Frailty Tools Research Articles

Impact of frailty on clinical outcomes and resource utilization of hospitalizations for renal stone surgery.

Frailty is reportedly associated with poorer outcomes among surgical patients. Using a coding-based frailty tool, we investigated the impact of frailty on clinical outcomes and resource utilization for urolithiasis hospitalizations. A cohort study using the 2018 National Inpatient Sample database. All adult elective hospitalizations for urolithiasis were included in the study. The study population was categorized into FRAIL and non-frail (nFRAIL) cohorts using the Johns Hopkins Adjusted Clinical Groups frailty clusters. The association between frailty and clinical and financial outcomes was evaluated using multivariate regression models. About 1028 (14.9%) out of 6900 total hospitalizations were frail. Frailty was not associated with a significant increase in the odds of in-hospital mortality (adjusted odds ratio (aOR) 1.73, 95% CI 0.15-20.02) or length of hospital stay, but was associated with a lower chance of surgery within 24h of admission (aOR 0.65, 95% CI 0.48-0.90, P = 0.008). A higher Charlson index was independently associated with an over 100% increase in the odds of in-hospital mortality (aOR 2.091, 95% CI 1.53-2.86, P < 0.001). Frail patients paid $15,993 higher in total hospital costs and had a higher likelihood of non-home discharges (aOR 4.29, 95% CI 2.74-6.71, P < 0.001) and peri-operative complications (aOR 1.77, 95% CI 1.14-2.73, P = 0.01). Frailty was correlated with unfavorable outcomes, except mortality and prolonged hospital stay. Incorporating frailty evaluation into risk models has the potential to enhance patient selection and preparation for urolithiasis intervention.

Validation of Frail Scale and comparison with hospital frailty risk score to predict hospital use in a cohort of older Australian women.

With no standard frailty tool for clinical care, research and policymaking, identifying frail older people is a challenge. This study aimed to compare two validated scales, which are the Frail Scale and Hospital Frailty Risk Score (HFRS) for their ability in identifying frailty in older Australian women and predicting hospital use. This study included older Australian women aged 75-95years, who had unplanned overnight hospital admission as an index admission between 2001 and 2016. Data from the Australian Longitudinal Study on Women's Health (ALSWH) were linked with administrative hospital data to calculate HFRS (using the International Statistical Classification of Diseases, Australia Modification (ICD-10-AM) diagnostic codes) and the Frail Scale (using the ALSWH self-reported survey). The Frail Scale identified a higher proportion of older frail women (30.54%) compared to the HFRS (23.0%). Frail older women, classified by Frail Scale, were at higher risk of long hospital stay (adjusted odds ratio=1.28, 95% CI=1.02-1.60), repeated admission (adjusted hazard ratio [AHR]=1.30, 95% CI=1.03-1.41) and death (AHR=1.70, 95% CI=1.45-2.01). HFRS was associated with longer hospital stay and mortality. The proportion of older women classified as frail by the Frail Scale tool was higher than women classified as frail by HFRS. The Frail Scale and HFRS were not significantly associated with each other. While both tools were associated with the risk of long hospital stay and mortality, only the Frail Scale predicted the risk of repeated admission.

Waiting time dictates impact of frailty: A Spanish multicenter prospective study

Frailty is prevalent in liver transplant (LT) candidates. It is considered an independent predictor of adverse outcomes pre- and post-transplant according to data obtained in the United States. We aimed to externally validate the liver frailty index (LFI) in a multicenter cohort of LT candidates. Outpatients with cirrhosis were prospectively recruited from five Spanish centers (2018-2020). Patients were defined as "frail" by an optimal cut-off of LFI ≥4.5. Patients were followed for at least 6 months to study associations of pre-LT frailty with pre- and post-transplant mortality, length of hospital and intensive care unit (ICU) stays, risk of early (<30 days) and late (30-90 days) post-transplant complications, retransplantation and cardiovascular events. Of 212 patients included, 45 patients (21%) were frail pre-LT, and the median LFI was 3.9 (IQR 3.5-4.4). After a median waiting time of 78 days, 2% died or were delisted for clinical worsening. The LFI at baseline was not predictive of mortality/delisting in LT candidates in univariable or multivariable analyses after adjusting for age and MELD-Na score (hazard ratio 1.48; p= 0.586). In contrast, compared to non-frail patients, frail LT candidates had a significantly higher length of hospital stay (9 vs. 13 days; p= 0.001) and rate of early (<30 days) post-transplant complications (55% vs. 100%; p= 0.021). In the context of a short LT waiting time, frailty does not impact pretransplant mortality and/or delisting. In contrast, LT frailty is predictive of higher post-transplant complication rates and length of hospital stay. Whether strategies aimed at pre- and/or re-habilitation are beneficial in settings with short waiting times needs to be confirmed in prospective studies. Literature is scarce on the actual impact of physical frailty on adverse outcomes in the liver transplant scenario outside North America. Evidence-based justification to extend the use of objective frailty tools in the decision-making processes in other liver transplant settings is needed. This study is the first to evaluate the predictive value of the liver frailty index in outpatients in the European liver transplant setting, showing that in a low MELD, high access system, frailty does not impact pretransplant mortality and/or delisting but is predictive of higher complication rates and longer post-transplant length of stay. In practical ways, physicians should consider physical frailty as a vital sign to be measured systematically and routinely during clinic visits; researchers are encouraged to initiate prospective studies to evaluate the benefit of applying strategies aimed at pre- and or re-habilitation in liver transplant settings with short waiting times.

Association of frailty with cognitive impairment and functional disability in older adults with affective disorders: a brief research report.

The Clinical-Functional Vulnerability Index (IVCF-20) is a validated multidimensional instrument that has been used in Brazil to evaluate functional disability in frail older adults. The main aim of this study was to assess frailty using this novel screening tool. In addition, to investigate whether frailty was associated with cognitive impairment and functional disability in older adults with affective disorders. Participants included were over 60 years old, with affective disorders (depressive or anxiety disorders), from two specialized outpatient clinics. The sample was comprised of 46 patients (30% of a total from 153). The following instruments were applied: Clock Drawing Test (CDT), Mini Mental State Examination (MMSE); Verbal Fluency Test (VFT); Pfeffer Questionnaire or Functional Assessment Questionnaire (FAQ); Katz Index; Geriatric Depression Scale (GDS-15); Geriatric Anxiety Inventory (GAI), and IVCF-20 as well as sociodemographic and clinical questionnaires. The association between the variables of interest was estimated using Spearman correlation. This study found a negative correlation between frailty and cognitive decline (MMSE; rs = -0.58; p < 0.001); (VFT; rs = -0.60; p < 0.001); (CDT; rs = -0.47; p = 0.001) and a positive correlation between frailty and depressive symptoms (GDS-15; rs = 0.34; p = 0.019) as well as disability for IADLs (FAQ; rs = 0.69; p < 0.001). However, there was no statistical difference in the association between frailty and anxiety symptoms (GAI; rs = 0.24; p = 0.103) or disability for BADLs (Katz; rs = -0.02; p = 0.895). Our data support that the associations between frailty, cognitive and functional disability are prevalent issues in Psychogeriatrics. Assessing frailty in a multidimensional context is essential using a rapid assessment frailty tool in clinical practice.

#5397 FRAILTY ASSESSMENT TOOLS, SURVIVAL TIME AND TIME TO INITIATE DIALYSIS IN OLDER PATIENTS WITH ADVANCED CHRONIC KIDNEY DISEASE

Abstract Background and Aims Chronic Kidney Disease (CKD) patients with frailty have been shown to have a shorter survival time compared to non-frail individuals. Additionally, frailty has been linked to earlier initiation of dialysis among CKD patients. Despite the availability of over 50 frailty assessment tools in the literature, few have been applied in studies of older adults with CKD. There is a need for a comprehensive analysis of different frailty tools to identify the most accurate tools that could predict survival time and time to start dialysis in older adults with CKD. The present study compares four commonly used assessment tools of frailty from different categories (self-reporting tools, clinical judgment tools and complex instruments) regarding their association with survival time and time to start dialysis. Method Two hundred forty patients with biochemical evidence of CKD Stages 4–5 were included in this prospective cohort study. The inclusion criteria included patients 65 years old or more with two consecutive measurements of estimated glomerular filtration rate (eGFR) &amp;lt;60 mL/min/1.73 m2 separated by more than three months, while exclusion criteria included dialysis dependence, history of kidney transplantation, recent acute kidney injury, initial visit with the provider, amputation, or cerebrovascular accident. The four frailty assessment tools used in the study were Prisma-7 and FRAIL Scale, Clinical Frailty Scale (CFS), and Frailty Phenotype (FP). Patients were followed-up for 36 months for death events or dialysis initiation. Results The study population (240 patients) comprised 46% male patients with a mean age of 73.8 ± 6.6 years. Approximately 25% of patients were considered frail using the FRAIL scale, 69% using Prisma-7, and almost 40% using CFS and FP. Except for Prisma-7, “frail” patients, as determined by the FRAIL, CFS, and FP scores (Fig. 1), had significantly shorter survival times, with a mean survival of 24.9 months (Log-rank p &amp;lt;0.001), 27.3 months (Log-rank p = 0.041), and 26.6 months (Log-rank p = 0.004) respectively. No significant differences were observed in time to dialysis initiation when comparing frail and non-frail patients using any of the frailty assessment tools (Table 1). Conclusion The findings suggest that the frailty scores derived from the FRAIL, CFS, and FP tools are better predictors of survival time in frail elderly patients with CKD, while further research is required to determine the most appropriate frailty tool to predict the time to start dialysis in this population.

#4146 LIMITATIONS AND UNCERTAINTIES OF ASSESSING AND MANAGING OLDER PATIENTS WITH ANCA ASSOCIATED VASCULITIS

Abstract Background and Aims ANCA associated vasculitis (AAV) has a peak incidence in 65 -74 yr olds. As a result, it affects an ageing population who are vulnerable to co-morbidities, polypharmacy and frailty. Due to the high burden of morbidity and mortality in these patients, it is increasingly recognised that individualised management is needed. Whilst current immunotherapies are effective, there remains caution in treating older patients due to the potential risks. Yet despite AAV being a condition that predominantly affects older people, few studies have looked specifically at the benefit of treating AAV in such age groups, or at frailty assessments tools to guide treatment. Method We aimed to evaluate treatment outcomes in older AAV patients, as well as frailty assessment tools to aid prognostication and management. A cohort study evaluating outcomes of induction immunosuppression in patients ≥75yrs was constructed from 2 centres, with subsequent meta-analysis of published data [1]. In addition, studies identifying frail patients, who may be at risk of adverse outcomes, were carried out using the quantitative tools; Hospital Frailty Risk Score (HFRS) [2] and the Clinical Frailty Scale (CFS). Primary outcomes were mortality and end stage kidney disease (ESKD). The HFRS was calculated using hospital coding data from any hospital admissions between a patient's AAV diagnosis to 2yr follow up. Patients were categorized into low, intermediate and high HFRS groups. CFS scores at presentation were documented prospectively and then repeated a minimum of 6 weeks from diagnosis. A CFS score of ≥5 was used to categorise frailty. Differences in the scores were assessed and compared to clinical outcomes. Results Retrospective analysis of our AAV cohort aged ≥75 yrs demonstrated that induction immunosuppression was associated with a significant reduction in the 2yr mortality risk [HR 0.29 (95% CI 0.09–0.93)]. Following systematic review, with a study population of 290 patients, the pooled HR by meta-analysis confirmed a significant reduction in the risk of death with induction treatment [HR 0.31 (95% CI 0.16 - 0.57)]. Treated patients had a lower rate of ESKD, but this was not statistically significant [HR 0.71 (95% CI 0.15 – 3.35)]. Looking separately at frailty assessments, mortality and ESKD were assessed according to HFRS and CFS. Thirty-four patients with AAV aged ≥75 yrs were assessed using HFRS and categorised into the low (n = 18), intermediate (n = 13) and high (n = 3) HFRS groups. All patients in the high HFRS groups had ≥1 episodes of hospitalization after diagnosis of AAV. However, there was no difference in mortality or duration of hospitalisation between the 3 categories. Forty-one patients with AAV aged ≥65yrs were assessed using the CFS. The median CFS at diagnosis and follow-up was 4. There was no significant interval change in CFS (P = 0.16) suggesting that patients did not become frailer. Instead, there was a tendency towards improved frailty scores at reassessment (n = 17, 43%), with some patients going from a CFS of 6 (moderately frail) to 3 (managing well). There was no significant difference in ESKD between those categorised as frail and non-frail (P = 1.0), although crude mortality was higher among those initially categorised as frail (P = 0.03). Conclusion Our research shows that older patients with AAV benefit from standard remission-induction therapy and those treated had favourable mortality outcomes compared to those who were not. Furthermore, frailty assessment tools do not correlate clearly with clinical outcomes. Whilst there is evidence to support the use of HFRS and CFS in a many diseases, its utility in determining frailty and potential susceptibility to adverse effects of therapy in patients with multifaceted, autoimmune inflammatory disease remains limited. Patients may present ‘frail’ as a result of significant disease burden, which has the potential to improve with appropriate treatment. We suggest that age alone and frailty at assessment should not be a limiting factor when considering treatment and prospective studies of this population are needed.

#5657 FRAILTY AND VASCULAR ACCESS IN HEMODIALYSIS PATIENTS

Abstract Background and Aims Frailty is a geriatric syndrome characterized by increased vulnerability to stressors. The elderly become vulnerable and susceptible to adverse outcomes for their health and to functional restrictions. Previous guidelines suggested fistula creation as first choice for vascular access. Current guidelines suggest a more tailored approach to the patient's needs. Despite the high prevalence of frailty in hemodialysis patients, there is paucity of work investigating the relationship between frailty and vascular access failure. The aim of the study was the estimation of frailty with different scores and relationship with the choice of first vascular access, the current vascular access and vascular failures. Method 67 patients in hemodialysis participated to the study (observational cross-sectional study). Frailty was assessed with 6 different scores,Clinical Frailty Scale (CFS), Frailty Phenotype (FP), Edmonton Frailty Scale (EFS), Groningen Frailty Index GFI), Short Physical Performance Battery (SPPB), Prisma-7 and ankle-brachial index (ABI) and hand grip were also estimated. The current vascular access, the first vascular access, the vascular access failures and the mean duration of the vascular accesses were also recorded. Finally, the levels of the hemoglobin, serum albumin, C reactive protein, cholesterol were measured for all patients and the hemodialysis adequacy (URR, sp Kt/V) was calculated from the levels of urea before and after the hemodialysis session. Finally, the levels of the hemoglobin, albumin, C reactive protein, cholesterol were measured for all patients and the hemodialysis adequacy was calculated from the levels of urea before and after the hemodialysis session. Results The first vascular access of hemodialysis presents statistically significant relation between frail and robust patients that start hemodialysis with central venus catheter and AVF-AVG respectively. (SPPB- tunneled CVC 85, 7%, non tunneled CVC 46,2% ρ=0,032, Prisma-7- frail tunneled CVC 100%, non tunneled CVC 76,9% ρ=0,018, Groningen FI -frail tunneled CVC 100%, non tunneled CVC 65,7% ρ=0,011, Εdmonton FS -AVF-AVG not frail 64,7%, vulnerable 20,6% ρ=0,042) (Table 1-4). ABI presented a statistically significant relationship with the current vascular access. 68,18% of the patients with normal ABI have AVF-AVG and 60,87% of patients with abnormal ABI have tunneled CVC (p=0,022). In addition, the number of vascular accesses per patient, the mean duration of the accesses and the premature failures (3 months after creation) don't present statistically significant relation with frailty. Conclusion The frailty score could be used as a tool for the choice of vascular access in hemodialysis patients. Further studies, in a larger number of patients, are required to define a reliable and easy to use frailty tool, which is best suited to dialysis access selection.

The Role of Multidimensional Prognostic Index to Identify Hospitalized Older Adults with COVID-19 Who Can Benefit from Remdesivir Treatment: An Observational, Prospective, Multicenter Study.

Data regarding the importance of multidimensional frailty to guide clinical decision making for remdesivir use in older patients with coronavirus disease 2019 (COVID-19) are largely unexplored. The aim of this research was to evaluate if the Multidimensional Prognostic Index (MPI), a multidimensional frailty tool based on the Comprehensive Geriatric Assessment (CGA), may help physicians in identifying older hospitalized patients affected by COVID-19 who might benefit from the use of remdesivir. This was a multicenter, prospective study of older adults hospitalized for COVID-19 in 10 European hospitals, followed-up for 90 days after hospital discharge. A standardized CGA was performed at hospital admission and the MPI was calculated, with a final score ranging between 0 (lowest mortality risk) and 1 (highest mortality risk). We assessed survival with Cox regression, and the impact of remdesivir on mortality (overall and in hospital) with propensity score analysis, stratified by MPI = 0.50. Among 496 older adults hospitalized for COVID-19 (mean age 80 years, female 59.9%), 140 (28.2% of patients) were treated with remdesivir. During the 90 days of follow-up, 175 deaths were reported, 115 in hospital. Remdesivir treatment significantly reduced the risk of overall mortality (hazard ratio [HR] 0.54, 95% confidence interval CI 0.35-0.83 in the propensity score analysis) in the sample as whole. Stratifying the population, based on MPI score, the effect was observed only in less frail participants (HR 0.47, 95% CI 0.22-0.96 in propensity score analysis), but not in frailer subjects. In-hospital mortality was not influenced by remdesivir use. MPI could help to identify less frail older adults hospitalized for COVID-19 who could benefit more from remdesivir treatment in terms of long-term survival.

Frailty Is a Risk Factor for Falls in the Older Adults: A Systematic Review and Meta-Analysis.

There is little evidence in the literature about the relationship between frailty and falls in older adults. Our objective was to explore the relationship between frailty and falls, and to analyze the effect factors (e.g., gender, different frailty assessment tools, areas, level of national economic development, and year of publication) of the association between frailty and falls among older adults. Systematic review and meta-analysis. Cohort studies that evaluated the association between frailty and falls in the older adults were included. We excluded any literature outside of cohort studies. We did a systematic literature search of English databases PubMed, Scopus, Web of Science, EBSCOhost, and SciElO, as well as the Chinese databases CNKI, WANFANG, and VIP from 2001 until October 2022. The eligible studies were evaluated for potential bias using the Newcastle-Ottawa Scale (NOS). Study selection, data extraction and assessment of study quality were each conducted by two investigators. In Stata/MP 17.0 software, we calculated pooled estimates of the prevalence of falls by using a random-effects model, Subgroup analysis was conducted based on gender, different frailty assessment tools, areas, level of economic development, and year of publication. The results are presented using a forest plot. Twenty-nine studies were included in this meta-analysis and a total of 1,093,270 participants aged 65 years and above were enrolled. Among the older adults, frailty was significantly associated with a higher risk for falls, compared with those without frailty (combined RR-relative risk = 1.48, 95% CI-confidence interval: 1.27-1.73, I2=98.9%). In addition, the results of subgroup analysis indicated that men had a higher risk for falls than women among the older adults with frailty (RR 1.94, 95% CI: 1.18-3.2 versus RR 1.44, 95% CI: 1.24-1.67). Subgroup analysis by different frailty assessment tools revealed an increased risk of falls in older adults with frailty when assessed using the Frailty Phenotype (combined RR 1.32, 95%CI: 1.17-1.48), FRAIL score (combined RR 1.82, 95%CI: 1.36-2.43), and Study of Osteoporotic Fractures index (combined RR 1.54, 95%CI: 1.10-2.16). Furthermore, subgroup analysis by areas and level of national economic development found the highest fall risk in Oceania (combined RR 2.35, 95%CI: 2.28-2.43) and the lowest in Europe (combined RR 1.20, 95%CI: 1.05-1.38). Developed countries exhibited a lower fall risk compared to developing countries (combined RR 1.44, 95%CI: 1.21-1.71). Analysis by year of publication showed the highest fall risk between 2013-2019 (combined RR 1.79, 95%CI: 1.45-2.20) and the lowest between 2001-2013 (combined RR 1.21, 95%CI: 1.13-1.29). Frailty represents a significant risk factor for falls in older adults, with the degree of risk varying according to the different frailty assessment tools employed, and notably highest when using the FRAIL scale. Additionally, factors such as gender, areas, level of national economic development, and healthcare managers' understanding of frailty may all impact the correlation between frailty and falls. Thus, it's imperative to select suitable frailty diagnostic tools tailored to the specific characteristics of the population in question. This, in turn, facilitates the accurate identification of frailty in older adults and informs the development of appropriate preventive and therapeutic strategies to mitigate fall risk.

Association of the frailty index with functional brain connectivity in the Irish Longitudinal Study on Ageing (TILDA)

AbstractBackgroundFrailty, expressed as accumulation of health deficits in older adults, could contribute to the risk of cognitive decline. We cross‐sectionally studied the brain connectivity signatures of frailty in The Irish Longitudinal Study on Ageing (TILDA).MethodWe included participants from Wave 3 of TILDA who underwent resting‐state functional MRI. Connectivity maps were based on Shen’s parcellation and connectome‐based predictive modeling was used to find associations between connectivity and frailty as measured by Frailty Index (FI) (Table 1).On each iteration of a 10‐fold cross‐validation the training folds were utilized to perform partial Spearman correlations (adjusted for age, sex, and mean framewise displacement) between each brain connection and FI scores. Connections with p&lt;0.001 correlations were selected. Network strength was computed by summing the correlations across all connections selected and a linear model built using the network strength to predict FI score. After 10 folds are complete the performance was measured with linear R values between predicted and true FI scores. This process was repeated 1000 times (with random cross‐validation splits) and mean performance metrics obtained. A permutation test was employed in which the above procedure was repeated 1000 times, with FI scores shuffled each time. Significance of selected connections was calculated as the number of permutations scores that were equal to or greater than the proper mean score, divided by 1000.Result347 participants were included (mean age 67.7 (SD 7.3) and 51.6% men). We obtained a connectivity network that positively correlated with frailty (“frailty network”) (R = 0.169, p = 0.006) and another that negatively correlated with frailty (“robustness network”) (R = ‐0.193, p = 0.006); and are depicted in Figure 1. The “frailty network” was more widespread and showed higher connectivity from right occipital to both prefrontal cortices, subcortical and left temporal cortex, whereas the “robustness network” exhibited higher functional connectivity in subcortical to left parietal and bilateral temporal cortices.ConclusionFunctional brain connectivity could be influenced by frailty. Further research should study the relationship of brain connectivity and different tools for frailty and establish how different patterns of deficit accumulation affect brain health across lifespan.

P.148 Perceptions of frailty in spinal metastatic disease: international survey of the AO spine community

Background: Frailty is increasingly recognized for an association with adverse events, mortality, and hospital discharge disposition among surgical patients. The purpose of this study was to describe how spinal surgeons conceptualize, define, and assess frailty in the context of spinal metastatic disease (SMD). Methods: We conducted an international, cross-sectional, 33-question survey of the AO Spine community. The survey was developed using a modified Delphi technique and was designed to elucidate preoperative surrogate markers of frailty in the context of SMD. Responses were ranked using weighted averages. Consensus was defined as ≥ 70% agreement among respondents. Results: Results were analyzed for 312 respondents (86% completion rate). Study participants represented 71 countries. Most respondents informally assess frailty in patients with SMD by forming a general perception based on clinical condition and patient history. Consensus was attained regarding the association between 14 clinical variables and frailty. Severe comorbidities, systemic disease burden, and poor performance status were most associated with frailty; severe comorbidities included high-risk cardio-pulmonary disease, renal failure, liver failure, and malnutrition. Conclusions: Surgeons recognized frailty is important but commonly evaluate it based on general clinical impression rather than using existing frailty tools. We identified preoperative surrogate markers of frailty perceived as most relevant in this population.

Frailty and Polypharmacy in Primary Care.

The Clinical Frailty Scale (CFS) is a clinical judgement-based frailty tool developed from the Canadian Study of Health and Aging. Many studies on the measurement of frailty and its effect on clinical outcomes have been conducted on patients hospitalized, especially in intensive care units. The purpose of this study is to examine the relationship between polypharmacy and frailty on outpatient older adult patients in primary care. This cross-sectional study included 298 patients who were aged ≥65years and admitted to Yenimahalle Family Health Center between May-2022 and July-2022. Frailty was evaluated by using CFS. Polypharmacy was defined as five medications or more and "excessive polypharmacy" as 10 medications or more. The medications below five are grouped as "no polypharmacy". There was a statistically significance between age groups, gender, smoking status, marital status, polypharmacy status, and FS (p = .003 and η2: .20; p < .001 and Cohen d: .80; p = .018 and Cohen d: .35; p < .001 and Cohen d: 1.10 and p < .001 and η2: 1.45 respectively). A strong, positive correlation was found between polypharmacy and the frailty score. Polypharmacy, especially excessive polypharmacy, may be a promising adjunct to frailty in identifying older patients whose health is more likely to worsen. Providers in primary care should also consider frailty when prescribing drugs.

A machine learning-based assistant tool for early frailty screening of patients receiving maintenance hemodialysis.

To develop an assistant tool based on machine learning for early frailty screening in patients receiving maintenance hemodialysis. This is a single-center retrospective study. 141 participants' basic information, scale results and laboratory findings were collected and the FRAIL scale was used to assess frailty. Then participants were divided into the frailty group (n = 84) and control group (n = 57). After feature selection, data split and oversampling, ten commonly used binary machine learning methods were performed and a voting classifier was developed. The grade results of Clinical Frailty Scale, age, serum magnesium, lactate dehydrogenase, comorbidity and fast blood glucose were considered to be the best feature set for early frailty screening. After abandoning models with overfitting or poor performance, the voting classifier based on Support Vector Machine, Adaptive Boosting and Naive Bayes achieved a good screening performance (sensitivity: 68.24% ± 8.40%, specificity:72.50% ± 11.81%, F1 score: 72.55% ± 4.65%, AUC:78.38% ± 6.94%). A simple and efficient early frailty screening assistant tool for patients receiving maintenance hemodialysis based on machine learning was developed. It can provide assistance on frailty, especially pre-frailty screening and decision-making tasks.

Preoperative Frailty Predicts Worse Outcomes after Microvascular Decompression for Trigeminal Neuralgia, Hemifacial Spasm, and Glossopharyngeal Neuralgia: A Multicenter Analysis of 1,473 Patients from a Prospective Surgical Registry

Introduction: Microvascular decompression (MVD) is an efficacious neurosurgical intervention for patients with medically intractable neurovascular compression syndromes. However, MVD may occasionally cause life-threatening or altering complications, particularly in patients unfit for surgical operations. Recent literature suggests a lack of association between chronological age and surgical outcomes for MVD. The Risk Analysis Index (RAI) is a validated frailty tool for surgical populations (both clinical and large database). The present study sought to evaluate the prognostic ability of frailty, as measured by RAI, to predict outcomes for patients undergoing MVD from a large multicenter surgical registry. Methods: The American College of Surgeons-National Surgical Quality Improvement Program (ACS-NSQIP) database (2011–2020) was queried using diagnosis/procedure codes for patients undergoing MVD procedures for trigeminal neuralgia (n = 1,211), hemifacial spasm (n = 236), or glossopharyngeal neuralgia (n = 26). The relationship between preoperative frailty (measured by RAI and 5-factor modified frailty index [mFI-5]) for primary endpoint of adverse discharge outcome (AD) was analyzed. AD was defined as discharge to a facility which was not home, hospice, or death within 30 days. Discriminatory accuracy for prediction of AD was assessed by computation of C-statistics (with 95% confidence interval) from receiver operating characteristic (ROC) curve analysis. Results: Patients undergoing MVD (N = 1,473) were stratified by RAI frailty bins: 71% with RAI 0–20, 28% with RAI 21–30, and 1.2% with RAI 31+. Compared to RAI score 19 and below, RAI 20 and above had significantly higher rates of postoperative major complications (2.8% vs. 1.1%, p = 0.01), Clavien-Dindo grade IV complications (2.8% vs. 0.7%, p = 0.001), and AD (6.1% vs. 1.0%, p < 0.001). The rate of primary endpoint was 2.4% (N = 36) and was positively associated with increasing frailty tier: 1.5% in 0–20, 5.8% in 21–30, and 11.8% in 31+. RAI score demonstrated excellent discriminatory accuracy for primary endpoint in ROC analysis (C-statistic: 0.77, 95% CI: 0.74–0.79) and demonstrated superior discrimination compared to mFI-5 (C-statistic: 0.64, 95% CI: 0.61–0.66) (DeLong pairwise test, p = 0.003). Conclusions: This was the first study to link preoperative frailty to worse surgical outcomes after MVD surgery. RAI frailty score predicts AD after MVD with excellent discrimination and holds promise for preoperative counseling and risk stratification of surgical candidates. A risk assessment tool was developed and deployed with a user-friendly calculator: https://nsgyfrailtyoutcomeslab.shinyapps.io/microvascularDecompression.

Prevalence and clinical impact of frailty in COPD: a systematic review and meta-analysis

BackgroundFrailty has been increasingly identified as a risk factor of adverse outcomes in chronic obstructive pulmonary disease (COPD). The prevalence and impact of frailty on health outcomes in people with COPD require clarification.MethodsPubMed, Embase, The Cochrane Library and Web of Science (January 1, 2002, to July 1, 2022) were comprehensively searched to identify studies related to frailty and COPD. Comparisons were made between people who did and did not have frailty for pulmonary function, dyspnea severity, 6-minute walking distance, activities of daily life, and mortality.ResultsTwenty studies (9 cross-sectional, 10 cohort studies,1 clinical trial) from Europe (9), Asia (6), and North and South America (4), Oceania (1) involving 11, 620 participants were included. The prevalence of frailty was 32.07% (95% confidence interval (CI) 26.64–37.49) with a range of 6.43–71.70% based on the frailty tool used. People with frailty had lower predicted forced expiratory volume in the first second (mean difference − 5.06%; 95%CI -6.70 to -3.42%), shorter 6-minute walking distance (mean difference − 90.23 m; 95%CI -124.70 to -55.76), poorer activities of daily life (standardized mean difference − 0.99; 95%CI -1.35 to -0.62), higher CAT(COPD Assessment Test) score(mean difference 6.2; 95%CI 4.43 to 7.96) and mMRC (modified Medical Research Council) grade (mean difference 0.93; 95%CI 0.85 to 1.02) compared with those who did not (P < 0.001 for all). Meta-analysis showed that frailty was associated with an increased risk of long-term all-cause mortality (HR 1.68; 95% CI 1.37–2.05; I2 = 0%, P < 0.001).ConclusionFrailty is prevalent in people with COPD and linked with negative clinical outcomes including pulmonary function, dyspnea severity, exercise capacity, quality of life and mortality.

An ensemble machine learning approach to predict postoperative mortality in older patients undergoing emergency surgery

BackgroundPrediction of preoperative frailty risk in the emergency setting is a challenging issue because preoperative evaluation cannot be done sufficiently. In a previous study, the preoperative frailty risk prediction model used only diagnostic and operation codes for emergency surgery and found poor predictive performance. This study developed a preoperative frailty prediction model using machine learning techniques that can be used in various clinical settings with improved predictive performance.MethodsThis is a national cohort study including 22,448 patients who were older than 75 years and visited the hospital for emergency surgery from the cohort of older patients among the retrieved sample from the Korean National Health Insurance Service. The diagnostic and operation codes were one-hot encoded and entered into the predictive model using the extreme gradient boosting (XGBoost) as a machine learning technique. The predictive performance of the model for postoperative 90-day mortality was compared with those of previous frailty evaluation tools such as Operation Frailty Risk Score (OFRS) and Hospital Frailty Risk Score (HFRS) using the receiver operating characteristic curve analysis.ResultsThe predictive performance of the XGBoost, OFRS, and HFRS for postoperative 90-day mortality was 0.840, 0.607, and 0.588 on a c-statistics basis, respectively.ConclusionsUsing machine learning techniques, XGBoost to predict postoperative 90-day mortality, using diagnostic and operation codes, the prediction performance was improved significantly over the previous risk assessment models such as OFRS and HFRS.

Prospective application of the risk analysis index to measure preoperative frailty in spinal tumor surgery: A single center outcomes analysis

IntroductionSurgeons are frequently faced with challenging clinical dilemmas evaluating whether the benefits of surgery outweigh the substantial risks routinely encountered with spinal tumor surgery. The Clinical Risk Analysis Index (RAI-C) is a robust frailty tool administered via a patient-friendly questionnaire that strives to augment preoperative risk stratification. The objective of the study was to prospectively measure frailty with RAI-C and track postoperative outcomes after spinal tumor surgery. MethodsPatients surgically treated for spinal tumors were followed prospectively from 7/2020–7/2022 at a single tertiary center. RAI-C was ascertained during preoperative visits and verified by the provider. The RAI-C scores were assessed in relation to postoperative functional status (measured by modified Rankin Scale score [mRS]) at the last follow-up visit. ResultsOf 39 patients, 47% were robust (RAI 0–20), 26% normal (21–30), 16% frail (31–40), and 11% severely frail (RAI 41+).). Pathology included primary (59%) and metastatic (41%) tumors with corresponding mRS>2 rates of 17% and 38%, respectively. Tumors were classified as extradural (49%), intradural extramedullary (46%), or intradural intramedullary (5.4%) with mRS>2 rates of 28%, 24%, and 50%, respectively. RAI-C had a positive association with mRS>2 ​at follow-up: 16% for robust, 20% for normal, 43% for frail, and 67% for severely frail. The two deaths in the series had the highest RAI-C scores (45 and 46) and were patients with metastatic cancer. The RAI-C was a robust and diagnostically accurate predictor of mRS>2 in receiver operating characteristic curve analysis (C-statistic: 0.70, 95 CI: 0.49–0.90). ConclusionsThe findings exemplify the clinical utility of RAI-C frailty scoring for prediction of outcomes after spinal tumor surgery and it has potential to help in the surgical decision-making process as well as surgical consent. As a preliminary case series, the authors intend to provide additional data with a larger sample size and longer follow-up duration in a future study.

Construction and validation of cognitive frailty risk prediction model for elderly patients with multimorbidity in Chinese community based on non-traditional factors

Background and objectivesEarly identification of risk factors and timely intervention can reduce the occurrence of cognitive frailty in elderly patients with multimorbidity and improve their quality of life. To explore the risk factors, a risk prediction model is established to provide a reference for early screening and intervention of cognitive frailty in elderly patients with multimorbidity.MethodsNine communities were selected based on multi-stage stratified random sampling from May–June 2022. A self-designed questionnaire and three cognitive frailty rating tools [Frailty Phenotype (FP), Montreal Cognitive Assessment (MoCA), and Clinical Qualitative Rating (CDR)] were used to collect data for elderly patients with multimorbidity in the community. The nomogram prediction model for the risk of cognitive frailty was established using Stata15.0.ResultsA total of 1200 questionnaires were distributed in this survey, and 1182 valid questionnaires were collected, 26 non-traditional risk factors were included. According to the characteristics of community health services and patient access and the logistic regression results, 9 non-traditional risk factors were screened out. Among them, age OR = 4.499 (95%CI:3.26–6.208), marital status OR = 3.709 (95%CI:2.748–5.005), living alone OR = 4.008 (95%CI:2.873–5.005), and sleep quality OR = 3.71(95%CI:2.730–5.042). The AUC values for the modeling and validation sets in the model were 0. 9908 and 0.9897. Hosmer and Lemeshow test values for the modeling set were χ2 = 3.857, p = 0.870 and for the validation set were χ2 = 2.875, p = 0.942.ConclusionThe prediction model could help the community health service personnel and elderly patients with multimorbidity and their families in making early judgments and interventions on the risk of cognitive frailty.

Item analysis of G8 screening in uro-oncologic geriatric patients

Introduction/backgroundThe G8 score is a widespread screening tool for geriatric frailty in oncology. The aim of this study was to evaluate the scores and relevance of G8 items in a standard screening of geriatric patients with uro-oncologic diseases to better understand the results of the assessment.MethodsEighty-two consecutive uro-oncologic geriatric patients aged 75 years and older were evaluated. All patients underwent a G8 screening that consisted of 8 items. Patients with a G8 score above 14 were considered geriatric “fit”, while others were considered to be “frail”. Overall results and single item scores were evaluated. Clinical data were gathered from patients’ charts.ResultsThe mean age of the patients was 82 years (min. 75–max. 102). In 36 of the patients, the G8 score indicated “no-frailty”, and in 46 patients, the G8 score indicated “frailty”. The mean G8 score was 12.9 (min 4–max 17 pts). Item analysis revealed that points were most often lost in items H (polypharmacy), P (comparison of health status to peers) and Age. Fifty-nine, 56 and 52 patients lost points on item Age, item H and item P, respectively. In contrast, the majority of patients reached the maximum score for nutritional items [i.e., items A (food intake), B (weight loss) and F (body mass index (BMI))]. For item A, 73 patients reached the maximum score; for item B, 62 patients reached the maximum score; and for item F, 72 patients reached the maximum score. There were no differences in this distribution pattern when comparing tumour entities, sex, and patients with local vs. metastatic disease.ConclusionThe present study revealed a high percentage of suspicious test results. Potential reasons for these findings include the low threshold of the G8 overall score and the fact that in some items, points were easily lost. Modifications of the test should be considered.

The tele-liver frailty index (TeLeFI): development of a novel frailty tool in patients with cirrhosis via telemedicine

Frailty is a critical determinant of outcomes in cirrhosis patients. The increasing use of telemedicine has created an unmet need for virtual frailty assessment. We aimed to develop a telemedicine-enabled frailty tool (tele-liver frailty index). Adults with cirrhosis in the liver transplant setting underwent ambulatory frailty testing with the liver frailty index (LFI) in-person, then virtual administration of (1) validated surveys (eg, SARC-F and Duke Activity Status Index [DASI]), (2) chair stands, and (3) balance. Two models were selected and internally validated for predicting LFI ≥4.4 using: (1) Bayesian information criterion (BIC), (2) C-statistics, and (3) ease of use. Of 145 patients, the median (interquartile range) LFI was 3.7 (3.3-4.2); 15% were frail. Frail (vs not frail) patients reported significantly greater impairment on all virtually assessed instruments. We selected 2 parsimonious models: (1) DASI + chair/bed transfer (SARC-F) (BIC 255, C-statistics 0.78), and (2) DASI + chair/bed transfer (SARC-F) + virtually assessed chair stands (BIC 244, C-statistics 0.79). Both models had high C-statistics (0.76-0.78) for predicting frailty. In conclusion, the tele-liver frailty index is a novel tool to screen frailty in liver transplant patients via telemedicine pragmatically and may be used to identify patients who require in-person frailty assessment, more frequent follow-up, or frailty intervention.