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

Hospitalizations for coronavirus disease 2019: an analysis of the occurrence waves

The pandemic has been characterized by several waves defined by viral strains responsible for the predominance of infections. We aimed to analyze the mean length of hospital stay for patients with COVID-19 during the first three waves of the pandemic and its distribution according to sociodemographic and clinical variables. This retrospective study used the notifications of patients hospitalized for COVID-19 in a Brazilian state during the period of the three waves of the disease as the data source. There were 13,910 hospitalizations for confirmed COVID-19 cases. The first wave was the longest, with 4101 (29.5%) hospitalizations, while the third, although shorter, had a higher number of hospitalized patients (N = 6960). The average length of stay in the hospital in all waves was associated with age groups up to 60 years old., elementary, high school and higher education, residents of the periurban area Regarding the presence of comorbidities, there was a statistically significant difference in the mean number of days of hospitalization among patients with chronic cardiovascular disease and obesity (P < 0.001). In conclusion, the COVID-19 pandemic has been distinctly revealed among the waves.

Incompleteness trends of epidemiological variables in a Brazilian high complexity cancer registry: An ecological time series study

Hospital Cancer Registries serve as a vital source of information for clinical and epidemiological research, allowing the evaluation of patient care outcomes through therapeutic protocol analysis and patient survival assessment. This study aims to assess the trend of incompleteness in the epidemiological variables within the Hospital Cancer Registry of a renowned oncology center in a Brazilian state. An ecological time-series study was conducted using secondary data from the Hospital Santa Rita de Cássia Cancer Registry in Espírito Santo between 2000 and 2016. Data completeness was categorized as follows: excellent (<5%), good (5%-10%), fair (10%-20%), poor (20%-50%), and very poor (>50%), based on the percentage of missing information. Descriptive and bivariate statistical analyses were performed using the free software RStudio (version 2022.07.2) and R (version 4.1.0). The Mann-Kendall test was used to assess temporal trends between the evaluated years, and the Friedman test was employed to evaluate quality scores across the years. Among the variables assessed, birthplace, race/color, education, occupation, origin, marital status, history of alcohol and tobacco consumption, previous diagnosis and treatment, the most important basis for tumor diagnosis, tumor-node-metastasis staging (TNM) staging, and clinical tumor staging by group (TNM) showed the highest levels of incompleteness. Conversely, other epidemiological variables demonstrated excellent completeness, reaching 100% throughout the study period. Significant trends were observed over the years for history of alcohol consumption (P < .001), history of tobacco consumption (P < .001), TNM staging (P = .016), clinical tumor staging by group (TNM) (P = .002), first treatment received at the hospital (P = .012), disease status at the end of the first treatment at the hospital (P < .001), and family history of cancer (P < .001), and tumor laterality (P = .032). While most epidemiological variables within the Hospital Santa Rita de Cássia Cancer Registry exhibited excellent completeness, some important variables, such as TNM staging and clinical staging, showed high levels of incompleteness. Ensuring high-quality data within Cancer Registries is crucial for a comprehensive understanding of the health-disease process.

Acute COVID-19 Management in Heart Failure Patients: A Specific Setting Requiring Detailed Inpatient and Outpatient Hospital Care

The relationship existing between heart failure (HF) and COVID-19 remains questioned and poorly elucidated. Many reports suggest that HF events are reduced during pandemics, although other studies have demonstrated higher mortality and sudden death in patients affected by HF. Several vascular, thrombotic, and respiratory features may deteriorate stable HF patients; therefore, the infection may directly cause direct myocardial damage, leading to cardiac function deterioration. Another concern is related to the possibility that antiviral, anti-inflammatory, and corticosteroid agents commonly employed during acute COVID-19 infection may have potentially deleterious effects on the cardiovascular (CV) system. For these reasons, HF patients deserve specific management with a tailored approach in order to avoid arrhythmic complications and fluid retention events. In this review, we describe the complex interplay between COVID-19 and HF, the evolving trend of infection with related CV events, and the specific management strategy to adopt in this setting.

Clinical Characterization of the Three Waves of COVID-19 Occurring in Southern Italy: Results of a Multicenter Cohort Study

AIMS

To characterize patients hospitalized for COVID-19 in the three waves in Southern Italy.

METHODS

We conducted a multicenter observational cohort study involving seventeen COVID-19 Units in Campania, southern Italy: All adult (≥18 years) patients, hospitalized with a diagnosis of SARS-CoV-2 infection from 28 February 2020 to 31 May 2021, were enrolled.

RESULTS

Two thousand and fifteen COVID-19 hospitalized patients were enrolled; 392 (19%) in the first wave, 917 (45%) in the second and 706 (35%) in the third wave. Patients showed a less severe clinical outcome in the first wave than in the second and third waves (73%, 65% and 72%, respectively; p = 0.003), but hospitalization expressed in days was longer in the first wave [Median (Q1-Q3): 17 (13-25) v.s. 14 (9-21) and 14 (9-19), respectively, p = 0.001)] and also mortality during hospitalization was higher in the first wave than in the second and third waves: 16.6% v.s. 11.3% and 6.5%, respectively (p = 0.0001). Multivariate analysis showed that older age [OR: 1.069, CI (1046-1092); p = 0.001], a worse Charlson comorbidity index [OR: 1042, CI (1233-1594; p = 0.0001] and enrolment during the first-wave [OR: 1.917, CI (1.054-3.485; p = 0.033] were predictors of mortality in hospitalized patients.

CONCLUSIONS

Improved organization of the healthcare facilities and the increase in knowledge of clinical and therapeutic management have contributed to a trend in the reduction in mortality during the three waves of COVID-19.