Temporal Trends in the Completeness of Epidemiological Variables in a Hospital-Based Cancer Registry of a Pediatric Oncology Center in Brazil.

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 (<5%), good (5-10%), regular (11-20%), poor (21-50%), and very poor (>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.

The impact of COVID-19 on maternal death and fetal death, a cohort study in Brazil.

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.

Completeness and quality of information about death from COVID-19 in a Brazilian state: A descriptive population-based register study.

Health information is particularly essential in times of pandemics in which rapid response is crucial for political and stakeholder decision-making processes, and therefore the availability of data as well as its quality analysis are necessary. This study aimed to describe the completeness and quality of the e-Sistema Único de Saúde (SUS) Health Surveillance database (SUS Vigilância em Saúde) of the state of Espírito Santo, Brazil, from the notification of deaths from corana virus disease 2019 (COVID-19) from January 2020 to June 2021. A descriptive population-based register study was conducted from the analysis of the completeness of secondary data from the record of deaths from COVID-19, retrieved from the e-SUS Vigilância em Saúde (Health Surveillance) (VS) database of the state of Espírito Santo, Brazil, from January 2020 to June 2021. A total of 11,359 death records from COVID-19 via e-SUS VS in the state of Espírito Santo, Brazil, were evaluated. The score used to assess incompleteness was the 1 proposed by Romero and Cunha which classifies as excellent (when < 5%), good (between 5% and 10%), regular (between 10% and 20%), poor (between 20% and 50%), and very poor (when > 50%), according to the percentage of the absence of information. Descriptive statistical analyses were conducted in the Stata program, version 15.1. "Case identification" variables, and "condition" variables were classified as excellent completeness. Among the evolution variables, only "hospitalization" was classified as regular. Among the laboratory variables, only the polymerase chain reaction presented excellent completeness, while the "rapid test" and "serologies for immunoglobulin G, and immunoglobulin M" variables were classified as good completeness. It is concluded that most of the variables available in e-SUS VS of the state of Espírito Santo, Brazil, of notification of deaths from COVID-19 in 2020 presented excellent completeness, confirming the excellent quality of the state database.

COVID-19 Mortality in Public Hospitals in a Brazilian State: An Analysis of the Three Waves of the Pandemic.

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.

Analysis of Survival of Patients Hospitalized with COVID-19 in Espírito Santo, Brazil.

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.