Exploring the Frailty Components Related to Hospitalization-Associated Disability in Older Patients After Cardiac Surgery Using a Comprehensive Frailty Assessment

Abstract

Background: We investigated the components of frailty associated with hospitalization-associated disability (HAD) after cardiac surgery.

Methods and Results: This retrospective, observational study evaluated 1,446 older patients after elective cardiac surgery at the Sakakibara Heart Institute. We examined the association between HAD and 7 domains of frailty assessed by the Kihon Checklist. HAD was defined as a decline in the ability to perform activities of daily living (ADL) between admission and discharge, as assessed by the Barthel Index. Logistic regression and decision tree analysis were used to identify associations between the number and type of frailty components and HAD. Of the 1,446 patients, 190 were excluded, and 90 (7%) developed HAD. An increase in the number of frailty components was a risk factor for HAD (odds ratio: 1.88, 95% confidence interval: 1.62–2.17). Decision tree analysis identified physical functional decline, depression, and cognitive dysfunction as factors associated with HAD. The incidence of HAD was highest in cases of physical functional decline (21%) and lowest for cases in which the 3 aforementioned factors were absent (2.8%).

Conclusions: An increased number of frailty factors increased the risk of HAD and the findings also reaffirmed the importance of a comprehensive assessment to evaluate the risk of HAD, including evaluation of physical function, cognitive function, and depression.

Cardiac rehabilitation in the acute to early recovery phase is recommended to prevent postoperative complications, functional decline, and prolonged postoperative in-hospital stay and to control medical costs after cardiac surgery.^1,2 Recently, early postoperative mobilization has been implemented in many Japanese hospitals, and cardiac rehabilitation is recognized as part of the perioperative management after cardiac surgery. However, older patients with multiple comorbidities often experience delayed progress in postoperative rehabilitation and reduced ability to perform activities of daily living (ADL) at discharge.

Hospitalization-associated disability (HAD) is the loss of independence in ADL after hospitalization that is not a result of the underlying disease.³ HAD is associated with adverse outcomes, such as longer hospital stays, non-home discharge, prolonged functional decline, increased number of rehospitalizations, and death after discharge.^4–7 Studies have indicated that roughly one-third of patients over 70 years of age admitted to acute care hospitals exhibit a decrease in their ability to perform ADL at discharge.³ Furthermore, according to previous studies, HAD occurred in approximately 5–33% of patients after cardiac surgery.^8–11 HAD is a concern in countries with aging populations, such as Japan, as advances in surgical techniques and perioperative management have expanded the indications for surgery in older patients. Therefore, preoperative assessment of the risk of HAD is important for minimizing its occurrence.

Frailty is a factor that affects the postoperative outcomes of cardiac surgery,^11–15 and the effect of both frailty factors and HAD has been reported in previous studies.^11,16 Frailty involves various factors, including physical and cognitive function and nutritional status; however, there is a lack of information regarding the components of frailty that affect HAD.

Therefore, in this study we examined the frailty components related to HAD in older patients who undergo elective cardiac surgery.

Methods

Study Design

This study was a retrospective, single-center observational study carried out at Sakakibara Heart Institute in Tokyo, Japan, that involved reviewing patient medical records. It was conducted in accordance with the principles of Declaration of Helsinki and the Guidelines for Medical and Health Research Involving Human Subjects by the Ministry of Health, Labor, and Welfare (MHLW) in Japan. The Ethics Committee of the Sakakibara Heart Institute approved the study protocol (no. 20-084). Additionally, the research participants were given an option to refuse participation in the study through an approved opt-out consent form.

Participants

We retrospectively reviewed the medical records of 1,446 consecutive patients aged ≥65 years after elective cardiac surgery at the Sakakibara Heart Institute performed between June 2017 and March 2021. The primary indications for cardiac surgery were ischemic heart disease (36%), valvular heart disease (69%), and others (46.5%). The exclusion criteria were: (1) Kihon Checklist (KCL) not assessed, (2) postoperative stroke, (3) transfer to another hospital because of the onset of other diseases, and (4) postoperative in-hospital death (Figure 1).

Figure 1.

Flowchart of the patient selection process. ARDS, acute respiratory distress syndrome; KCL, Kihon Checklist.

Assessment of the Components of Frailty

The components of frailty were assessed using the KCL,¹⁷ which is a screening method developed by the MHLW in Japan to identify older adults requiring new certification for long-term care insurance.¹⁷ In a previous study, the KCL was reported as a useful screening tool for frailty.¹⁸ It is a self-reported questionnaire comprising 25 items in 7 domains: 5 items regarding instrumental ADL (IADL) (#1–5), 5 items regarding physical function (#6–10), 2 items regarding nutritional status (#11, 12), 3 items regarding oral function (#13–15), 2 items regarding socialization (#16, 17), 3 items regarding memory (#18–20), and 5 items regarding mood (#21–25). Each question on the KCL requires a “yes” or “no” answer, scored as 1 and 0 points, respectively.

As in a previous study,¹⁹ we defined IADL impairment as a score ≥1 in the IADL domain, physical functional decline as a score ≥3 in the physical domain, malnutrition as a score ≥2 in the nutrition domain, oral dysfunction as a score ≥2 in the eating domain, cognitive impairment as a score ≥1 in the memory domain, and depression as a score ≥2 in the mood domain. Additionally, a “no” response to question #16 in the socialization domain was deemed to indicate a housebound status. In this study, we applied the KCL by interviewing patients about their living conditions before hospitalization.

Definition of HAD

We defined HAD as a decline in the patient’s ability to perform ADL as evaluated by the Barthel Index (BI) between the time of hospital admission and discharge. BI is a tool consisting of 10 items that is used to assess a person’s ability to carry out basic ADL, including feeding, transfer, grooming, toilet use, bathing, ambulation, stair climbing, dressing, and managing urination and defecation.²⁰ Each of these items is assigned a score of 0, 5, 10, or 15 points based on the person’s level of independence. The total score ranges from 0 to 100 points, with higher scores indicating a higher level of independence. In this study, the BI was evaluated by physical therapists and trained registered nurses.

Collected Clinical Characteristics

We collected the following preoperative clinical characteristic data from the medical records of all patients included in this study: age, sex, body mass index (BMI), New York Heart Association functional classification, medical history, European System for Cardiac Operative Risk Evaluation II (EuroSCORE II), hematologic data, left ventricular ejection fraction, respiratory function, Short Physical Performance Battery score, and KCL score. Further, as the peri- and postoperative clinical characteristics, the following data were collected: type of surgery, operation time, use of cardiopulmonary bypass (CPB), CPB time, bleeding volume, ventilator time, postoperative mobilization start day, length of postoperative intensive care unit (ICU) stay, rate of return to home, and length of in-hospital stay.

Postoperative Rehabilitation Program

Postoperative rehabilitation was carried out in accordance with the JCS guidelines for rehabilitation in patients with cardiovascular disease.²¹ The early mobilization process began in the ICU the day after cardiac surgery was performed. Subsequently, the amount of physical activity was progressively increased based on the patient’s general condition and physical function.

Statistical Analysis

We conducted a 3-step statistical analysis. First, we used conventional descriptive statistics to examine the demographic and clinical characteristics. The t-test or chi-square test was performed, depending on the type of variable, to evaluate differences in the baseline characteristics between HAD and non-HAD patients. For these analyses, a two-sided P<0.05 was considered statistically significant.

Second, we used logistic regression analysis to examine whether an increase in the number of frailty components was a significant factor associated with HAD. Confounding factors in the logistic regression analysis were determined based on the results of previous studies and clinical importance.

Finally, a decision tree analysis was performed to explore the risk profile of HAD-associated frailty components. Decision tree analysis is a valuable technique for data mining that predicts which class an item belongs to, based on its features. The method is presented as a tree structure, with each branch indicating the significance of a variable. The results of the analysis are organized hierarchically, starting with the variable that has the strongest relationship with the dependent variable, making it easy to understand the interconnections between variables. Furthermore, decision trees are able to handle incomplete or discrete data and can be effortlessly applied to complex data sets due to their automatic variable selection ability. The dependent variable was HAD, and the independent variables included the 7 domains of the KCL. The trees were grown using the chi-squared automatic interaction detector, and the maximum tree depth was set to 3. Cross-validation was used to verify the accuracy of the model.

All analyses were performed using SPSS version 22.0 for Windows (IBM Corp., Armonk, NY, USA).

Results

Clinical Characteristics

Of the 1,446 patients investigated, 190 were excluded according to the exclusion criteria, which resulted in a sample size of 1,256 (Figure 1). Table 1 summarizes their preoperative characteristics. The mean age was 74 years, and 42% were women. Table 2 summarizes the KCL assessment. The mean KCL score was 4.4 points, and 32.9% of patients had zero components, 31.1% had 1 component, 18.2% had 2 components, 10.5% had 3 components, 4.9% had 4 components, 2.0% had 5 components, and 0.5% had 6 components. None of the patients had all 7 domains. The percentage of patients who met the criterion for each frailty component was 46.6% for IADL, 16.6% for physical function, 3.3% for nutritional status, 10.6% for oral function, 6.1% for socialization, 23.0% for memory, and 25.0% for mood.

Table 1. Preoperative Clinical Characteristics

	Total (n=1,256)	HAD group (n=90)	Non-HAD group (n=1,166)	P value
Age, years	74.0±5.5	78.8±5.9	73.7±5.3	<0.001
Sex, female, n (%)	529 (42.1)	59 (65.6)	470 (40.3)	0.009
BMI, kg/m2	22.8±3.4	21.2±3.8	23.0±3.4	<0.001
NYHA class ≥III, n (%)	103 (8.2)	17 (18.9)	86 (7.4)	<0.001
Comorbidity, n (%)
Hypertension	798 (63.5)	65 (72.2)	733 (62.9)	0.076
Diabetes	305 (24.3)	24 (26.7)	281 (24.1)	0.584
Dyslipidemia	577 (45.9)	43 (47.8)	534 (45.8)	0.716
Renal dysfunction	690 (54.9)	61 (67.8)	629 (53.9)	0.011
Hemodialysis	44 (3.5)	14 (15.5)	30 (2.5)	<0.001
Coronary artery disease	194 (15.4)	22 (24.4)	172 (14.8)	0.014
History of hospital admission for CHF	175 (13.9)	23 (25.6)	152 (13.0)	0.001
History of cardiac surgery	89 (7.1)	11 (12.2)	78 (6.7)	0.049
Atrial fibrillation	294 (23.4)	28 (31.1)	266 (22.8)	0.073
COPD	38 (3.0)	6 (6.7)	32 (2.7)	0.036
Musculoskeletal disease	237 (18.9)	29 (32.2)	208 (17.8)	0.001
Cerebrovascular accident	162 (12.9)	25 (27.8)	137 (11.7)	<0.001
EuroSCORE II, %	3.37±4.08	7.16±8.52	3.07±3.35	<0.001
Laboratory data
Hemoglobin, g/dL	12.7±1.6	11.6±1.7	12.8±1.6	<0.001
eGFR, mL/min/1.73 m2	56.3±18.1	45.6±23.5	57.1±17.4	<0.001
Serum sodium, mEq/L	140.0±2.7	138.8±3.8	140.1±2.6	0.002
Serum albumin, g/dL	4.0±0.3	3.7±0.5	4.0±0.3	<0.001
NT-proBNP, pg/mg	2,403±9,519	10,744±27,344	1,746±5,812	0.010
LVEF, %	57.9±10.1	54.8±12.6	58.1±9.9	0.018
VC, %	87.2±16.9	76.4±17.4	88.0±16.6	<0.001
FEV1.0%	79.8±8.4	80.6±10.2	80.0±10.2	0.838
BI score, points	99.2±4.2	95.7±9.7	99.5±3.3	<0.001
SPPB score, points	11.1±1.7	8.2±3.0	11.3±1.3	<0.001

Values are presented as mean±standard deviation or number (%). Differences between HAD and non-HAD groups analyzed using a t-test or chi-square test. BI, Barthel Index; BMI, body mass index; CHF, chronic heart failure; COPD, chronic obstructive pulmonary disease; eGFR, estimated glomerular filtration rate; EuroSCORE II, European System for Cardiac Operative Risk Evaluation II; FEV1.0%, forced expiratory volume in 1 s; HAD, hospitalization-associated disability; LVEF, left ventricular ejection fraction; NT-proBNP, N-terminal prohormone of B-type natriuretic peptide; NYHA, New York Heart Association; SPPB, Short Physical Performance Battery; VC, vital capacity.

Table 2. Results of KCL Assessment

	Total (n=1,256)	HAD group (n=90)	Non-HAD group (n=1,166)	P value
KCL score, points	4.4±3.7	8.7±4.3	4.1±3.5	<0.001
0–3, n (%)	620 (49.4)	12 (13.3)	608 (52.1)
4–7, n (%)	397 (31.6)	23 (25.6)	374 (32.1)
8–25, n (%)	239 (19.0)	55 (61.1)	184 (15.8)
KCL domains
IADL, n (%)	585 (46.6)	61 (67.8)	524 (44.9)	<0.001
Physical function, n (%)	208 (16.6)	43 (47.8)	165 (14.2)	<0.001
Nutritional status, n (%)	42 (3.3)	11 (12.2)	31 (2.7)	<0.001
Oral function, n (%)	133 (10.6)	19 (21.1)	114 (9.8)	<0.001
Socialization, n (%)	77 (6.1)	18 (20.0)	59 (5.1)	<0.001
Memory, n (%)	289 (23.0)	36 (40.0)	253 (21.7)	<0.001
Depressive mood, n (%)	315 (25.0)	42 (46.7)	273 (23.4)	<0.001
No. of identified KCL domains				<0.001
0	413 (32.9)	9 (10.0)	404 (34.6)
1	390 (31.1)	15 (16.7)	375 (32.2)
2	229 (18.2)	22 (24.4)	207 (17.8)
3	132 (10.5)	18 (20.0)	114 (9.8)
4	61 (4.9)	17 (18.9)	44 (3.8)
5	25 (2.0)	5 (5.6)	20 (1.7)
≥6	6 (0.5)	4 (4.4)	2 (0.2)

Values are presented as mean±standard deviation or number (%). Differences between HAD and non-HAD groups analyzed using a t-test or chi-square test. HAD, hospitalization-associated disability; IADL, instrumental activities of daily living; KCL, Kihon Checklist.

Characteristics of Patients With and Without HAD

Table 1 shows the incidence of HAD and a comparison of the preoperative clinical characteristics in the HAD and non-HAD groups. Of the 1,256 study patients, 90 (7%) developed HAD after cardiac surgery. The HAD group had older patients, a higher prevalence of female patients and patients with multiple comorbidities, higher EuroSCORE II, and lower physical function than the non-HAD group (all P<0.05). Additionally, the HAD group had a significantly higher total KCL score and a higher percentage of patients meeting the criterion of each frailty component (all P<0.05) than the non-HAD group (Table 2).

Table 3 compares the peri-postoperative clinical characteristics in the HAD and non-HAD groups. The HAD group had significantly longer operation, CPB, and ventilator times than the non-HAD group (all P<0.05). In addition, there were significant delays in sitting, standing, and ambulatory start days. The length of stays in the ICU and hospital after cardiac surgery were also significantly longer in the HAD group than in the non-HAD group (P<0.05).

Table 3. Perioperative to Postoperative Clinical Characteristics of the Patients

	Total (n=1,256)	HAD group (n=90)	Non-HAD group (n=1,166)	P value
Type of surgery, n (%)				0.003
CABG	288 (22.9)	23 (25.6)	265 (22.7)
Valve surgery	326 (26.0)	10 (11.1)	316 (27.1)
Other	32 (2.5)	0 (0.0)	32 (2.7)
Combined surgery
CABG + valve surgery	178 (14.2)	19 (21.1)	159 (13.6)
Combined valve surgery	202 (16.1)	14 (15.6)	188 (16.1)
Other	230 (18.3)	24 (26.7)	206 (17.7)
Operation time, min	273±97	322±121	270±94	<0.001
Use of CPB, n (%)	988 (78.7)	67 (74.4)	921 (79.0)	0.311
CPB time, min*	119±84	143±111	118±81	0.038
Bleeding volume, mL	216±205	308±368	208±185	0.013
Ventilator time, min	1,059±758	1,516±1,119	1,024±712	<0.038
Progression of mobilization
Sitting start, days	1.2±0.7	1.7±1.2	1.2±0.6	<0.001
Standing start, days	1.3±0.9	1.9±1.5	1.3±0.8	<0.001
Ambulation start, days	2.6±2.1	5.3±4.9	2.4±1.5	<0.001
Length of ICU stay, days	2.5±2.7	5.5±6.3	2.2±2.0	<0.001
Reintubation, n (%)	15 (1.2)	6 (6.7)	9 (0.8)	<0.001
CRRT, n (%)	63 (5.0)	19 (21.1)	44 (3.8)	<0.001
Delirium, n (%)	182 (14.5)	43 (47.8)	139 (11.9)	<0.001
Return to home, n (%)	1,193 (95.0)	52 (57.8)	1,141 (97.9)	<0.001
Length of in-hospital stay, days	14.8±10.0	26.2±22.6	13.9±7.6	<0.001
BI score, points	97.8±9.8	74.7±26.2	99.6±2.6	<0.001

Values are presented as mean±standard deviation or number (%). Differences between HAD and non-HAD groups analyzed using a t-test or chi-square test. *Patients who did not undergo CPB were excluded. BI, Barthel Index; CABG, coronary artery bypass grafting; CPB, cardiopulmonary bypass; CRRT, continuous renal replacement therapy; HAD, hospitalization-associated disability; ICU, intensive care unit.

Relationship Between Frailty Components and HAD After Cardiac Surgery

Figure 2 shows the incidence of HAD for each of the frailty components. Patients who met any criterion in each domain of the KCL (cases) were significantly more likely to develop HAD than the controls.

Figure 2.

Percentage of patients meeting the HAD criteria for each domain of the KCL in the case and control groups. The graph shows the incidence of HAD for each of the frailty components, with patients corresponding to each component as “cases” and those not corresponding to each component as “controls”. HAD, hospitalization-associated disability; IADL, instrumental activities of daily living; KCL, Kihon Checklist.

Logistic regression analysis showed that the odds ratio of HAD occurrence increased with the number of frailty factors, and remained true even after adjustment for age, sex, BMI, EuroSCORE II, preoperative BI score, and peri-postoperative factors (Table 4).

Table 4. Association Between HAD and the Number of Frailty Domains

	Non-adjusted			Adjusted*
	OR	95% CI	P value	OR	95% CI	P value
No. of frailty domains (every 1 domain increase)	1.88	1.62–2.17	<0.01	1.56	1.31–1.86	<0.01

*Confounding factors: age, sex (female), BMI, EuroSCORE II, preoperative BI score, operation time, use of CPB, postoperative ambulation start day (≥3 days). CI, confidence interval; OR, odds ratio. Other abbreviations as in Tables 1,2.

Decision tree analysis conducted with the 7 domains as dependent variables revealed the strongest association between the physical domain and the risk of HAD (Figure 3). The mood domain had the next strongest association, followed by the cognitive domain. Patients who met the criterion for physical functional decline had the highest incidence of HAD (21%). In patients without reduced physical function, the incidence of HAD tended to increase if the criteria for depressive mood and cognitive impairment were met. The patient group that had normal function in these 3 domains had the lowest incidence of HAD (2.8%).

Figure 3.

Exploration of the HAD risk profiles using a decision tree. Df, degrees of freedom; HAD, hospitalization-associated disability.

Discussion

Recent epidemiological studies have reported on the incidence, outcomes, and risk factors of HAD.^4–11 and although frailty is a recognized risk factor for HAD after cardiac surgery,¹¹ there is limited information on the components of frailty that affect the outcomes of cardiac surgery.

This study is one of the few to examine the components of frailty that are related to HAD after cardiac surgery using a relatively large number of cases.

Incidence of HAD and Patients’ Clinical Characteristics

In this study, HAD occurred in 90 (7.2%) of the 1,256 patients included. Recent studies on HAD after cardiac surgery reported its occurrence in 5–33% of the patients,^8–11 so our reported incidence was within that range. However, we used the BI to assess HAD and different assessment methods may affect the incidence of HAD. In addition, we only included cases of elective surgery, and emergency surgical cases and cases of hospital transfer due to the onset of other diseases were excluded, so it is possible that the patients included in our study had a relatively low risk of HAD.

However, the characteristics of the patients with HAD were similar to those in previous studies, including higher age, female sex, low physical function, and multiple comorbidities. The HAD group also had significantly higher total KCL scores than the non-HAD group, and all domains of the frailty components were significantly higher. The KCL cut-off value to determine frailty was 8 points.¹⁸ The mean KCL score of the HAD group in this study was 8.7 points, with 61% of patients scoring ≥8, which suggested that most of the HAD group were frail. The HAD group also had a higher rate of complex surgeries, longer operation, CPB and ventilatory times, delayed progression of postoperative mobilization, and longer ICU stays.

Previous studies have shown that delayed progress in postoperative rehabilitation after cardiac surgery is a risk factor for postoperative functional decline and HAD.^9,22 Furthermore, perioperative factors such as ventilator and CPB times,²³ and delayed postoperative rehabilitation are directly or indirectly associated with HAD.

Relationship Between HAD and Frailty Components

Matsue et al reported that an increased number of frailty factors in elderly patients with heart failure increases the risk of death and rehospitalization.²⁴ In our study, an increase in 1 frailty domain increased the odds ratio by 1.56, which corroborated results from previous studies and reaffirmed the importance of comprehensive assessment to identify the risk of HAD after cardiac surgery in older patients.

Identification of Factors Related to HAD Using Decision Tree Analysis

Decision tree analysis was performed to identify the risk profile of HAD, and physical impairment was the most important risk factor for HAD. The association between preoperative physical function and adverse outcomes after cardiac surgery has been clearly shown in previous studies.^9,22,25,26 Arnadottir et al reported that among various frailty components, physical decline was most strongly associated with adverse health outcomes,²⁷ which corroborated our results.

Cognitive impairment and depression are also important factors that affect outcomes after cardiac surgery. Chen et al reported that cognitive impairment and depression are risk factors for postoperative delirium,²⁸ which is a serious problem affecting postoperative hospitalization and prognosis, and possibly HAD. Previous studies have reported that postoperative delirium after cardiac surgery is associated with decreased performance of ADL after discharge.^29,30 In this study, the incidence of postoperative delirium was higher in the HAD group than that in the non-HAD group, which was consistent with the results of previous studies.

Our study did not identify nutritional status, oral function, IADL, and socialization as risk factors for HAD after cardiac surgery. This is because the results were determined according to the relative importance of each variable in terms of its relationship with the dependent variable using decision tree analysis. However, these factors are known from previous studies as affecting adverse outcomes in older patients with cardiovascular disease.^31–36 The results of our study re-iterate the significance of comprehensive preoperative assessment of older patients undergoing heart surgery. In addition, physical frailty is a reversible component that can be improved with appropriate intervention, and this study suggests the potential of prehabilitation.

Study Limitations

There were several limitations of this study that should be considered. First, it was a retrospective observational study, which limits the generalizability of the results. Second, we did not include high-risk patients for whom catheterization would be the treatment of choice at the time surgery was planned. Also, this study excluded stroke patients and those who required unplanned transfers due to serious complications. The inclusion of such patients would probably increase the incidence of HAD. The association between frailty factors and HAD in such cases requires further research. Third, as noted in the discussion, the indices used to define HAD vary across studies, which could lead to differences in the incidence of HAD.

Conclusions

The risk of HAD after cardiac surgery in the older patients increased with an increase in the number of frailty components. The incidence of HAD was highest in patients with reduced physical function. Impaired cognitive function and depression increased the incidence of HAD in the absence of reduced physical function.

Acknowledgments

The authors thank all members of the Sakakibara cardiovascular physical therapy and cardiac rehabilitation research teams.

Sources of Funding

This study was supported by the Sakakibara Clinical Research Grant for Promotion of Sciences, 2022.

IRB Statement

The study protocol was approved by the Ethics Committee of Sakakibara Heart Institute (no. 20-084).

Disclosures / Conflicts of Interest

None.

Data Availability

The deidentified participant data will not be shared.

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