The impact of COVID-19 for postoperative outcomes using a nationwide Japanese database of patients undergoing distal gastrectomy for gastric cancer

Background: The coronavirus disease 2019 (COVID-19) pandemic had resulted in either failure to provide required medical resources or delayed treatment for gastric cancer patients. This study aimed to investigate the impact of COVID-19 on the incidence of postoperative complications using a nationwide Japanese database of patients undergoing distal gastrectomy for gastric cancer. Method(s): We collected the data of patients who underwent distal gastrectomy from January 2018 to December 2021 from the National Clinical Database (NCD), a web-based surgical registration system in Japan. The number of surgical cases, the use of intensive care units, and the incidence of morbidity per month were analyzed. We also calculated the standardized mortality ratio (SMR), defined as the ratio of the number of observed patients to the expected number of patients calculated using the risk calculator established in the NCD, for several morbidities, including pneumonia, sepsis, 30-day mortality, and surgical mortality. Result(s): A decrease of 568 gastrectomies was observed from April 2020 to May 2020. Although the absolute number of patients admitted to intensive care units had declined since 2020, the proportion of patients admitted to the ICU did not change before and after the pandemic. Mortality and critical morbidity (such as pneumonia and sepsis) rates were not worse during the pandemic compared to pre-pandemic periods per the SMR. Conclusion(s): Surgical management was conducted adequately through the organized efforts of the entire surgery department in our country even in a pandemic during which medical resources and staff may have been limited.Copyright © 2023 The Authors. Annals of Gastroenterological Surgery published by John Wiley & Sons Australia, Ltd on behalf of The Japanese Society of Gastroenterological Surgery.

Estimates of excess mortality during the COVID-19 pandemic strongly depend on subjective methodological choices.

Excess mortality is often used to assess the health impact of the COVID-19 pandemic. It involves comparing the number of deaths observed during the pandemic with the number of deaths that would counterfactually have been expected in the absence of the pandemic. However, published data on excess mortality often vary even for the same country. The reason for these discrepancies is that the estimation of excess mortality involves a number of subjective methodological choices. The aim of this paper was to summarize these subjective choices. In several publications, excess mortality was overestimated because population aging was not adjusted for. Another important reason for different estimates of excess mortality is the choice of different pre-pandemic reference periods that are used to estimate the expected number of deaths (e.g., only 2019 or 2015-2019). Other reasons for divergent results include different choices of index periods (e.g., 2020 or 2020-2021), different modeling to determine expected mortality rates (e.g., averaging mortality rates from previous years or using linear trends), the issue of accounting for irregular risk factors such as heat waves and seasonal influenza, and differences in the quality of the data used. We suggest that future studies present the results not only for a single set of analytic choices, but also for sets with different analytic choices, so that the dependence of the results on these choices becomes explicit.

Epidemiology of Pemphigus.

Pemphigus is an epidemiologically heterogeneous group of autoimmune bullous diseases comprising pemphigus vulgaris (PV), pemphigus foliaceus, paraneoplastic pemphigus, IgA pemphigus, and pemphigus herpetiformis. Recently, our knowledge about the frequency of pemphigus, which is highly variable between different populations, has considerably expanded, and the first non-HLA genes associated with PV have been identified. In addition, a variety of comorbidities, including other autoimmune diseases, hematological malignancies, and psoriasis, have been described in this variant. Here, initial data about the impact of COVID-19 on this fragile patient population are discussed and perspectives for future epidemiological studies are outlined.

How Did the Two Years of the COVID-19 Pandemic Affect the Outcomes of the Patients with Inflammatory Rheumatic Diseases in Lithuania?

Background and objectives: the COVID-19 pandemic globally caused more than 18 million deaths over the period of 2020-2021. Although inflammatory rheumatic diseases (RD) are generally associated with premature mortality, it is not yet clear whether RD patients are at a greater risk for COVID-19-related mortality. The aim of our study was to evaluate mortality and causes of death in a retrospective inflammatory RD patient cohort during the COVID-19 pandemic years. Methods: We identified patients with a first-time diagnosis of inflammatory RD and followed them up during the pandemic years of 2020-2021. Death rates, and sex- and age-standardized mortality ratios (SMRs) were calculated for the prepandemic and pandemic periods. Results: We obtained data from 11,636 patients that had been newly diagnosed with inflammatory RD and followed up until the end of 2021 or their death. The mean duration of the follow-up was 5.5 years. In total, 1531 deaths occurred between 2013 and 2021. The prevailing causes of death in the prepandemic period were cardiovascular diseases, neoplasms, and diseases of the respiratory system. In the pandemic years, cardiovascular diseases and neoplasms remained the two most common causes of death, with COVID-19 in third place. The SMR of the total RD cohort was 0.83. This trend was observed in rheumatoid arthritis and spondyloarthropathy patients. The SMR in the group of connective-tissue diseases and vasculitis was higher at 0.93, but did not differ from that of the general population. The excess of deaths in the RD cohort during the pandemic period was negative (-27.2%), meaning that RD patients endured the pandemic period better than the general population did. Conclusions: The COVID-19 pandemic did not influence the mortality of RD patients. Strict lockdown measures, social distancing, and early vaccination were the main factors that resulted in reduced mortality in this cohort during the pandemic years.

Area Deprivation and COVID-19 Incidence and Mortality in Bavaria, Germany: A Bayesian Geographical Analysis.

Background: Area deprivation has been shown to be associated with various adverse health outcomes including communicable as well as non-communicable diseases. Our objective was to assess potential associations between area deprivation and COVID-19 standardized incidence and mortality ratios in Bavaria over a period of nearly 2 years. Bavaria is the federal state with the highest infection dynamics in Germany and demographically comparable to several other European countries. Methods: In this retrospective, observational ecological study, we estimated the strength of associations between area deprivation and standardized COVID-19 incidence and mortality ratios (SIR and SMR) in Bavaria, Germany. We used official SARS-CoV-2 reporting data aggregated in monthly periods between March 1, 2020 and December 31, 2021. Area deprivation was assessed using the quintiles of the 2015 version of the Bavarian Index of Multiple Deprivation (BIMD 2015) at district level, analyzing the overall index as well as its single domains. Results: Deprived districts showed higher SIR and SMR than less deprived districts. Aggregated over the whole period, the SIR increased by 1.04 (95% confidence interval (95% CI): 1.01 to 1.07, p = 0.002), and the SMR by 1.11 (95% CI: 1.07 to 1.16, p < 0.001) per BIMD quintile. This represents a maximum difference of 41% between districts in the most and least deprived quintiles in the SIR and 110% in the SMR. Looking at individual months revealed clear linear association between the BIMD quintiles and the SIR and SMR in the first, second and last quarter of 2021. In the summers of 2020 and 2021, infection activity was low. Conclusions: In more deprived areas in Bavaria, Germany, higher incidence and mortality ratios were observed during the COVID-19 pandemic with particularly strong associations during infection waves 3 and 4 in 2020/2021. Only high infection levels reveal the effect of risk factors and socioeconomic inequalities. There may be confounding between the highly deprived areas and border regions in the north and east of Bavaria, making the relationship between area deprivation and infection burden more complex. Vaccination appeared to balance incidence and mortality rates between the most and least deprived districts. Vaccination makes an important contribution to health equality.

The association of the COVID-19 pandemic and short-term outcomes of non-COVID-19 critically ill patients: an observational cohort study in Brazilian ICUs.

PURPOSE: To assess whether intensive care unit (ICU) outcomes for patients not affected by coronavirus disease 2019 (COVID-19) worsened during the COVID-19 pandemic. METHODS: Retrospective cohort study including prospectively collected information of patients admitted to 165 ICUs in a hospital network in Brazil between 2011 and 2020. Association between admission in 2020 and worse hospital outcomes was performed using different techniques, including assessment of changes in illness severity of admitted patients, a variable life-adjusted display of mortality during 2020, a multivariate mixed regression model with admission year as both fixed effect and random slope adjusted for SAPS 3 score, an analysis of trends in performance using standardized mortality ratio (SMR) and standardized resource use (SRU), and perturbation analysis. RESULTS: A total of 644,644 admissions were considered. After excluding readmissions and patients with COVID-19, 514,219 patients were available for analysis. Non-COVID-19 patients admitted in 2020 had slightly lower age and SAPS 3 score but a higher mortality (6.4%) when compared with previous years (2019: 5.6%; 2018: 6.1%). Variable-adjusted life display (VLAD) in 2020 increased but started to decrease as the number of COVID-19 cases increased; this trend reversed as number of COVID cases reduced but recurred on the second wave. After logistic regression, being admitted in 2020 was associated with higher mortality when compared to previous years from 2016 and 2019. Individual ICUs standardized mortality ratio also increased during 2020 (higher SMR) while resource use remained constant, suggesting worsening performance. A perturbation analysis further confirmed changes in ICU outcomes for non-COVID-19 patients. CONCLUSION: Hospital outcomes of non-COVID-19 critically ill patients worsened during the pandemic in 2020, possibly resulting in an increased number of deaths in critically ill non-COVID patients.

Quantifying and communicating the burden of COVID-19.

BACKGROUND: An essential aspect of preventing further COVID-19 outbreaks and to learn for future pandemics is the evaluation of different political strategies, which aim at reducing transmission of and mortality due to COVID-19. One important aspect in this context is the comparison of attributable mortality. METHODS: We give a comprehensive overview of six epidemiological measures that are used to quantify COVID-19 attributable mortality (p-score, standardized mortality ratio, absolute number of excess deaths, per capita rate, z-score and the population attributable fraction). RESULTS: By defining the six measures based on observed and expected deaths, we explain their relationship. Moreover, three publicly available data examples serve to illustrate the interpretational strengths and weaknesses of the various measures. Finally, we give recommendation which measures are suitable for an evaluation of public health strategies against COVID-19. The R code to reproduce the results is available as online supplementary material. CONCLUSION: The number of excess deaths should be always reported together with the population attributable fraction, the p-score or the standardized mortality ratio instead of a per capita rate. For a complete picture of COVID-19 attributable mortality, quantifying and communicating its relative burden also to a lay audience is of major importance.