of developing symptoms related to mental health, especially depression, anxiety, and stress.ObjectiveTo identify mental disorder symptoms among Brazilian healthcare workers during the Sars-Cov-2 pandemic and compare findings in different work categories.MethodsThis was an online cross-sectional study. Information related to the pandemic and mental disorder symptoms was collected. The Depression, Anxiety, and Stress Scale and the Impact of Event Scale-revised were used. Associations were estimated by the chi-square test. The mean scores were compared among work categories with ANOVA (α = 5%) and the prevalence of symptoms was estimated.Results1,609 healthcare workers participated in the survey [mean age: 36.9 (SD = 11.6) years, women = 83.6%]. There was no association between work category and changes in mental health during the pandemic (p = 0.288) or prevalence of unsafe feeling (p = 0.218). A significant relationship was observed between maintaining work activities during the pandemic and work category (p < 0.001). Physicians had the lowest out-of-work prevalence (9.5%) while dentists had the highest (32.3%). Physicians and nurses showed the highest prevalence of in-person work routine. Psychologists presented the highest prevalence of remote work (64.0%) while dentists had the lowest (20.2%). A high prevalence of depression (D), anxiety (A), and stress (S) symptoms was observed in all professional categories (D: 57.2, 95% CI 48.3-66.1%; A: 46.20%, 95% CI = 37.2-55.2%; S: 55.80%, 95% CI = 46.8-64.8%), with physicians (D = 38.4%, A = 25.80%, S = 37.90%), psychologists (D = 50.2%, A = 39.0%, S = 43.1%), and nurses (D = 50.0%, A = 40.9%, S = 49.0%) having significantly lower scores. Psychologists had the lowest pandemic-related psychological impact (42.70%, 95% CI 36.8-48.6%).ConclusionExtreme changes in the work routine of dentists and psychologists and an overall high prevalence of mental symptoms due to the pandemic were found. Researchers should focus on gathering information that can identify workers at increased risk of mental illness to guide discussions and develop actions to minimize the harm of the pandemic. In addition, we suggest that healthcare and support systems urgently adopt mental health care measures with specialized professionals to protect the psychological well-being of the healthcare community.

Project description:BackgroundFetal loss is one of the most serious adverse outcomes of pregnancy. Since the onset of the COVID-19 pandemic, Brazil has recorded an unprecedented number of hospitalizations of pregnant women due to acute respiratory distress (ARD), thereby, we aimed to assess the risk of fetal deaths associated to ARD during pregnancy in Bahia state, Brazil, in the context of the COVID-19 pandemic.MethodsThis is an observational population-based retrospective cohort study, developed with women at or after 20 weeks of pregnancy, residents in Bahia, Brazil. Women who had acute respiratory distress (ARD) in pregnancy during the COVID-19 pandemic (Jan 2020 to Jun 2021) were considered 'exposed'. Women who did not have ARD in pregnancy, and whose pregnancy occurred before the onset of the COVID-19 pandemic (Jan 2019 to Dec 2019) were considered 'non-exposed'. The main outcome was fetal death. We linked administrative data (under mandatory registration) on live births, fetal deaths, and acute respiratory syndrome, using a probabilistic linkage method, and analyzed them with multivariable logistic regression models.Results200,979 pregnant women participated in this study, 765 exposed and 200,214 unexposed. We found four times higher chance of fetal death in women with ARD during pregnancy, of all etiologies (adjusted odds ratio [aOR] 4.06 confidence interval [CI] 95% 2.66; 6.21), and due to SARS-CoV-2 (aOR 4.45 CI 95% 2.41; 8.20). The risk of fetal death increased more when ARD in pregnancy was accompanied by vaginal delivery (aOR 7.06 CI 95% 4.21; 11.83), or admission to Intensive Care Unit (aOR 8.79 CI 95% 4.96; 15.58), or use of invasive mechanical ventilation (aOR 21.22 CI 95% 9.93; 45.36).ConclusionOur findings can contribute to expanding the understanding of health professionals and managers about the harmful effects of SARS-CoV-2 on maternal-fetal health and alerts the need to prioritize pregnant women in preventive actions against SARS-CoV-2 and other respiratory viruses. It also suggests that pregnant women, infected with SARS-CoV-2, need to be monitored to prevent complications of ARD, including a careful assessment of the risks and benefits of early delivery to prevent fetal death.

Project description:BackgroundThe coronavirus disease 19 (COVID-19) pandemic has spread rapidly around the globe with considerable morbidity and mortality. Coexistence of comorbidities with COVID-19 had consistently been reported as risk factors for unfavorable outcome. We aimed to evaluate the impact of comorbidities in COVID-19 patients on the outcome and determine predictors of prolonged hospital stay, requisite for intensive care unit (ICU) admission. Four hundred and thirty-nine adult patients who are admitted through (June and July 2020) in our University Hospitals were included in the study. All participants were diagnosed with COVID-19 according to Egyptian Ministry of Health guidance as definite case or probable case.ResultsPatients with comorbidities represented 61.7% of all cases. Constitutional symptoms especially myalgia and lower respiratory tract (LRT) symptoms such as dyspnea were significantly higher in patients with comorbidities (P < 0.05). Patients with comorbidities had significantly worse laboratory parameters. ICU admission was higher in patients with comorbidities (35.8%). Among different comorbidities 45.4% of cardiovascular diseases (CVD) cases were admitted in ICU followed by diabetes mellitus (DM) cases (40.8%). Also, patients with comorbidities needed invasive mechanical ventilation more than those without comorbidity (31 versus 10.7%, P < 0.001). Significant lower frequency of recovery was found in COVID-19 patients with comorbidities (59% versus 81%, P < 0.001) and death rate was significantly higher in cases with comorbidities (P < 0.001) . The survival rates in cases with pre-existing CVD and neurological diseases were lower than those without disease (P < 0.002 and 0.001, respectively).ConclusionsAssociation of cardiovascular comorbid conditions including hypertension or neurological diseases including old cerebrovascular strokes together with COVID-19 infections carries higher risks of mortality. However, other comorbidities such as diabetes mellitus, chronic pulmonary or kidney diseases may also contribute to increased COVID-19 severity.

Dataset Information

Correlation between hospitalized patients' demographics, symptoms, comorbidities, and COVID-19 pandemic in Bahia, Brazil.

Publications

Correlation between hospitalized patients' demographics, symptoms, comorbidities, and COVID-19 pandemic in Bahia, Brazil.

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