FRAIL-NH Predicts Outcomes in Long Term Care

Frailty detection by healthcare professionals: a systematic review of the available English and French tools and their validation

BACKGROUND

There is a wide variety of frailty detection tools, but no gold standard. Choosing the most appropriate tool can therefore be complicated. Our systematic review seeks to provide useful data on the frailty detection tools available to help healthcare professionals in choosing a tool.

METHOD

We systematically searched for articles published between January 2001 and December 2022 in three electronic databases. Articles were to be written in English or French and were to discuss a frailty detection tool used by healthcare professionals in a population without specific health conditions. Any self-testing, physical testing or biomarkers were excluded. Systematic reviews and meta-analyses were also excluded. Data were extracted from two coding grids; one for the criteria used by the tools to detect frailty and the other for the evaluation of clinimetric parameters. The quality of the articles was assessed using QUADAS-2.

RESULTS

A total of 52 articles, covering 36 frailty detection tools, were included and analysed in the systematic review. Forty-nine different criteria were identified, with a median of 9 (IQR 6-15) criteria per tool. Regarding the evaluation of tool performances, 13 different clinimetric properties were identified, with a mean of 3.6 (± 2.2) properties assessed per tool.

CONCLUSION

There is considerable heterogeneity in the criteria used to detect frailty, as well as in the way tools are evaluated.

Prediction of Nursing Home Admission Using the FRAIL-NH Scale Among Older Adults in Post-Acute Care Settings

OBJECTIVES

The FRAIL-NH scale was developed to identify frailty status in nursing home residents. The purpose of this study was to examine the utility of the FRAIL-NH scale for predicting nursing home admission among patients in post-acute care settings. Design/ Setting/ Participants: This single-center, prospective, observational cohort study included participants aged 65 years or older who were admitted to a community-based integrated care ward (CICW) between July 2015 and November 2020.

MEASUREMENTS

Using the CICW database, we retrospectively classified participants as robust, prefrail, or frail based on the FRAIL-NH scale the score by identifying variables from our database that were most representative of each component. The following data were collected: examination findings, CICW admission and discharge information, length of CICW stay, and nursing home admission. The participants were divided into two groups based on whether or not they were admitted to a nursing home after CICW discharge. The hazard ratios (HRs) and 95% confidence intervals (CIs) for nursing home admission were calculated according to the FRAIL-NH categories using the Cox proportional hazards models with reference to the robust group. In the multivariate adjusted model, we adjusted for age, sex, nutritional status, cognitive function, living status, and economic status.

RESULTS

Data of 550 older adults were analyzed, of which 118 were admitted and 432 were not admitted to a nursing home. The frail group had a higher risk of nursing home admission (HR, 2.22; 95% CI 1.32-3.76) than the robust group.

CONCLUSIONS

This study showed that the FRAIL-NH scale was beneficial for predicting nursing home admission among older adults in the post-acute care setting. Thus, assessment using the FRAIL-NH scale may help to consider preparation and support for life after discharge.

Frailty in Nursing Homes-A Prospective Study Comparing the FRAIL-NH and the Clinical Frailty Scale

OBJECTIVES

Frailty is common in nursing home (NH) residents, but its prevalence in German institutions is unknown. Valid and easy-to-use screening tools are needed to identify frail residents. We used the FRAIL-NH scale and the Clinical Frailty Scale (CFS) to (1) obtain the prevalence of frailty, (2) investigate the agreement between both instruments, and (3) evaluate their predictive validity for adverse health events in German NH residents.

DESIGN

Prospective cohort study.

SETTING AND PARTICIPANTS

German NH residents (n = 246, age 84 ± 8 years, 67% female).

METHODS

Frailty status was categorized according to FRAIL-NH (nonfrail, frail, most frail) and CFS (not frail, mild to moderately frail, severely frail). Agreement between instruments was examined by Spearman correlation, an area under the receiver operating characteristic curve (AUC) with 95% CI, and sensitivity and specificity using the "most frail" category of FRAIL-NH as reference standard. Adverse health events (death, hospital admissions, falls) were recorded for 12 months, and multivariate cox and logistic regression models calculated.

RESULTS

According to FRAIL-NH, 71.1% were most frail, 26.4% frail, and 2.5% nonfrail. According to CFS, 66.3% were severely frail, 26.8% mild to moderately frail, and 6.9% not frail. Both scales correlated significantly (r = 0.78; R² = 60%). The AUC was 0.92 (95% CI 0.88-0.96). Using a CFS cutoff of 7 points, sensitivity was 0.90 and specificity 0.92. The frailest groups according to both instruments had an increased risk of death [FRAIL-NH hazard ratio (HR) 2.19, 95% CI 1.21-3.99; CFS HR 2.56, 95% CI 1.43-4.58] and hospital admission [FRAIL-NH odds ratio (OR) 1.95, 95% CI 1.06-3.58; CFS OR 1.79, 95% CI 1.01-3.20] compared to less frail residents. The FRAIL-NH predicted recurrent faller status (OR 2.57, 95% CI 1.23-5.39).

CONCLUSIONS AND IMPLICATIONS

Frailty is highly prevalent in German NH residents. Both instruments show good agreement despite different approaches and are able to predict adverse health outcomes. Based on our findings and because of its simple administration, CFS may be an alternative to FRAIL-NH for assessing frailty in NHs.

Trajectories of physical frailty and cognitive impairment in older adults in United States nursing homes

Background

U.S. nursing homes provide long-term care to over 1.2 million older adults, 60% of whom were physically frail and 68% had moderate or severe cognitive impairment. Limited research has examined the longitudinal experience of these two conditions in older nursing home residents.

Methods

This national longitudinal study included newly-admitted non-skilled nursing care older residents who had Minimum Data Set (MDS) 3.0 (2014–16) assessments at admission, 3 months, and 6 months (n = 266,001). Physical frailty was measured by FRAIL-NH and cognitive impairment by the Brief Interview for Mental Status. Separate sets of group-based trajectory models were fitted to identify the trajectories of physical frailty and trajectories of cognitive impairment, and to estimate the association between older residents’ characteristics at admission with each set of trajectories. A dual trajectory model was used to quantify the association between the physical frailty trajectories and cognitive impairment trajectories.

Results

Over the course of the first six months post-admission, five physical frailty trajectories [“Consistently Frail” (prevalence: 53.0%), “Consistently Pre-frail” (29.0%), “Worsening Frailty” (7.6%), “Improving Frailty” (5.5%), and “Consistently Robust” (4.8%)] and three cognitive impairment trajectories [“Consistently Severe Cognitive Impairment” (35.5%), “Consistently Moderate Cognitive Impairment” (31.8%), “Consistently Intact/Mild Cognitive Impairment” (32.7%)] were identified. One in five older residents simultaneously followed the trajectories of “Consistently Frail” and “Consistently Severe Cognitive Impairment”. Characteristics associated with higher odds of the “Improving Frailty”, “Worsening Frailty”, “Consistently Pre-frail” and “Consistently Frail” trajectories included greater at-admission cognitive impairment, age ≥ 85 years, admitted from acute hospitals, cardiovascular/metabolic diagnoses, neurological diagnoses, hip or other fractures, and presence of pain. Characteristics associated with higher odds of the “Consistently Moderate Cognitive Impairment” and “Consistently Severe Cognitive Impairment” included worse at-admission physical frailty, neurological diagnoses, hip fracture, and receipt of antipsychotics.

Conclusions

Findings provided information regarding the trajectories of physical frailty, the trajectories of cognitive impairment, the association between the two sets of trajectories, and their association with residents’ characteristics in older adults’ first six months post-admission to U.S. nursing homes. Understanding the trajectory that the residents would most likely follow may provide information to develop a comprehensive care approach tailored to their specific healthcare goals.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12877-022-03012-8.

Identifying older adults with frailty approaching end-of-life: A systematic review

BACKGROUND

People with frailty may have specific needs for end-of-life care, but there is no consensus on how to identify these people in a timely way, or whether they will benefit from intervention.

AIM

To synthesise evidence on identification of older people with frailty approaching end-of-life, and whether associated intervention improves outcomes.

DESIGN

Systematic review (PROSPERO: CRD42020462624).

DATA SOURCES

Six databases were searched, with no date restrictions, for articles reporting prognostic or intervention studies. Key inclusion criteria were adults aged 65 and over, identified as frail via an established measure. End-of-life was defined as the final 12 months. Key exclusion criteria were proxy definitions of frailty, or studies involving people with cancer, even if also frail.

RESULTS

Three articles met the inclusion criteria. Strongest evidence came from one study in English primary care, which showed distinct trajectories in electronic Frailty Index scores in the last 12 months of life, associated with increased risk of death. We found no studies evaluating established clinical tools (e.g. Gold Standards Framework) with existing frail populations. We found no intervention studies; the literature on advance care planning with people with frailty has relied on proxy definitions of frailty.

CONCLUSION

Clear implications for policy and practice are hindered by the lack of studies using an established approach to assessing frailty. Future end-of-life research needs to use explicit approaches to the measurement and reporting of frailty, and address the evidence gap on interventions. A focus on models of care that incorporate a palliative approach is essential.

Physical frailty and cognitive impairment in older nursing home residents: a latent class analysis

BACKGROUND

Little is known about the heterogeneous clinical profile of physical frailty and its association with cognitive impairment in older U.S. nursing home (NH) residents.

METHODS

Minimum Data Set 3.0 at admission was used to identify older adults newly-admitted to nursing homes with life expectancy ≥6 months and length of stay ≥100 days (n = 871,801). Latent class analysis was used to identify physical frailty subgroups, using FRAIL-NH items as indicators. The association between the identified physical frailty subgroups and cognitive impairment (measured by Brief Interview for Mental Status/Cognitive Performance Scale: none/mild; moderate; severe), adjusting for demographic and clinical characteristics, was estimated by multinomial logistic regression and presented in adjusted odds ratios (aOR) and 95% confidence intervals (CIs).

RESULTS

In older nursing home residents at admission, three physical frailty subgroups were identified: "mild physical frailty" (prevalence: 7.6%), "moderate physical frailty" (44.5%) and "severe physical frailty" (47.9%). Those in "moderate physical frailty" or "severe physical frailty" had high probabilities of needing assistance in transferring between locations and inability to walk in a room. Residents in "severe physical frailty" also had greater probability of bowel incontinence. Compared to those with none/mild cognitive impairment, older residents with moderate or severe impairment had slightly higher odds of belonging to "moderate physical frailty" [aOR (95%CI)moderate cognitive impairment: 1.01 (0.99-1.03); aOR (95%CI)severe cognitive impairment: 1.03 (1.01-1.05)] and much higher odds to the "severe physical frailty" subgroup [aOR (95%CI)moderate cognitive impairment: 2.41 (2.35-2.47); aOR (95%CI)severe cognitive impairment: 5.74 (5.58-5.90)].

CONCLUSIONS

Findings indicate the heterogeneous presentations of physical frailty in older nursing home residents and additional evidence on the interrelationship between physical frailty and cognitive impairment.

Terms used by physicians when deciding to withhold treatment for older patients not having received palliative care in an acute geriatric care unit

PURPOSE

There are no guidelines or consensus statements on the terms to be used when discussing withholding of treatment for patients in acute geriatric care units and who have not received palliative care. The objective of the present study was to analyze the terms used in medical records to refer to the withholding of treatment for patients who died in an acute geriatric care unit and did not receive palliative care.

METHODS

We conducted an ambispective multicentre cohort study based on the DAMAGE study. Data on 53 patients who died in the acute geriatric care unit and who had not received palliative care were extracted from medical records. The verbatims referring to the withholding of treatment were analyzed in terms of keywords and then key concepts, as defined by several reviewers in a consensus-based approach.

RESULTS

The mean age of the patients was 86.4 years, 34.1% were male. Terms referring to the withholding of treatment were found for 25 of the 53 patients (47.2%). Most of the decisions on the withholding of treatment were recorded in the week following admission to the acute geriatric care unit. Our analysis of the terms identified 11 key concepts: treatment limitation, no resuscitation, withholding diagnostic procedures, justification of care, ethical considerations, disease progression, uncertainty, the patient's wishes, the family's wishes, patient's comfort, and collegiality. The terms used to describe key concepts varied markedly from one physician to another.

CONCLUSION

Decisions about the withholding of treatment are frequently noted in the medical records of patients who die in the acute geriatric care unit without having received palliative care. The broad variety of key concepts and differences in the choice of words highlight the need for standardized terms.

Understanding Frailty Screening: a Domain Mapping Exercise

Background

Many definitions and operationalisations of frailty exclude psychosocial factors, such as social isolation and mental health, despite considerable evidence of the links between frailty and these factors. This study aimed to investigate the health domains covered by frailty screening tools.

Methods

A systematic search of the literature was conducted in accordance with PRISMA guidelines. MEDLINE, CINAHL, EMBASE, and PsycInfo were searched from inception to December 31, 2018. Data related to the domains of each screening tool were extracted and mapped onto a framework based on the biopsychosocial model of Lehmans et al. (2009) and Wade & Halligans (2017).

Results

Sixty-seven frailty screening tools were captured in 79 articles. All screening tools assessed biological factors, 73% assessed psychological factors, 52% assessed social factors, and 78% assessed contextual factors. Under half (43%) of the tools evaluated all four domains, 33% evaluated three of four domains, 12% reported two of four domains, and 13% reported one domain (biological).

Conclusion

This review found considerable variation in the assessment domains covered by frailty screening tools. Frailty is a broad construct, and frailty screening tools need to cover a wide variety of domains to enhance screening and outcomes assessment.

Concurrent and Predictive Validity of FRAIL-NH in Hospitalized Older Persons: An Exploratory Study

OBJECTIVES

The FRAIL-NH was originally developed for frailty assessment of nursing home (NH) residents. We aimed to compare concurrent, predictive, and known-groups validity between FRAIL-NH and FRAIL, using the Frailty Index (FI) as gold standard reference. We also examined for ceiling effect of both measures in the detection of severe frailty.

DESIGN

A secondary analysis of a prospective cohort study.

SETTING & PARTICIPANTS

Older adults (mean age 89.4 years) hospitalized for an acute medical illness in a 1300-bed tertiary hospital.

MEASUREMENTS

Baseline data on demographics, comorbidities, severity of illness, functional status, and cognitive status were gathered. We also captured outcomes of mortality, length of stay (LOS), institutionalization, and functional decline. For concurrent validity, we compared areas under the operating characteristic curves (AUCs) for both measures against the FI. For predictive validity, univariate analyses and multiple logistic regression were used to compare both measures against the adverse outcomes of interest. For known-groups validity, we compared both measures against comorbidities and functional status via 1-way analysis of variance, and dementia diagnosis via independent t test. Box plots were also derived to investigate for possible ceiling effect.

RESULTS

Both measures had good concurrent validity (both AUC > 0.8 and P < .001), with FRAIL-NH detecting more frailty cases (79.5% vs 50.0%). Although FRAIL-frail was superior for in-hospital mortality [6.7% vs 1.0%, P = .031, odds ratio (OR) 9.29, 95% confidence interval (CI) 1.09-79.20, P < .042] and LOS (10 vs 8 days, P = .043), FRAIL-NH-frail better predicted mortality (OR 6.62, 95% CI 1.91-22.94, P = .003) and institutionalization (OR 6.03, 95% CI 2.01-18.09, P = .001) up to 12 months postenrollment. Known-groups validity was good for both measures with FRAIL-NH yielding greater F values for functional status and dementia. Lastly, box plots revealed a ceiling effect for FRAIL in the severely frail group.

CONCLUSIONS AND IMPLICATIONS

This exploratory study highlights the potential for expanding the role of FRAIL-NH beyond NH to acute care settings. Contrasted to FRAIL, FRAIL-NH had better overall validity with less ceiling effect in discrimination of severe frailty.

Physical Frailty and Cognitive Impairment in Older Adults in United States Nursing Homes

INTRODUCTION

In older US nursing home (NH) residents, there is limited research on the prevalence of physical frailty, its potential dynamic changes, and its association with cognitive impairment in older adults' first 6 months of NH stay.

METHODS

Minimum Data Set (MDS) 3.0 is the national database on residents in US Medicare-/Medicaid-certified NHs. MDS 3.0 was used to identify older adults aged ≥65 years, newly admitted to NHs during January 1, 2014, and June 30, 2016, with life expectancy ≥6 months at admission and NH length of stay ≥6 months (N = 571,139). MDS 3.0 assessments at admission, 3 months, and 6 months were used. In each assessment, physical frailty was measured by FRAIL-NH (robust, prefrail, and frail) and cognitive impairment by Brief Interview for Mental Status and Cognitive Performance Scale (none/mild, moderate, and severe). Demographic characteristics and diagnosed conditions were measured at admission, while presence of pain and receipt of psychotropic medications were at each assessment. Distribution of physical frailty and its change over time by cognitive impairment were described. A nonproportional odds model was fitted with a generalized estimation equation to longitudinally examine the association between physical frailty and cognitive impairment, adjusting for demographic and clinical characteristics.

RESULTS

Around 60% of older residents were physically frail in the first 6 months. Improvement and worsening across physical frailty levels were observed. Particularly, in those who were prefrail at admission, 23% improved to robust by 3 months. At admission, 3 months, and 6 months, over 37% of older residents had severe cognitive impairment and about 70% of those with cognitive impairment were physically frail. At admission, older residents with moderate cognitive impairment were 35% more likely (adjusted odds ratio [aOR]: 1.35, 95% confidence interval [CI]: 1.33-1.37) and those with severe impairment were 74% more likely (aOR: 1.74, 95% CI: 1.72-1.77) to be frail than prefrail/robust, compared to those with none/mild impairment. The association between the 2 conditions remained positive and consistently increased over time.

DISCUSSION/CONCLUSION

Physical frailty was prevalent in NHs with potential to improve and was strongly associated with cognitive impairment. Physical frailty could be a modifiable target, and interventions may include efforts to address cognitive impairment.

The FRAIL-NH Scale: Systematic Review of the Use, Validity and Adaptations for Frailty Screening in Nursing Homes

OBJECTIVES

To investigate frailty prevalence, cross-sectional associations, predictive validity, concurrent validity, and cross-cultural adaptations of the FRAIL-NH scale.

DESIGN

Systematic review.

SETTING AND PARTICIPANTS

Frail residents living in nursing homes.

METHODS

MEDLINE, EMBASE, CINAHL, and Cochrane Library were searched from January 2015 to June 2021 for primary studies that used the FRAIL-NH scale, irrespective of study designs and publication language.

RESULTS

Overall, 40 studies conducted across 20 countries utilized the FRAIL-NH scale; majority in Australia (n=14), followed by China (n=6), United States (n=3), and Spain (n=3). The scale has been translated and back-translated into Brazilian Portuguese, Chinese, and Japanese. Various cut-offs have been used, with ≥2 and ≥6 being the most common cut-offs for frail and most frail, respectively. When defined using these cut-offs, frailty prevalence varied from 15.1-79.5% (frail) to 28.5-75.0% (most frail). FRAIL-NH predicted falls (n=2), hospitalization or length of stay (n=4), functional or cognitive decline (n=4), and mortality (n=9) over a median follow-up of 12 months. FRAIL-NH has been compared to 16 other scales, and was correlated with Fried's phenotype (FP), Frailty Index (FI), and FI-Lab. Four studies reported fair-to-moderate agreements between FRAIL-NH and FI, FP, and the Comprehensive Geriatric Assessment. Ten studies assessed the sensitivity and specificity of different FRAIL-NH cut-offs, with ≥8 having the highest sensitivity (94.1%) and specificity (82.8%) for classifying residents as frail based on FI, while two studies reported an optimal cut-off of ≥2 based on FI and FP, respectively.

CONCLUSION

In seven years, the FRAIL-NH scale has been applied in 20 countries and adapted into three languages. Despite being applied with a range of cut-offs, FRAIL-NH was associated with higher care needs and demonstrated good agreement with other well-established but more complex scales. FRAIL-NH was predictive of adverse outcomes across different settings, highlighting its value in guiding care for frail residents in nursing homes.

Nutritional domains in frailty tools: Working towards an operational definition of nutritional frailty

Different methods have been proposed for the assessment of the nutritional status in frailty phenotypes. In the present narrative review article, we have summarized the number and specifications of nutritional items in existing frailty tools, in order to develop a possible means of assessment and operational definition of the nutritional frailty phenotype. In six different databases until December 2019, we searched for original articles regarding frailty tools (i.e., scales, indexes, scores, questionnaires, instruments, evaluations, screening, indicators), analyzing each tool regarding nutritional items. We identified 160 articles describing 71 frailty tools. Among the selected frailty tools, 54 were community-based (70 %), 17 hospital-based (22 %), 4 validated in long-term care institutions for older adults (LTCIOA) (5.1 %) and 2 validated in both community- and hospital-based settings, including LTCIOA (2.5 %). Fifty-two of these tools (73 %) included at least one nutritional item. Twenty-two (42 %) reported two or more nutritional items. The items were grouped in the following categories: A) anthropometric measurements, B) laboratory measurements, and C) other nutritional-related measurements. Anthropometric measurements stood out compared to all other items. Nutritional items are included in the majority of frailty tools, strengthening the concept that they may have a direct implication on an increased risk of adverse health-related outcomes in frail subjects. This supports the development of the concept of nutritional frailty as an independent frailty phenotype. Subsequent steps will be to assess the contribution of each nutritional item to a possible operational definition of nutritional frailty and define the items that may best identify this new frailty phenotype.

Cross-cultural adaptation and validation of the FRAIL-NH scale for Chinese nursing home residents: A methodological and cross-sectional study

BACKGROUND

Frailty is a common condition in older adults, and has a particularly high prevalence among nursing home residents. Therefore, it is essential to assess frailty in nursing homes. The FRAIL-NH scale is a brief, quick-to-complete, and user-friendly measurement tool. However, it has not been used in China, and further cross-cultural adaptation and validation need to be undertaken.

OBJECTIVES

To cross-culturally adapt and validate the FRAIL-NH scale for Chinese nursing home residents.

DESIGN

Methodological and cross-sectional study.

SETTING

Twenty-seven nursing homes in Jinan, China.

PARTICIPANTS

Older Chinese nursing home residents (n = 353, age ≥60 years, 197 women; 156 men).

METHODS

Interviewers obtained data on frailty, demographics, comorbidity, physical function, nutritional status, and self-rated health. The Chinese FRAIL-NH scale version was generated using the translation-backward translation method. Psychometric properties, including internal consistency, test-retest reliability, convergent validity, criterion validity, and diagnosis accuracy were evaluated.

RESULTS

The FRAIL-NH scale showed acceptable internal consistency (Cronbach's alpha: 0.67) and satisfactory test-retest reliability within a 1- to 2-week interval (intraclass correlation coefficient: 0.84). As expected, the FRAIL-NH scale was correlated to the validated measurements, presenting convergent validity. Using the frailty phenotype as a reference criterion, the area under the curve was 0.79. The optimal cutoff point for frailty was 2 (sensitivity: 69.90% and 77.33%) in Chinese nursing homes. The FRAIL-NH scale was significantly associated with the frailty phenotype (correlation coefficient = 0.61, P < 0.001), but showed fair agreement with it (kappa = 0.46, p < 0.001).

CONCLUSIONS

The FRAIL-NH scale was found to be suitable for frailty measurement with acceptable validity and reliability, and the optimal cutoff point for frailty was 2. The FRAIL-NH scale can be applied in Chinese nursing homes.

Association of Hospital Readmissions and Survivability With Frailty and Palliative Performance Scores Among Long-Term Care Residents

BACKGROUND

Frailty and palliative performance scores are 2 markers used in the measurement of functional decline in oncology and hospice care.

OBJECTIVE

To evaluate the frailty and palliative performance scores of a long-term care resident community and determine whether frailty and palliative performance scores can predict hospital readmissions (HR) and survivability of the long-term care resident.

METHODS

One hundred seventy-one long-term care residents from 2 urban facilities were evaluated for functional decline using the Clinical Frailty Scale (CFS) and Palliative Performance Scale (PPS). Sociodemographic, HR, and survival data for 1 year from study initiation were recorded.

RESULTS

The 171 long-term care residents, of lower socioeconomic status, primarily Medicare/Medicaid or dual-eligible, evaluated for functional decline using the CFS and PPS, had mean age of 73.1 years, 52.6% female, 94.7% African American, with 18.1% having HR and 87.1% surviving more than a year. There was a negative association between age and HR (P = .384). Among functional evaluation scales, CFS was positively associated with age (P = .013) but not PPS (P = .673). The residents scored 6.0 ± 1.2 on CFS and 52.8 ± 13.2 on PPS (%) with those residents readmitted to hospital having poorer outcomes. Readmission to hospital and survivability of the long-term care resident were both strongly associated with CFS (P = .001) and PPS (P = .001).

CONCLUSION

There is a strong association between the 2 markers used in the measurement of functional decline-Frailty measured by CFS and Palliative Performance Score measured by PPS. Frailty and palliative performance scores can strongly predict HR and survivability of the long-term care resident.

Frailty and Comprehensive Geriatric Assessment

Frailty is defined as a reduced physiologic reserve vulnerable to external stressors. For older individuals, frailty plays a decisive role in increasing adverse health outcomes in most clinical situations. Many tools or criteria have been introduced to define frailty in recent years, and the definition of frailty has gradually converged into several consensuses. Frail older adults often have multi-domain risk factors in terms of physical, psychological, and social health. Comprehensive geriatric assessment (CGA) is the process of identifying and quantifying frailty by examining various risky domains and body functions, which is the basis for geriatric medicine and research. CGA provides physicians with information on the reversible area of frailty and the leading cause of deterioration in frail older adults. Therefore frailty assessment based on understanding CGA and its relationship with frailty, can help establish treatment strategies and intervention in frail older adults. This review article summarizes the recent consensus and evidence of frailty and CGA.

The Prevalence of Frailty by the FRAIL-NH Scale in Taiwan Nursing Home Residents

INTRODUCTION

The prevalence of frailty defined by FRAIL-NH varies among different studies in nursing homes, ranging from 19.0% to 75.6%. This study investigated the prevalence of frailty in a nursing home in Taiwan using different diagnostic criteria for frailty.

METHODS

The 7-item FRAIL-NH scale was used for assessing frailty. There are 7 components: fatigue, resistance, mobility, incontinence or disease, weight loss, eating style and assistance with dressing. Each item is worth 0, 1, or 2 points for a total score of 14 points. We sorted and summarized the patients, according to the number of variables, into the not frail, frail, and most frail groups. Descriptive analysis was applied to understand the basic attributes of the elderly with different degrees of frailty, the influencing factors of frailty, and the occurrence of frailty.

RESULTS

Our final sample included 34 residents. They were aged between 56 and 100 years (mean age 83.91 ± 10.84), and 18 (52.94%) were female. The frail group revealed a higher prevalence of males than of females. The marital status composition of participants was as follows: 2 (5.88%) unmarried, 24 (70.59%) married, and 8 (23.53%) widowed. The mean FRAIL-NH score was 5.79±3.72.

CONCLUSIONS

A significant prevalence of frailty defined by FRAIL-NH was observed in a nursing home in Taiwan. Our findings indicate that frailty is an important issue in nursing homes. Further prospective cohort studies using FRAIL-NH evaluation are warranted.

Comparing Diagnostic Properties of the FRAIL-NH Scale and 4 Frailty Screening Instruments among Chinese Institutionalized Older Adults

OBJECTIVE

To examine the diagnostic test accuracy (DTA) of the FRAIL-NH and four frailty screening instruments among institutionalized older adults.

DESIGN

Cross-sectional study.

SETTING

Institutionalized setting, Jinan, China.

PARTICIPANTS

A total of 305 older adults (mean age 79.3 ± 8.4 years, 57.0% female) were enrolled from nursing homes.

MEASUREMENTS

Frailty was assessed by the FRAIL-NH, Physical Frailty Phenotype (PFP), FRAIL, Tilburg Frailty Indicator (TFI), and Groningen Frailty Indicator (GFI), respectively. The Comprehensive Geriatric Assessment (CGA) was used as a reference standard of frailty. The receiver operating characteristic (ROC) curve was plotted to examine the DTA of five frailty screening instruments against the CGA. The optimal cut-point was determined by the maximum value of the Youden index (YI, calculated as sensitivity + specificity - 1).

RESULTS

The prevalence of frailty ranged from 25.9% (FRAIL) to 56.4% (GFI). Areas under the curve (AUCs) against the CGA ranged from 0.80 [95% confidence interval (CI) 0.74 - 0.85: FRAIL] to 0.83 (95% CI 0.78 - 0.88: PFP). At their original cut-points, all five frailty screening instruments presented low sensitivity (32.9% - 69.3%) and high specificity (80.0% - 93.8%), as well as high positive predictive values (90.7% - 94.9%) and low negative predictive values (33.2% - 48.1%). At their optimal cut-points, the sensitivity and specificity of the FRAIL-NH, PFP, and FRAIL tended to be balanced, and their correctly classified rates (76.1% - 81.3%) and kappa values (0.465 - 0.523) increased a lot. ROC contrasts showed that all five frailty screening instruments had similarly good diagnostic accuracy (χ2: 0.0003 - 1.38, P > .05).

CONCLUSION

In the institutionalized setting, the specific FRAIL-NH, self-report FRAIL, TFI, and GFI as well as hybrid PFP, show similarly good diagnostic properties in identifying frailty against the CGA.

Prediction of Death with the FRAIL-NH in Institutionalized Older Adults: A Longitudinal Study from a Middle-Income Country

BACKGROUND/OBJECTIVES

Frailty is common in nursing homes. However, few studies reported longitudinal validation for death prediction or cut-off scores with the FRAIL-NH, which is designed to be used in nursing homes. Moreover, no studies came from Latin America, where frailty is highly prevalent. Our objectives were to evaluate (1) the prevalence of frailty according to the FRAIL-NH scale, and (2) its association to and the best cut-off score for predicting death after 12 months.

DESIGN

longitudinal study with 12-month follow-up.

SETTING

6 nursing homes in southwest of Brazil.

PARTICIPANTS

293 residents with 60 years old or more.

METHODS

Frailty was evaluated through the FRAIL-NH scale. Logistic regression was used to estimate the associated between frailty and mortality adjusted for age and sex. ROC curve was used to evaluate the accuracy of the scale for mortality prediction.

RESULTS

Frailty was prevalent (47.4%) and was associated with death (odds ratio=1.31, 95% confidence interval [CI]=1.18-1.48, p<0.001). The area under the curve was 0.741 (95%CI=0.68-0.79). The sensitivity and specificity of the FRAIL-NH scale according to the best value of the Youden Index was 72.9% and 66.5%, respectively, for a cut-off > 8 points.

CONCLUSIONS

Frailty is prevalent in nursing homes according to the FRAIL-NH and it was associated with one-year prediction of death for a cut-off > 8 points.

Frailty Screening (FRAIL-NH) and Mortality in French Nursing Homes: Results From the Incidence of Pneumonia and Related Consequences in Nursing Home Residents Study

OBJECTIVES

To investigate the ability of the fatigue, resistance, ambulation, incontinence or illness, loss of weight, nutritional approach, and help with dressing (FRAIL-NH) tool to predict mortality.

DESIGN

The Incidence of Pneumonia and Related Consequences in Nursing Home Residents (INCUR) study database was used. This was an observational cohort study in French nursing homes conducted over 12 months in 2012.

PARTICIPANTS

A total of 788 residents aged 60 years or older, from 13 randomly selected French nursing homes.

MEASUREMENTS

FRAIL-NH was generated from the available variables at baseline. FRAIL-NH scores ranged from 0 to 14 and people were categorized as nonfrail (0‒1), frail (2‒5), and most frail (6‒14). Mortality data were obtained from medical charts and confirmed by the nursing home administrative documentation.

RESULTS

Mean age of the participants was 86.2 ± 7.5 years, and 74.5% were women. The prevalence of persons with FRAIL-NH score greater than 1 was 88.8%, with 54.2% and 34.6% of residents identified as most frail and frail, respectively. The mean FRAIL-NH score was 6.0 ± 3.4. Women (N = 583) were frailer (6.1 ± 3.4) than men (N = 200, 5.5 ± 3.4; P = .027). Overall, 136 residents died over the 1-year follow-up period. The FRAIL-NH score was a predictor of mortality (adjusted hazard ratios: for frail group 1.15, 95% confidence interval 0.55‒2.41; for most frail group 2.14, 95% confidence interval 1.07‒ 4.27).

CONCLUSIONS

FRAIL-NH is a predictor of mortality in nursing home residents and the score could assist with guiding appropriate care planning.

Accessing the discriminatory performance of FRAIL-NH in two-class and three-class frailty and examining its agreement with the frailty index among nursing home residents in mainland China

Background

FRAIL-NH has been commonly used to assess frailty in nursing home residents and validated in many ethnic populations; however, it has not been validated in mainland China, where such an assessment tool is lacking. This study aimed to (1) assess the discriminatory performance of FRAIL-NH in two-class frailty (non-frail+ pre-frail vs. frail) and three-class frailty (non-frail vs. pre-frail vs. frail), based on the Frailty Index (FI), (2) determine the appropriate cutoff points for FRAIL-NH that distinguish two-class and three-class frailty, and (3) examine the agreement in classification between FRAIL-NH and FI.

Methods

A cross-sectional study of 302 residents aged 60 years or older from six nursing homes in Changsha was conducted. The FRAIL-NH scale and 34-item FI were used to measure frailty. Two-way and three-way receiver operating characteristic (ROC) curves were used to estimate the performance of FRAIL-NH. Cohen’s Kappa statistics were used to examine the agreement between these two measures.

Results

The agreement between FRAIL-NH and FI ranged from 0.33 to 0.55. Regardless of what FI cutoff points were based on, the volume under the ROC surface (VUS) for FRAIL-NH from the three-way ROC were higher than the VUS of a useless test (1/6), and the area under the ROC curve (AUC) for FRAIL-NH from the two-way ROC were higher than the clinically meaningless value (0.5). When using FI cutoff points of 0.20 for pre-frail and 0.45 for frail, FRAIL-NH cutoff points of 1 and 9 in classifying three-class frailty had the highest VUS and the largest correct classification rates. Whichever FI was chosen, the performance of FRAIL-NH in distinguishing between pre-frailty and frailty, and between non-frailty and pre-frailty was equivalent. According to FRAIL-NH, the proportion of individuals with frailty misclassified as pre-frailty was higher than that of individuals with non-frailty misclassified as pre-frailty.

Conclusion

FRAIL-NH can be used as a preliminary frailty screening tool in nursing homes in mainland China. FI should be further used especially for those classified as pre-frailty by FRAIL-NH. It is not advisable to simply combine adjacent two classes of FRAIL-NH to create a new frailty variable in research settings.

Frailty, Hospitalization, and Mortality in Residential Aged Care

Background

Frailty predicts mortality in residential aged care, but the relationship with hospitalization is inconsistent. The purpose of this study was to investigate and compare whether frailty is associated with hospitalization and mortality among residents of aged care services.

Methods

A prospective cohort study of 383 residents aged 65 years and older was conducted in six Australian residential aged care services. Frailty was assessed using the FRAIL-NH scale and a 66-item frailty index.

Results

Overall, 125 residents were hospitalized on 192 occasions and 85 died over the 12-month follow-up. Over this period, less than 3% of the nonfrail/vulnerable residents but more than 20% of the most frail residents died at the facility without hospitalization. Using the FRAIL-NH, residents with mild/moderate frailty had higher numbers of hospitalizations (adjusted incidence rate ratio 1.57, 95% confidence interval [CI] 1.11-2.20) and hospital days (incidence rate ratio 1.48, 95% CI 1.32-1.66) than nonfrail residents. Residents who were most frail had lower numbers of hospitalizations (incidence rate ratio 0.65, 95% CI 0.42-0.99) and hospital days (incidence rate ratio 0.39, 95% CI 0.33-0.46) than nonfrail residents. Similar patterns of associations with number of hospital days were observed for the frailty index. Most frail residents had a higher risk of death than nonfrail residents (for FRAIL-NH, adjusted hazard ratio 2.96, 95% CI 1.50-5.83; for frailty index, hazard ratio 5.28, 95% CI 2.05-13.59).

Conclusions

Residents with mild/moderate frailty had higher risk of hospitalization and death than nonfrail residents. Residents who were most frail had higher risk of death but lower risk of hospitalization than nonfrail residents.

End of life care for long-term care residents with dementia, chronic illness and cancer: prospective staff survey

Background

Little is known about the quality of end of life care in long-term care (LTC) for residents with different diagnostic trajectories. The aim of this study was to compare symptoms before death in LTC for those with cancer, dementia or chronic illness.

Methods

After-death prospective staff survey of resident deaths with random cluster sampling in 61 representative LTC facilities across New Zealand (3709 beds). Deaths (n = 286) were studied over 3 months in each facility. Standardised questionnaires - Symptom Management (SM-EOLD) and Comfort Assessment in End of life with Dementia (CAD-EOLD) - were administered to staff after the resident’s death.

Results

Primary diagnoses at the time of death were dementia (49%), chronic illness (30%), cancer (17%), and dementia and cancer (4%). Residents with cancer had more community hospice involvement (30%) than those with chronic illness (12%) or dementia (5%). There was no difference in mean SM-EOLD in the last month of life by diagnosis (cancer 26.9 (8.6), dementia 26.5(8.2), chronic illness 26.9(8.6). Planned contrast analyses of individual items found people with dementia had more pain and those with cancer had less anxiety. There was no difference in mean CAD-EOLD scores in the week before death by diagnosis (total sample 33.7(SD 5.2), dementia 34.4(SD 5.2), chronic illness 33.0(SD 5.1), cancer 33.3(5.1)). Planned contrast analyses showed significantly more physical symptoms for those with dementia and chronic illness in the last month of life than those with cancer.

Conclusions

Overall, symptoms in the last week and month of life did not vary by diagnosis. However, sub-group planned contrast analyses found those with dementia and chronic illness experienced more physical distress during the last weeks and months of life than those with cancer. These results highlight the complex nature of LTC end of life care that requires an integrated gerontology/palliative care approach.

Frailty as a Predictor of All-Cause Mortality Among Older Nursing Home Residents: A Systematic Review and Meta-analysis

OBJECTIVES

We performed a meta-analysis based on prospective cohort studies to synthesize the pooled risk effect and to determine whether frailty is a predictor of all-cause mortality.

DESIGN

Systematic review and meta-analysis.

SETTING

PubMed, EMBASE, and the Cochrane Library were systematically searched in October 2018. A random effects model was applied to combine the results according to the heterogeneity of the included studies.

PARTICIPANTS

Older nursing home residents.

MEASUREMENTS

Mortality risk due to frailty.

RESULTS

Fourteen studies (9076 participants) were included in this meta-analysis. Pooled results demonstrated that nursing home residents with frailty were at an increased risk of mortality [pooled hazards ratio (HR) = 1.88, 95% confidence interval (CI) = 1.57, 2.25, I² = 47.8%, P < .001] compared to those without frailty. Results of subgroup analyses showed that frailty was significantly associated with the risk of mortality among older nursing home residents when using FRAIL-NH (pooled HR = 2.10, 95% CI = 1.60-2.77, P < .001) and Frailty Index (pooled HR = 1.74, 95% CI = 1.40-2.18, P < .001) to define frail people, whereas when using the diagnosis criteria of CSHA-CFS for frailty, the pooled HR was 2.82 (95% CI = 0.79-10.10, P = .111). In addition, the subgroup analysis for length of follow-up showed that studies with a follow-up period of 1 year or more (pooled HR = 1.83, 95% CI = 1.52, 2.21, P < .001) reported a significantly higher rate of mortality among individuals with frailty, compared to those without frailty. Similar results were also found in studies with a follow-up period of less than 1 year (pooled HR = 2.67, 95% CI = 1.43, 5.00, P = .002).

CONCLUSIONS AND IMPLICATIONS

Frailty is a significant predictor of all-cause mortality in older nursing home residents. Therefore, there is an urgent need to screen for frailty in nursing home residents and carry out appropriate multidisciplinary intervention strategies to prevent poor outcomes and reduce the rate of mortality among older nursing home residents.

Assessing Frailty in Chinese Nursing Home Older Adults: A Comparison between the Frail-NH Scale and Frailty Index

OBJECTIVE

(1) To establish appropriate FRAIL-NH cutoff points in nursing homes in Mainland China; (2) To compare the FRAIL-NH scale and Frailty Index in assessing frailty prevalence and associated factors in nursing homes.

DESIGN

A cross-sectional study.

SETTING

Six nursing homes in Changsha, China.

PARTICIPANTS

A total of 302 residents aged 60 years or older (mean aged 82.71±8.49, 71.2% female).

MEASUREMENTS

Frailty was assessed using the 34-item Frailty Index and the FRAIL-NH scale.

RESULTS

The appropriate FRAIL-NH cutoff points to classify frail status and frailest status were 1.5 (87.6% sensitivity, 63.3% specificity) and 7.5 (94.1% sensitivity, 73.4% specificity), respectively. Based on the FRAIL-NH and Frailty Index, 69.5% (48% for frail and 21.5% for frailest), and 66.5% (60.9% for frail and 5.6% for frailest) of residents were at risk of frailty, respectively. There was no statistically significant difference in the total frailty prevalence assessed by FRAIL-NH and Frailty Index (χ2=0.617, P=0.432). The FRAIL-NH Scale is significantly associated with the Frailty Index (correlation coefficient (r) = 0.74, P < 0.001), but there was a Kappa agreement of 0.39 for frailty classification between the FRAIL-NH and Frailty Index, with the Frailty Index classifying a larger number of individuals as frail. When using FRAIL-NH scale, disease and self-reported health status were associated with frail and frailest status while age was just associated with frailest status. regarding the Frailty Index, age, diseases, medications and self-reported health status were associated with frail and frailest status.

CONCLUSION

The FRAIL-NH is a simple and effective tool to assess the overall frailty rate in nursing homes, and the Frailty Index may be more suitable capturing the multidimensionality of frailty at an individual level. Careful consideration in the selection of a frailty instrument, based on the intended purpose, is necessary.

Predictive validity of two frailty tools for mortality in Chinese nursing home residents: frailty index based on common laboratory tests (FI-Lab) versus FRAIL-NH

BACKGROUND

Little is known about frailty in Chinese nursing home residents.

AIMS

(1) To evaluate the prevalence of frailty in nursing home residents according to the FI-Lab or FRAIL-NH; and (2) to compare the predictive validity of these two tools for mortality.

METHODS

We conducted a prospective study in four nursing homes in China. Frailty was assessed using the fatigue, resistance, ambulation, illness, loss of weight, nutrition, and help with dressing questionnaire (FRAIL-NH) and frailty index based on common laboratory tests (FI-Lab), respectively. The survival status was collected via medical records or telephone interviews. Receiver-operating characteristic (ROC) curves were calculated to estimate the area under the ROC curves (AUCs) for FI-Lab and FRAIL-NH in relation to mortality. Cox proportional hazard models were applied to calculate the hazard ratios (HRs) and 95% confidence intervals (CIs) for mortality by FRAIL-NH and FI-Lab, separately.

RESULTS

We included 329 participants. The FI-Lab score was significantly and strongly associated with the FRAIL-NH score (r = 0.799, p < 0.001). Frailty was defined as the FI-Lab score ≥ 0.3 or the FRAIL-NH score ≥ 6, and the prevalence of frailty was 56.2% and 58.7%, respectively. Seventy-three participants (22.7%) died during the 1-year follow-up. The FI-Lab (AUC 0.700, 95% CI 0.647-0.750) was slightly better than the FRAIL-NH (AUC 0.676, 95% CI 0.622-0.727) for predicting mortality (p = 0.025). After adjusted for age and gender, the increment of the FI-Lab score was associated with mortality (adjusted HR per 0.01 increment in score 1.07, 95% CI 1.05-1.09), the increment of the FRAIL-NH score was also associated with mortality (adjusted HR per 1 increment in score 1.28, 95% CI 1.19-1.46).

CONCLUSION

The FI-Lab and FRAIL-NH are valuable for predicting mortality in Chinese nursing home residents.

Investigation on the frailty status of the elderly inpatients in Shanghai using the FRAIL (fatigue, resistance, ambulation, illness, and loss) questionnaire

This study was to investigate the frailty status of inpatients older than 65 years old in Shanghai.A 6-month cross-sectional survey was conducted using FRAIL (fatigue, resistance, ambulation, illness, and loss) questionnaire. Totally 587 patients were included. The data, including demographic characteristics, constipation, urinary retention, urinary incontinence, grip strength, and muscle strength, were collected. The data of serum prealbumin, serum albumin, serum total protein, and hemoglobin were obtained from laboratory blood tests.The incidence of nonfrailty, prefrailty, and frailty was 0.249, 0.417, and 0.334, respectively. The high incidence age of frailty was 86 to 90 years old (0.342), and the high incidence age of prefrailty was 65 to 70 years old (0.282). There was significant difference in the grip strength among different degrees of frailty (P < .01). The influencing factors related to prefrailty included prealbumin, grip strength, urinary retention, constipation and education level of illiterate (P < .05). The populations with high prealbumin level, high grip strength and illiteracy population were not easy to enter the prefrailty period, while those with constipation (OR (odds ratio) = 1.867, 95% CI (confidence interval): 1.046-3.330) and urinary retention (OR = 7.007, 95% CI: 1.137-2.757) were more likely to enter the prefrailty period. Factors associated with frailty included age, prealbumin, grip strength, muscle strength, urinary incontinence, urinary retention, and constipation (P < .05). The populations with high prealbumin level, high grip strength, and high muscle strength were not easy to enter frailty period, while those with older age (OR = 1.141, 95% CI: 1.085-1.200), urinary incontinence (OR = 10.314, 95% CI: 1.950-54.548), urinary retention (OR = 3.058, 95% CI: 1.571-5.952), and constipation (OR = 3.004, 95% CI: 1.540-5.857) were easy to enter frailty period.The high incidence ages of frailty and prefrailty are 86 to 90 years old and 65 to 70 years old, respectively. Age, low education level, low grip strength, low muscle strength, low serum prealbumin, urinary retention, urinary incontinence, and constipation are the risk factors of frailty. It is recommended to include frailty as an indicator in the existing assessment to rate the disease and develop a disease observation plan.

Use of the Frailty Index and FRAIL-NH Scale for the Assessment of the Frailty Status of Elderly Individuals Admitted in a Long-term Care Hospital in Korea

Background

Numerous elderly individuals with multimorbidity and impaired function are admitted in long-term care hospitals (LTCHs) in Korea. In this study, we aimed to describe the frailty status of elderly patients admitted in a LTCH using the FRAIL-NH scale and to identify the clinical relevance of frailty status on clinical outcomes, including death.

Methods

We retrospectively reviewed the medical records of 100 elderly patients who were hospitalized and died in an LTCH from March 2011 to February 2017. The monthly assessment results obtained from the inpatients' data set (IDS) were used as main data sources for the 6-item FRAIL-NH scale and frailty index that was composed of 22 newly established items.

Results

The mean frailty index of the patients included in the analysis (mean age, 81.5±7.2 years; men, 53%) was 0.60 (standard deviation [SD], 0.10; range, 0.28-0.80). The distribution of the FRAIL-NH score in this population was in accordance with the 22-item frailty index, which shows a standardized beta of 0.571 (p<0.001, R=0.572). When the patients were categorized based on the FRAIL-NH score, the mean survival durations of the more fail group (FRAIL-NH >10, n=49) and less frail group (FRAIL-NH ≤10, n=51) were 529.3 days (SD, 453.4) and 888 days (SD, 679.9), respectively. Similarly, the frailty index was associated with earlier mortality.

Conclusion

Frailty is extremely common in elderly patients admitted in an LTCH and can be easily measured using the FRAIL-NH scale that utilizes the IDS of LTCHs in Korea. Since frailty is associated with earlier mortality, the assessment of frailty status in patients admitted in LTCHs may be helpful in clinical decision-making.

Frailty and the Prediction of Negative Health Outcomes: A Meta-Analysis

INTRODUCTION

Frailty is one of the most important concerns regarding our aging population. Evidence grows that the syndrome is linked to several important health outcomes. A general overview of frailty concepts and a comprehensive meta-analysis of their relation with negative health outcomes still lacks in literature, making it difficult for health care professionals and researchers to recognize frailty and the related health risks on the one hand and on the other hand to appropriately follow up the frailty process and take substantiated action. Therefore, this study aims to give an overview of the predictive value of the main frailty concepts for negative health outcomes in community-dwelling older adults.

METHODS

This review and meta-analysis assembles prospective studies regarding the relation between frailty and any potential health outcome. Frailty instruments were subdivided into frailty concepts, so as to make comprehensive comparisons. Odds ratios (ORs), hazard ratios (HRs), and relative risk (RR) scores were extracted from the studies, and meta-analyses were conducted in OpenMeta Analyst software.

RESULTS

In total, 31 articles retrieved from PubMed, Web of Knowledge, and PsycInfo provided sufficient information for the systematic review and meta-analysis. Overall, (pre)frailty increased the likelihood for developing negative health outcomes; for example, premature mortality (OR 2.34 [1.77-3.09]; HR/RR 1.83 [1.68-1.98]), hospitalization (OR 1.82 [1.53-2.15]; HR/RR 1.18 [1.10-1.28]), or the development of disabilities in basic activities of daily living (OR 2.05 [1.73-2.44]); HR/RR 1.62 [1.50-1.76]).

CONCLUSION

Overall, frailty increases the risk for developing any discussed negative health outcome, with a 1.8- to 2.3-fold risk for mortality; a 1.6- to 2.0-fold risk for loss of activities of daily living; 1.2- to 1.8-fold risk for hospitalization; 1.5- to 2.6-fold risk for physical limitation; and a 1.2- to 2.8-fold risk for falls and fractures. The analyses presented in this study can be used as a guideline for the prediction of negative outcomes according to the frailty concept used, as well as to estimate the time frame within which these events can be expected to occur.

Heterogeneity of Different Tools for Detecting the Prevalence of Frailty in Nursing Homes: Feasibility and Meaning of Different Approaches

BACKGROUND AND OBJECTIVE

The identification of frail individuals has been recognized as a priority for the effective implementation of healthy aging strategies. Only a limited number of studies have examined frailty in nursing homes, and there is a big heterogeneity in the methods used. The primary objective of this study was to determine the prevalence and feasibility of different frailty screening tools in nursing homes as well as its relationship with multimorbidity and disability.

DESIGN, SETTING, AND PARTICIPANTS

Cross-sectional analysis from a concurrent cohort study, which included 110 participants aged over 65 years and with different degrees of disability at 2 nursing homes.

MEASUREMENTS

The study used 4 different frailty scales: The Fried frailty criteria, the imputed Fried frailty criteria, the Rockwood clinical frailty scale, and the frailty in nursing home scale, and we analyzed their relationship with disability and multimorbidity.

RESULTS

The mean age of the study population was 86.3 years (standard deviation 7.3), and 71.8% were female. Most residents had a high percentage of cognitive and functional impairment, multimorbidity, and risk of malnutrition. The following prevalence rates for frailty were determined: 71.8% (62.8, 79.4), 42.7% (33.9, 52.1), and 36.4% (23.8, 51.1) as per according to the Rockwood clinical frailty scale, frailty in nursing home scale, and Fried index (95% confidence interval), respectively. In the case of the Fried index, the prevalence of frailty is based on the percentage of patients meeting the criteria, which is 40% due to the large number of missing values. After the imputation of variables with the multivariate imputation by chained equation software, the prevalence of frailty increased to 66.4% (57.1, 74.5). We observed different statistically significant associations between the frailty scales and the clinical and demographic variables, and also with disability and multimorbidity.

CONCLUSIONS

Most residents of nursing homes are likely to be frail, but there is no single operational definition of frailty. Although all measures of frailty had similar associations with the clinical variables of the study, there are important conceptual differences that must be considered in addressing the relationships between frailty, disability, and multimorbidity. Further research is required, and homogeneous frailty criteria must be used so that studies and interventions can be compared.

Operationalizing a frailty index using routine blood and urine tests

Background

Uncomplicated frailty instruments are desirable for use in a busy clinical setting. The aim of this study was to operationalize a frailty index (FI) from routine blood and urine tests, and to evaluate the properties of this FI compared to other frailty instruments.

Materials and methods

We conducted a secondary analysis of a prospective cohort study on 306 patients aged ≥65 years hospitalized on geriatric wards. An FI comprising 22 routine blood parameters and one standard urine parameter (FI-Lab), a 50-item FI based on a comprehensive geriatric assessment (FI-CGA), a combined FI (FI-combined [items from the FI-Lab + others from the FI-CGA]), the Clinical Frailty Scale, rule-based frailty definition, and frailty phenotype were operationalized from data obtained during patients’ hospital stays (ie, before discharge [baseline examination]). Follow-up data were obtained up to 1 year after the baseline examination.

Results

The mean FI-Lab score was 0.34±15, with an upper limit of 0.74. The FI-Lab was correlated with all the other frailty instruments (all P<0.001). The FI-Lab revealed an area under the receiver-operating characteristic curve (AUC) for 6-month and 1-year mortality of 0.765 (0.694–0.836) and 0.769 (0.706–0.833), respectively (all P<0.001). Each 0.01 increment in FI-Lab increased the risk (adjusted for age and sex) for 6-month and 1-year mortality by 7.2% and 7.1%, respectively (all adjusted P<0.001). When any of the other FIs (except the FI-combined) were also included in the models, each 0.01 increment in FI-Lab score was associated with an increase in the risk of 6-month and 1-year mortality by 4.1%–5.4% (all adjusted P<0.001).

Conclusion

The FI-Lab showed key characteristics of an FI. The FI-Lab can be applied as a single frailty measure or in combination with/in addition to other frailty instruments.

Rapid Geriatric Assessment: Secondary Prevention to Stop Age-Associated Disability

The Rapid Geriatric Assessment (RGA) measures frailty, sarcopenia, anorexia, cognition, and advanced directives. The RGA is a screen for primary care physicians to be able to detect geriatric syndromes. Early intervention when geriatric syndromes are recognized can decrease disability, hospitalization, and mortality.

Anorexia of aging and its role for frailty

PURPOSE OF REVIEW

The purpose of this review is to examine the concept of anorexia of aging, including its complex pathophysiology and the multifaceted interventions required to prevent adverse health consequences from this geriatric syndrome.

RECENT FINDINGS

Anorexia of aging is extremely common, occurring in up to 30% of elderly individuals; however, this diagnosis is frequently missed or erroneously attributed to a normal part of the aging process. With aging, impairments in smell and taste can limit the desire to eat. Alterations in stress hormones and inflammatory mediators can lead to excess catabolism, cachexia, and reduced appetite. In addition, mood disorders, such as anxiety and depression, are powerful inhibitors of appetite. Anorexia of aging, with its negative consequences on weight and muscle mass, is a risk factor for the development of frailty and is important to screen for, as early intervention is key to reversing this debilitating condition.

SUMMARY

Anorexia of aging is a complex geriatric syndrome and a direct risk factor for frailty and thus should not be accepted as normal consequence of aging. Early diagnosis and formulating a plan for targeted interventions is critical to prevent disability and preserve function in elderly patients.

Frailty and sarcopenia in elderly

Frailty is a pre-disability syndrome where an older person can be identified as being at risk when exposed to stressors associated with high risk for disability or needing to be hospitalized. Two major frailty definitions exist. The physical phenotype of frailty and the multiple deficit model. A simple frailty screening tool-FRAIL-has been validated. Treatment of frailty involves resistance exercise, optimization of nutrition, and treatment of fatigue (sleep apnea, depression), treatable causes of weight loss and adjustment of polypharmacy. Sarcopenia (decline in function with low muscle mass) is a major cause of frailty. A simple sarcopenia screening tool-SARC-F-has been validated. The multiple causes of sarcopenia are reviewed. Optimal treatment is resistance exercise, leucine-enriched essential amino acids and vitamin D replacement.

The prevalence and health consequences of frailty in a population-based older home care cohort: a comparison of different measures

Background

Evaluating different approaches to identifying frail home care clients at heightened risk for adverse health outcomes is an important but understudied area. Our objectives were to determine the prevalence and correlates of frailty (as operationally defined by three measures) in a home care cohort, the agreement between these measures, and their predictive validity for several outcomes assessed over one year.

Methods

We conducted a retrospective cohort study with linked population-based administrative and clinical (Resident Assessment Instrument [RAI]) data for all long-stay home care clients (aged 66+) assessed between April 2010–2013 in Ontario, Canada (n = 234,552). We examined two versions of a frailty index (FI), a full and modified FI, and the CHESS scale, compared their baseline characteristics and their predictive accuracy (by calculating the area under the ROC curve [AUC]) for death, long-term care (LTC) admission, and hospitalization endpoints in models adjusted for age, sex and comorbidity.

Results

Frailty prevalence varied by measure (19.5, 24.4 and 44.1 %, for full FI, modified FI and CHESS, respectively) and was similar among female and male clients. All three measures were associated with a significantly increased risk of death, LTC admission and hospitalization endpoints in adjusted analyses but their addition to base models resulted in modest improvement for most AUC estimates. There were significant differences between measures in predictive accuracy, with the full FI demonstrating a higher AUC for LTC admission and CHESS a higher AUC for hospitalization - although none of the measures performed well for the hospitalization endpoints.

Conclusions

The different approaches to detecting vulnerability resulted in different estimates of frailty prevalence among home care clients in Ontario. Although all three measures were significant predictors of the health outcomes examined, the gains in predictive accuracy were often modest with the exception of the full FI in predicting LTC admission. Our findings provide some support for the clinical utility of a comprehensive FI measure and also illustrate that it is feasible to derive such a measure at the population level using routinely collected data. This may facilitate further research on frailty in this setting, including the development and evaluation of interventions for frailty.

Electronic supplementary material

The online version of this article (doi:10.1186/s12877-016-0309-z) contains supplementary material, which is available to authorized users.