Objectives: To systematically evaluate the performance of COVID-19 prognostic models and scores for mortality risk in older populations across three health-care settings: hospitals, primary care,... Show moreObjectives: To systematically evaluate the performance of COVID-19 prognostic models and scores for mortality risk in older populations across three health-care settings: hospitals, primary care, and nursing homes.Study Design and Setting: This retrospective external validation study included 14,092 older individuals of >=70 years of age with a clinical or polymerase chain reaction-confirmed COVID-19 diagnosis from March 2020 to December 2020. The six validation cohorts include three hospital-based (CliniCo, COVID-OLD, COVID-PREDICT), two primary care-based (Julius General Practitioners Network/Academisch network huisartsgeneeskunde/Network of Academic general Practitioners, PHARMO), and one nursing home cohort (YSIS) in the Netherlands. Based on a living systematic review of COVID-19 prediction models using Prediction model Risk Of Bias ASsessment Tool for quality and risk of bias assessment and considering predictor availability in validation cohorts, we selected six prognostic models predicting mortality risk in adults with COVID-19 infection (GAL-COVID-19 mortality, 4C Mortality Score, National Early Warning Score 2-extended model, Xie model, Wang clinical model, and CURB65 score). All six prognostic models were validated in the hospital cohorts and the GAL-COVID-19 mortality model was validated in all three healthcare settings. The primary outcome was in-hospital mortality for hospitals and 28-day mortality for primary care and nursing home settings. Model performance was evaluated in each validation cohort separately in terms of discrimination, calibration, and decision curves. An intercept update was performed in models indicating miscalibration followed by predictive performance re-evaluation. Main Outcome Measure: In-hospital mortality for hospitals and 28-day mortality for primary care and nursing home setting. Results: All six prognostic models performed poorly and showed miscalibration in the older population cohorts. In the hospital settings, model performance ranged from calibration-in-the-large 1.45 to 7.46, calibration slopes 0.24e0.81, and C-statistic 0.55e0.71 with 4C Mortality Score performing as the most discriminative and well-calibrated model. Performance across health-care settings was similar for the GAL-COVID-19 model, with a calibration-in-the-large in the range of 2.35 to 0.15 indicating overestimation, calibration slopes of 0.24e0.81 indicating signs of overfitting, and C-statistic of 0.55e0.71. Conclusion: Our results show that most prognostic models for predicting mortality risk performed poorly in the older population with COVID-19, in each health-care setting: hospital, primary care, and nursing home settings. Insights into factors influencing predictive model performance in the older population are needed for pandemic preparedness and reliable prognostication of health-related outcomes in this demographic Show less
Roi-Teeuw, H.M. la; Luijken, K.; Blom, M.T.; Gussekloo, J.; Mooijaart, S.P.; Polinder-Bos, H.A.; ... ; Dries, C.J. van den 2024
BackgroundDuring the COVID-19 pandemic, older patients in primary care were triaged based on their frailty or assumed vulnerability for poor outcomes, while evidence on the prognostic value of... Show moreBackgroundDuring the COVID-19 pandemic, older patients in primary care were triaged based on their frailty or assumed vulnerability for poor outcomes, while evidence on the prognostic value of vulnerability measures in COVID-19 patients in primary care was lacking. Still, knowledge on the role of vulnerability is pivotal in understanding the resilience of older people during acute illness, and hence important for future pandemic preparedness. Therefore, we assessed the predictive value of different routine care-based vulnerability measures in addition to age and sex for 28-day mortality in an older primary care population of patients with COVID-19.MethodsFrom primary care medical records using three routinely collected Dutch primary care databases, we included all patients aged 70 years or older with a COVID-19 diagnosis registration in 2020 and 2021. All-cause mortality was predicted using logistic regression based on age and sex only (basic model), and separately adding six vulnerability measures: renal function, cognitive impairment, number of chronic drugs, Charlson Comorbidity Index, Chronic Comorbidity Score, and a Frailty Index. Predictive performance of the basic model and the six vulnerability models was compared in terms of area under the receiver operator characteristic curve (AUC), index of prediction accuracy and the distribution of predicted risks.ResultsOf the 4,065 included patients, 9% died within 28 days after COVID-19 diagnosis. Predicted mortality risk ranged between 7–26% for the basic model including age and sex, changing to 4–41% by addition of comorbidity-based vulnerability measures (Charlson Comorbidity Index, Chronic Comorbidity Score), more reflecting impaired organ functioning. Similarly, the AUC of the basic model slightly increased from 0.69 (95%CI 0.66 – 0.72) to 0.74 (95%CI 0.71 – 0.76) by addition of either of these comorbidity scores. Addition of a Frailty Index, renal function, the number of chronic drugs or cognitive impairment yielded no substantial change in predictions.ConclusionIn our dataset of older COVID-19 patients in primary care, the 28-day mortality fraction was substantial at 9%. Six different vulnerability measures had little incremental predictive value in addition to age and sex in predicting short-term mortality. Show less
ObjectivesDelirium is a serious condition, which poses treatment challenges during hospitalisation for COVID-19. Improvements in testing, vaccination and treatment might have changed patient... Show moreObjectivesDelirium is a serious condition, which poses treatment challenges during hospitalisation for COVID-19. Improvements in testing, vaccination and treatment might have changed patient characteristics and outcomes through the pandemic. We evaluated whether the prevalence and risk factors for delirium, and the association of delirium with in-hospital mortality changed through the pandemic.MethodsThis study was part of the COVID-OLD study in 19 Dutch hospitals including patients ≥70 years in the first (spring 2020), second (autumn 2020) and third wave (autumn 2021). Multivariable logistic regression models were used to study risk factors for delirium, and in-hospital mortality. Differences in effect sizes between waves were studied by including interaction terms between wave and risk factor in logistic regression models.Results1540, 884 and 370 patients were included in the first, second and third wave, respectively. Prevalence of delirium in the third wave (12.7%) was significantly lower compared to the first (22.5%) and second wave (23.5%). In multivariable-adjusted analyses, pre-existing memory problems was a consistent risk factor for delirium across waves. Previous delirium was a risk factor for delirium in the first wave (OR 4.02), but not in the second (OR 1.61) and third wave (OR 2.59, p-value interaction-term 0.028). In multivariable-adjusted analyses, delirium was not associated with in-hospital mortality in all waves.ConclusionDelirium prevalence declined in the third wave, which might be the result of vaccination and improved treatment strategies. Risk factors for delirium remained consistent across waves, although some attenuation was seen in the second wave. Show less
Kuiper, L.M.; Polinder-Bos, H.A.; Bizzarri, D.; Vojinovic, D.; Vallerga, C.L.; Beekman, M.; ... ; Meurs, J.B.J. van 2023
Biological age captures a person’s age-related risk of unfavorable outcomes using biophysiological information. Multivariate biological age measures include frailty scores and molecular biomarkers... Show moreBiological age captures a person’s age-related risk of unfavorable outcomes using biophysiological information. Multivariate biological age measures include frailty scores and molecular biomarkers. These measures are often studied in isolation, but here we present a large-scale study comparing them. In 2 prospective cohorts (n = 3 222), we compared epigenetic (DNAm Horvath, DNAm Hannum, DNAm Lin, DNAm epiTOC, DNAm PhenoAge, DNAm DunedinPoAm, DNAm GrimAge, and DNAm Zhang) and metabolomic-based (MetaboAge and MetaboHealth) biomarkers in reflection of biological age, as represented by 5 frailty measures and overall mortality. Biomarkers trained on outcomes with biophysiological and/or mortality information outperformed age-trained biomarkers in frailty reflection and mortality prediction. DNAm GrimAge and MetaboHealth, trained on mortality, showed the strongest association with these outcomes. The associations of DNAm GrimAge and MetaboHealth with frailty and mortality were independent of each other and of the frailty score mimicking clinical geriatric assessment. Epigenetic, metabolomic, and clinical biological age markers seem to capture different aspects of aging. These findings suggest that mortality-trained molecular markers may provide novel phenotype reflecting biological age and strengthen current clinical geriatric health and well-being assessment. Show less
PurposeOlder patients with COVID-19 can present with atypical complaints, such as falls or delirium. In other diseases, such an atypical presentation is associated with worse clinical outcomes.... Show morePurposeOlder patients with COVID-19 can present with atypical complaints, such as falls or delirium. In other diseases, such an atypical presentation is associated with worse clinical outcomes. However, it is not known whether this extends to COVID-19. We aimed to study the association between atypical presentation of COVID-19, frailty and adverse outcomes, as well as the incidence of atypical presentation.MethodsWe conducted a retrospective observational multi-center cohort study in eight hospitals in the Netherlands. We included patients aged >= 70 years hospitalized with COVID-19 between February 2020 until May 2020. Atypical presentation of COVID-19 was defined as presentation without fever, cough and/or dyspnea. We collected data concerning symptoms on admission, demographics and frailty parameters [e.g., Charlson Comorbidity Index (CCI) and Clinical Frailty Scale (CFS)]. Outcome data included Intensive Care Unit (ICU) admission, discharge destination and 30-day mortality.ResultsWe included 780 patients, 9.5% (n = 74) of those patients had an atypical presentation. Patients with an atypical presentation were older (80 years, IQR 76-86 years; versus 79 years, IQR 74-84, p = 0.044) and were more often classified as severely frail (CFS 6-9) compared to patients with a typical presentation (47.6% vs 28.7%, p = 0.004). Overall, there was no significant difference in 30-day mortality between the two groups in univariate analysis (32.4% vs 41.5%; p = 0.173) or in multivariate analysis [OR 0.59 (95% CI 0.34-1.0); p = 0.058].ConclusionsIn this study, patients with an atypical presentation of COVID-19 were more frail compared to patients with a typical presentation. Contrary to our expectations, an atypical presentation was not associated with worse outcomes.Key Summary PointsAimTo study the association between atypical presentation of COVID-19, frailty and adverse outcomes, as well as the incidence of atypical presentation.FindingsIn this study, an atypical presentation of COVID-19 was significantly associated with frailty. However, patients with an atypical presentation of COVID-19 did not have worse disease outcomes.MessagePhysicians need to remain alert for COVID-19 in frail older patients, as they may present without typical complaints. Show less
Background as the coronavirus disease of 2019 (COVID-19) pandemic progressed diagnostics and treatment changed. Objective to investigate differences in characteristics, disease presentation and... Show moreBackground as the coronavirus disease of 2019 (COVID-19) pandemic progressed diagnostics and treatment changed. Objective to investigate differences in characteristics, disease presentation and outcomes of older hospitalised COVID-19 patients between the first and second pandemic wave in The Netherlands. Methods this was a multicentre retrospective cohort study in 16 hospitals in The Netherlands including patients aged >= 70 years, hospitalised for COVID-19 in Spring 2020 (first wave) and Autumn 2020 (second wave). Data included Charlson comorbidity index (CCI), disease severity and Clinical Frailty Scale (CFS). Main outcome was in-hospital mortality. Results a total of 1,376 patients in the first wave (median age 78 years, 60% male) and 946 patients in the second wave (median age 79 years, 61% male) were included. There was no relevant difference in presence of comorbidity (median CCI 2) or frailty (median CFS 4). Patients in the second wave were admitted earlier in the disease course (median 6 versus 7 symptomatic days; P < 0.001). In-hospital mortality was lower in the second wave (38.1% first wave versus 27.0% second wave; P < 0.001). Mortality risk was 40% lower in the second wave compared with the first wave (95% confidence interval: 28-51%) after adjustment for differences in patient characteristics, comorbidity, symptomatic days until admission, disease severity and frailty. Conclusions compared with older patients hospitalised in the first COVID-19 wave, patients in the second wave had lower in-hospital mortality, independent of risk factors for mortality. The better prognosis likely reflects earlier diagnosis, the effect of improvement in treatment and is relevant for future guidelines and treatment decisions. Show less
BackgroundDuring the first wave of the COVID-19 pandemic older patients had an increased risk of hospitalisation and death. Reports on the association of frailty with poor outcome have been... Show moreBackgroundDuring the first wave of the COVID-19 pandemic older patients had an increased risk of hospitalisation and death. Reports on the association of frailty with poor outcome have been conflicting.ObjectiveThe aim of the present study was to investigate the independent association between frailty and in-hospital mortality in older hospitalised COVID-19 patients in the Netherlands.MethodsThis was a multi-centre retrospective cohort study in 15 hospitals in the Netherlands, including all patients aged ≥70 years, who were hospitalised with clinically confirmed COVID-19 between February and May 2020. Data were collected on demographics, co-morbidity, disease severity and Clinical Frailty Scale (CFS). Primary outcome was in-hospital mortality.ResultsA total of 1,376 patients were included (median age 78 years (IQR 74-84), 60% male). In total, 499 (38%) patients died during hospital admission. Parameters indicating presence of frailty (CFS 6-9) were associated with more co-morbidities, shorter symptom duration upon presentation (median 4 vs. 7 days), lower oxygen demand and lower levels of CRP. In multivariable analyses, the CFS was independently associated with in-hospital mortality: compared to patients with CFS 1-3, patients with CFS 4-5 had a two times higher risk (odds ratio (OR) 2.0 (95%CI 1.3-3.0) and patients with CFS 6-9 had a three times higher risk of in-hospital mortality (OR 2.8 (95%CI 1.8-4.3)).ConclusionsThe in-hospital mortality of older hospitalised COVID-19 patients in the Netherlands was 38%. Frailty was independently associated with higher in-hospital mortality, even though COVID-19 patients with frailty presented earlier to the hospital with less severe symptoms. Show less
Sablerolles, R.S.G.; Lafeber, M.; Kempen, J.A.L. van; Loo, B.P.A. van de; Boersma, E.; Rietdijk, W.J.R.; ... ; COMET Res Team 2021
Background During the COVID-19 pandemic, the scarcity of resources has necessitated triage of critical care for patients with the disease. In patients aged 65 years and older, triage decisions are... Show moreBackground During the COVID-19 pandemic, the scarcity of resources has necessitated triage of critical care for patients with the disease. In patients aged 65 years and older, triage decisions are regularly based on degree of frailty measured by the Clinical Frailty Scale (CFS). However, the CFS could also be useful in patients younger than 65 years. We aimed to examine the association between CFS score and hospital mortality and between CFS score and admission to intensive care in adult patients of all ages with COVID-19 across Europe.Methods This analysis was part of the COVID Medication (COMET) study, an international, multicentre, retrospective observational cohort study in 63 hospitals in 11 countries in Europe. Eligible patients were aged 18 years and older, had been admitted to hospital, and either tested positive by PCR for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) or were judged to have a high clinical likelihood of having SARS-CoV-2 infection by the local COVID-19 expert team. CFS was used to assess level of frailty: fit (CFS1-3), mildly frail (CFS4-5), or frail (CFS6-9). The primary outcome was hospital mortality. The secondary outcome was admission to intensive care. Data were analysed using a multivariable binary logistic regression model adjusted for covariates (age, sex, number of drugs prescribed, and type of drug class as a proxy for comorbidities).Findings Between March 30 and July 15, 2020, 2434 patients (median age 68 years [IQR(55-77)]; 1480 [61%] men, 954 [30%] women) had CFS scores available and were included in the analyses. In the total sample and in patients aged 65 years and older, frail patients and mildly frail patients had a significantly higher risk of hospital mortality than fit patients (total sample: CFS6-9 vs CFS1-3 odds ratio [OR] 2.71 [95% CI 2.04-3.60], p<0.0001 and CFS4-5 vs CFS1-3 OR 1.54 [1.16-2.06], p=0.0030; age >= 65 years: CFS6-9 vs CFS1-3 OR 2.90 [2.12-3.97], p<0.0001 and CFS4-5 vs CFS1-3 OR 1.64 [1.20-2.25], p=0.0020). In patients younger than 65 years, an increased hospital mortality risk was only observed in frail patients (CFS6-9 vs CFS1-3 OR 2.22 [1.08-4.57], p=0.030; CFS4-5 vs CFS1-3 OR 1.08 [0.48-2.39], p=0.86). Frail patients had a higher incidence of admission to intensive care than fit patients (CFS6-9 vs CFS1-3 OR 1.54 [1.21-1.97], p=0.0010), whereas mildly frail patients had a lower incidence than fit patients (CFS4-5 vs CFS1-3 OR 0.71 [0.55-0.92], p=0.0090). Among patients younger than 65 years, frail patients had an increased incidence of admission to intensive care (CFS6-9 vs CFS1-3 OR 2.96 [1.98-4.43], p<0.0001), whereas mildly frail patients had no significant difference in incidence compared with fit patients (CFS4-5 vs CFS1-3 OR 0.93 [0.63-1.38], p=0.72). Among patients aged 65 years and older, frail patients had no significant difference in the incidence of admission to intensive care compared with fit patients (CFS6-9 vs CFS1-3 OR 1.27 [0.92-1.75], p=0.14), whereas mildly frail patients had a lower incidence than fit patients (CFS4-5 vs CFS1-3 OR 0.66 [0.47-0.93], p=0.018).Interpretation The results of this study suggest that CFS score is a suitable risk marker for hospital mortality in adult patients with COVID-19. However, treatment decisions based on the CFS in patients younger than 65 years should be made with caution. Copyright (C) 2021 The Author(s). Published by Elsevier Ltd. Show less
