A Cumulative Deficit Laboratory Test-based Frailty Index: Personal and Neighborhood Associations

A Sense of Control and Wellbeing in Older People Living with Frailty: A Scoping Review

A sense of control is important for supporting older people living with frailty to develop adaptive functioning to optimize wellbeing. This scoping review examined the literature on the sense of control and wellbeing in older people living with frailty within their everyday life and care service use. Nine databases were searched using the timeframe 2000 to 2021 to identify key ideas regarding control and wellbeing in older people with frailty. The review highlighted three major themes: a) Control as conveyed in bodily expressions and daily activities, b) Sense of control and influence of place of residence, and c) Control within health and social care relationships. Maintaining a sense of control is not only an internal feeling but is impacted by physical and social environments. Greater focus is needed on the nature of relationships between older people living with frailty and those who work alongside them, which support control and wellbeing.

Predictive Strategies to Reduce the Risk of Rehospitalization with a Focus on Frail Older Adults: A Narrative Review

Frailty is a geriatric syndrome that has physical, cognitive, psychological, social, and environmental components and is characterized by a decrease in physiological reserves. Frailty is associated with several adverse health outcomes such as an increase in rehospitalization rates, falls, delirium, incontinence, dependency on daily living activities, morbidity, and mortality. Older adults may become frailer with each hospitalization; thus, it is beneficial to develop and implement preventive strategies. The present review aims to highlight the epidemiological importance of frailty in rehospitalization and to compile predictive strategies and related interventions to prevent hospitalizations. Firstly, it is important to identify pre-frail and frail older adults using an instrument with high validity and reliability, which can be a practically applicable screening tool. Comprehensive geriatric assessment-based care is an important strategy known to reduce morbidity, mortality, and rehospitalization in older adults and aims to meet the needs of frail patients with a multidisciplinary approach and intervention that includes physiological, psychological, and social domains. Moreover, effective multimorbidity management, physical activity, nutritional support, preventing cognitive frailty, avoiding polypharmacy and anticholinergic drug burden, immunization, social support, and reducing the caregiver burden are other recommended predictive strategies to prevent post-discharge rehospitalization in frail older adults.

Machine learning functional impairment classification with electronic health record data

BACKGROUND

Poor functional status is a key marker of morbidity, yet is not routinely captured in clinical encounters. We developed and evaluated the accuracy of a machine learning algorithm that leveraged electronic health record (EHR) data to provide a scalable process for identification of functional impairment.

METHODS

We identified a cohort of patients with an electronically captured screening measure of functional status (Older Americans Resources and Services ADL/IADL) between 2018 and 2020 (N = 6484). Patients were classified using unsupervised learning K means and t-distributed Stochastic Neighbor Embedding into normal function (NF), mild to moderate functional impairment (MFI), and severe functional impairment (SFI) states. Using 11 EHR clinical variable domains (832 variable input features), we trained an Extreme Gradient Boosting supervised machine learning algorithm to distinguish functional status states, and measured prediction accuracies. Data were randomly split into training (80%) and test (20%) sets. The SHapley Additive Explanations (SHAP) feature importance analysis was used to list the EHR features in rank order of their contribution to the outcome.

RESULTS

Median age was 75.3 years, 62% female, 60% White. Patients were classified as 53% NF (n = 3453), 30% MFI (n = 1947), and 17% SFI (n = 1084). Summary of model performance for identifying functional status state (NF, MFI, SFI) was AUROC (area under the receiving operating characteristic curve) 0.92, 0.89, and 0.87, respectively. Age, falls, hospitalization, home health use, labs (e.g., albumin), comorbidities (e.g., dementia, heart failure, chronic kidney disease, chronic pain), and social determinants of health (e.g., alcohol use) were highly ranked features in predicting functional status states.

CONCLUSION

A machine learning algorithm run on EHR clinical data has potential utility for differentiating functional status in the clinical setting. Through further validation and refinement, such algorithms can complement traditional screening methods and result in a population-based strategy for identifying patients with poor functional status who need additional health resources.

Development, validation and performance of laboratory frailty indices: A scoping review

INTRODUCTION

Frailty is a syndrome characterised by decline in functional ability and increasing vulnerability to disease and associated with adverse outcomes. Several established methods exist for assessing frailty. This scoping review aims to characterise the development and validation of frailty indices based on laboratory test results (FI-Lab) and to assess their utility.

METHODS

Studies were included in the review if they included data concerning the development and/or testing an FI-Lab using the deficit accumulation method. Studies were identified using PubMed/MEDLINE, Embase (Elsevier), OpenGrey and Google Scholar from 2010 to 2021. Two reviewers independently screened all abstracts, and those that met the inclusion criteria were reviewed in detail. Data extracted included details about the study characteristics, number, type and coding of laboratory variables included, validation, and outcomes. A narrative synthesis of the available evidence was adopted.

RESULTS

The search yielded 915 articles, of which 29 studies were included. In general, 89% of studies were conducted after 2016 and 51% in a hospital-based setting. The number of variables included in FI-Labs ranged from 13 to 77, and 51% included some non-laboratory variables in their indices, with pulse and blood pressure being the most frequent. The validity of FI-Lab was demonstrated through change with age, correlation with established frailty indices and association with adverse health outcomes. The most frequent outcome studied was mortality (79% of the studies), with FI-Lab associated with increased mortality in all but one. Other outcomes studied included self-reported health, institutionalisation, and activities of daily living. The effect of combining the FI-Lab with a non-laboratory-based FI was assessed in 7 studies with a marginal increase in predictive ability.

CONCLUSION

Frailty indices constructed based on the assessment of laboratory variables, appear to be a valid measure of frailty and robust to the choice of variables included.

The frailty index based on laboratory test data as a tool to investigate the impact of frailty on health outcomes: a systematic review and meta-analysis

The frailty index (FI) quantifies frailty as deficit accumulation. It has been adapted to employ laboratory test data (FI-Lab). Our objective was to systematically review and meta-analyse the FI-Lab's ability to predict mortality. Secondary objectives were to review the FI-Lab's association with adverse health outcomes and whether FI-Lab scores differed between the sexes. A systematic literature search was carried out using six online databases to identify studies that measured the FI-Lab in humans. Hazard ratios (HRs) were combined in a meta-analysis to create a pooled risk estimate for mortality. Of the 1,201 papers identified, spanning January 2010 until 11 July 2022, 38 were included. FI-Lab scores per 0.01 unit increase predicted mortality overall (HR = 1.04; 95% confidence interval (CI) = 1.03-1.05) and for studies with a mean age of 81+ years (HR = 1.04; 95% CI = 1.03-1.05). The quality of evidence for these meta-analyses are moderate and high, respectively. Further, higher FI-Lab scores were associated with more frequent adverse health outcomes. Sex differences in FI-Lab scores varied, with no consistent indication of a sex effect. The FI-Lab is associated with mortality and with a variety of adverse health outcomes. No consistent sex differences in FI-Lab scores were observed, with several studies in disagreement. Notably, these conclusions were most relevant to older (65+ years old) individuals; further evidence in younger people is needed in both clinical and population representative studies.

The degree of frailty as a translational measure of health in aging

Frailty is a multiply determined, age-related state of increased risk for adverse health outcomes. We review how the degree of frailty conditions the development of late-life diseases and modifies their expression. The risks for frailty range from subcellular damage to social determinants. These risks are often synergistic-circumstances that favor damage also make repair less likely. We explore how age-related damage and decline in repair result in cellular and molecular deficits that scale up to tissue, organ and system levels, where they are jointly expressed as frailty. The degree of frailty can help to explain the distinction between carrying damage and expressing its usual clinical manifestations. Studying people-and animals-who live with frailty, including them in clinical trials and measuring the impact of the degree of frailty are ways to better understand the diseases of old age and to establish best practices for the care of older adults.

Utility of Frailty Assessment in Urologic Stone Surgery: A Review of the Literature

Introduction & Objective As life expectancy continues to rise, the prevalence of frailty is also increasing. The idea of frailty and its effect on the operative patient has been previously studied, but not regularly incorporated into routine practice. We present a review on frailty metrics in the literature, validated assessment methods, and simplified screening tools, to better predict and optimize patient outcomes. Methods An online Pubmed search was conducted by 3 authors (TA, TB, MM) for all frailty, frailty assessment, and pre-operative risk assessment. Only English publications were included in the analysis. Full text analysis was then conducted by all three authors to validate the data. Results An abundance of literature was found on frailty. Even though some methods are validated as very effective for assessing frailty, they may be time consuming and require a specialist. various quick screening methods are also present, many already validated, and should be utilized by urologist more regularly. Conclusions Multiple studies demonstrate the relationship between frailty and surgical patients' outcome. Many quick, office based, validated tools to screen for frailty are described, and should be incorporated into our practice in appropriate patients. Future research is now focused on the concept of "prehabilitation" to improve patient frailty status in the pre-operative setting, and consequently operative outcomes.

Neighborhood Characteristics and Frailty: A Scoping Review

BACKGROUND AND OBJECTIVES

Frailty is highly prevalent in later life and associated with early mortality and adverse health outcomes. The neighborhood has been identified as an important contributor to individual health, and neighborhood characteristics may contribute to frailty development. A scoping review was conducted of the peer-reviewed literature to better understand how physical and social neighborhood characteristics contribute to frailty.

RESEARCH DESIGN AND METHODS

Following an established scoping review methodology, we searched four peer-reviewed databases for relevant studies published from January 1, 2008, to December 31, 2018. Data extracted from studies included study characteristics, operationalization of neighborhood, the conceptual model of the neighborhood-frailty relationship, operationalization of frailty, and study findings for associations among neighborhood variables and frailty indicators.

RESULTS

A total of 522 articles were identified and 13 articles were included in the final data charting. Existing studies suggest that neighborhood characteristics are associated with frailty in later life. Few studies articulated a conceptual model identifying exact mechanisms through which neighborhood factors affected frailty. Studies designs were mostly cross-sectional. Longitudinal studies did not measure neighborhood characteristics over time. Studies varied considerably in how they operationalized the neighborhood. Frailty was most commonly assessed using a 5-point phenotype or a frailty index approach.

DISCUSSION AND IMPLICATIONS

Findings indicate that research on the relationship between neighborhood characteristics and frailty is an emerging area of inquiry. Additional studies are needed to more definitely explicate mechanisms through which neighborhoods contribute to, or protect older adults from, frailty.

Association of Blood Chemistry Quantifications of Biological Aging With Disability and Mortality in Older Adults

Quantification of biological aging has been proposed for population surveillance of age-related decline in system integrity and evaluation of geroprotective therapies. However, methods of quantifying biological aging have been little studied in geriatric populations. We analyzed three clinical-biomarker-algorithm methods to quantify biological aging. Klemera-Doubal method Biological Age and homeostatic dysregulation algorithms were parameterized from analysis of U.S. National Health and Nutrition Examination Surveys (NHANES) data (N = 36,207) based on published methods. Levine method Biological Age was adapted from published analysis of NHANES data. Algorithms were applied to biomarker data from the Duke Established Populations for Epidemiologic Studies of the Elderly (Duke-EPESE) cohort of older adults (N = 1,374, aged 71-102 years, 35% male, 52% African American). We tested associations of biological aging measures with participant reported Activities of daily living (ADL), instrumental activities of daily living (IADL) dependencies, and mortality. We evaluated the sensitivity of results to the demographic composition of reference samples and biomarker sets used to develop biological aging algorithms. African American and white Duke-EPESE participants with more advanced biological aging reported dependence in more ADLs and IADLs and were at increased risk of death over follow-up through 2017. Effect sizes were similar across algorithms, but were strongest for Levine method Biological Age (per-quintile increase in ADL incidence rate ratio = 1.25, 95% confidence interval [1.17-1.37], IADL incidence rate ratio = 1.23 [1.15-1.32], mortality hazard ratio = 1.12 [1.08-1.16]). Results were insensitive to demographic composition of reference samples, but modestly sensitive to the biomarker sets used to develop biological aging algorithms. Blood-chemistry-based quantifications of biological aging show promise for evaluating the effectiveness of interventions to extend healthy life span in older adults.

Complementing chronic frailty assessment at hospital admission with an electronic frailty index (FI-Laboratory) comprising routine blood test results

BACKGROUND

Acutely ill and frail older adults have complex social and health care needs. It is important to understand how this complexity affects acute outcomes for admission to hospital. We validated a frailty index using routine admission laboratory tests with outcomes after patients were admitted to hospital.

METHODS

In a prospective cohort of older adults admitted to a large tertiary hospital in the United Kingdom, we created a frailty index from routine admission laboratory investigations (FI-Laboratory) linked to data comprising hospital outcomes. We evaluated the association between the FI-Laboratory and total days spent in hospital, discharge to a higher level of care, readmission and mortality.

RESULTS

Of 2552 admissions among 1750 older adults, we were able to generate FI-Laboratory values for 2254 admissions (88.3% of the cohort). More than half of admitted patients were women (55.3%) and the mean age was 84.6 (SD 14.0) years. We found that the FI-Laboratory correlated weakly with the Clinical Frailty Scale (CFS; r ² = 0.09). An increase in the CFS and the equivalent of 3 additional abnormal laboratory test results in the FI-Laboratory, respectively, were associated with an increased proportion of inpatient days (rate ratios [RRs] 1.43, 95% confidence interval [CI] 1.35-1.52; and 1.47, 95% CI 1.41-1.54), discharge to a higher level of care (odd ratios [ORs] 1.39, 95% CI 1.27-1.52; and 1.30, 95% CI 1.16-1.47) and increased readmission rate (hazard ratios [HRs] 1.26, 95% CI 1.17-1.37; and 1.18, 95% CI 1.11-1.26). Increases in the CFS and FI-Laboratory were associated with increased mortality HRs of 1.39 (95% CI 1.28-1.51) and 1.45 (95% CI 1.37-1.54), respectively.

INTERPRETATION

We determined that FI-Laboratory, distinct from baseline frailty, could be used to predict risk of many adverse outcomes. The score is therefore a useful way to quantify the degree of acute illness in frail older adults.

Race/Ethnic and Educational Disparities in the Association Between Pathogen Burden and a Laboratory-Based Cumulative Deficits Index

BACKGROUND

Disparities in adult morbidity and mortality may be rooted in patterns of biological dysfunction in early life. We sought to examine the association between pathogen burden and a cumulative deficits index (CDI), conceptualized as a pre-clinical marker of an unhealthy biomarker profile, specifically focusing on patterns across levels of social disadvantage.

METHODS

Using the data from the National Health and Nutrition Examination Survey 2003-2004 wave (aged 20-49 years), we examined the association of pathogen burden, composed of seven pathogens, with the CDI. The CDI comprised 28 biomarkers corresponding to available clinical laboratory measures. Models were stratified by race/ethnicity and education level.

RESULTS

The CDI ranged from 0.04 to 0.78. Nearly half of Blacks were classified in the high burden pathogen class compared with 8% of Whites. Among both Mexican Americans and other Hispanic groups, the largest proportion of individuals were classified in the common pathogens class. Among educational classes, 19% of those with less than a high school education were classified in the high burden class compared with 7% of those with at least a college education. Blacks in the high burden pathogen class had a CDI 0.05 greater than those in the low burden class (P < 0.05). Whites in the high burden class had a CDI only 0.03 greater than those in the low burden class (P < 0.01).

DISCUSSION

Our findings suggest there are significant social disparities in the distribution of pathogen burden across race/ethnic groups, and the effects of pathogen burden may be more significant for socially disadvantaged individuals.

Bed rest and accelerated aging in relation to the musculoskeletal and cardiovascular systems and frailty biomarkers: A review

Prolonged bed rest and lifelong physical inactivity cause deleterious effects to multiple physiological systems that appear to hasten aging processes. Many such changes are similar to those seen with microgravity in space, but at a much faster rate. Head down tilt bed rest models are used to study whole-body changes that occur with spaceflight. We propose that bed rest can be used to quantify accelerated human aging in relation to frailty. In particular, frailty as a measure of the accumulation of deficits estimates the variability in aging across systems, and moves away from the traditional single-system approach. Here, we provide an overview of the impact of bed rest on the musculoskeletal and cardiovascular systems as well as frailty-related biological markers and inflammatory cytokines. We also propose future inquiries to study the accumulation of deficits with head down bed rest and bed rest in the clinical setting, specifically to understand how unrepaired and unremoved subclinical and subcellular damage give rise to clinically observable health problems.

Frailty Screening and Interventions: Considerations for Clinical Practice

Frailty is recognized as a cornerstone of geriatric medicine. It increases the risk of geriatric syndromes and adverse health outcomes in older and vulnerable populations. Although multiple screening instruments have been developed and validated to improve feasibility in clinical practice, frequent lack of agreement between frailty instruments has slowed broad implementation of these tools. Despite this, interventions to improve frailty-related health outcomes developed to date include exercise, nutrition, multicomponent interventions, and individually tailored geriatric care models. Possible strategies to prevent frailty include lifestyle or behavioral interventions, proper nutrition, and increased activity levels and social engagement.

Investigating pathogen burden in relation to a cumulative deficits index in a representative sample of US adults

Pathogen burden is a construct developed to assess the cumulative effects of multiple, persistent pathogens on morbidity and mortality. Despite the likely biological wear and tear on multiple body systems caused by persistent infections, few studies have examined the impact of total pathogen burden on such outcomes and specifically on preclinical markers of dysfunction. Using data from two waves of the National Health and Nutrition Examination Survey, we compared three alternative methods for measuring pathogen burden, composed of mainly persistent viral infections, using a cumulative deficits index (CDI) as an outcome: single pathogen associations, a pathogen burden summary score and latent class analyses. We found significant heterogeneity in the distribution of the CDI by age, sex, race/ethnicity and education. There was an association between pathogen burden and the CDI by all three metrics. The latent class classification of pathogen burden showed particularly strong associations with the CDI; these associations remained after controlling for age, sex, body mass index, smoking, race/ethnicity and education. Our results suggest that pathogen burden may influence early clinical indicators of poor health as measured by the CDI. Our results are salient since we were able to detect these associations in a relatively young population. These findings suggest that reducing pathogen burden and the specific pathogens that drive the CDI may provide a target for preventing the early development of age-related physiological changes.

Development of a Physiological Frailty Index for the World Trade Center General Responder Cohort

Responders to the 9/11/2001 WTC attacks were exposed to multiple toxic pollutants. Since 2002, the health of the responder cohort has been continuously tracked by the WTC Health Monitoring Program. However, no assessments have been made of frailty, an important health metric given the current average age of the WTC responder cohort (55 years). In this study, we use laboratory test results and other physiological parameters to construct a physiological frailty index (FI-Lab) for this cohort. The study sample comprised responders aged 40 years or older who completed a health monitoring visit at Mount Sinai Center within the past 5 years. For each subject, FI-Lab was computed as the proportion of 20 physiological parameters (lab tests, pulmonary function, and blood pressure) on which the subject had abnormal values. Using negative binomial regression models, we tested FI-Lab's association with the SF-12 wellbeing score and various demographic characteristics. FI-Lab showed strong associations with the physical and mental components of the SF-12 as well as age, race, and smoking status. Using a cutoff of 0.25 to define presence of physiological/preclinical frailty, we found frailty prevalence in the study sample to be approximately 12%. This study demonstrates the feasibility of assessing preclinical frailty in the WTC responder cohort.

A frailty index from common clinical and laboratory tests predicts increased risk of death across the life course

A frailty index (FI) based entirely on common clinical and laboratory tests might offer scientific advantages in understanding ageing and pragmatic advantages in screening. Our main objective was to compare an FI based on common laboratory tests with an FI based on self-reported data; we additionally investigated if the combination of subclinical deficits with clinical ones increased the ability of the FI to predict mortality. In this secondary analysis of the 2003–2004 and 2005–2006 National Health and Nutrition Examination Survey data, 8888 individuals aged 20+ were evaluated. Three FIs were constructed: a 36-item FI using self-reported questionnaire data (FI-Self-report); a 32-item FI using data from laboratory test values plus pulse and blood pressure measures (FI-Lab); and a 68-item FI that combined all items from each index (FI-Combined). The mean FI-Lab score was 0.15 ± 0.09, the FI-Self-report was 0.11 ± 0.11 and FI-Combined was 0.13 ± 0.08. Each index showed some typical FI characteristics (skewed distribution with long right tail, non-linear increase with age). Even so, there were fewer people with low frailty levels and a slower increase with age for the FI-Lab compared to the FI-Self-report. Higher frailty level was associated with higher risk of death, although it was strongest at older ages. Both FI-Lab and FI-Self-report remained significant in a combined model predicting death. The FI-Lab was feasible and valid, demonstrating that even subclinical deficit accumulation increased mortality risk. This suggests that deficit accumulation, from the subcellular to the clinically visible is a useful construct that may advance our understanding of the ageing process.