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

Development, Validation, and Application of the Electronic Frailty Index: A Scoping Review

OBJECTIVE

The aim of this scoping review was to examine the scope and characteristics of the published literature related to the Electronic Frailty Index (eFI).

DESIGN

Scoping review.

SETTING AND PARTICIPANTS

Original studies related to the eFI in older adults.

METHODS

Six databases were searched for articles published between March 2016 and August 2024: PubMed, Web of Science, Cochrane Library, Scopus, China National Knowledge Infrastructure (CNKI), and Wanfang Database. Data extracted included the publication year, country, sample size, data sources for developing an eFI, number of items included in the eFI, performance of the eFI, and application of the eFI.

RESULTS

Of the 424 articles initially retrieved, this scoping review included 50 studies for analysis. Thirty-nine (78%) of these studies were conducted after the year 2019. Moreover, we identified 8 distinct eFIs. Twelve studies assessed the performance of eFIs, whereas 30 studies used them. The eFIs covered 4 key domains: diseases, functional information, laboratory tests and measures, and symptoms and signs. The most common outcome examined was mortality. Furthermore, the eFIs were applied for diverse purposes, including exploring the relationship between frailty and health outcomes.

CONCLUSIONS AND IMPLICATIONS

This scoping review revealed that eFIs can be developed using various electronic health care data sources, and they have been extensively employed for various population-level purposes. The observed associations between the eFIs, existing frailty assessment tools, and health outcomes highlight their utility in evaluating the care needs of an aging population.

Frailty indices based on routinely collected data: a scoping review

A frailty index (FI) is a frailty assessment tool calculated as the proportion of the number of health-related deficits an individual has to the total number of variables in the index. Routinely collected clinical and administrative data can be used as sources of deficits to automatically calculate FIs. This scoping review aimed to evaluate the current research landscape on routine data-based FIs. We searched seven databases to find literature published in 2013-2023. Main inclusion criteria were original research articles on FIs constructed from routine data, with deficits in at least two of the following categories: "symptoms/signs", "laboratory values", "diseases", "disabilities", and "others". From 7526 publications screened, 218 were included. Studies were primarily from North America (47.7 %), conducted in the community (35.3 %), and used routine data-based FIs for risk stratification (51.4 %). FIs were calculated using various routine data sources; however, most were initially developed and validated using hospital records. We noted geographical differences in study settings and routine data sources. We identified 611 unique deficits comprising these FIs. Most were either "diseases" (34.4 %) or "symptoms/signs" (32.1 %). Routine data-based FIs are feasible and valid risk stratification tools, but research is confined to high-income countries, their routine adoption is slow, and deficits comprising these FIs emphasise a reactive and overtly medical approach in addressing frailty. Future directions include exploring the feasibility and applicability of using routine databases for frailty assessment in lower- and middle-income countries, and leveraging non-clinical routine data through data linkages to proactively identify and manage frailty.

Association between laboratory data-based frailty index and clinical health outcomes in critically ill older patients: A retrospective correlational study

BACKGROUND

Although frailty assessment is crucial for understanding critically ill patients' prognosis, traditional frailty measures require substantial efforts and time from health care professionals. To address this limitation, the laboratory frailty index (FI-LAB) based on laboratory clinical data was developed. However, knowledge regarding its correlation with health outcomes among critically ill older patients is limited.

AIM

To identify the association between the FI-LAB and acute, mid- and long-term outcomes among critically ill older adults.

STUDY DESIGN

This retrospective correlational study used electronic health records of 2106 older patients who were admitted to the intensive care unit at a tertiary hospital in Seoul, Korea. Acute and mid-term outcomes included occurrence of delirium and in-hospital mortality, and the long-term outcome included 1-year mortality. Logistic regression was used to explore the relationships across FI-LAB, delirium, and in-hospital mortality, while Cox proportional hazard regression was used to analyse the relationship between FI-LAB and 1-year mortality.

RESULTS

Frailty assessed by FI-LAB was significantly associated with increased risk of delirium (odds ratio [OR] = 6.21, 95% confidence interval [CI] = 2.31-25.39, p = .009), in-hospital mortality (OR = 2.38, 95% CI = 1.15-5.79, p = .014), and 1-year mortality (hazard ratio = 2.47, 95% CI = 1.16-5.25, p = .019) after controlling for covariates.

CONCLUSIONS

The study highlighted the importance of using FI-LAB for screening frailty in critically ill older adults. Health care providers can improve patients' acute, mid- and long-term outcomes to develop more individualised management plans based on FI-LAB scores.

RELEVANCE TO CLINICAL PRACTICE

The FI-LAB score calculated from routine laboratory data can be used by nurses as a screening tool to identify frail older adults in critical care. Early detection of frailty would allow for closer monitoring and the implementation of interventions to reduce delirium and mortality.

Explainable machine learning framework for biomarker discovery by combining biological age and frailty prediction

Biological age (BA) and frailty represent two distinct health measures that offer valuable insights into the aging process. Comparing and analyzing blood-based biomarkers from the machine learning (ML) predictors of BA and frailty helps deepen our understanding of aging. This study aimed to develop a novel framework to identify biomarkers of aging by combining BA and frailty ML predictors with eXplainable Artificial Intelligence (XAI) techniques. We utilized data from middle-aged and older Chinese adults (≥ 45 years) in the 2011/2012 wave (n = 9702) and the 2015/2016 wave (n = 9455, as test set validation) of the China Health and Retirement Longitudinal Study (CHARLS). Sixteen blood-based biomarkers were used to predict BA and frailty. Four tree-based ML algorithms were employed in the training and validation, and performance metrics were compared to select the best models. Then, SHapley Additive exPlanations (SHAP) analysis was conducted on the selected models. CatBoost performed the best in the BA predictor, and Gradient Boosting performed the best in the frailty predictor. Traditional ML feature importance identified cystatin C and glycated hemoglobin as the major contributors for their respective models. However, subsequent SHAP analysis demonstrated that only cystatin C was the primary contributor in both models. The proposed framework can easily incorporate additional biomarkers, providing a scalable and comprehensive toolset that offers a quantitative understanding of biomarkers of aging.

Relationship between the laboratory test-based frailty index and overall mortality in critically ill patients with acute pancreatitis: a retrospective study based on the MIMIC-IV database

Background and aims

The frailty index, based on laboratory assessments, helps identify individuals at risk for adverse health outcomes. However, its relationship with overall mortality in acute pancreatitis patients in ICUs remains unclear. This study aims to investigate the association between the frailty index and all-cause mortality and assess its prognostic value for these patients.

Methods

We carried out a retrospective observational investigation utilizing data from the Medical Information Mart for Intensive Care IV (MIMIC-IV 2.2) database. Extract data from the database for all ICU patients (first-time ICU admissions, age ≥ 18 years) who meet the diagnostic criteria for acute pancreatitis. The frailty index derived from laboratory tests (FI-lab) encompassed three vital sign indicators and 30 laboratory test indicators. Patients were categorized into four groups based on quartiles of the FI-lab score. To assess the differences in 28-day all-cause mortality among these groups, we employed Kaplan-Meier analysis, whereas the relationship between FI-lab scores and 28-day mortality was explored through Cox proportional hazards analysis. In addition, we applied Harrell's C statistic, Integrated Discrimination Improvement (IDI), and Net Reclassification Improvement (NRI) to assess the additional predictive capability of FI-lab scores compare to traditional disease severity metrics.

Results

The study included a total of 741 patients (all age ≥ 18 years, 19.84% age > 75 years, 41.16% Female). The Kaplan-Meier analysis demonstrated that individuals with elevated FI-lab scores exhibited a significantly heightened risk of all-cause mortality (log-rank p < 0.0001). The multivariate Cox regression analysis suggested that treating FI-lab as a continuous variable (per 0.01 increment) was linked to an increased risk of 28-day all-cause mortality [hazard ratio (HR) 1.072, 95% confidence interval (CI) (1.055-1.089), p < 0.001]. Moreover, when FI-lab was analyzed as a categorical variable, patients in the fourth quartile of FI-lab had a notably greater risk of 28-day all-cause mortality in comparison to those in the first quartile [HR 9.933, 95% CI (4.676-21.104), p < 0.001]. Additionally, the integration of FI-lab scores with conventional disease severity scores improved the predictive performance for 28-day mortality.

Conclusion

In patients in the ICU who have been diagnosed with acute pancreatitis, the FI-lab score functions as a reliable indicator of short-term mortality. Early detection of patients at high risk for acute pancreatitis through the implementation of the FI-lab score, along with prompt interventions, is essential for enhancing these individuals' prognoses.

Application of laboratory frailty index in predicting delirium in elderly patients with community-acquired pneumonia

Background

With the global aging population, community-acquired pneumonia and delirium are increasingly critical health issues among the elderly. The Laboratory Frailty Index provides an objective measure of frailty. This study explores its capacity in predicting delirium and examines the interplay between frailty and nutritional status in elderly patients with community-acquired pneumonia.

Methods and materials

This retrospective study included 481 elderly patients aged 75 and above diagnosed with community-acquired pneumonia. The Laboratory Frailty Index was calculated by dividing the sum of abnormal indicator scores by the total number of test indicators, resulting in a score ranging from 0 to 1, with higher values indicating greater frailty.

Results

Higher Laboratory Frailty Index scores were associated with an increased risk of delirium. The index's predictive accuracy improved when combined with nutritional assessments. Patients experiencing malnutrition alongside higher frailty scores exhibited a higher risk of adverse outcomes. Nutritional status mediated the relationship between frailty and delirium, underlining the significance of addressing both variables.

Conclusion

The Laboratory Frailty Index is a robust predictor of delirium in elderly patients with community-acquired pneumonia. These findings provide valuable insights for the early identification and intervention of delirium in clinical settings.

Association between frailty index based on laboratory tests and all-cause mortality in critically ill patients with heart failure

BACKGROUND

The frailty index based on laboratory tests (FI-lab) can identify individuals at increased risk for adverse health outcomes. The association between the FI-lab and all-cause mortality in patients with heart failure (HF) in the intensive care unit (ICU) remains unknown. This study aimed to determine the correlation between FI-lab and all-cause mortality to evaluate the impact of FI-lab on the prognosis of critically ill patients with HF.

METHODS

This retrospective observational study utilized data extracted from the Medical Information Mart for Intensive Care IV database. The FI-lab, which consists of 33 laboratory tests, was constructed. Patients were then grouped into quartiles (Q1-Q4) based on their FI-lab scores. Kaplan-Meier analysis was used to compare all-cause mortality among the four groups. A Cox proportional hazard analysis was conducted to examine the association between the FI-lab score and all-cause mortality. The incremental predictive value of adding FI-lab to classical disease severity scores was assessed using Harrell's C statistic, integrated discrimination improvement (IDI) and net reclassification improvement (NRI).

RESULTS

Among 3021 patients, 838 (27.74%) died within 28 days, and 1400 (46.34%) died within a 360 day follow-up period. Kaplan-Meier analysis indicated that patients with higher FI-lab scores had significantly higher risks of all-cause mortality (log-rank P < 0.001). Multivariable Cox regression suggested that FI-lab, evaluated as a continuous variable (for each 0.01 increase), was associated with increased 28 day mortality [hazard ratio (HR) 1.02, 95% confidence interval (CI) (1.01-1.03), P < 0.001] and 360 day mortality [HR 1.02, 95% CI (1.01-1.02), P < 0.001]. When assessed in quartiles, the 28 day mortality risk [HR 1.66, 95% CI (1.28-2.15), P < 0.001] and 360 day mortality risk [HR 1.48, 95% CI (1.23-1.8), P < 0.001] were significantly higher for FI-lab Q4 compared with FI-lab Q1. FI-lab significantly improved the predictive capability of classical disease severity scores for 28 and 360 day mortality.

CONCLUSIONS

In ICU patients diagnosed with HF, the FI-lab is a potent predictor of short-term and long-term mortality in critically ill patients with HF. The active use of FI-lab to identify high-risk groups among critically ill HF patients and initiate timely interventions may have significant value in improving the prognosis of critically ill patients with HF.

FI-lab in the emergency department and adverse outcomes among acutely hospitalized older adults

BACKGROUND

The emergency department is treating a growing number of older patients with frailty, which has been linked to poorer outcomes. Urgency is generally emphasized in the emergency department based on indicators such as triage scores and early warning scores for decision-making. However, this approach may not be sufficient for frail older people. The Frailty Index-laboratory (FI-lab) has been used as a simple assessment tool for frailty, but it may also reflect disease severity and predict adverse outcomes in the emergency care setting. Therefore, we aimed to evaluate the association between FI-lab in the emergency room and adverse outcomes during hospitalization through comparison with assessments using triage and early warning scores.

METHODS

This was a retrospective cohort study conducted in a tertiary hospital. The study included patients aged 65 years or older who were admitted to the general internal medicine ward after being initially evaluated in the emergency department. FI-lab was calculated using 24 laboratory parameters from blood tests. The National Early Warning Score (NEWS), the Japan Triage and Acuity Scale (JTAS), and the modified JTAS were also used as prognostic indicators, and their association with adverse outcomes was compared with that of FI-lab.

RESULTS

In total, 872 patients (mean age, 80.9 years; male, 52.6 %) were analyzed. Patients who died during hospitalization had a higher FI-lab than those who survived. In multiple regression analysis, FI-lab, NEWS, and the modified JTAS were significantly associated with in-hospital death and prolonged length of hospital stay. In contrast, none of these indices were associated with in-hospital falls. The FI-lab was independently associated with the likelihood of discharge to home.

CONCLUSIONS

FI-lab evaluated in the emergency department reflected the severity of illness in acutely hospitalized older adults, similarly to NEWS and JTAS, and was a useful indicator for predicting adverse outcomes. These results may indicate the value of FI-lab for older adults in the acute care setting.

Longitudinal association between Body mass index (BMI), BMI trajectories and the risk of frailty among older adults: A systematic review and meta-analysis of prospective cohort studies

OBJECTIVE

We aimed to determine whether BMI categories and BMI trajectories were longitudinally associated with frailty in older adults via systematic review and meta-analysis of prospective cohort studies.

METHOD

3 databases (PubMed/MEDLINE, EMBASE and Web of Science) were systematically searched from inception to 8 September 2023. Two independent reviewers extracted data and appraised study quality. The quality of the studies was assessed using the Newcastle-Ottawa Scale. Data were pooled using random-effects models.

RESULTS

7 prospective cohort studies with 23043 participants were included in final BMI categories analyses, and 3 studies included BMI trajectory(23725 individuals). Compared with normal weight, we found a positive association between obesity (odds ratios(OR) = 1.74, 95 % confidence interval (CI): 1.21-2.51, P = 0.003), underweight (OR = 1.70, 95 % CI: 1.13-2.57, P = 0.011) and frailty in older adults. In middle age subgroup, compared with normal weight, OR of 2.21 (95 % CI: 1.44-3.38;I2 = 0 %) for overweight and OR of 5.20 (95 % CI: 2.56-10.55; I2 = 0 %) for obesity were significantly associated with frailty. In old age subgroup, compared with normal weight, only OR of 1.41 (95 % CI: 1.13-1.77; I2 = 65 %) for obesity was significantly associated with frailty. The results of BMI trajectories found that decreasing BMI (OR = 3.25, 95 % CI: 2.20-4.79, P < 0.0001) and consistently high BMI (OR = 3.66, 95 % CI: 2.03-6.61, P < 0.0001) increase the risk of frailty compared to consistently normal or overweight.

CONCLUSION

Overweight and obesity in middle age were associated with significantly higher frailty in older adults, while obesity and underweight in old age were associated with relatively higher frailty in older adults. Early weight control may be beneficial for old age.

Frailty Index Based on Common Laboratory Tests for Patients Starting Home-Based Medical Care

OBJECTIVES

To determine whether a Frailty Index based on laboratory tests (FI-lab) is associated with clinical outcomes independently of a standard nonlaboratory Frailty Index (FI-clinical) in older patients starting home-based medical care.

DESIGN

Secondary analysis of data from a multicenter prospective cohort study.

SETTING AND PARTICIPANTS

Patients aged ≥65 years who were starting home-based medical care services provided by doctors and nurses at Nagoya, Japan.

METHODS

We calculated FI-lab (proportion of abnormal results out of 25 commonly tested laboratory parameters) and FI-clinical using 42 items based on data obtained at enrollment. The primary outcome was mortality within 2 years after starting home-based medical care. A sensitivity analysis was also conducted with 1-year mortality as the outcome. Other outcomes included hospitalization and nursing home admission within 2 years.

RESULTS

In total, 188 patients (mean age 79.9 ± 10.2 years, 57.5% male) were included. The median FI-lab was 0.40 [interquartile range (IQR) 0.29-0.50] and the median FI-clinical was 0.32 (IQR 0.24-0.43). Sixty-nine patients (36.7%) died within 2 years of starting home-based medical care. A Cox proportional hazards regression analysis including age, sex, FI-lab, and FI-clinical as independent variables revealed that FI-lab was associated with 2-year mortality independently of FI-clinical [FI-lab per 0.1 unit, odds ratio (OR) 1.49, 95% CI 1.25-1.77; FI-clinical per 0.1 unit, OR 1.13, 95% CI 0.90-1.41]. The sensitivity analysis showed similar results for 1-year mortality. Neither FI-lab nor FI-clinical was associated with hospitalization or nursing home admission within 2 years.

CONCLUSIONS AND IMPLICATIONS

FI-lab was associated with 2-year mortality in patients starting home-based medical care, independently of FI-clinical, and may be useful for risk assessment in this population. Studies with larger sample sizes are needed.

Rehabilitation interventions to modify physical frailty in adults before lung transplantation: a systematic review protocol

INTRODUCTION

Lung transplantation is the gold-standard treatment for end-stage lung disease for a small group of patients meeting strict acceptance criteria after optimal medical management has failed. Physical frailty is prevalent in lung transplant candidates and has been linked to worse outcomes both on the waiting list and postoperatively. Exercise has been proven to be beneficial in optimising exercise capacity and quality of life in lung transplant candidates, but its impact on physical frailty is unknown. This review aims to assess the effectiveness of exercise interventions in modifying physical frailty for adults awaiting lung transplantation.

METHODS AND ANALYSIS

This protocol was prospectively registered on the PROSPERO database. We will search four databases plus trial registries to identify primary studies of adult candidates for lung transplantation undertaking exercise interventions and assessing outcomes pertaining to physical frailty. Studies must include at least 10 participants. Article screening will be performed by two researchers independently at each stage. Extraction will be performed by one reviewer and checked by a second. The risk of bias in studies will be assessed by two independent reviewers using tools appropriate for the research design of each study; where appropriate, we will use Cochrane Risk of Bias 2 or ROBINS-I. At each stage of the review process, discrepancies will be resolved through a consensus or consultation with a third reviewer. Meta-analyses of frailty outcomes will be performed if possible and appropriate as will prespecified subgroup and sensitivity analyses. Where we are unable to perform meta-analysis, we will conduct narrative synthesis following Synthesis without Meta-analysis guidance. The review will be reported using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist.

ETHICS AND DISSEMINATION

No ethical issues are predicted due to the nature of this study. Dissemination will occur via conference abstracts, professional networks, peer-reviewed journals and patient support groups.

PROSPERO REGISTRATION NUMBER

CRD42022363730.

Perspectives on Aging and Quality of Life

The aging of the world's population and the health problems accompanying it are becoming increasingly severe. Healthcare policies in developed countries focus on how to prevent and treat diseases associated with aging and how to maintain quality of life. Typical age-related diseases include deafness, cataracts, osteoarthritis, chronic obstructive pulmonary disease, diabetes mellitus, and dementia. Although the mechanisms by which these diseases develop differ, they are all caused by the accumulation of molecular and cellular damage over time. In addition, age-related diseases can cause a decline in physical and mental functions and the ability to perform activities of daily living, as well as the loss of roles in society and a sense of fulfillment in life. Therefore, there is a need for treatment and measures to accurately grasp and maintain quality of life. This review aims to introduce areas and representative papers expected to be contributed to the special issue of "Aging and Quality of Life".