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      „Coronavirus disease 2019“ und Frailty Translated title: Coronavirus disease 2019 and frailty

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          Abstract

          Der Verlauf der Coronavirus disease 2019 (COVID-19) ist individuell sehr unterschiedlich. Menschen höheren Lebensalters mit Komorbiditäten sind gefährdeter, schwer zu erkranken oder zu versterben. Gebrechlichkeit (Frailty) ist ein wesentlicher Risikofaktor. Ein Fünftel der Bevölkerung in Mitteleuropa ist älter als 65 Jahre, 10–15 % davon sind als „frail“ anzusehen. Die Pandemie bringt die Gesundheitssysteme vieler Länder an deren Grenzen. Die Entscheidung, welche Patienten noch intensivmedizinisch behandelt werden, führt zu ethischen Diskussionen. Die Clinical Frailty Scale von Rockwood (CFS; CMAJ 173:489–495, 2005) wird in manchen Ländern eingesetzt, diese Entscheidungen zu unterstützen.

          Von COVID-19 betroffene 80-jährige Patienten haben ein fast 3,6faches Sterblichkeitsrisiko, verglichen mit der Altersgruppe von 18 bis 49 Jahren. Das Risiko gebrechlicher Patienten (CFS-Scores 6–9) ist mehr als 3fach höher als von robusten (CFS-Scores 1–3). Ein CFS-Cut-off-Wert ≥ 6 korreliert mit der Mortalität von COVID-19-Patienten über 65 Jahre. Das mittel- und längerfristige Überleben ist auch mit dem Ausmaß von „Frailty“ vor der Erkrankung und weniger mit dem Schweregrad der COVID-19 assoziiert.

          Besonders Patienten über 60 Jahre sind gefährdet, bei moderaten und schweren COVID-19-Verläufen rasch Muskelmasse zu verlieren. Patienten auf Intensive Care Units (ICU) verlieren innerhalb von 10 Tagen 20–30 % der Oberschenkelstreckmuskulaturmasse. Das Ausmaß der COVID-19-assoziierten Sarkopenie bestimmt wesentlich den Verlauf der Erkrankung und macht individuelle Rehabilitationsprogrammen erforderlich. Bis zu 50 % der hospitalisierten Patienten benötigen weitere Rehabilitation nach der Entlassung. Aerobes Training mit niedriger Intensität, kombiniert mit Krafttraining, sowie die Sicherstellung einer ausreichenden Energie- und Eiweißzufuhr sind unerlässlich.

          Translated abstract

          The course of coronavirus disease 2019 (COVID-19) varies from individual to individual. People of advanced age with comorbidities have been identified as having a higher risk for severe disease or to die from COVID-19. Frailty is an essential risk factor in this respect. Approximately one fifth of the middle European population are older than 65 years, and of these 10–15% can be categorized as frail. The pandemic brings the healthcare systems in many countries to their limits. Deciding which patients should be transferred to intensive care units (ICU) raises ethical discussions. In some countries the Rockwood Clinical Frailty Scale (CFS) is used to support this decision. Patients over 80 years of age suffering from COVID-19 show a 3.6-fold increase in the risk of mortality compared to the group aged 18–49 years. The risk of frail (CFS scores 6–9) patients is three times higher than for robust patients (CFS scores 1–3). A CFS score cut-off ≥ 6 clearly correlates with mortality of COVID-19 patients older than 65 years. Additionally, mid-term and long-term survival is determined by the degree of frailty at the time before COVID-19 rather than by the severity of the disease. Patients over 60 years are particularly at risk to develop a rapid loss of muscle mass during moderate or severe COVID-19. Patients being treated on ICUs lose 20–30% of their thigh extensor muscle mass within 10 days. The extent of sarcopenia associated with COVID-19 is decisive in determining the course of the disease and makes individually tailored rehabilitation programs necessary. Up to 50% of hospitalized patients need further rehabilitation after discharge. Aerobic training of low intensity combined with resistance training as well as a sufficient supply of calories and proteins in the diet are essential in this respect.

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          Most cited references30

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          A global clinical measure of fitness and frailty in elderly people.

          There is no single generally accepted clinical definition of frailty. Previously developed tools to assess frailty that have been shown to be predictive of death or need for entry into an institutional facility have not gained acceptance among practising clinicians. We aimed to develop a tool that would be both predictive and easy to use. We developed the 7-point Clinical Frailty Scale and applied it and other established tools that measure frailty to 2305 elderly patients who participated in the second stage of the Canadian Study of Health and Aging (CSHA). We followed this cohort prospectively; after 5 years, we determined the ability of the Clinical Frailty Scale to predict death or need for institutional care, and correlated the results with those obtained from other established tools. The CSHA Clinical Frailty Scale was highly correlated (r = 0.80) with the Frailty Index. Each 1-category increment of our scale significantly increased the medium-term risks of death (21.2% within about 70 mo, 95% confidence interval [CI] 12.5%-30.6%) and entry into an institution (23.9%, 95% CI 8.8%-41.2%) in multivariable models that adjusted for age, sex and education. Analyses of receiver operating characteristic curves showed that our Clinical Frailty Scale performed better than measures of cognition, function or comorbidity in assessing risk for death (area under the curve 0.77 for 18-month and 0.70 for 70-month mortality). Frailty is a valid and clinically important construct that is recognizable by physicians. Clinical judgments about frailty can yield useful predictive information.
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            6-month neurological and psychiatric outcomes in 236 379 survivors of COVID-19: a retrospective cohort study using electronic health records

            Background Neurological and psychiatric sequelae of COVID-19 have been reported, but more data are needed to adequately assess the effects of COVID-19 on brain health. We aimed to provide robust estimates of incidence rates and relative risks of neurological and psychiatric diagnoses in patients in the 6 months following a COVID-19 diagnosis. Methods For this retrospective cohort study and time-to-event analysis, we used data obtained from the TriNetX electronic health records network (with over 81 million patients). Our primary cohort comprised patients who had a COVID-19 diagnosis; one matched control cohort included patients diagnosed with influenza, and the other matched control cohort included patients diagnosed with any respiratory tract infection including influenza in the same period. Patients with a diagnosis of COVID-19 or a positive test for SARS-CoV-2 were excluded from the control cohorts. All cohorts included patients older than 10 years who had an index event on or after Jan 20, 2020, and who were still alive on Dec 13, 2020. We estimated the incidence of 14 neurological and psychiatric outcomes in the 6 months after a confirmed diagnosis of COVID-19: intracranial haemorrhage; ischaemic stroke; parkinsonism; Guillain-Barré syndrome; nerve, nerve root, and plexus disorders; myoneural junction and muscle disease; encephalitis; dementia; psychotic, mood, and anxiety disorders (grouped and separately); substance use disorder; and insomnia. Using a Cox model, we compared incidences with those in propensity score-matched cohorts of patients with influenza or other respiratory tract infections. We investigated how these estimates were affected by COVID-19 severity, as proxied by hospitalisation, intensive therapy unit (ITU) admission, and encephalopathy (delirium and related disorders). We assessed the robustness of the differences in outcomes between cohorts by repeating the analysis in different scenarios. To provide benchmarking for the incidence and risk of neurological and psychiatric sequelae, we compared our primary cohort with four cohorts of patients diagnosed in the same period with additional index events: skin infection, urolithiasis, fracture of a large bone, and pulmonary embolism. Findings Among 236 379 patients diagnosed with COVID-19, the estimated incidence of a neurological or psychiatric diagnosis in the following 6 months was 33·62% (95% CI 33·17–34·07), with 12·84% (12·36–13·33) receiving their first such diagnosis. For patients who had been admitted to an ITU, the estimated incidence of a diagnosis was 46·42% (44·78–48·09) and for a first diagnosis was 25·79% (23·50–28·25). Regarding individual diagnoses of the study outcomes, the whole COVID-19 cohort had estimated incidences of 0·56% (0·50–0·63) for intracranial haemorrhage, 2·10% (1·97–2·23) for ischaemic stroke, 0·11% (0·08–0·14) for parkinsonism, 0·67% (0·59–0·75) for dementia, 17·39% (17·04–17·74) for anxiety disorder, and 1·40% (1·30–1·51) for psychotic disorder, among others. In the group with ITU admission, estimated incidences were 2·66% (2·24–3·16) for intracranial haemorrhage, 6·92% (6·17–7·76) for ischaemic stroke, 0·26% (0·15–0·45) for parkinsonism, 1·74% (1·31–2·30) for dementia, 19·15% (17·90–20·48) for anxiety disorder, and 2·77% (2·31–3·33) for psychotic disorder. Most diagnostic categories were more common in patients who had COVID-19 than in those who had influenza (hazard ratio [HR] 1·44, 95% CI 1·40–1·47, for any diagnosis; 1·78, 1·68–1·89, for any first diagnosis) and those who had other respiratory tract infections (1·16, 1·14–1·17, for any diagnosis; 1·32, 1·27–1·36, for any first diagnosis). As with incidences, HRs were higher in patients who had more severe COVID-19 (eg, those admitted to ITU compared with those who were not: 1·58, 1·50–1·67, for any diagnosis; 2·87, 2·45–3·35, for any first diagnosis). Results were robust to various sensitivity analyses and benchmarking against the four additional index health events. Interpretation Our study provides evidence for substantial neurological and psychiatric morbidity in the 6 months after COVID-19 infection. Risks were greatest in, but not limited to, patients who had severe COVID-19. This information could help in service planning and identification of research priorities. Complementary study designs, including prospective cohorts, are needed to corroborate and explain these findings. Funding National Institute for Health Research (NIHR) Oxford Health Biomedical Research Centre.
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              Prevalence of frailty in 62 countries across the world: a systematic review and meta-analysis of population-level studies

              The prevalence of frailty at population level is unclear. We examined this in population-based studies, investigating sources of heterogeneity. PubMed, Embase, CINAHL and Cochrane Library databases were searched for observational population-level studies published between 1 January 1998 and 1 April 2020, including individuals aged ≥50 years, identified using any frailty measure. Prevalence estimates were extracted independently, assessed for bias and analysed using a random-effects model. In total, 240 studies reporting 265 prevalence proportions from 62 countries and territories, representing 1,755,497 participants, were included. Pooled prevalence in studies using physical frailty measures was 12% (95% CI = 11–13%; n = 178), compared with 24% (95% CI = 22–26%; n = 71) for the deficit accumulation model (those using a frailty index, FI). For pre-frailty, this was 46% (95% CI = 45–48%; n = 147) and 49% (95% CI = 46–52%; n = 29), respectively. For physical frailty, the prevalence was higher among females, 15% (95% CI = 14–17%; n = 142), than males, 11% (95% CI = 10–12%; n = 144). For studies using a FI, the prevalence was also higher in females, 29% (95% CI = 24–35%; n = 34) versus 20% (95% CI = 16–24%; n = 34), for males. These values were similar for pre-frailty. Prevalence increased according to the minimum age at study inclusion. Analysing only data from nationally representative studies gave a frailty prevalence of 7% (95% CI = 5–9%; n = 46) for physical frailty and 24% (95% CI = 22–26%; n = 44) for FIs. Population-level frailty prevalence varied by classification and sex. Data were heterogenous and limited, particularly from nationally representative studies making the interpretation of differences by geographic region challenging. Common methodological approaches to gathering data are required to improve the accuracy of population-level prevalence estimates. PROSPERO-CRD42018105431.
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                Author and article information

                Contributors
                marcus.koeller@gesundheitsverbund.at
                Journal
                Z Gerontol Geriatr
                Z Gerontol Geriatr
                Zeitschrift Fur Gerontologie Und Geriatrie
                Springer Medizin (Heidelberg )
                0948-6704
                1435-1269
                6 September 2022
                : 1-5
                Affiliations
                Abteilung für Akutgeriatrie, Klinikum Favoriten, Kundratstr. 3, 1100 Wien, Österreich
                Article
                2101
                10.1007/s00391-022-02101-y
                9446611
                36066605
                a4e0f600-50ef-4e21-be3c-3fa21b9e6421
                © The Author(s), under exclusive licence to Springer Medizin Verlag GmbH, ein Teil von Springer Nature 2022

                This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.

                History
                : 11 August 2022
                Categories
                Themenschwerpunkt

                ältere,sarkopenie,mortalität,prognose,rehabilitation,aged,sarcopenia,prognosis,mortality

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