Objective: The study aimed to evaluate the risk of maternal death and fetal death among pregnant women infected with SARS-CoV-2. Methods: This is a retrospective cohort study among pregnant women with secondary data from the National Live Births System (Sistema Nacional de Nascidos Vivos), National Mortality System (Sistema Nacional de Mortalidade), and e-SUS Health Surveillance System (Sistema e-SUS Vigilância em Saúde). Pregnant women confirmed for COVID-19 had positive RT-PCR between March 2020 and May 2021, pregnant women without COVID-19 were those without notification for disease. Maternal death, fetal death, and stillbirth were assessed as primary outcomes. Results: We included 68,673 pregnant women not notified as suspected of COVID-19 and 1,386 with a confirmed diagnosis of COVID-19. Among pregnant women with COVID-19, 1013 (73.0%) were aged 20 to 34 years, 655 (47.2%) were brown, 907 (65.4%) had ≥ 8 years of education, in the third trimester of pregnancy (41.5%), undergoing cesarean section (64.5%). In adjusted analyses, COVID-19 in pregnancy had a higher risk of maternal death (relative risk [RR] 18.73–95% confidence interval [95%CI] 11.07–31.69), fetal death/stillbirth (RR 1.96–95%CI 1.18–3.25), preterm birth [RR 1.18–95%CI 1.01–1.39], cesarean delivery (RR 1.07–95%CI 1.02–1.11), and cesarean delivery occurring before the onset of labor (RR 1.33–95%CI 1.23–1.44). Conclusion: COVID-19 may contribute to unfavorable pregnancy outcomes. Results showed that pregnant women infected with SARS-CoV-2 had a higher risk of maternal death, fetal death/stillbirth, preterm birth, cesarean delivery, and cesarean section occurring before the onset of labor.

Objective: To evaluate the completeness and consistency of data from hospital-based cancer registries (HCRs) in a Brazilian state. Methods: This retrospective descriptive study was based on secondary data from an HCR in the state of Espírito Santo (ES) between 2010 and 2017. The data were collected between August and November 2020 by the ES State Health Department (SESA/ES). Cancer data were obtained from the HCR of ES using the tumor registration form of the Brazilian Hospital Cancer Registry Integrator and complete databases within the SESA/ES. The incompleteness of the data was classified as excellent (50%), according to the percentage of the absence of information. Descriptive statistical analyses were performed using Statistical Package for the Social Sciences (SPSS^® Inc., Chicago, IL, USA) version 20.0. Results: Complete data were observed for the variables of sex, date of the first hospital visit, and histological type of the primary tumor; that is, there were no missing data. Most epidemiological variables, including age, origin, date of first tumor diagnosis, previous diagnosis and treatment, location of the primary tumor, first treatment received at the hospital, date of death of the patient, and probable location of the primary tumor, were classified as having excellent completeness throughout the study period. However, the variables schooling, smoking, alcohol consumption, occupation, family history of cancer, and clinical staging of the tumor were classified as poor. Conclusion: Most epidemiological variables from the HCR in the state of ES, Brazil, showed excellent completeness. It is essential to elucidate the sociodemographic and clinical variables of epidemiological importance for a better understanding of the health-disease process.

Objective: To analyze the survival of patients hospitalized with COVID-19 and its associated factors. Methods: Retrospective study of survival analysis in individuals notified and hospitalized with COVID-19 in the state of Espírito Santo, Brazil. As data source, the reports of hospitalized patients in the period from 1 March 2020, to 31 July 2021 were used. The Cox regression analysis plus the proportional risk assessment (assumption) were used to compare hospitalization time until the occurrence of the event (death from COVID-19) associated with possible risk factors. Results: The sample comprised 9806 notifications of cases, with the occurrence of 1885 deaths from the disease (19.22%). The mean age of the group was 58 years (SD ± 18.3) and the mean hospital length of stay was 10.5 days (SD ± 11.8). The factors that presented a higher risk of death from COVID-19, associated with a lower survival rate, were non-work-related infection (HR = 4.33; p < 0.001), age group 60–79 years (HR: 1.62; p < 0.001) and 80 years or older (HR = 2.56; p < 0.001), presence of chronic cardiovascular disease (HR = 1.18; p = 0.028), chronic kidney disease (HR = 1.5; p = 0.004), smoking (HR = 1.41; p < 0.001), obesity (HR = 2.28; p < 0.001), neoplasms (HR = 1.81; p < 0.001) and chronic neurological disease (HR = 1.68; p < 0.001). Conclusion: It was concluded that non-work-related infection, age group above or equal to 60 years, presence of chronic cardiovascular disease, chronic kidney disease, chronic neurological disease, smoking, obesity and neoplasms were associated with a higher risk of death, and, therefore, a lower survival in Brazilian patients hospitalized with COVID-19. The identification of priority groups is crucial for Health Surveillance and can guide prevention, control, monitoring, and intervention strategies against the new coronavirus.

Objective: To analyze COVID-19 deaths in public hospitals in a Brazilian state, stratified by the three waves of the pandemic, and to test their association with socio-clinical variables. Methods: Observational analytical study, where 5436 deaths by COVID-19 occurred in hospitals of the public network of Espírito Santo, between 1 April 2020, and 31 August 2021, stratified by the three waves of the pandemic, were analyzed. For the bivariate analyses, the Pearson’s chi-square, Fisher’s Exact or Friedman’s tests were performed depending on the Gaussian or non-Gaussian distribution of the data. For the relationship between time from diagnosis to death in each wave, quantile regression was used, and multinomial regression for multiple analyses. Results: The mean time between diagnosis and death was 18.5 days in the first wave, 20.5 days in the second wave, and 21.4 days in the third wave. In the first wave, deaths in public hospitals were associated with the following variables: immunodeficiency, obesity, neoplasia, and origin. In the second wave, deaths were associated with education, O₂ saturation < 95%, chronic neurological disease, and origin. In the third wave, deaths were associated with race/color, education, difficulty breathing, nasal or conjunctival congestion, irritability or confusion, adynamia or weakness, chronic cardiovascular disease, neoplasms, and diabetes mellitus. Origin was associated with the outcome in the three waves of the pandemic, in the same way that education was in the second and third waves (p < 0.05). Conclusion: The time interval between diagnosis and death can be impacted by several factors, such as: plasticity of the health system, improved clinical management of patients, and the start of vaccination at the end of January 2021, which covered the age group with the higher incidence of deaths. The deaths occurring in public hospitals were associated with socio-clinical characteristics.

Objectives: to analyze the completeness of variables from Hospital-Based Cancer Registries of cases of prostate neoplasm in the Oncology Care Network of a Brazilian state between 2000 and 2020. Methods: an ecological time series study, based on secondary data on prostate cancer Hospital-Based Cancer Registries prostate. Data incompleteness was classified as excellent (50%), according to the percentage of lack of information. Results: there were 13,519 cases of prostate cancer in the Hospital-Based Cancer Registries analyzed. The variables “family history of cancer” (p<0.001), “alcoholism” (p<0.001), “smoking” (p<0.001), “TNM staging” (p<0.001) had a decreasing trend, while “clinical start of treatment” (p<0.001), “origin” (p=0.008) and “occupation” (p<0.001) indicated an increasing trend. Conclusions: most Hospital-Based Cancer Registries variables showed excellent completeness, but important variables had high percentages of incompleteness, such as TNM and clinical staging, in addition to alcoholism and smoking.

This ecological time series study aimed to examine the temporal trends in the completeness of epidemiological variables from a hospital-based cancer registry (HbCR) of a reference center for pediatric oncology in Brazil from 2010 to 2016. Completeness categories were based on the percentage of missing data, with the categories excellent (50%). Descriptive and bivariate analyses were performed using R.4.1.0; a Mann–Kendall trend test was performed to examine the temporal trends. Variables with the highest incompleteness included race/color (17.24% in 2016), level of education (51.40% in 2015), TNM (56.88% in 2012), disease status at the end of the first treatment (12.09% in 2013), cancer family history (79.12% in 2013), history of alcoholic consumption (39.25% in 2015), history of tobacco consumption (38.32% in 2015), and type of admission clinic (10.28% in 2015). Nevertheless, most variables achieved 100% completeness and were classified as excellent across the time series. A significant trend was observed for race/color, TNM, and history of tobacco consumption. While most variables maintained excellent completeness, the increasing incompleteness trend in race/color and decreasing trend in TNM underscore the importance of reliable and complete HbCRs for personalized cancer care, for planning public policies, and for conducting research on cancer control.