Comprehensive Geriatric Assessment, Treatment Decisions, and Outcomes in Older Patients Eligible for Pancreatic Surgery.

INTRODUCTION: Periampullary cancer has a poor prognosis. Surgical resection is a potentially curative but high-risk treatment. Comprehensive geriatric assessment (CGA) can inform treatment decisions, but has not yet been evaluated in older patients eligible for pancreatic surgery. METHODS: This prospective observational study included patients ≥ 70 years of age eligible for pancreatic surgery. Frailty was defined as impairment in at least two of five domains: somatic, psychological, functional, nutritional, and social. Outcomes included postoperative complications, functional decline, and mortality. RESULTS: Of the 88 patients included, 87 had a complete CGA. Sixty-five patients (75%) were frail and 22 (25%) were non-frail. Frail patients were more likely to receive nonsurgical treatment (43.1% vs. 9.1% p = 0.004). Fifty-seven patients underwent surgery, of which 52 (59%) underwent pancreaticoduodenectomy. The incidence of postoperative delirium was three times higher in frail patients (29.7% vs. 0%, p = 0.005). The risk of mortality was three times higher in frail patients (HR: 3.36, 95% CI: 1.43-7.89, p = 0.006). CONCLUSION: Frailty is common in older patients eligible for pancreatic surgery and is associated with treatment decision, a higher incidence of delirium and a three times higher risk of all-cause mortality. CGA can contribute to shared decision-making and optimize perioperative care in older patients.

The association of inflammatory markers with frailty and in-hospital mortality in older COVID-19 patients.

INTRODUCTION: During the COVID19 pandemic, older patients hospitalized for COVID-19 exhibited an increased mortality risk compared to younger patients. While ageing is associated with compromised immune responses and frailty, their contributions and interplay remain understudied. This study investigated the association between inflammatory markers and mortality and potential modification by frailty among older patients hospitalized for COVID-19. METHODS: Data were from three multicenter Dutch cohorts (COVID-OLD, CliniCo, Covid-Predict). Patients were 70 years or older, hospitalized for COVID-19and categorized into three frailty groups: fit (Clinical frailty score (CFS) 1-3), pre-frail (CFS 4-5), and frail (CFS 6-9). Immunological markers (lymphocyte count, neutrophil count, C-reactive protein, neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR) and systemic inflammation index (SII)) were measured at baseline. Associations with in hospital mortality were examined using logistic regression. RESULTS: A total of 1697 patients were included from COVID-OLD, 656 from Covid-Predict, and 574 from CliniCo. The median age was 79, 77, and 78 years for each cohort. Hospital mortality rates were 33 %, 27 % and 39 % in the three cohorts, respectively. A lower CRP was associated with a higher frailty score in all three cohorts (all p < 0.01). Lymphocyte count, neutrophil count, NLR, PLR, or SII, were similar across frailty groups. Higher CRP levels were associated with increased in-hospital mortality risk across all frailty groups, across all cohorts (OR (95 % CI), 2.88 (2.20-3.78), 3.15 (1.95-5.16), and 3.28 (1.87-5.92)), and frailty did not modify the association between inflammatory markers and in-hospital mortality (all p-interaction>0.05). CONCLUSION: While frailty is a significant factor in determining overall outcomes in older patients, our study suggests that the elevated risk of mortality in older patients with frailty compared to fit patients is likely not explained by difference in inflammatory responses.

Selecting the right treatment: Health outcome priorities in older patients with bladder cancer.

INTRODUCTION: Selecting the appropriate treatment for older patients with non-muscle invasive (NMIBC) or muscle-invasive bladder cancer (MIBC) is challenging due to smoking-related comorbidities, treatment toxicity, and an increased risk of adverse health outcomes. Considering patient preferences prior to treatment is therefore crucial. Here, we aimed to identify the health outcome priorities of older patients with high-risk NMIBC (HR-NMIBC) or MIBC. MATERIALS AND METHODS: Patients aged 70 years or older or at risk for frailty, diagnosed with HR-NMIBC or MIBC without distant metastases, were referred for a comprehensive geriatric assessment (CGA). The CGA consisted of an interview, physical examination, and several tests to examine physical, cognitive, functional, and social status. Quality of life was assessed using EQ5D and EORTC QLQ-C30 questionnaires. Health outcome priorities were discussed using the Outcome Prioritization Tool (OPT) and associations between health outcome priorities and CGA-determinants and quality of life were studied. RESULTS: Of 146 patients (14 HR-NMIBC, 132 MIBC), OPT data was available for 139. Life extension was most often prioritized (44%), closely followed by preserving independence (40%). Reducing pain (7%) and other symptoms (9%) were less often prioritized. Patients prioritizing life extension had fewer musculoskeletal problems than patients prioritizing reducing pain or other symptoms (p = 0.02). Patients at risk of or suffering from malnutrition more frequently selected reducing pain or other symptoms as their health outcome priority (p = 0.004). For all other CGA-determinants and quality of life, there were no significant differences between groups based on health outcome priorities. DISCUSSION: In older patients with HR-NMIBC and MIBC, life extension and preserving independence are the most common health outcomes priorities. CGA-determinants and quality of life are generally not associated with the prioritization of health outcomes. As health outcome priorities cannot be predicted by CGA-determinants or quality of life, it is crucial to discuss health outcome priorities with patients to promote shared decision-making.

Creatinine, cystatin C, muscle mass, and mortality: Findings from a primary and replication population-based cohort.

BACKGROUND: Serum creatinine is used as initial test to derive eGFR and confirmatory testing with serum cystatin C is recommended when creatinine-based eGFR is considered less accurate due to deviant muscle mass. Low muscle mass is associated with increased risk of premature mortality. However, the associations of serum creatinine and cystatin C with muscle mass and mortality remain unclear and require further investigation to better inform clinical decision-making. METHODS: We included 8437 community-dwelling adults enrolled in the Dutch PREVEND study and 5033 in the US NHANES replication cohort. Associations of serum creatinine and/or cystatin C with muscle mass surrogates and mortality were quantified with linear and Cox proportional hazards regression, respectively. Missing observations in covariates were multiply imputed using Substantive Model Compatible Fully Conditional Specification. RESULTS: Mean (SD) age of PREVEND and NHANES participants (50% and 48% male) were 49.8 (12.6) and 48.7 (18.7) years, respectively. Median (Q1-Q3) serum creatinine and cystatin C were 71 (61-80) and 80 (62-88) µmol/L and 0.87 (0.78-0.98) and 0.91 (0.80-1.10) mg/L, respectively. Higher serum creatinine was associated with greater muscle mass, while serum cystatin C was not associated with muscle mass. Adjusting both markers for each other strengthened the positive relationship between serum creatinine and muscle mass and revealed an inverse association between serum cystatin C and muscle mass. In the PREVEND cohort, 1636 (19%) deaths were registered over a median follow-up of 12.9 (5.8-16.3) years with a 10-year mortality rate (95% CI) of 7.6% (7.1-8.2%). In the NHANES, 1273 (25%) deaths were registered over a median follow-up of 17.9 (17.3-18.5) years with a 10-year mortality rate of 13.8% (12.8-14.7%). Both markers were associated with increased mortality. Notably, when adjusted for each other, higher serum creatinine was associated with decreased mortality, while the association between serum cystatin C and increased mortality strengthened. The shapes of the associations in the PREVEND study and NHANES were almost identical. CONCLUSIONS: The strong association between serum creatinine and muscle mass challenges its reliability as GFR marker, necessitating a more cautious approach in its clinical use. The minimal association between serum cystatin C and muscle mass supports its increased use as a more reliable alternative in routine clinical practice.

Preparing for future pandemics: frailty associates with mortality in hospitalised older people during the entire COVID-19 pandemic, a Dutch multicentre cohort study.

PURPOSE: Viral mutations and improved prevention or treatment options may have changed the association of frailty with mortality throughout the COVID-19 pandemic. We investigated how associations of frailty with in-hospital mortality changed throughout the pandemic in older people hospitalised for COVID-19. METHODS: The COVID-OLD study included COVID-19 patients aged ≥ 70 years hospitalised during the first (early 2020), second (late 2020), third (late 2021) or fourth wave (early 2022). Based on the clinical frailty scale, patients were categorised as fit (1-3), pre-frail (4-5) or frail (6-9). Associations of frailty with in-hospital mortality were assessed with pairwise comparisons with fit as reference category and modelled using binary logistic regression adjusted for age and sex. RESULTS: This study included 2362 patients (mean age 79.7 years, 60% men). In the first wave, in-hospital mortality was 46% in patients with frailty and 27% in fit patients. In-hospital mortality decreased in each subsequent wave to 25% in patients with frailty and 11% in fit patients in the fourth wave. After adjustments, an overall higher risk of in-hospital mortality was found in frail (OR 2.26, 95% CI: 1.66-3.07) and pre-frail (OR 1.73, 95% CI: 1.27-2.35) patients compared to fit patients, which did not change over time (p for interaction = 0.74). CONCLUSIONS: Frailty remained associated with a higher risk of in-hospital mortality throughout the entire COVID-19 pandemic, although overall in-hospital mortality rates decreased. Frailty therefore remains a relevant risk factor in all stages of a pandemic and is important to consider in prevention and treatment guidelines for future pandemics.

Differences in characteristics and outcomes of older patients hospitalized for COVID-19 after introduction of vaccination.

PURPOSE: The aim of the present study was to investigate characteristics and outcomes in vaccinated and unvaccinated older patients hospitalized for COVID-19 infection. METHODS: A retrospective multicentre cohort study among patients aged ≥70 years hospitalized for COVID-19 infection. RESULTS: 263 vaccinated and 82 unvaccinated patients were included. Vaccinated patients were older (median age 79 vs. 76 years; p < 0.001), more patients were male (66.2% vs. 53.7%; p = 0.040), had more comorbidities [median Charlson Comorbidity Index (CCI) 2 vs. 1; p 0.016] and were frailer [Clinical Frailty Scale (CFS) ≥ 4 68% vs. 49%; p 0.015]. Vaccinated patients were admitted earlier after symptom onset (median 5 days vs. 7 days) but were equally ill at time of hospital admission. After correction for frailty, comorbidity and disease severity, risk of in-hospital mortality was three times lower for vaccinated patients (HR 0.30 95% CI 0.16-0.56; p < 0.001) compared to unvaccinated patients. CONCLUSION: Vaccinated patients had lower risk of in-hospital mortality than unvaccinated patients with COVID-19 infection. These findings suggest that vaccinated patients benefit from the protective effect of the vaccine against death during hospital stay, outweighing the increased mortality risk that is associated with older age, greater frailty and more numerous comorbidities. This could be an encouragement for older people to receive age-appropriate vaccines, although no definite conclusions can be drawn for this was no intervention study.

Older people's goals of care in relation to frailty status-the COOP-study.

BACKGROUND: Literature relating older people's goals of care to their varying frailty status is scarce. OBJECTIVE: To investigate goals of care in case of acute and/or severe disease in relationship to frailty status among the general older population. METHOD: Older people aged ≥70 in the Netherlands completed a questionnaire. They were divided into three subgroups based on a self-reported Clinical Frailty Scale: fit (CFS 1-3), mildly frail (CFS 4-5) and severely frail (CFS 6-8). Seven goals were graded as unimportant (1-5), somewhat important (6-7) or very important (8-10): extending life, preserving quality of life (QoL), staying independent, relieving symptoms, supporting others, preventing hospital admission and preventing nursing home admission. RESULTS: Of the 1,278 participants (median age 76 years, 63% female), 57% was fit, 32% mildly frail and 12% severely frail. Overall, participants most frequently considered preventing nursing home admission as very important (87%), followed by staying independent (84%) and preserving QoL (83%), and least frequently considered extending life as very important (31%). All frailty subgroups reported similar preferences out of the surveyed goals as the overall study population. However, participants with a higher frailty status attached slightly less importance to each individual goal compared with fit participants (Ptrend-values ≤ 0.037). CONCLUSION: Preferred goals of care are not related to frailty status, while the importance ascribed to individual goals is slightly lower with higher frailty status. Future research should prioritise outcomes related to the shared goals of fit, mildly frail and severely frail older people to improve personalised medicine for older patients.

External validation of six COVID-19 prognostic models for predicting mortality risk in older populations in a hospital, primary care, and nursing home setting.

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, 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 0.24-0.81, and C-statistic 0.55-0.71 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 0.24-0.81 indicating signs of overfitting, and C-statistic of 0.55-0.71. 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.

Limited incremental predictive value of the frailty index and other vulnerability measures from routine care data for mortality risk prediction in older patients with COVID-19 in primary care.

BACKGROUND: During 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. METHODS: From 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. RESULTS: Of 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. CONCLUSION: In 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.

Delirium in older patients with COVID-19: Prevalence, risk factors and clinical outcomes across the first three waves of the pandemic.

OBJECTIVES: Delirium 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. METHODS: This 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. RESULTS: 1540, 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. CONCLUSION: Delirium 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.

Cardiovascular Risk Management for All Older Patients?

Current guidelines on cardiovascular risk management are extrapolated to all older adults. It is, however, highly debatable whether recommendations also apply for patients with dementia since previous studies have not included this specific population. Time to benefit as well as higher risk of adverse events play a crucial role in the decision process of prescribing or deprescribing. Regular monitoring is needed in older patients with dementia, in order to make individual-based treatment strategies. Cardiovascular risk management in older patients with dementia should focus on quality of life, preventing cognitive and functional deterioration, and maintaining independence.

Epigenetic and Metabolomic Biomarkers for Biological Age: A Comparative Analysis of Mortality and Frailty Risk.

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. 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.

Frailty in Non-geriatric Patients With Head and Neck cancer.

OBJECTIVE: Patients with head and neck cancer (HNC) are characterized by a poor lifestyle and comorbidity. The Geriatric 8 (G8) is an established screening tool to identify frail older patients with cancer. However, studies evaluating frailty in younger HNC patients are lacking. The aim of this study is to evaluate if the G8 can identify frailty and if it is related to mortality in younger HNC patients. STUDY DESIGN: Case-control study design. SETTING: Tertiary cancer center. METHODS: We studied patients <70 years with HNC. Patients with G8 ≤ 14 were considered frail. Patients were matched to nonfrail (G8 > 14) control patients. Patients were matched according to sex, age, smoking, tumor location, and period of first consultation. Baseline health characteristics were compared between frail patients and nonfrail controls. Second, the treatment plan and adverse outcomes were compared. RESULTS: Forty-five patients with G8 ≤ 14 were included and matched to 90 nonfrail controls. The median follow-up time was 357 days. Frail patients had a significantly lower body mass index and level of education, a worse World Health Organization performance status, and reported lower experienced overall health. 28.9% of the frail patients died after 1 year versus 10% of the nonfrail control patients (hazard ratio: 3.87 [95% confidence interval: 1.32-11.36], p = 0.014). CONCLUSION: The G8 is a valid screening tool to identify frail patients in younger HNC patients.

A study protocol of external validation of eight COVID-19 prognostic models for predicting mortality risk in older populations in a hospital, primary care, and nursing home setting.

BACKGROUND: The COVID-19 pandemic has a large impact worldwide and is known to particularly affect the older population. This paper outlines the protocol for external validation of prognostic models predicting mortality risk after presentation with COVID-19 in the older population. These prognostic models were originally developed in an adult population and will be validated in an older population (≥ 70 years of age) in three healthcare settings: the hospital setting, the primary care setting, and the nursing home setting. METHODS: Based on a living systematic review of COVID-19 prediction models, we identified eight prognostic models predicting the risk of mortality in adults with a COVID-19 infection (five COVID-19 specific models: GAL-COVID-19 mortality, 4C Mortality Score, NEWS2 + model, Xie model, and Wang clinical model and three pre-existing prognostic scores: APACHE-II, CURB65, SOFA). These eight models will be validated in six different cohorts of the Dutch older population (three hospital cohorts, two primary care cohorts, and a nursing home cohort). All prognostic models will be validated in a hospital setting while the GAL-COVID-19 mortality model will be validated in hospital, primary care, and nursing home settings. The study will include individuals ≥ 70 years of age with a highly suspected or PCR-confirmed COVID-19 infection from March 2020 to December 2020 (and up to December 2021 in a sensitivity analysis). The predictive performance will be evaluated in terms of discrimination, calibration, and decision curves for each of the prognostic models in each cohort individually. For prognostic models with indications of miscalibration, an intercept update will be performed after which predictive performance will be re-evaluated. DISCUSSION: Insight into the performance of existing prognostic models in one of the most vulnerable populations clarifies the extent to which tailoring of COVID-19 prognostic models is needed when models are applied to the older population. Such insight will be important for possible future waves of the COVID-19 pandemic or future pandemics.

Atypical presentation of COVID-19 in older patients is associated with frailty but not with adverse outcomes.

PURPOSE: Older 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. METHODS: We 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. RESULTS: We 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]. CONCLUSIONS: In 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.

A prospective, multicentre study to assess frailty in elderly patients with leg ulcers (GERAS study).

BACKGROUND: Although leg ulcers are a burdensome disease most common in those aged 65 years and older, frailty in this population has not yet been well established. OBJECTIVES: The aim of this study was to prospectively explore and compare the presence of frailty in elderly patients with chronic leg or foot ulcers by applying different validated frailty screening methods in three healthcare settings and to assess the feasibility of frailty screening. METHODS: We compared frailty of leg ulcer patients referred to an academic hospital with a non-academic hospital, leg ulcer patients receiving (primary) homecare, and a dermato-oncology patient population (control group). Frailty and quality of life were assessed using four validated questionnaires: the Groninger Frailty Indicator, Geriatric-8, Mini-Cog and Wound Quality of Life. To analyse data multiple (non)-parametric tests were performed. RESULTS: Fifty of 60 included leg ulcer patients (83%) scored "frail" on at least one frailty questionnaire (GFI, G8 or Mini-Cog). The number of patients scoring "frail" on two or three out of three applied frailty questionnaires were significantly higher in the academic and homecare ulcer population compared with the non-academic ulcer population and control group (p = 0.002). In the academic ulcer population mean Wound Quality of Life scores were 30.2 (SD 17.6), compared with 17.7 (SD 13.1) in the non-academic and 15.0 (SD 10.4) in the homecare ulcer population (p = 0.002). CONCLUSION: The majority of patients suffering from leg ulcers in this study was frail. The highest frailty prevalence was observed in the academic and homecare ulcer populations. The largest impaired quality of life was reported in the academic ulcer population. In dermatology practice, implementing frailty screening and initiating appropriate (paramedical) supportive care should be considered to improve patient outcomes.

Inflammaging and Blood Pressure Profiles in Late Life: The Screening for CKD among Older People across Europe (SCOPE) Study.

The neutrophil-to-lymphocyte ratio (NLR) is a marker for systemic inflammation. Since inflammation plays a relevant role in vascular aging, the aim of this study was to investigate whether NLR is associated with blood pressure profiles in older adults. This study was performed within the framework of the SCOPE study including 2461 outpatients aged 75 years and over. Mean blood pressure values, namely systolic blood pressure (SBP), diastolic blood pressure (DBP) and pulse pressure (PP) were investigated across tertiles of NLR. Change in blood pressure levels in 2 years of follow-up were compared across categories of baseline NLR. Data of 2397 individuals were used, of which 1854 individuals had hypertension. Mean values of blood pressure did not differ across categories of baseline NLR in individuals without hypertension. Individuals with hypertension with a high-range NLR had lower SBP and PP when compared to those in low-range NLR (mean difference SBP -2.94 mmHg, p = 0.032 and PP -2.55 mmHg, p = 0.030). Mean change in blood pressure in 2 years did only slightly differ in non-clinically relevant ranges, when compared across tertiles of baseline NLR. NLR as a marker of inflammaging was not associated with unfavorable blood pressure profiles in older individuals with or without hypertension.

Delirium in older COVID-19 patients: Evaluating risk factors and outcomes.

OBJECTIVES: A high incidence of delirium has been reported in older patients with Coronavirus disease 2019 (COVID-19). We aimed to identify determinants of delirium, including the Clinical Frailty Scale, in hospitalized older patients with COVID-19. Furthermore, we aimed to study the association of delirium independent of frailty with in-hospital outcomes in older COVID-19 patients. METHODS: This study was performed within the framework of the multi-center COVID-OLD cohort study and included patients aged ≥60 years who were admitted to the general ward because of COVID-19 in the Netherlands between February and May 2020. Data were collected on demographics, co-morbidity, disease severity, and geriatric parameters. Prevalence of delirium during hospital admission was recorded based on delirium screening using the Delirium Observation Screening Scale (DOSS) which was scored three times daily. A DOSS score ≥3 was followed by a delirium assessment by the ward physician In-hospital outcomes included length of stay, discharge destination, and mortality. RESULTS: A total of 412 patients were included (median age 76, 58% male). Delirium was present in 82 patients. In multivariable analysis, previous episode of delirium (Odds ratio [OR] 8.9 [95% CI 2.3-33.6] p = 0.001), and pre-existent memory problems (OR 7.6 [95% CI 3.1-22.5] p < 0.001) were associated with increased delirium risk. Clinical Frailty Scale was associated with increased delirium risk (OR 1.63 [95%CI 1.40-1.90] p < 0.001) in univariable analysis, but not in multivariable analysis. Patients who developed delirium had a shorter symptom duration and lower levels of C-reactive protein upon presentation, whereas vital parameters did not differ. Patients who developed a delirium had a longer hospital stay and were more often discharged to a nursing home. Delirium was associated with mortality (OR 2.84 [95% CI1.71-4.72] p < 0.001), but not in multivariable analyses. CONCLUSIONS: A previous delirium and pre-existent memory problems were associated with delirium risk in COVID-19. Delirium was not an independent predictor of mortality after adjustment for frailty.

Muscle mass and estimates of renal function: a longitudinal cohort study.

BACKGROUND: Creatinine is the most widely used test to estimate the glomerular filtration rate (GFR), but muscle mass as key determinant of creatinine next to renal function may confound such estimates. We explored effects of 24-h height-indexed creatinine excretion rate (CER index) on GFR estimated with creatinine (eGFRCr ), muscle mass-independent cystatin C (eGFRCys ), and the combination of creatinine and cystatin C (eGFRCr-Cys ) and predicted probabilities of discordant classification given age, sex, and CER index. METHODS: We included 8076 adults enrolled in the PREVEND study. Discordant classification was defined as not having eGFRCr  <60 mL/min per 1.73 m2 when eGFRCys was <60 mL/min/1.73 m2 . Baseline effects of age and sex on CER index were quantified with linear models using generalized least squares. Baseline effects of CER index on eGFR were quantified with quantile regression and logistic regression. Effects of annual changes in CER index on trajectories of eGFR were quantified with linear mixed-effects models. Missing observations in covariates were multiply imputed. RESULTS: Mean (SD) CER index was 8.0 (1.7) and 6.1 (1.3) mmol/24 h per meter in male and female participants, respectively (Pdifference  < 0.001). In male participants, baseline CER index increased until 45 years of age followed by a gradual decrease, whereas a gradual decrease across the entire range of age was observed in female participants. For a 70-year-old male participant with low muscle mass (CER index of 2 mmol/24 h per meter), predicted baseline eGFRCr and eGFRCys disagreed by 24.7 mL/min/1.73 m2 (and 30.1 mL/min/1.73 m2 when creatinine was not corrected for race). Percentages (95% CI) of discordant classification in male and female participants aged 60 years and older with low muscle mass were 18.5% (14.8-22.1%) and 15.2% (11.4-18.5%), respectively. For a 70-year-old male participant who lost muscle during follow-up, eGFRCr and eGFRCys disagreed by 1.5, 5.0, 8.5, and 12.0 mL/min/1.73 m2 (and 6.7, 10.7, 13.5, and 15.9 mL/min/1.73 m2 when creatinine was not corrected for race) at baseline, 5 years, 10 years, and 15 years of follow-up, respectively. CONCLUSIONS: Low muscle mass may cause considerable overestimation of single measurements of eGFRCr . Muscle wasting may cause spurious overestimation of repeatedly measured eGFRCr . Implementing muscle mass-independent markers for estimating renal function, like cystatin C as superior alternative to creatinine, is crucial to accurately assess renal function in settings of low muscle mass or muscle wasting. This would also eliminate the negative consequences of current race-based approaches.

The Multidimensional Prognostic Index Predicts Mortality in Older Outpatients with Cognitive Decline.

Since the heterogeneity of the growing group of older outpatients with cognitive decline, it is challenging to evaluate survival rates in clinical shared decision making. The primary outcome was to determine whether the Multidimensional Prognostic Index (MPI) predicts mortality, whilst assessing the MPI distribution was considered secondary. This retrospective chart review included 311 outpatients aged ≥65 years and diagnosed with dementia or mild cognitive impairment (MCI). The MPI includes several domains of the comprehensive geriatric assessment (CGA). All characteristics and data to calculate the risk score and mortality data were extracted from administrative information in the database of the Alzheimer's Center and medical records. The study population (mean age 76.8 years, men = 51.4%) was divided as follows: 34.1% belonged to MPI category 1, 52.1% to MPI category 2 and 13.8% to MPI category 3. Patients with dementia have a higher mean MPI risk score than patients with MCI (0.47 vs. 0.32; p < 0.001). The HRs and corresponding 95% CIs for mortality in patients in MPI categories 2 and 3 were 1.67 (0.81−3.45) and 3.80 (1.56−9.24) compared with MPI category 1, respectively. This study shows that the MPI predicts mortality in outpatients with cognitive decline.