Development of Korean Frailty Index for Primary Care (KFI-PC) and Its Criterion Validity

Article information

Ann Geriatr Med Res. 2020;24(2):125-138

Publication date (electronic) : 2020 June 22

doi : https://doi.org/10.4235/agmr.20.0021

Chang Won Won^1,2, Yunhwan Lee³, Seoyoon Lee^1,4, Miji Kim^,1,5

¹Elderly Frailty Research Center, Department of Family Medicine, College of Medicine, Kyung Hee University, Seoul, Korea

²Department of Family Medicine, Kyung Hee University Medical Center, Seoul, Korea

³Department of Preventive Medicine and Public Health, Ajou University School of Medicine, Suwon, Korea

⁴Graduate School of Social Welfare, Yonsei University, Seoul, Korea

⁵Department of Biomedical Science and Technology, East-West Medical Research Institute, College of Medicine, Kyung Hee University, Seoul, Korea

Corresponding Author: Miji Kim, PhD Department of Biomedical Science and Technology, East-West Medical Research Institute, College of Medicine, Kyung Hee University, 23 Kyungheedae-ro, Dongdaemun-gu, Seoul 02447, Korea E-mail: mijiak@khu.ac.kr

Received 2020 April 8; Revised 2020 May 19; Accepted 2020 May 31.

Abstract

INTRODUCTION

Number of frail older people has been ever growing with the increase of global population aging. Frailty is defined as a status of vulnerability to identified stressors that exposes individuals to higher risks of negative health-related outcomes. The condition is usually caused by the interaction between progressive aging-related declines in multiple organ function and chronic diseases that often lead to a decreased level of functional reserve capacities.1)

Both phenotypic and deficit accumulation approaches are commonly used to define frailty. Representing the phenotypic approach, Fried’s frailty phenotype defines frailty as the presence of three or more of five frailty items; namely, slow walking speed, impaired grip strength, declining physical activity levels, exhaustion, and unintended weight loss.2) The other approach to defining frailty is through the use of a frailty index that sums health deficits. In this context, health deficits can be any physical or mental disability, symptom and sign, disease, laboratory finding, etc.3) Healthcare professionals have used comprehensive geriatric assessment (CGA) to develop a holistic overview of patients with complex needs, which is the essential step for the development of individualized, patient-centered care plans. CGA evaluates multiple aspects of older adults’ health, including cognition, emotion, motivation, health attitude, vision, hearing, speech, sleep, pain, strength, balance, mobility, activities of daily living, social engagement, medication, control of life, etc. In primary care settings, frailty indices can be developed based on CGA.

A CGA-based frailty index (FI-CGA) was first developed using clinical examination data from the Canadian Study of Health and Aging.4,5) The standardized CGA used to constitute the frailty index comprises assessments in 10 standard domains: (1) cognitive status including delirium or dementia; (2) mood and motivation; (3) communication including vision, hearing, and speech; (4) mobility; (5) balance; (6) bowel function; (7) bladder function; (8) instrumental activities of daily livings (IADLs) and activities of daily living (ADLs); (9) nutrition; and (10) social resources.4) Based on this principle, Theou et al.3) constructed FI-CGA containing 56 variables chosen from among a CGA adapted for use within the primary care setting.

The authors demonstrated that FI-CGA was feasible to assess frailty in primary care for a multidisciplinary primary care program for frailty. Additionally, FI-CGA was useful for the care of frail older persons in primary care as any specific problems out of 10 domains can be identified and managed effectively. Following these principles and the example of FI-CGA in Canada, we developed a Korean Frailty Index for Primary Care (KFI-PC) and investigated its validity and reliability.

MATERIALS AND METHODS

Development of KFI-PC

The deficits included in KFI-PC, along with their cutoff values, scoring measures, and related references, are described in Table 1.2,6-18) The Korean version of the KFI-PC is provided in Supplementary Table S1. We adopted questionnaires or assessments validated in Korea for items of KFI-PC while referring to FI-CGA and the validated Korean frailty indices. We replaced or excluded items that were not appropriate for use in busy primary care settings in Korea; for example, “low mood” in FI-CGA was excluded because it is duplicated with the evaluation of “depression”. We also excluded “motivation”, “health attitude”, and “control of life events” because they were not appropriate for Korean older adults. We excluded the timed up and go test because it requires a 3-m length of space to perform; it was replaced by a chair stand test (rising from a chair five times).19) We also excluded IADLs of cooking and cleaning as those activities are not appropriate to assess older Korean men. We replaced these IADLs with “walking to distant destinations”. FI-CGA also includes the Montreal Cognitive Assessment; however, as it takes more than 20 minutes to complete, we replaced it with the Mini-Cog test. The Mini-Cog test combines two simple cognitive tasks (a three-item word memory and clock drawing) with a scoring algorithm.20) It can be completed in 2–4 minutes and has shown high diagnostic accuracy for dementia (sensitivity 76%, specificity 99%). We included factors related to hospital admission within 1 year and self-assessment of health as they are included in the Korean frailty index.8) Contact frequency with friends,17) living with family (a spouse), and frequency of going out of the home7) were included as known social risk factors for frailty. Finally, we included data regarding appetite and number of full meals eaten per day from the Short Nutritional Assessment Questionnaire (SNAQ) as nutritional assessment.18) Regarding comorbidities, FI-CGA allowed a maximum of 18 current conditions. The comorbidities included hypertension, diabetes, cancer, chronic obstructive pulmonary disease, myocardial infarction, heart failure, angina, asthma, arthritis, stroke, and kidney disease as they are embedded in the Fatigue, Resistance, Ambulation, Illnesses, and Loss of weight (FRAIL) questionnaire.21) Spinal stenosis was included as the 12th disease to be questioned.22) If the subjects had other diseases, each additional condition was recorded up to 18 diseases. We selected these items through article review and the consensus of three experts and authors (CWW, MK, and YL).

Table 1.

Overview of deficits included in the KFI-PC

RESULTS

Table 2 shows the characteristics of the study participants. Overall, the mean age was 77.9 and 28.9% of participants were living in rural areas. As the KFACS cohort study included participants who could visit 10 centers, ADL disability in any of five basic activities of daily living (i.e., dressing, bathing, toileting, transferring, and feeding) was rare (1.5%). Furthermore, the average overall KFI-PC score was 0.17. The KFI-PC score was higher in women and older groups in both sexes. The median and quartile KFI-PC scores for men and women and for age groups are shown in Supplementary Table S2. The KFI-PC scores showed a right-skewed distribution ranging from 0.02 to 0.52 (Fig. 1). Participants with KFI-PC score over 0.25, usually recognized the cutoff of frailty, represented 17.5% of the total population; however, the frailty prevalence by Fried’s phenotype criteria was 9.2%. The KFI-PC score increased with age levels and the pattern was more exaggerated in women (Fig. 2). The deficit scores and missing data for each item of KFI-PC are presented in Table 3. The highest saturated deficit score was 60.2% with the current condition of hypertension. The highest rate of missing was 1.4% for the sleeping pattern item. The Cronbach’s alpha coefficient of the 54 items total was 0.737, within the acceptable range (0.7 or above) for internal consistency (reliability).

Table 2.

Characteristics of the study sample

Fig. 1.

The Korean Frailty Index for Primary Care (KFI-PC) score distribution in the study sample.

Fig. 2.

Boxplot of the Korean Frailty Index for Primary Care (KFI-PC) scores for men and women and for three age groups. The median (horizontal line) is shown within each box. The KFI-PC score differed significantly between men and women in all age groups (p<0.001) and between the three age groups in men and women (p<0.01) except for 70–74 years vs. 75–79 years in men (p=0.144).

Table 3.

The KFI-PC characteristics of the study sample

Construct Validity of KFI-PC

To assess the construct validity (convergent validity) of KFI-PC, we compared it to Fried’s physical frailty (Fig. 3, Table 4). ROC analysis performed to confirm the criterion-related validity of KFI-PC for Fried’s physical frailty showed an area under the curve of 0.921 (95% confidence interval, 0.910–0.940). The ROC analysis revealed an optimal cutoff value, statistically defined as the best compromise between sensitivity and specificity, of 0.23 (sensitivity=89%, specificity=81%). The KFI-PC score showed correlations with physical, cognitive, and psychological functions, as well as nutritional status, disability in ADLs, and IADLs irrespective of age and sex (Table 4).

Fig. 3.

Receiver operating characteristic (ROC) curve of the Korean Frailty Index for Primary Care (KFI-PC) score according to Fried's phenotype criteria. AUC, area under the ROC curve; CI, confidence interval.

Table 4.

Construct validation of the KFI-PC

DISCUSSION

We developed a KFI-PC containing 54 items with a maximum deficit score of 53 and demonstrated its acceptable internal consistency and construct validity. Broadly speaking, KFI-PC is a comprehensive assessment that covers health-related areas related to cognitive, mental, physical, social, and nutritional factors, as well as ADLs and medical illness.

Generally, frailty indices should contain at least 30 items and cover a range of health indicators including chronic conditions, physical/cognitive limitations, and general health. Another characteristic of frailty index is that each deficit should be health-related and increase with age.24) Previous studies used 30–70 deficits to construct frailty indices. However, Searle et al.23) recommended that frailty indices should include at least 30–40 total deficits. Another criterion is that the deficit should not saturate too early, i.e., it should not be present in all or most people. A reasonable criterion for saturation appears to be about 80% or less as any deficits present in more than 80% of people do not make a significant difference in grading frailty.28) KFI-PC satisfied all these requirements. Moreover, it covers a range of not only chronic conditions, physical/cognitive limitations, and general health but also the factors related to social and psychological health.

In this study, the ROC analysis demonstrated an optimal KFI-PC cutoff value of 0.23, consistent with the consensus cutoff point for frailty of 0.25 for the frailty index used to define frailty in other studies.29) The original paper suggested a frailty cutoff of 0.25 based on a physical frailty index containing 70 deficits and data from participants aged 70 years and older in the Canadian Study of Health and Aging. However, another paper proposed a frailty cutoff of 0.21.30) A study analyzing Canadian Health Survey data from participants aged 65 years and over reported that the risk of hospital-related events increased at a value of 0.21. The cutoff is the lowest point for predicting outcomes; it may be sensitive but not specific and, therefore, not the optimal threshold.

Regarding participants with missing variables, studies commonly exclude any item with more than 5% of missing data31) and any participant with at least one missing item from more than 20% of the items.30) In this study, 40 of 53 (75.5%) items had complete data. Of the 13 items with missing data, 10 items were missing only 1 or 2 value; the other three items had 3, 6, and 18 missing values. Thus, missing variables were not an issue in this study. KFI-PC is easily evaluated in primary care, as it is mainly made of self-responding questionnaires, with only the Mini-Cog and chair rise tests requiring healthcare provider evaluations. The Mini-Cog test can be completed in 2–4 minutes. The chair rise test takes approximately 1–2 minutes to administer after a simple demonstration. The chair rise test can be used as an alternative for gait speed or handgrip strength. It is particularly valuable and applicable to studies that do not or cannot include gait testing due to a lack of space or instrument to measure handgrip strength.

The KFI-PC score increased with age levels, a pattern that was more pronounced in women. Previous studies reported that deficits consistently accumulate exponentially with age at an average relative rate of approximately 3% per year on a log scale and that in general, at any given age, women on an average have more deficits than do men.32) The reason for the sex difference may be mainly because of a higher incidence of comorbidities in women than in men, in addition to social, behavioral, and biological differences between men and women.33)

We observed a frailty prevalence of 9.2% based on Fried’s phenotype criteria and 17.5% based on KFI-PC, with a cutoff of 0.25. This result is compatible with that of previous reports of a 10% higher frailty prevalence using the frailty index compared with that using the phenotype criteria.34) The frailty index is associated with adverse health outcomes even among people categorized as non-frail by frailty phenotype.34) This finding suggests that the frailty index is a more sensitive measure for determining frailty owing to its ability to detect this condition at even the early stage of a frailty trajectory.34) Furthermore, the continuous nature of the frailty index allows it to trace slight changes in frailty to intervene before an individual reaches a definite frail phenotype.33) The prevalence of ADL disability in this study was only 1.5%. As the participants of the KFACS are comparatively healthy older adults who can visit the centers, the percentage of ADL disability may be lower than other home visit surveys. However, KFI-PC was developed for use in outpatient primary care and those patients must be ambulatory to visit clinics. In comparison, the reported prevalence of ADL disability was 2.6% in four outpatient clinics and two welfare centers.35)

In conclusion, we developed KFI-PC containing 53 deficits including comprehensive geriatric assessment components. KFI-PC comprises mainly self-administered questionnaires; only the Mini-Cog and chair rise tests are assessed by medical personnel and require limited time to perform. We demonstrated the construct validity and internal consistency (reliability) of KFI-PC. KFI-PC is easily assessed, was not considered a burden on the medical personnel who practice in primary care, and was well validated. Further studies are needed to determine whether KFI-PC is a good indicator for the prevention of adverse health outcomes and if it is feasible in real-world primary care settings.

SUPPLEMENTARY MATERIALS

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