Multidimensional Frailty and Mortality in Transcatheter Aortic Valve Implantation Patients - Prognostic Value of the Kihon Checklist

Q: What was the purpose of using the Kihon Checklist in TAVI patients?

The study assessed the prognostic value of the KCL, which captures physical, cognitive, and social domains, for predicting all-cause mortality after discharge in TAVI patients.

Q: How did the researchers classify frailty levels?

Frailty was categorized using KCL scores: non-frail (0–3), pre-frail (4–7), and frail (≥8).

Q: Which factors were identified as independent predictors of mortality?

Impaired socialization and physical function were found as independent predictors, and CART analysis identified socialization as the primary node in risk stratification.

Sep 30, 2026

Uploaded by Margaret

Frailty is evaluated as a key prognostic factor in transcatheter aortic valve implantation (TAVI) patients. Using the Kihon Checklist (KCL), which measures physical, cognitive, and social domains, a retrospective single-center analysis assessed outcomes in 986 elective TAVI patients (May 2017–September 2022). Frailty categories were non-frail (0–3), pre-frail (4–7), and frail (≥8), with all-cause mortality after discharge as the endpoint. Over a mean follow-up of 968±578 days, 18.1% died. Frailty showed a significant adjusted association with mortality, and socialization emerged as the primary CART risk node.

LanguageEnglish

CategoryHealthcare

FormatPDF

Pages9

Reading Time23 min

AccessFree to download

Background

Methods and Results

Study design and cohort

Frailty assessment and outcomes

Conclusions

Key Words

Circulation Reports Circ Rep 2026; 8: 153–161 doi:10.1253/circrep.CR-25-0221 ORIGINAL ARTICLE Valvular Heart Disease | Multidimensional Frailty and Mortality in Transcatheter Aortic Valve Implantation Patients
―Prognostic Value of the Kihon Checklist― | | | --- | --- | | Daichi Kobayashi; Masakazu Saitoh, PhD; Kentaro Hori; Shinya Tajima, MS; Kotaro Takizawa, BSc; Junko Sakamoto, MS; Atsuko Nakayama, MD, PhD, FJCS
Background: Frailty is a crucial factor in the prognoses of patients who undergo transcatheter aortic valve implantation (TAVI); however, comprehensive assessments of this parameter are not frequently performed in this regard. This study evaluated the prognostic value of the Kihon Checklist (KCL), which covers physical, cognitive, and social domains, for patients receiving TAVI.
Methods and Results: We retrospectively analyzed data from 986 patients who underwent elective TAVI between May 2017 and September 2022. Frailty was classified according to the KCL as non-frail (for scores of 0–3), pre-frail (4–7), or frail (≥8) . The primary outcome measure was all-cause mortality following discharge. Kaplan-Meier, Cox regression, and classification and regression tree (CART) analyses were used. Of the overall patient cohort, 47.4% were classified as frail. Over a mean follow-up period of 968±578 days, 18.1% died. Frailty was significantly associated with higher mortality (adjusted hazard ratio 1.771; 95% confidence interval 1.096–2.862; P<0.02) . Impaired socialization and physical function were also found to represent independent predictors of mortality. CART identified socialization as the primary node in the risk stratification.
Conclusions: Preoperative frailty, as defined by the KCL, was found to be independently associated with mortality after TAVI. Social and physical domains were also found to have strong prognostic relevance in this context.
Key Words: Aortic stenosis; Frailty; Kihon Checklist; Prognostication; Transcatheter aortic valve implantation | | | T
ranscatheter aortic valve implantation (TAVI) is predominantly performed in older patients with severe aortic stenosis who are classified as high risk
for surgical interventions.1 Frailty has emerged as a significant predictor of adverse outcomes in this population, including increased mortality, delayed functional recovery, and prolonged hospitalization.2–4 Various assessment tools, such as the Fried frailty phenotype and the Clinical Frailty Scale, have been used to evaluate frailty in clinical settings.5–7 However, these instruments primarily focus on physical and activities of daily living (ADL) domains, thus potentially overlooking certain psychological and social vulnerabilities that are often more prevalent in older adults. As a result, a standardized and comprehensive approach to assessing frailty remains elusive.8,9 The Kihon Checklist (KCL), developed by the Japanese Ministry of Health, Labor, and Welfare, comprises a 25-item self-administered questionnaire that encompasses 7 domains: instrumental | ADL (IADL), physical function, nutritional status, oral function, social engagement, cognitive function, and depressive mood.10 Its multidimensional nature facilitatesa holistic evaluation of frailty, capturing aspects beyond physical decline alone. Previous studies have indicated an association between higher KCL scores and higher mortality following TAVI procedures;11 however, these studies classified frailty based on quartiles rather than established thresholds (i.e., non-frail [0–3 points], pre-frail [4–7 points], and frail [≥8 points]), and the prognostic significance of individual KCL subdomains has not yet been fully explored. Given that frailty encompasses a spectrum of physical, cognitive, psychological, and social deficits, analyzing both overall KCL score and its individual domains may provide detailed insights into patient prognosis after TAVI. This study aimed to evaluate the association between preoperative fra

FAQs

What was the purpose of using the Kihon Checklist in TAVI patients?

The study assessed the prognostic value of the KCL, which captures physical, cognitive, and social domains, for predicting all-cause mortality after discharge in TAVI patients.

How did the researchers classify frailty levels?

Frailty was categorized using KCL scores: non-frail (0–3), pre-frail (4–7), and frail (≥8).

Which factors were identified as independent predictors of mortality?

Impaired socialization and physical function were found as independent predictors, and CART analysis identified socialization as the primary node in risk stratification.

Sep 30, 2026

Uploaded by Margaret