Comorbidities predict 30-day hospital mortality of older adults with COVID-19

Charlson comorbidity index has no incremental value for mortality risk prediction in nursing home residents with COVID-19 disease

BACKGROUND

During the COVID-19 pandemic, nursing home (NH) residents faced the highest risk of severe COVID-19 disease and mortality. Due to their frailty status, comorbidity burden can serve as a useful predictive indicator of vulnerability in this frail population. However, the prognostic value of these cumulative comorbidity scores like the Charlson comorbidity index (CCI) remained unclear in this population. We evaluated the incremental predictive value of the CCI for predicting 28-day mortality in NH residents with COVID-19, compared to prediction using age and sex only.

METHODS

We included older individuals of ≥ 70 years of age in a large retrospective observational cohort across NHs in the Netherlands. Individuals with PCR-confirmed COVID-19 diagnosis from 1 March 2020 to 31 December 2021 were included. The CCI score was computed by searching for the comorbidities recorded in the electronic patient records. All-cause mortality within 28 days was predicted using logistic regression based on age and sex only (base model) and by adding the CCI to the base model (CCI model). The predictive performance of the base model and the CCI model were compared visually by the distribution of predicted risks and area under the receiver operator characteristic curve (AUROC), scaled Brier score, and calibration slope.

RESULTS

A total of 4318 older NH residents were included in this study with a median age of 88 years [IQR: 83-93] and a median CCI score of 6 [IQR: 5-7]. 1357 (31%) residents died within 28 days after COVID-19 diagnosis. The base model, with age and sex as predictors, had an AUROC of 0.61 (CI: 0.60 to 0.63), a scaled brier score of 0.03 (CI: 0.02 to 0.04), and a calibration slope of 0.97 (CI: 0.83 to 1.13). The addition of CCI did not improve these predictive performance measures.

CONCLUSION

The addition of the CCI as a vulnerability indicator did not improve short-term mortality prediction in NH residents. Similar (high) age and number of comorbidities in the NH population could reduce the effectiveness of these predictors, emphasizing the need for other population-specific predictors that can be utilized in the frail NH residents.

Immunological insights: assessing immune parameters in medical professionals exposed to SARS-CoV-2

BACKGROUND

The immunological background responsible for the severe course of COVID-19 and the immune factors that protect against SARS-CoV-2 infection are still unclear. The aim of this study was to investigate immune system status in persons with high exposure to SARS-CoV-2 infection.

METHODS

Seventy-one persons employed in the observation and infectious diseases unit were qualified for the study between November 2020 and October 2021. Symptomatic COVID-19 was diagnosed in 35 persons. Anti-SARS-CoV-2 antibodies were also found in 8 persons. Peripheral blood mononuclear cells subpopulations were analyzed by flow cytometry, and the concentrations of cytokines and anti-SARS-CoV-2 antibodies were determined by ELISA.

RESULTS

The percentages of cytotoxic T lymphocytes (CTLs), CD28+ and T helper (Th) cells with invariant T-cell receptors were significantly higher in persons with symptomatic COVID-19 than in those who did not develop COVID-19' symptoms. Conversely, symptomatic COVID-19 persons had significantly lower percentages of: a) CTLs in the late stage of activation (CD8+/CD95+), b) NK cells, c) regulatory-like Th cells (CD4+/CTLA-4+), and d) Th17-like cells (CD4+/CD161+) compared to asymptomatic COVID-19' persons. Additionally, persons with anti-SARS-CoV-2 antibodies had a significantly higher lymphocyte count and IL-6 concentration than persons without these antibodies.

CONCLUSION

Numerous lymphocyte populations are permanently altered by SARS-CoV-2 infection. High percentages of both populations: NK cells-as a part of the non-specific response, and T helper cells' as those regulating the immune response, could protect against the acute COVID-19 symptoms development. Understanding the immune background of COVID-19 may improve the prevention of this disease by identifying people at risk of a severe course of infection.

TRIAL REGISTRATION

This is a retrospective observational study without a trial registration number.

Increased risk of SARS-CoV-2 infection and COVID-19 death among older patients at long-term care hospitals in Korea

Introduction

Long-term care hospitals are known to be vulnerable to SARS-CoV-2 infection and death given their numerous older chronic disease patients. However, the actual effect of long-term care hospital admission is not well known in Korea; hence, this study sought to analyze the effect of long-term care hospitalization on SARS-CoV-2 infection and COVID-19 death by correcting for patients' characteristics.

Methods

This cross-sectional study used the data from K-COV-N cohort, which is linked to the National Health Insurance Service and the Korea Disease Control and Prevention Agency; it analyzed 70,373 individuals aged ≥60 years, who had been tested for COVID-19 between January 1 and May 30, 2020 (KDCA-NHIS-2020-1-601). Patients admitted to a long-term care hospital were defined as those with a confirmed history of hospitalization within 30 days of the COVID-19 testing date. The final data analysis was performed in December 2022. Logistic regression analysis of the national data was employed to determine the association between long-term care hospital admission, the risk of SARS-CoV-2 infection, and death from COVID-19. The odds ratios for SARS-CoV-2 infection and death from COVID-19 were calculated by adjusting for sex, age, residential area, health insurance premium, disability, and the Charlson Comorbidity Index.

Results

Older patients at long-term care hospitals had a high risk of SARS-CoV-2 infection (OR:2.91, 95% CI:2.33-3.64) and death from COVID-19 (OR:3.58, 95% CI:2.13-6.02). A difference in SARS-CoV-2 infection risk was observed based on residential area, health insurance premium (economic level), and disability; no difference was observed for COVID-19 mortality risk.

Discussion

Admission to a long-term care hospital itself could be a risk factor for SARS-CoV-2 infection and the consequent high mortality risk after adjusting for sex, age, disability, and comorbidities. Patients are at high risk of infection through contact with workers, leading to death; therefore, quarantine policies for workers must be strengthened.

Probabilistic survival modeling in health research: an assessment using cohort data from hospitalized patients with COVID-19 in a Latin American city

Probabilistic survival methods have been used in health research to analyze risk factors and adverse health outcomes associated with COVID-19. The aim of this study was to employ a probabilistic model selected among three distributions (exponential, Weibull, and lognormal) to investigate the time from hospitalization to death and determine the mortality risks among hospitalized patients with COVID-19. A retrospective cohort study was conducted for patients hospitalized due to COVID-19 within 30 days in Londrina, Brazil, between January 2021 and February 2022, registered in the database for severe acute respiratory infections (SIVEP-Gripe). Graphical and Akaike Information Criterion (AIC) methods were used to compare the efficiency of the three probabilistic models. The results from the final model were presented as hazard and event time ratios. Our study comprised of 7,684 individuals, with an overall case fatality rate of 32.78%. Data suggested that older age, male sex, severe comorbidity score, intensive care unit admission, and invasive ventilation significantly increased risks for in-hospital mortality. Our study highlights the conditions that confer higher risks for adverse clinical outcomes attributed to COVID-19. The step-by-step process for selecting appropriate probabilistic models may be extended to other investigations in health research to provide more reliable evidence on this topic.

COVID-19 vaccination and case fatality rates: a case report in a Brazilian municipality

Vaccination campaigns played a crucial role in reducing the incidence of COVID-19. However, a scant number of studies evaluated the impact of vaccination on case fatality rates (CFRs), including in Brazil. Our study aimed to compare CFRs according to vaccination status among subjects living in Arapongas (Paraná State, Brazil), considering the age composition of the population. Several strategies adopted by the Arapongas City Hall to minimize the spread of the virus were also elaborated upon. We accessed the 2021 database of the Arapongas Municipal Health Department, in which a total of 16,437 confirmed cases and 425 deaths were reported. The CFR was calculated as the ratio between COVID-19 deaths and the number of confirmed cases. Differences in age composition between unvaccinated and fully vaccinated individuals were observed in our study. Considering that CFR is a crude indicator and is highly sensitive to the age composition of the population, we adopted the average age distribution of confirmed cases among the three vaccination statuses (unvaccinated, partially, and fully) as a standard age distribution. The age-standardized CFR for unvaccinated and fully vaccinated groups were 4.55% and 2.42%, respectively. Fully vaccinated individuals showed lower age-specific CFRs in all age groups above 60 years than unvaccinated populations. Our findings strengthen the role of vaccination as a critical measure for preventing deaths among infected people and is particularly important to the ongoing reassessment of public health interventions and policies.

Age and Comorbidity Burden of Patients Critically Ill with COVID-19 Affect Both Access to and Outcome of Ventilation Therapy in Intensive Care Units

During the COVID-19 pandemic, large numbers of elderly, multimorbid people required treatment in intensive care units. This study investigated how the inherent patient factors age and comorbidity burden affected the treatment strategy and the outcome achieved. Retrospective analysis of data from intensive care patients enrolled in the Lean European Open Survey on SARS-CoV2-Infected Patients (LEOSS) cohort found that a patient's age and comorbidity burden in fact influenced their mortality rate and the use of ventilation therapy. Evidence showed that advanced age and multimorbidity were associated with the restrictive use of invasive ventilation therapies, particularly ECMO. Geriatric patients with a high comorbidity burden were clustered in the sub-cohort of non-ventilated ICU patients characterized by a high mortality rate. The risk of death generally increased with older age and accumulating comorbidity burden. Here, the more aggressive an applied procedure, the younger the age in which a majority of patients died. Clearly, geriatric, multimorbid COVID-19 patients benefit less from invasive ventilation therapies. This implies the need for a holistic approach to therapy decisions, taking into account the patient's wishes.

Factors associated with death in COVID-19 patients over 60 years of age at Kinshasa University Hospital, Democratic Republic of Congo (DRC)

Introduction

the objectives of the present study were to determine the mortality rate in patients over 60 years of age with COVID-19 and to identify risk factors.

Methods

the present historical cohort study took place at the Kinshasa University Hospital (KUH), DRC. Older patients admitted from March 2020 to May 2021 and diagnosed COVID-19 positive at the laboratory were selected. The relationship between clinical and biological risk factors, treatment, and in-hospital mortality was modeled using Cox regression.

Results

of two hundred and twenty-two patients at least 60 years old, 97 died, for a mortality rate of 43.69%. The median age was 70 years (64-74) with extremes of 60 to 88 years. Low oxygen saturation of < 90% (aHR 1.69; 95% CI [1.03-2.77]; p=0.038) was an independent predictor of mortality. The risk of death was reduced with corticosteroid use (aHR 0.54; 95% CI [0.40-0.75]; p=0.01) and anticoagulant treatment (aHR 0.53; 95% CI [0.38-0.73]; p=0.01).

Conclusion

mortality was high in seniors during COVID-19 and low oxygen saturation on admission was a risk factor for mortality. Corticosteroid therapy and anticoagulation were protective factors. These should be considered in management to reduce mortality.