Suchergebnisse

Funding: he support of the study in France by a grant from Fondation Assistance Publique-Hôpitaux de Paris Pour la Recherche is greatly appreciated. In Norway, the study was supported by a grant from Health Region West. In addition, EOSCsecretariat.eu provided support and has received funding from the European Union's Horizon Programme call H2020-INFRAEOSC-05-2018-2019, grant agreement number 831644. This work was supported by the Forschungskommission of the Medical Faculty of Heinrich-Heine-University Düsseldorf (grant 2018-32 to GW and grant 2020-21 to RB for a Clinician Scientist Track). The complete list of COVIP collaborators is provided in Multimedia Appendix 10. ; 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. ; publishersversion ; published

Funding: This study was endorsed by the ESICM. Free support for running the electronic database was granted from the Department of Epidemiology, Aarhus University, Denmark. The support of the study in France by a grant from 'Fondation Assistance Publique-Hôpitaux de Paris pour la recherche' is greatly appreciated. In Norway, the study was supported by a grant from the Health Region West. In addition, the study was supported by a grant from the European Open Science Cloud (EOSC). EOSCsecretariat.eu has received funding from the European Union's Horizon 2020 Framework Programme called H2020-INFRAEOSC-05-2018-2019, Grant Agreement Number 831644. This work was supported by the Forschungskommission of the Medical Faculty of the Heinrich Heine University Düsseldorf, No. 2018-32 to G.W. and No. 2020-21 to R.R.B. for a Clinician Scientist Track. Open access funding was enabled and organized by Projekt DEAL. No (industry) sponsorship has been received for this investigator-initiated study. ; 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. ; publishersversion ; epub_ahead_of_print

Open Access funding enabled and organized by Projekt DEAL. This study was endorsed by the ESICM. Free support for running the electronic database and was granted from the dep. of Epidemiology, University of Aarhus, Denmark. Bruno et al. Annals of Intensive Care (2022) 12:26 Page 10 of 11 The support of the study in France by a grant from Fondation Assistance Publique-Hôpitaux de Paris pour la recherche is greatly appreciated. In Norway, the study was supported by a grant from the Health Region West. In addition, the study was supported by a grant from the European Open Science Cloud (EOSC). EOSCsecretariat.eu has received funding from the European Union's Horizon Programme call H2020-INFRAEOSC-05-2018-2019, grant agreement number 831644. This work was supported by the Collaborative Research Center SFB 1116 (German Research Foundation, DFG) and by the Forschungskommission of the Medical Faculty of the Heinrich-Heine-University Düsseldorf and No. 2020–21 to RRB for a Clinician Scientist Track. No (industry) sponsorship has been received for this investigator-initiated study. ; 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). ...

Funding: In addition, the study was supported by a grant from the European Open Science Cloud (EOSC). EOSCsecretariat.eu has received funding from the European Union's Horizon Programme call H2020-INFRAEOSC-05-2018-2019, grant agreement number 831644. This work was supported by the Forschungskommission of the Medical Faculty of the Heinrich-Heine-University Düsseldorf, No. 2018-32 to G.W. and No. 2020-21 to R.R.B. for a Clinician Scientist Track. ; BACKGROUND: health-related quality of life (HRQoL) is an important patient-centred outcome in patients surviving ICU admission for COVID-19. It is currently not clear which domains of the HRQoL are most affected. OBJECTIVE: to quantify HRQoL in order to identify areas of interventions. DESIGN: prospective observation study. SETTING: admissions to European ICUs between March 2020 and February 2021. SUBJECTS: patients aged 70 years or older admitted with COVID-19 disease. METHODS: collected determinants include SOFA-score, Clinical Frailty Scale (CFS), number and timing of ICU procedures and limitation of care, Katz Activities of Daily Living (ADL) dependence score. HRQoL was assessed at 3 months after ICU admission with the Euro-QoL-5D-5L questionnaire. An outcome of ≥4 on any of Euro-QoL-5D-5L domains was considered unfavourable. RESULTS: in total 3,140 patients from 14 European countries were included in this study. Three months after inclusion, 1,224 patients (39.0%) were alive and the EQ-5D-5L from was obtained. The CFS was associated with an increased odds ratio for an unfavourable HRQoL outcome after 3 months; OR 1.15 (95% confidence interval (CI): 0.71-1.87) for CFS 2 to OR 4.33 (95% CI: 1.57-11.9) for CFS ≧ 7. The Katz ADL was not statistically significantly associated with HRQoL after 3 months. CONCLUSIONS: in critically ill old intensive care patients suffering from COVID-19, the CFS is associated with the subjectively perceived quality of life. The CFS on admission can be used to inform patients and relatives on the risk of an unfavourable qualitative outcome if such patients survive. ; publishersversion ; published