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Baseline characteristics of the study population across the two surges

Baseline characteristics of the study population across the two surges

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Article
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Background: The primary aim of this study was to assess the outcome of elderly intensive care unit (ICU) patients treated during the spring and autumn COVID-19 surges in Europe. Methods: This was a prospective European observational study (the COVIP study) in ICU patients aged 70 years and older admitted with COVID-19 disease from March to Decem...

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... illustrated in Table 1, 2625 patients from European countries were included in the COVIP study during the two surges. There were nearly equal numbers of patients recruited during the first and the second surge of the pandemic. ...

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... Furthermore, patients ≥70 years old have six times more likely to die than patients < 70 years old [6]. Even in short time followup, the mortality rate of geriatric patients with COVID-19 in ICU is relatively high, reaching up to 80% in several studies [24][25][26]. A comparison using Indonesian Task Force big data showed that although the most common age group admitted to the hospital in the COVID-19 pandemic was 31-45 years old, the elderly population experienced the most mortality rate (> 60 years old) with roughly 18% [27]. ...
Article
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Background With the more advanced science in the field of medicine and disease management, the population of geriatric intensive care patients is increasing. The COVID-19 pandemic has impacted healthcare management around the globe, especially on critically-ill elderly patients. We aim to analyse the relationship between underlying illnesses, including COVID-19, and the survival rate of elderly patients who are treated in the intensive care setting. Methods We conducted a prospective cohort study at 14 teaching hospitals for Anaesthesiology and Intensive Therapy Education in Indonesia. We selected all subjects with 60 years of age or older in the period between February to May 2021. Variables recorded included subject characteristics, comorbidities, and COVID-19 status. Subjects were followed for 30-day mortality as an outcome. We analysed the data using Kaplan-Meier survival analysis. Results We recruited 982 elderly patients, and 728 subjects were in the final analysis (60.7% male; 68.0 ± 6.6 years old). The 30-day mortality was 38.6%. The top five comorbidities are hypertension (21.1%), diabetes (16.2%), moderate or severe renal disease (10.6%), congestive heart failure (9.2%), and cerebrovascular disease (9.1%). Subjects with Charlson’s Comorbidity Index Score > 5 experienced 66% death. Subjects with COVID-19 who died were 57.4%. Subjects with comorbidities and COVID-19 had lower survival time than subjects without those conditions (p < 0.005). Based on linear correlation analysis, the more comorbidities the geriatric patients in the ICU had, the higher chance of mortality in 30 days (p < 0.005, R coefficient 0.22). Conclusion Approximately one in four elderly intensive care patients die, and the number is increasing with comorbidities and COVID-19 status.
... Furthermore, comorbidities such as hypertension, diabetes, obesity, and smoking have been described as key contributors to an undesirable outcome [6]. Other parameters, such as medical [7], genetic [8], environmental [9], physical [10,11], mental/psychological [12], social [13], economical [14], and political [15], whose effect cannot be precisely determined, at least at an individual level, are believed to contribute to country-specific CFR disparities. Last, concerning vaccination for SARS-CoV-2, it has been reported that vaccination uptake is closely associated with elderly people saved, independently of the vaccine type administered [16]. ...
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Aim To investigate the reasons for disparity regarding the country-specific COVID-19-related case fatality rate (CFR) within the 30 countries of the European Economic Area (EEA). Materials and methods Data regarding population, area, COVID-19-associated infections/deaths, vaccination, life expectancy, elderly population, infant mortality, gender disparity, urbanization, gross domestic product (GDP), income per capita, health spending per capita, physicians, nursing personnel, hospital beds, ICU beds, hypertension, diabetes, obesity, and smoking from all EEA countries were collected from official sources on January 16, 2022. Correlation coefficients were computed, and optimal scaling using ridge regression was used to reach the most parsimonious multivariate model assessing any potential independent correlation of public health parameters with COVID-19 CFR. Results COVID-19 CFR ranges from 0.1% (Iceland) to 4.0% (Bulgaria). All parameters but population density, GDP, total health spending (% of GDP), ICU beds, diabetes, and obesity were correlated with COVID-19 CFR. In the most parsimonious multivariate model, elderly population rate (P = 0.018), males/total ratio (P = 0.013), nurses/hospital beds (P = 0.001), physicians/hospital beds (P = 0.026), public health spending (P = 0.013), smoking rate (P = 0.013), and unvaccinated population rate (P = 0.00005) were demonstrated to present independent correlation with COVID-19 CFR. In detail, the COVID-19 CFR is estimated to increase by 1.24 times in countries with vaccination rate of <0.34, 1.11 times in countries with an elderly population rate of ≥0.20, 1.14 times in countries with male ratio values ≥0.493, 1.12 times in countries spending <2,000$ annually per capita for public health, 1.14 and 1.10 times in countries with <2.30 nurses and <0.88 physicians per hospital bed, respectively, and 1.12 in countries with smoking ratio ≥0.22, while holding all other independent variables of the model constant. Conclusion COVID-19 CFR varies substantially among EEA countries and is independently linked with low vaccination rates, increased elderly population rate, diminished public health spending per capita, insufficient physicians and nursing personnel per hospital bed, and prevalent smoking habits. Therefore, public health authorities are awaited to consider these parameters in prioritizing actions to manage the SARS-CoV-2 pandemic.
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The outbreak and continuing impact of COVID-19 have significantly increased the rates of hospitalization and admissions to intensive care units (ICU). This study evaluates clinical outcomes in critically ill patients and investigates variables tied to poor prognosis. A secondary database analysis was conducted to investigate the predictors of poor outcome among critically ill COVID-19 patients in Saudi Arabia. Multivariable logistic regression analysis was used to assess the association between various demographic characteristics, comorbidities, and COVID-19 symptoms and patients’ poor prognosis, as a composite outcome. A total of 2257 critically ill patients were identified (male (71.8%), and elderly (37.3%)). The mortality rate was 50.0%, and the composite poor outcome was 68.4%. The predictors of poor outcome were being elderly (OR = 4.79, 95%CI 3.19–7.18), obesity (OR = 1.43, 95%CI 1.1–1.87), having a severe or critical case at admission (OR = 6.46, 95%CI 2.34–17.8; OR = 22.3, 95%CI 11.0–45, respectively), and some signs and symptoms of COVID-19 such as shortness of breath, feeling fatigued or headache, respiratory rate ≥ 30/min, PaO2/FiO2 ratio < 300, and altered consciousness. In conclusion, identifying high-risk populations that are expected to have a poor prognosis based on their criteria upon admission helps policymakers and practitioners better triage patients when faced with limited healthcare resources.
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Purpose: Critically ill old intensive care unit (ICU) patients suffering from Sars-CoV-2 disease (COVID-19) are at increased risk for adverse outcomes. This post hoc analysis investigates the association of the Activities of Daily Living (ADL) with the outcome in this vulnerable patient group. Methods: The COVIP study is a prospective international observational study that recruited ICU patients ≥ 70 years admitted with COVID-19 (NCT04321265). Several parameters including ADL (ADL; 0 = disability, 6 = no disability), Clinical Frailty Scale (CFS), SOFA score, intensive care treatment, ICU- and 3-month survival were recorded. A mixed-effects Weibull proportional hazard regression analyses for 3-month mortality adjusted for multiple confounders. Results: This pre-specified analysis included 2359 patients with a documented ADL and CFS. Most patients evidenced independence in their daily living before hospital admission (80% with ADL = 6). Patients with no frailty and no disability showed the lowest, patients with frailty (CFS ≥ 5) and disability (ADL < 6) the highest 3-month mortality (52 vs. 78%, p < 0.001). ADL was independently associated with 3-month mortality (ADL as a continuous variable: aHR 0.88 (95% CI 0.82-0.94, p < 0.001). Being "disable" resulted in a significant increased risk for 3-month mortality (aHR 1.53 (95% CI 1.19-1.97, p 0.001) even after adjustment for multiple confounders. Conclusion: Baseline Activities of Daily Living (ADL) on admission provides additional information for outcome prediction, although most critically ill old intensive care patients suffering from COVID-19 had no restriction in their ADL prior to ICU admission. Combining frailty and disability identifies a subgroup with particularly high mortality. Trial registration number: NCT04321265.
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Aims: Chronic heart failure (CHF) is a major risk factor for mortality in coronavirus disease 2019 (COVID-19). This prospective international multicentre study investigates the role of pre-existing CHF on clinical outcomes of critically ill old (≥70 years) intensive care patients with COVID-19. Methods and results: Patients with pre-existing CHF were subclassified as having ischaemic or non-ischaemic cardiac disease; patients with a documented ejection fraction (EF) were subclassified according to heart failure EF: reduced (HFrEF, n = 132), mild (HFmrEF, n = 91), or preserved (HFpEF, n = 103). Associations of heart failure characteristics with the 30 day mortality were analysed in univariate and multivariate logistic regression analyses. Pre-existing CHF was reported in 566 of 3917 patients (14%). Patients with CHF were older, frailer, and had significantly higher SOFA scores on admission. CHF patients showed significantly higher crude 30 day mortality [60% vs. 48%, P < 0.001; odds ratio 1.87, 95% confidence interval (CI) 1.5-2.3] and 3 month mortality (69% vs. 56%, P < 0.001). After multivariate adjustment for confounders (SOFA, age, sex, and frailty), no independent association of CHF with mortality remained [adjusted odds ratio (aOR) 1.2, 95% CI 0.5-1.5; P = 0.137]. More patients suffered from pre-existing ischaemic than from non-ischaemic disease [233 vs. 328 patients (n = 5 unknown aetiology)]. There were no differences in baseline characteristics between ischaemic and non-ischaemic disease or between HFrEF, HFmrEF, and HFpEF. Crude 30 day mortality was significantly higher in HFrEF compared with HFpEF (64% vs. 48%, P = 0.042). EF as a continuous variable was not independently associated with 30 day mortality (aOR 0.98, 95% CI 0.9-1.0; P = 0.128). Conclusions: In critically ill older COVID-19 patients, pre-existing CHF was not independently associated with 30 day mortality. Trial registration number: NCT04321265.
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Background Elderly patients represent a high-risk group with increased risk of death from COVID-19. Despite the amount of published studies, several unmet needs about the care for older adults exist. Objectives To discuss unmet needs of COVID-19 in this special population. Sources A literature review for studies on COVID-19 in elderly patients published between December 2019 and November 2021 was performed. Clinical questions were formulated to guide the literature search. The search was conducted in the MEDLINE database combining specific search terms. Two reviewers independently conducted the search and selected the studies according to the pre-specified clinical questions. Content Elderly patients with COVID-19 have peculiar characteristics. They may have atypical clinical presentation, with no fever and delirium or neurological manifestations as the most common signs, with potential delayed diagnosis and increased risk of death. The reported fatality rates among elderly patients with COVID-19 are extremely high. Several factors, including comorbidities, atypical presentation, and exclusion from ICU care contribute to this excess of mortality. Age alone is frequently used as key factor to exclude elderly from intensive care, but there is evidence that frailty instead of age better predicts the risk of poor outcome in this category. Durability of vaccine efficacy in the elderly remains debated and need for the third booster dose is becoming more and more evident. Finally, efforts to care for elderly who survived after acute COVID-19 should be implemented, considering the high rates of long COVID sequelae and the risk of longitudinal functional and cognitive decline. Implications We hereby highlighted peculiar aspects of COVID-19 in elderly patients and factors contributing to high risk of poor outcome in this category. We also illuminated gaps in current evidence suggesting future research directions and underlining the need of further studies about the optimal management of elderly patients with COVID-19.
Article
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Introduction: For the past two years, healthcare systems worldwide have been battling the ongoing COVID-19 pandemic. Several studies tried to find predictive factors of mortality in COVID-19 patients. We aimed to research age as a predictive factor associated with in-hospital mortality in severe and critical SARS-CoV-2 infection. Methods: Between 1 March and 20 April 2020, we conducted a multicenter and retrospective study on a cohort of severe COVID-19 patients who were all hospitalized in the Intensive Care Unit (ICU). We led our study in nine hospitals of northeast France, one of the pandemic's epicenters in Europe. Results: The median age of our study population was 66 years (58-72 years). Mortality was 24.6% (CI 95%: 20.6-29%) in the ICU and 26.5% (CI 95%: 22.3-31%) in the hospital. Non-survivors were significantly older (69 versus 64 years, p < 0.001) than the survivors. Although a history of cardio-vascular diseases was more frequent in the non-survivor group (p = 0.015), other underlying conditions and prior level of autonomy did not differ between the two groups. On multivariable analysis, age appeared to be an interesting predictive factor of in-hospital mortality. Thus, age ranges of 65 to 74 years (OR = 2.962, CI 95%: 1.231-7.132, p = 0.015) were predictive of mortality, whereas the group of patients aged over 75 years was not (OR = 3.084, CI 95%: 0.952-9.992, p = 0.06). Similarly, all comorbidities except for immunodeficiency (OR = 4.207, CI 95%: 1.006-17.586, p = 0.049) were not predictive of mortality. Finally, survival follow-up was obtained for the study population. Conclusion: Age appears to be a relevant predictive factor of in-hospital mortality in cases of severe or critical SARS-CoV-2 infection.
Article
Background: The SARS-CoV-2 coronavirus disease (COVID-19) pandemic is challenging health care systems globally. The disease disproportionately affects the elderly population, both in terms of disease severity and mortality risk. Objective: This study aimed to evaluate machine-learning based prognostication models for critically ill elderly COVID-19 patients, which dynamically incorporated multifaceted clinical information on the evolution of the disease. Methods: This multi-centre cohort study obtained patient data from 151 ICUs from 26 countries (COVIP study). Different models based on the Sequential Organ Failure Assessment (SOFA), Logistic Regression (LR), Random Forest (RF) and Extreme Gradient Boosting (XGBoost) were derived as baseline models that included admission variables only. We subsequently included clinical events and time-to-event as additional variables to derive the final models using the same algorithms and compared their performance with the baseline group. Furthermore, we derived baseline and final models on a European patient cohort and externally validated them on a non-European cohort that included Asian, African and American patients. Results: In total, 1,432 elderly (≥70 years) COVID-19 positive patients were admitted to an intensive care unit. Of these 809 (56.5%) patients survived up to 30 days after admission. The average length of stay was 21.6 (±18.2) days. Final models that incorporated clinical events and time-to-event provided superior performance with AUC of 0.81 (95% CI 0.804-0.811), with respect to both, the baseline models that used admission variables only and conventional ICU prediction models (SOFA-score, p<.001). The average precision increased from 0.65 (95% CI 0.650-0.655) to 0.77 (95% CI 0.759-0.770). Conclusions: Integrating important clinical events and time-to-event information led to a superior accuracy of 30-day mortality prediction compared with models based on the admission information and conventional ICU prediction models. The present study shows that machine-learning models provide additional information and may support complex decision-making in critically ill elderly COVID-19 patients. Clinicaltrial: Nct04321265.
Article
Introduction: We analyzed the association of age with ventilation practice and outcomes in critically ill COVID-19 patients requiring invasive ventilation. Methods: Posthoc analysis of the PRoVENT-COVID study, an observational study performed in 22 ICUs in the first 3 months of the national outbreak in the Netherlands. The coprimary endpoint was a set of ventilator parameters, including tidal volume normalized for predicted bodyweight, positive end-expiratory pressure, driving pressure, and respiratory system compliance in the first 4 days of invasive ventilation. Secondary endpoints were other ventilation parameters, the use of rescue therapies, pulmonary and extrapulmonary complications in the first 28 days in the ICU, hospital- and ICU stay, and mortality. Results: 1122 patients were divided into four groups based on age quartiles. No meaningful differences were found in ventilation parameters and in the use of rescue therapies for refractory hypoxemia in the first 4 days of invasive ventilation. Older patients received more often a tracheostomy, developed more frequently acute kidney injury and myocardial infarction, stayed longer in hospital and ICU, and had a higher mortality. Conclusions: In this cohort of invasively ventilated critically ill COVID-19 patients, age had no effect on ventilator management. Higher age was associated with more complications, longer length of stay in ICU and hospital and a higher mortality.
Preprint
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Background: With the more advanced science in the field of medicine and disease management, the population of geriatric intensive care patients is increasing. The COVID-19 pandemic has impacted healthcare management around the globe, especially on critically-ill elderly patients. We aim to analyse the relationship between underlying illnesses, including COVID-19, and the survival rate of elderly patients who are treated in the intensive care setting. Methods: We conducted a prospective cohort study at 14 teaching hospitals for Anaesthesiology and Intensive Therapy Education in Indonesia. We selected all subjects with 60 years of age or older in the period between February to May 2021. Variables recorded included subject characteristics, comorbidities, and COVID-19 status. Subjects were followed for 30-day mortality as an outcome. We analysed the data using Kaplan-Meier survival analysis. Results: We recruited 982 elderly patients, and 728 subjects were in the final analysis (60.7% male; 68.0 ± 6.6 years old). The 30-day mortality was 38.6%. The top five comorbidities are hypertension (21.1%), diabetes (16.2%), moderate or severe renal disease (10.6%), congestive heart failure (9.2%), and cerebrovascular disease (9.1%). Subjects with Charlson's Comorbidity Index Score >5 experienced 66% death. Subjects with COVID-19 who died were 57.4%. Subjects with comorbidities and COVID-19 had lower survival rates than subjects without those conditions (p < 0.005). Conclusion: Approximately one in four elderly intensive care patients die, and the number is increasing with comorbidities and COVID-19 status.