Association between complete blood count-derived inflammatory markers and the risk of frailty and mortality in middle-aged and older adults.

Objective: This study aimed to evaluate the association between six complete blood count (CBC)-derived inflammatory markers [neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), platelet-to-lymphocyte ratio (PLR), systemic immune-inflammatory index (SII), systemic inflammatory response index (SIRI), and pan-immune inflammation value (PIV)] and the risk of frailty and mortality. Methods: Data were obtained from the National Health and Nutrition Examination Survey (NHANES) 1999-2018. Mortality was identified using the National Death Index until December 31, 2019. Multiple logistic regression analysis was conducted to evaluate the association between six CBC-derived inflammatory markers and frailty. The Cox regression model assessed the association between six CBC-derived inflammatory markers and mortality in frail populations. Restricted cubic spline (RCS) was used to visualize the association of the six CBC-derived inflammatory markers with mortality risk. The predictive value of CBC-derived inflammatory markers for mortality was further assessed using a random survival forest (RSF) approach. Results: This study analyzed data from a total of 16,705 middle-aged and older participants. Among them, 6,503 participants were frail, with a mortality rate of 41.47%. Multiple logistic regression analysis showed that NLR, MLR, PLR, SII, SIRI, and PIV were positively associated with frailty risk. The Cox regression model revealed that participants in the highest quartile had a significantly increased risk of death compared to those in the lowest quartile: NLR (HR = 1.73, 95% CI:1.54, 1.94), MLR (HR = 1.71, 95% CI:1.51, 1.93), PLR (HR = 1.28, 95%CI: 1.15, 1.43), SII (HR = 1.50, 95%CI:1.34, 1.68), SIRI (HR = 1.88, CI 95%:1.67, 2.12), PIV (HR = 1.55, 95%CI:1.38, 1.73). Random survival forest (RSF) analyses demonstrated that MLR had the highest predictive value for mortality risk middle-aged and older adult frail participants. Conclusion: The results suggest that CBC-derived inflammatory markers are associated with a higher risk of frailty as well as mortality in the middle and old-aged population of the United States.

Comparison of two different frailty screening scales for predicting mortality due to all causes in older inpatients.

OBJECTIVE: This study examines the relationship between two frailty screening tools and 90-day all-cause mortality in geriatric inpatients. METHODS: The study included patients aged ≥60 years who were admitted to the geriatrics unit of a university hospital between June 2021 and August 2022 and whose mortality status and duration of hospitalization data were obtained from the Health Ministry System. During hospitalization, the patients were screened using two different frailty scales: the Simpler Modified Fried Frailty Scale (sMFS) and the Clinical Frailty Scale (CFS). Patients scoring ≥5 on the CFS and ≥3 on the sMFS were considered frail. RESULTS: A total of 84 participants with a mean age of 78.3±7.6 years were included in this study, of which 36.9% were male. Of the total, 60.7% and 89.3% were considered frail according to the CFS and sMFS, respectively, and the prevalence of all-cause mortality within 90 days was 19%. A univariate analysis using the Kaplan-Meier survival method revealed CFS scores to be statistically significantly related to 90-day all-cause mortality (p<0.001), while sMFS scores were not found to be statistically significant (p=0.849). Furthermore, a statistically significant relationship was identified between CFS score and all-cause mortality in multivariate analysis with Cox regression analysis [(p<0.001), hazard ratio (HR): 3.078; (95% confidence interval: 1.746-5.425)]. CONCLUSION: An evaluation of frailty in hospitalized older adults using two different scales revealed the CFS to be superior to the sMFS in predicting all-cause mortality within 90 days.

Measuring Frailty Using Self-Report or Automated Tools to Identify Risk of Cardiovascular Events and Mortality: The Million Veteran Program.

BACKGROUND: Frailty, a syndrome of physiologic vulnerability, increases cardiovascular disease (CVD) risk. Whether in person or automated frailty tools are ideal for identifying CVD risk remains unclear. We calculated 3 distinct frailty scores and examined their associations with mortality and CVD events in the Million Veteran Program, a prospective cohort of nearly 1 million US veterans. METHODS AND RESULTS: Veterans aged ≥50 years and enrolled from 2011 to 2018 were included. Two frailty indices (FI) based on the deficit accumulation theory were calculated: the questionnaire-based 36-item Million Veteran Program-FI and 31-item Veterans Affairs-FI using claims data. We calculated Fried physical frailty using the self-reported, 3-item Study of Osteoporotic Fractures. Multivariable-adjusted Cox models examined the association of frailty by each score with primary (all-cause and CVD mortality) and secondary (myocardial infarction, stroke, and heart failure) outcomes. In 190 688 veterans (69±9 years, 94% male, 85% White), 33, 233 (17%) all-cause and 10 115 (5%) CVD deaths occurred. Using Million Veteran Program-FI, 29% were robust, 42% pre-frail, and 29% frail. Frailty prevalence increased by age group (27% in 50-59 to 42% in ≥90 years). Using the Million Veteran Program-FI, over 6±2 years, frail veterans had a higher hazard of all-cause (hazard ratio [HR], 3.05 [95% CI, 2.95-3.16]) and CVD mortality (HR, 3.65 [95% CI, 3.43-3.90]). Findings were concordant for the Veterans Affairs-FI and Study of Osteoporotic Fractures frailty definitions, and remained significant even among younger veterans aged 50-59 years. CONCLUSIONS: Irrespective of frailty measure, frailty is associated with a higher risk of all-cause mortality and adverse CVD events. Further study of frailty in veterans aged <60 years old is warranted.

The association between frailty and the risk of mortality in critically ill congestive heart failure patients: findings from the MIMIC-IV database.

Background: Frailty is a severe, common co-morbidity associated with congestive heart failure (CHF). This retrospective cohort study assesses the association between frailty and the risk of mortality in critically ill CHF patients. Methods: Eligible patients with CHF from the Medical Information Base for Intensive Care IV database were retrospectively analyzed. The frailty index based on laboratory tests (FI_Lab) index was calculated using 33 variables to assess frailty status. The primary outcomes were in-hospital mortality and one-year mortality. The secondary outcomes were the incidence of acute kidney injury (AKI) and the administration of renal replacement therapy (RRT) in patients with concurrent AKI. Survival disparities among the FI_Lab subgroups were estimated with Kaplan-Meier survival analysis. The association between the FI_Lab index and mortality was examined with Cox proportional risk modeling. Results: A total of 3273 adult patients aged 18 years and older were enrolled in the study, with 1820 men and 1453 women included. The incidence rates of in-hospital mortality and one-year mortality rate were 0.96 per 1,000 person-days and 263.8 per 1,000 person-years, respectively. Multivariable regression analysis identified baseline FI_Lab > 0.45 as an independent risk factor predicting in-hospital mortality (odds ratio = 3.221, 95% CI 2.341-4.432, p < 0.001) and one-year mortality (hazard ratio=2.152, 95% CI: 1.730-2.678, p < 0.001). In terms of predicting mortality, adding FI_Lab to the six disease severity scores significantly improved the overall performance of the model (all p < 0.001). Conclusions: We established a positive correlation between the baseline FI_Lab and the likelihood of adverse outcomes in critical CHF patients. Given its potential as a reliable prognostic tool for such patients, further validation of FI_Lab across multiple centers is recommended for future research.

The effect of frailty on mortality and hospital admission in patients with benign pleural disease in Wales: a cohort study.

BACKGROUND: Pleural disease is common, representing 5% of the acute medical workload, and its incidence is rising, partly due to the ageing population. Frailty is an important feature and little is known about disease progression in patients with frailty and pleural disease. We aimed to examine the effect of frailty on mortality and other relevant outcomes in patients diagnosed with pleural disease. METHODS: In this cohort study in Wales, the national Secure Anonymised Information Linkage databank was used to identify a cohort of individuals diagnosed with non-malignant pleural disease between Jan 1, 2005, and March 1, 2023, who were not known to have left Wales. Frailty was assessed at diagnosis of pleural disease using an electronic Frailty Index. The primary outcome was time from diagnosis to all-cause mortality for all patients. Data were analysed using multilevel mixed-effects Cox proportional hazards regression adjusting for the prespecified covariates of age, sex, Welsh Index of Multiple Deprivation quintile, smoking status, comorbidity, and subtype of pleural disease. FINDINGS: 54 566 individuals were included in the final sample (median age 66 years [IQR 47-77]; 26 477 [48·5%] were female and 28 089 [51·5%] were male). By the end of the study period, 25 698 (47·1%) participants had died, with a median follow-up of 1·0 years (IQR 0·2-3·6). There was an association between frailty and all-cause mortality, which increased as frailty worsened. Compared with fit individuals, there was increasing mortality for those with mild frailty (adjusted hazard ratio 1·11 [95% CI 1·08-1·15]; p<0·0001), moderate frailty (1·25 [1·20-1·31]; p<0·0001), and severe frailty (1·36 [1·28-1·44]; p<0·0001). INTERPRETATION: Independent of age and comorbidities, frailty status at diagnosis of pleural disease appeared to be useful as a prognostic indicator. Patients with moderate or severe frailty had a rapid decline in health. Future patients should be assessed for frailty at the time of diagnosis of pleural disease and might benefit from optimised care and advance care planning. FUNDING: Cardiff University's Wellcome Trust iTPA funding award.

Clinical trial results in context: comparison of baseline characteristics and outcomes of 38,510 RECOVERY trial participants versus a reference population of 346,271 people hospitalised with COVID-19 in England.

BACKGROUND: Randomised trials are essential to reliably assess medical interventions. Nevertheless, interpretation of such studies, particularly when considering absolute effects, is enhanced by understanding how the trial population may differ from the populations it aims to represent. METHODS: We compared baseline characteristics and mortality of RECOVERY participants recruited in England (n = 38,510) with a reference population hospitalised with COVID-19 in England (n = 346,271) from March 2020 to November 2021. We used linked hospitalisation and mortality data for both cohorts to extract demographics, comorbidity/frailty scores, and crude and age- and sex-adjusted 28-day all-cause mortality. RESULTS: Demographics of RECOVERY participants were broadly similar to the reference population, but RECOVERY participants were younger (mean age [standard deviation]: RECOVERY 62.6 [15.3] vs reference 65.7 [18.5] years) and less frequently female (37% vs 45%). Comorbidity and frailty scores were lower in RECOVERY, but differences were attenuated after age stratification. Age- and sex-adjusted 28-day mortality declined over time but was similar between cohorts across the study period (RECOVERY 23.7% [95% confidence interval: 23.3-24.1%]; vs reference 24.8% [24.6-25.0%]), except during the first pandemic wave in the UK (March-May 2020) when adjusted mortality was lower in RECOVERY. CONCLUSIONS: Adjusted 28-day mortality in RECOVERY was similar to a nationwide reference population of patients admitted with COVID-19 in England during the same period but varied substantially over time in both cohorts. Therefore, the absolute effect estimates from RECOVERY were broadly applicable to the target population at the time but should be interpreted in the light of current mortality estimates. TRIAL REGISTRATION: ISRCTN50189673- Feb. 04, 2020, NCT04381936- May 11, 2020.

Frailty and its association with long-term mortality among community-dwelling older adults aged 75 years and over.

BACKGROUND: Frailty, a significant risk factor for adverse outcomes and mortality, poses an emerging challenge with profound implications for public health and clinical practice. The measurement of frailty offers potential enhancements in healthcare services for older adults. The prevalence of frailty and its association with long-term mortality in a nationwide, unselected population of community-dwelling older adults, particularly those aged 75 and over, has not been previously studied on a large scale in Israel. METHODS: A retrospective cohort study was conducted at Meuhedet Health Maintenance Organization, Israel's third largest healthcare service provider, serving 1,276,000 people (13.8% of Israelis). The prevalence of frailty and its association with all-cause mortality were studied among older adults aged 75 years and over who were followed for 2-8 years. Frailty, defined by the cumulative deficit method, utilized clinical data from the preceding 10-year period, comprising 28 chronic diseases and age-related health deficits. RESULTS: The cohort included 43,737 older adults, with a median age of 77 years (IQR 75-82 years); among them, 19,300 (44.1%) were males. Overall, 19,396 (44.3%) older adults were frail: 12,260 (28.0%) mildly frail, 5,533 (12.7%) moderately frail and 1,603 (3.7%) severely frail. During the follow-up period 15,064 (34.4%) older adults died: 4,782 (39.0%) mildly frail, 3,016 (54.5%) moderately frail and 1,080 (67.4%) severely frail. Cox regression analysis demonstrated that mortality was associated with severe frailty (HR 2.63, 95%CI 2.45-2.80), moderate frailty (HR 2.05, 95%CI 1.96-2.14), and mild frailty (HR 1.45, 95%CI 1.39-1.51), independent of age, gender, and population sector. Among patients aged 90 years and over, no significant differences in cumulative survival were found between those with moderate and severe frailty (p = 0.408). CONCLUSIONS: Frailty is prevalent among community-dwelling Israeli older adults aged 75 years and over, and it is associated with long-term mortality. Considering its association with long-term mortality across frailty levels until the age of 90, early identification and intervention for frailty are recommended within this population. Policymakers should consider the use of the cumulative deficit method for evaluating frailty at both the population health and clinical levels.

The electronic frailty index and outcomes in patients with myocardial infarction.

BACKGROUND: Frailty is increasingly present in patients with acute myocardial infarction. The electronic Frailty Index (eFI) is a validated method of identifying vulnerable older patients in the community from routine primary care data. Our aim was to assess the relationship between the eFI and outcomes in older patients hospitalised with acute myocardial infarction. STUDY DESIGN AND SETTING: Retrospective cohort study using the DataLoch Heart Disease Registry comprising consecutive patients aged 65 years or over hospitalised with a myocardial infarction between October 2013 and March 2021. METHODS: Patients were classified as fit, mild, moderate, or severely frail based on their eFI score. Cox-regression analysis was used to determine the association between frailty category and all-cause mortality. RESULTS: In 4670 patients (median age 77 years [71-84], 43% female), 1865 (40%) were classified as fit, with 1699 (36%), 798 (17%) and 308 (7%) classified as mild, moderate and severely frail, respectively. In total, 1142 patients died within 12 months of which 248 (13%) and 147 (48%) were classified as fit and severely frail, respectively. After adjustment, any degree of frailty was associated with an increased risk of all-cause death with the risk greatest in the severely frail (reference = fit, adjusted hazard ratio 2.87 [95% confidence intervals 2.24 to 3.66]). CONCLUSION: The eFI identified patients at high risk of death following myocardial infarction. Automatic calculation within administrative data is feasible and could provide a low-cost method of identifying vulnerable older patients on hospital presentation.

High-Sensitivity Cardiac Troponin T and Frailty Predict Short-Term Mortality in Patients ≥75 Years Undergoing Emergency Abdominal Surgery: A Prospective Observational Study.

BACKGROUND: An elevated cardiac troponin concentration is a prognostic factor for perioperative cardiac morbidity and mortality. In elderly patients undergoing emergency abdominal surgery, frailty is a recognized risk factor, but little is known about the prognostic value of cardiac troponin in these vulnerable patients. Therefore, we investigated the prognostic significance of elevated high-sensitivity cardiac troponin T (hs-cTnT) concentration and frailty in a cohort of elderly patients undergoing emergency abdominal surgery. METHODS: We included consecutive patients ≥75 years of age who presented for emergency abdominal surgery, defined as abdominal pathology requiring surgery within 72 hours, in a university hospital in Norway. Patients who underwent vascular procedures or palliative surgery for inoperable malignancies were excluded. Preoperatively, frailty was assessed using the Clinical Frailty Scale (CFS), and blood samples were measured for hs-cTnT. We evaluated the predictive power of CFS and hs-cTnT concentrations using receiver operating characteristic (ROC) curves and Cox proportional hazard regression with 30-day mortality as the primary outcome. Secondary outcomes included (1) a composite of 30-day all-cause mortality and major adverse cardiac event (MACE), defined as myocardial infarction, nonfatal cardiac arrest, or coronary revascularization; and (2) 90-day mortality. RESULTS: Of the 210 screened and 156 eligible patients, blood samples were available in 146, who were included. Troponin concentration exceeded the 99th percentile upper reference limit (URL) in 83% and 89% of the patients pre- and postoperatively. Of the participants, 53% were classified as vulnerable or frail (CFS ≥4). The 30-day mortality rate was 12% (18 of 146). Preoperatively, a threshold of hs-cTnT ≥34 ng/L independently predicted 30-day mortality (hazard ratio [HR] 3.14, 95% confidence interval [CI], 1.13-9.45), and the composite outcome of 30-day mortality and MACE (HR 2.58, 95% CI, 1.07-6.49). In this model, frailty (continuous CFS score) also independently predicted 30-day mortality (HR 1.42, 95% CI, 1.01-2.00) and 30-day mortality or MACE (HR 1.37, 95% CI, 1.02-1.84). The combination of troponin and frailty, 0.14 × hs-cTnT +4.0 × CFS, yielded apparent superior predictive power (area under the receiver operating characteristics curve [AUC] 0.79, 95% CI, 0.68-0.88), compared to troponin concentration (AUC 0.69, 95% CI, 0.55-0.83) or frailty (AUC 0.69, 95% CI, 0.57-0.82) alone. CONCLUSIONS: After emergency abdominal surgery in elderly patients, increased preoperative troponin concentration and frailty were independent predictors of 30-day mortality. The combination of increased troponin concentration and frailty seemed to provide better prognostic information than troponin or frailty alone. These results must be validated in an independent sample.

Frailty Is More Predictive of Mortality than Age in Patients With Hip Fractures.

OBJECTIVES: To investigate the association between the Comprehensive Geriatric Assessment-based Frailty Index and adverse outcomes in older adult patients undergoing hip fracture surgery. DESIGN: Retrospective cohort study. SETTING: Academic Level 1 Trauma Center. PATIENTS: All patients aged 65 or older who underwent surgical repair of a hip fracture between May 2018 and August 2020 were identified through institutional database review. OUTCOME MEASURES AND COMPARISONS: Data including demographics, FI, injury presentation, and hospital course were collected. Patients were grouped by FI as nonfrail (FI < 0.21), frail (0.21 ≤ FI < 0.45), and severely frail (FI > 0.45). Adverse outcomes of these groups were compared using Kaplan Meier survival analysis. Risk factors for 1-year rehospitalization and 2-year mortality were evaluated using Cox hazard regression. RESULTS: Three hundred sixteen patients were included, with 62 nonfrail, 185 frail, and 69 severely frail patients. The total population was on average 83.8 years old, predominantly white (88.0%), and majority female (69.9%) with an average FI of 0.33 (SD: 0.14). The nonfrail cohort was on average 78.8 years old, 93.6% white, and 80.7% female; the frail cohort was on average 84.5 years old, 92.4% white, and 71.9% female; and the severely frail cohort was on average 86.4 years old, 71.0% white, and 55.1% female. Rate of 1-year readmission increased with frailty level, with a rate of 38% in nonfrail patients, 55.6% in frail patients, and 74.2% in severely frail patients (P = 0.001). The same pattern was seen in 2-year mortality rates, with a rate of 2.8% in nonfrail patients, 36.7% in frail patients, and 77.5% in severely frail patients (P < 0.0001). Being classified as frail or severely frail exhibited greater association with mortality within 2 years than age, with hazard ratio of 17.81 for frail patients and 56.81 for severely frail patients compared with 1.19 per 5 years of age. CONCLUSIONS: Increased frailty as measured by the Frailty Index is significantly associated with increased 2-year mortality and 1-year hospital readmission rates after hip fracture surgery. Degree of frailty predicts mortality more strongly than age alone. Assessing frailty with the Frailty Index can identify higher-risk surgical candidates, facilitate clinical decision making, and guide discussions about goals of care with family members, surgeons, and geriatricians. LEVEL OF EVIDENCE: Prognostic Level III. See Instructions for Authors for a complete description of levels of evidence.

The Modified Five-Item Frailty Index, Mortality, and Hospital Length of Stay in Geriatric Traumatic Fall Injuries.

This study investigates the association between frailty, measured by the modified five-item frailty index (mFI-5), with inpatient mortality and hospital length of stay for geriatric patients with fall-related injuries. Despite falls being major contributors to morbidity and mortality in those over 65, the interaction between frailty and post-fall outcomes remains underexplored. Data for patients aged 65 and above, admitted between 2014-2020 to Rhode Island Hospital's trauma service for fall-related injuries, were extracted from its Trauma Registry. Frailty scores were retrospectively assigned using mFI-5. Logistic- and linear-regression analyses examined the relationship between mFI-5 scores, mortality, and hospital length-of-stay. Among 6,782 patients (mean age: 81.7 ± 8.66 years), higher frailty scores correlated with increased inpatient mortality (OR: 1.259; 95% CI: 1.14-1.39; P<0.000) and longer hospital stays (Coeff.: 0.460; 95% CI: 0.35-0.57, P<0.000). Notably, age showed a negative association with hospital length of stay but no significant association with inpatient mortality.

Frailty and all-cause and cancer-related mortality in cancer patients: A prospective cohort study.

PURPOSE: To evaluate the associations between frailty and all-cause and cancer-related mortality. Additionally, the objective is to compare the magnitude of these associations between older adults and younger adults. METHODS: We gathered baseline data from NHANES (1999-2018) and developed a cumulative index consisting of 39 items to evaluate frailty. The National Death Index database was utilized to track the survival status of individuals. The Cox regression model was employed to estimate the associations between frailty status and all-cause and cancer-related mortality. RESULTS: Ultimately, 3398 cancer patients were included in the analysis, comprising 910 younger adults and 2488 older adults. Compared to non-frail patients, the elevated all-cause and cancer-related mortality among pre-frail patients was not statistically significant (HRs = 1.312, 95%CI: 0.956-1.800, P = 0.092; HRs = 1.462, 0.811-2.635, P = 0.207). However, a significant elevation of both all-cause and cancer-related mortality risk was observed among frail patients (HRs = 2.213, 1.617-3.030, P < 0.001; HRs = 2.463, 95%CI = 1.370-4.429, P = 0.003). Frailty individuals demonstrated a more pronounced association with the prediction of all-cause mortality in younger (HRs = 2.230, 1.073-4.634, P = 0.032) than in older adults (HRs = 2.090, 1.475-2.960, P < 0.001). Sensitivity analysis consistently revealed robust results. RCS plots suggested a progressively escalating dose-response correlation between frailty and both all-cause and cancer-related mortality risk. CONCLUSIONS: Pre-frailty did not result in an increase in mortality risks compared to non-frailty. However, frailty caused a higher all-cause and cancer-related mortality risk than non-frailty. Identifying those at risk and implementing targeted interventions may contribute to extending healthy life expectancy, regardless of age.

Joint association of cardiovascular health and frailty with all-cause and cause-specific mortality: a prospective study.

BACKGROUND: Poor cardiovascular health (CVH) and physical frailty were reported to increase mortality risk, but their joint effects have not been fully elucidated. OBJECTIVES: We aimed to explore the separate and joint effects of CVH and frailty on mortality based on two perspectives of Life's Essential 8 (LE8) and Framingham Risk Score (FRS). METHODS: 21 062 participants in the National Health and Nutrition Examination Survey (NHANES) from 2007 to 2018 were involved in this study. CVH was evaluated by the LE8 and FRS, and categorized into low, moderate and high CVH groups. Cox proportional hazard models were applied to estimate the separate and joint associations of CVH and frailty index (FI) with all-cause, cardiovascular disease (CVD) and cancer mortality. RESULTS: Over a median follow-up period of 87 months (95% CI: 86.0-88.0), 2036 deaths occurred. The separate linear dose-response relationships between CVH, frailty and mortality were observed (nonlinear P > .05). The combination of low CVH/frailty was negatively associated with all-cause mortality [hazard ratio (HR) and 95%CI: low LE8*FI, 5.30 (3.74, 7.52); high FRS*FI, 4.34 (3.20, 5.88)], CVD mortality [low LE8*FI, 6.57 (3.54, 12.22); high FRS*FI, 7.29 (3.92, 13.55)] and cancer mortality [low LE8*FI, 1.99 (1.14, 3.25); high FRS*FI, 2.32 (1.30, 4.15)], with high CVH/fit group as reference. Further stratified analyses showed that the combined burden of mortality from frailty and low CVH was greater among the young and females. CONCLUSIONS: Low CVH and frailty were independently and jointly correlated with greater risk of all-cause, CVD and cancer deaths, especially among the young and females.

The Association Between Frailty Evaluated by Clinical Frailty Scale and Mortality of Older Patients in the Emergency Department: A Prospective Cohort Study.

Background: Frailty epitomizes the most complex consequence of an aging population. This study aimed to evaluate the impact of frailty, measured using the Clinical Frailty Scale (CFS), on outcomes of older people in an emergency department (ED). Methods: We conducted a prospective observational study enrolling patients aged 65 years and older in a medical center of Taiwan between March 8, 2021, and November 30, 2021. The primary outcome was 90-day mortality rate. Individuals were categorized into three groups based on the CFS scores. Logistic regression was employed to examine the influence of frailty on clinical outcomes following covariate adjustment. Survival analysis was conducted using Kaplan-Meier curves and Log rank tests. Results: A total of 473 individuals were included in the study, with a mean age of 82.1 years, and 60.5% of them were males. The 90-day mortality rate was 10.6%. Among these groups, the CFS score 7-9 group had the highest 90-day mortality rate (15.9%), followed by the CFS score 4-6 group (8.0%) and the CFS score 1-3 group (7.1%). The multiple logistic regression analyses demonstrated a significant impact of CFS score on prognosis, with adjusted odd ratios of 1.24 (95% CI 1.06-1.47) for 90-day mortality, 1.18 (95% CI 1.06-1.31) for hospitalization, and 1.30 (95% CI 1.12-1.52) for 180-day mortality. The Kaplan-Meier curves revealed a significantly higher 90-day mortality rate for patients with high CFS scores (Log rank tests, p = 0.019). Conclusion: In the older ED population, the severity of frailty assessed by the CFS emerged as a significant and important prognostic factor for hospitalization, 90-day mortality, and 180-day mortality.

Influence of frailty on cardiovascular events and mortality in patients with Chronic Obstructive Pulmonary Disease (COPD): Study protocol for a multicentre European observational study.

BACKGROUND: Frailty is a clinical state that increases susceptibility to minor stressor events. The risk of frailty is higher in chronic conditions, such as Chronic Obstructive Pulmonary Disease (COPD). Recent studies on COPD have shown that patients living with frailty have an increased risk of mortality. The presence of cardiovascular diseases or conditions are common in COPD and may increase the risk of death. METHODS: This protocol describes a European prospective cohort study of community-based people, in a stable condition with diagnosis of COPD (as defined by GOLD guidelines) across hospitals in Italy and UK. Frailty prevalence will be assessed using the Clinical Frailty Scale. At 1- and 2-year follow up, primary outcome will be the impact of frailty on the number of cardiovascular events; secondary outcomes: the influence of frailty on cardiovascular mortality, all-cause mortality, and deaths due to COPD. For the primary outcome a zero-inflated Poisson regression will compare the number of cardiovascular events at 1 year. Secondary outcomes will be analysed using the time to mortality. DISCUSSION: This multicentre study will assess the association between frailty and cardiovascular events and mortality in population with COPD. Data collection is prospective and includes routine clinical data. This research will have important implications for the management of patients with COPD to improve their quality of care, and potentially prognosis. TRIAL REGISTRATION NUMBER: NCT05922202 (www.clinicaltrials.gov).

Development and validation of a frailty index for use in the osteoarthritis initiative.

BACKGROUND: The Osteoarthritis Initiative (OAI) evaluates the development and progression of osteoarthritis. Frailty captures the heterogeneity in aging. Use of this resource-intensive dataset to answer aging-related research questions could be enhanced by a frailty measure. OBJECTIVE: To: (i) develop a deficit accumulation frailty index (FI) for the OAI; (ii) examine its relationship with age and compare between sexes, (iii) validate the FI versus all-cause mortality and (iv) compare this association with mortality with a modified frailty phenotype. DESIGN: OAI cohort study. SETTING: North America. SUBJECTS: An FI was determined for 4,755/4,796 and 4,149/4,796 who had a valid FI and frailty phenotype. METHODS: Fifty-nine-variables were screened for inclusion. Multivariate Cox regression evaluated the impact of FI or phenotype on all-cause mortality at follow-up (up to 146 months), controlling for age and sex. RESULTS: Thirty-one items were included. FI scores (0.16 ± 0.09) were higher in older adults and among females (both, P < 0.001). By follow-up, 264 people had died (6.4%). Older age, being male, and greater FI were associated with a higher risk of all-cause mortality (all, P < 0.001). The model including FI was a better fit than the model including the phenotype (AIC: 4,167 vs. 4,178) and was a better predictor of all-cause mortality than the phenotype with an area under receiver operating characteristic curve: 0.652 vs. 0.581. CONCLUSION: We developed an FI using the OAI and validated it in relation to all-cause mortality. The FI may be used to study aging on clinical, functional and structural aspects of osteoarthritis included in the OAI.

Frailty progression in adults aged 40 years and older in rural Burkina Faso: a longitudinal, population-based study.

BACKGROUND: Little is known about ageing and frailty progression in low-income settings. We aimed to describe frailty changes over time in individuals living in rural Burkina Faso and to assess which sociodemographic, disability, and multimorbidity factors are associated with frailty progression and mortality. METHODS: This longitudinal, population-based study was conducted at the Nouna Health and Demographic Surveillance Systems (HDSS) site in northwestern Burkina Faso. Eligible participants were aged 40 years or older and had been primarily resident in a household within the HDSS area for at least the past 6 months before the baseline survey and were selected from the 2015 HDSS household census using a stratified random sample of adults living in unique households within the area. Participants were interviewed in their homes in 2018 (baseline), 2021 (follow-up), or both. We derived the Fried frailty score for each participant at each timepoint using data on grip strength, gait speed, self-reported weight loss, self-reported exhaustion, and physical activity, and described changes in frailty status (no frailty, pre-frailty, or frailty) between 2018 and 2021. We used multivariate regression models to assess factors (ie, sex, age, marital status, educational attainment, wealth quintile, WHO Disability Assessment Schedule (WHODAS) score, and multimorbidity) associated with frailty progression (either worsening frailty status or dying, compared with frailty status remaining the same or improving) and with mortality, and developed sequential models: unadjusted, adjusting for sociodemographic factors (sex, age, marital status, educational attainment, and wealth quintile), and adjusting for sociodemographic factors, disability, and multimorbidity. FINDINGS: Between May 25 and July 19, 2018, and between July 1 and Aug 22, 2021, 5952 individuals were invited to participate: 1709 (28·7%) did not consent, 1054 (17·8%) participated in 2018 only and were lost to follow-up, 1214 (20·4%) participated in 2021 only, and 1975 (33·2%) were included in both years or died between years. Of 1967 participants followed up with complete demographic data, 190 (9·7%) were frail or unable to complete the frailty assessment in 2018, compared with 77 (3·9%) in 2021. Between 2018 and 2021, frailty status improved in 567 (28·8%) participants and worsened in 327 (16·6%), and 101 (5·1%) participants died. The relative risk of frailty status worsening or of dying (compared with frailty impRoving or no change) increased with age and WHODAS score, whereas female sex appeared protective. After controlling for all sociodemographic factors, multimorbidity, and WHODAS score, odds of mortality were 1·07 (odds ratio 2·07, 95% CI 1·05-4·09) times higher among pre-frail individuals and 1·1 (2·21, 0·90-5·41) times higher among frail individuals than among non-frail individuals. INTERPRETATION: Frailty status was highly dynamic in this low-income setting and appears to be modifiable. Given the rapid increase in the numbers of older adults in low-income or middle-income countries, understanding the behaviour of frailty in these settings is of high importance for the development of policies and health systems to ensure the maintenance of health and wellbeing in ageing populations. Future work should focus on designing context-appropriate interventions to improve frailty status. FUNDING: Alexander Von Humboldt Foundation, Institute for Global Innovation, University of Birmingham, and Wellcome Trust.

Deep learning-based prediction of one-year mortality in Finland is an accurate but unfair aging marker.

Short-term mortality risk, which is indicative of individual frailty, serves as a marker for aging. Previous age clocks focused on predicting either chronological age or longer-term mortality. Aging clocks predicting short-term mortality are lacking and their algorithmic fairness remains unexamined. We developed a deep learning model to predict 1-year mortality using nationwide longitudinal data from the Finnish population (FinRegistry; n = 5.4 million), incorporating more than 8,000 features spanning up to 50 years. We achieved an area under the curve (AUC) of 0.944, outperforming a baseline model that included only age and sex (AUC = 0.897). The model generalized well to different causes of death (AUC > 0.800 for 45 of 50 causes), including coronavirus disease 2019, which was absent in the training data. Performance varied among demographics, with young females exhibiting the best and older males the worst results. Extensive prediction fairness analyses highlighted disparities among disadvantaged groups, posing challenges to equitable integration into public health interventions. Our model accurately identified short-term mortality risk, potentially serving as a population-wide aging marker.

Reweighting and validation of the hospital frailty risk score using electronic health records in Germany: a retrospective observational study.

BACKGROUND: In the hospital setting, frailty is a significant risk factor, but difficult to measure in clinical practice. We propose a reweighting of an existing diagnoses-based frailty score using routine data from a tertiary care teaching hospital in southern Germany. METHODS: The dataset includes patient characteristics such as sex, age, primary and secondary diagnoses and in-hospital mortality. Based on this information, we recalculate the existing Hospital Frailty Risk Score. The cohort includes patients aged ≥ 75 and was divided into a development cohort (admission year 2011 to 2013, N = 30,525) and a validation cohort (2014, N = 11,202). A limited external validation is also conducted in a second validation cohort containing inpatient cases aged ≥ 75 in 2022 throughout Germany (N = 491,251). In the development cohort, LASSO regression analysis was used to select the most relevant variables and to generate a reweighted Frailty Score for the German setting. Discrimination is assessed using the area under the receiver operating characteristic curve (AUC). Visualization of calibration curves and decision curve analysis were carried out. Applicability of the reweighted Frailty Score in a non-elderly population was assessed using logistic regression models. RESULTS: Reweighting of the Frailty Score included only 53 out of the 109 frailty-related diagnoses and resulted in substantially better discrimination than the initial weighting of the score (AUC = 0.89 vs. AUC = 0.80, p < 0.001 in the validation cohort). Calibration curves show a good agreement between score-based predictions and actual observed mortality. Additional external validation using inpatient cases aged ≥ 75 in 2022 throughout Germany (N = 491,251) confirms the results regarding discrimination and calibration and underlines the geographic and temporal validity of the reweighted Frailty Score. Decision curve analysis indicates that the clinical usefulness of the reweighted score as a general decision support tool is superior to the initial version of the score. Assessment of the applicability of the reweighted Frailty Score in a non-elderly population (N = 198,819) shows that discrimination is superior to the initial version of the score (AUC = 0.92 vs. AUC = 0.87, p < 0.001). In addition, we observe a fairly age-stable influence of the reweighted Frailty Score on in-hospital mortality, which does not differ substantially for women and men. CONCLUSIONS: Our data indicate that the reweighted Frailty Score is superior to the original Frailty Score for identification of older, frail patients at risk for in-hospital mortality. Hence, we recommend using the reweighted Frailty Score in the German in-hospital setting.

Impact of pre-existing frailty on survival outcomes in solid-organ transplant candidates and recipients: A meta-analysis.

BACKGROUND: There is controversy surrounding the association between preexisting frailty and increased mortality in candidates and recipients of solid-organ transplants. This meta-analysis aimed to evaluate the impact of preexisting frailty on survival outcomes in solid-organ transplant candidates and recipients. METHODS: A systematic search was conducted in the PubMed, Web of Sciences, and Embase databases until October 2, 2023. Two reviewers independently selected the eligible studies according to the PECOS criteria: Participants (candidates and recipients of solid-organ transplants), Exposure (frailty), Comparison (no-frailty), Outcomes (waitlist or posttransplant mortality), and Study design (retrospective or prospective cohort studies). The pooled effects were summarized by pooling the adjusted hazard ratio (HR) with 95 % confidence intervals (CI) for the frail patients than those without frailty. RESULTS: Sixteen studies with 10091 patients met the eligibility criteria. Depending on the frailty tools used, the prevalence of frailty in solid-organ transplant candidates/recipients ranged from 4.6 % to 45.1 %. Frailty was significantly associated with an increased risk of waitlist mortality (HR 2.44; 95 % CI 1.84-3.24) and posttransplant mortality (HR 2.23; 95 % CI 1.61-3.09) in solid-organ transplant candidates and recipients, respectively. Subgroup analyses showed that the association of preexisting frailty with waitlist mortality and posttransplant mortality appeared to stronger in kidney transplant candidates (HR 2.70; 95 % CI 1.93-3.78) and lung transplantation recipients (HR 2.52; 95 % CI 1.23-5.15). CONCLUSION: Frailty is a significant predictor of reduced survival in solid-organ transplant candidates and recipients. Assessment of frailty has the potential to identify patients who are suitable for transplantation.