Association Between Frailty Scoring and Cardiopulmonary Exercise Testing: A Retrospective Cohort Study

Abstract

Introduction: Cardiopulmonary exercise testing (CPET) is the gold-standard assessment of functional capacity and predicts postoperative outcomes in major abdominal and thoracic surgery, as well as in older individuals undergoing elective surgery for colorectal cancer. However, CPET is resource-intensive and not universally available. Simpler objective assessments of functional capacity, such as Clinical Frailty Scale (CFS) scoring, predict postoperative complications and may be useful in aiding shared decision and perioperative planning. Objectives: This study aimed to assess local cohort data and investigate the association between Clinical Frailty Scoring, CPET outcomes, and length of hospital stay. Methods: We conducted a retrospective cohort analysis of all patients who had received a cardiopulmonary exercise test as part of their preoperative assessment for major abdominal and thoracic surgery between May 2018 and December 2022 in four district general hospitals. Results: This study featured 174 patients, age 73 (mean), CFS 3 (mean), who underwent CPET with associated CFS scoring. The CFS scores were weakly correlated with the anaerobic threshold, VO₂ peak, and ventilatory equivalents, coefficients measuring −0.34, −0.36, and 0.31 (all p < 0.001), respectively. Linear regression demonstrated a negative coefficient for the association of CFS with the VO₂ peak and the AT, measuring −1.22 and −1.70, respectively, both p < 0.001. The CFS score was not predictive of 1-year mortality in this group. In a subgroup analysis (n = 59), there was no association between the CFS score and the length of stay. Conclusions: Our data suggest a weak relationship between the CFS score and the CPET results. Further investigations with larger prospective datasets are required to explore the use of CFS as a surrogate for CPET and its use as an independent predictor for perioperative outcomes. This study supports the limited literature available on this subject.

1. Introduction

Cardiopulmonary exercise testing (CPET) is increasingly utilised as a preoperative risk stratification tool to predict postoperative outcomes and inform shared decision-making processes [1,2,3]. An accurate functional assessment is critical for reliable preoperative evaluation and can guide strategies for both prehabilitation and rehabilitation [4]. These strategies aim to deliver individualised perioperative care while reducing the risk of surgical complications, which are costly for both patients and healthcare providers.

However, as surgical demand grows alongside an ageing and increasingly medically complex population, the demand for CPET also increases. CPET is time-consuming, expensive, and not universally available, as few centres have the capacity to test all patients requiring risk stratification. Current national guidelines [5] recommend screening all patients with validated tools, such as the Duke Activity Status Index, the Godin–Shepard Leisure-Time Exercise Questionnaire, or the International Physical Activity Questionnaire. Patients identified as having reduced fitness through these tools should then be referred for CPET.

Simpler objective tests of functional capacity, including the incremental shuttle walk test, the six-minute walk test, the one-minute sit-to-stand test, and the timed up-and-go test, have been explored as alternative strategies for routine preoperative assessment. These tests may serve as either a replacement for CPET in resource-limited settings or as screening tools to identify patients who would benefit most from CPET [4]. Notably, the Duke Activity Status Index and the six-minute walk test have demonstrated predictive value for postoperative outcomes in perioperative cohorts [4,6].

Frailty assessments have also emerged as valuable adjuncts in preoperative risk stratification. The importance of frailty screening is highlighted both in recent research [7] and in recent European Journal of Anaesthesia guidelines [8]. Tools such as the Rockwood Clinical Frailty Scale (CFS) [9] and the Fried Frailty Phenotype have shown promise in predicting postoperative outcomes, particularly in major abdominal and thoracic surgeries, as well as in older adults undergoing elective colorectal cancer surgery [10,11]. The CFS is a clinician-administered tool that evaluates frailty based on physical, cognitive, and functional impairments. It categorises individuals on a scale from “very fit (1)” to “terminally ill (9)” based on the accumulation of health deficits. Despite its potential, limited research has investigated the utility of the CFS as a surrogate for CPET or as an independent tool for preoperative risk stratification [12]. We hypothesise that the CFS could serve as a useful adjunct to identify patients with reduced functional capacity and predict those at higher perioperative mortality risk.

2. Materials and Methods

A retrospective observational study of adult patients (≥18 years) undergoing CPET at a single district general hospital site between May 2018 and December 2022 was performed. Patients received their CPET test as part of the standard perioperative referral pathway following referrals from the surgical teams at the study site or three other district general hospitals in the region. Patients were referred according to local criteria, including major elective surgery, anticipated major surgical risk (ASA class ≥ III), or reduced functional capacity assessed through clinical evaluation by the referring team. Patients were excluded from analysis if they had either missing CPET data (either VO₂ peak or anaerobic threshold) or an incomplete CFS score.

In this cohort of patients, a minimum sample size of 39 participants per annum was required to achieve a 95% confidence level to ensure that the true population values of CPET variables, as predicted by CFS, would fall within ±5% of the observed values.

Data were extracted from electronic health records and included demographics (e.g., age, sex, BMI), comorbidities, and CPET results. Descriptive data were collected from clinical notes and hospital episode records at the test site and calculated for the study population. CPET was performed on a cycle ergometer using an incremental ramp protocol. All tests were completed at the study site and validated by a single trained physiologist following a standardised protocol [13]. CPET data included peak oxygen uptake (VO₂ peak), anaerobic threshold (AT), and ventilatory equivalents at the anaerobic threshold (VE/VCO₂). The Rockwood CFS score [9] was assessed at presentation for CPET for all patients by their clinical team.

The primary endpoint was the association between the Clinical Frailty Scale (CFS) scores and the cardiopulmonary exercise testing (CPET) variables, including VO₂ peak, anaerobic threshold (AT), and ventilatory efficiency (VE/VCO₂). Linear regression models were used to analyse the relationships between the CFS scores and the CPET parameters, while Spearman’s rank correlation tested the strength and direction of the associations. Linear models were fitted using the lm() function in R. Predictor variables were entered into the model as continuous or categorical variables, as appropriate. The intercept term was included by default, and the coefficients were estimated using the method of ordinary least squares (OLSs). Model assumptions were assessed using diagnostic plots and relevant statistical tests. The overall fit of the model was evaluated using R-squared (R²) values.

Additionally, as a further analysis, an ordinal logistic regression model was applied to explore the association between the CPET variables and the CFS scores, assessing an ordered outcome of the CFS scores as predicted from the CPET variables. The correlation between the CFS score and the 1-year mortality in the same group was also evaluated. A logistic regression model was applied to determine the predictive power of the CFS score for the 1-year mortality. Statistical significance was assessed for all tested associations.

A subgroup analysis was conducted to assess the correlation (Spearman’s rank) between the CFS score and the length of hospital stay in patients who proceeded to surgery at the host site. The authors had approved access to data on the length of stay at the host site only.

All data were analysed using R, v4.1, R Foundation for Statistical Computing, and r-project.org. The following packages were used: tidyverse, dplyr, devtools, and janitor.

Ethical approval was not required as this was a retrospective review of pseudonymised routinely collected data, meeting the criteria for a service evaluation. This was assessed by the local research team at the host site.

3. Results

A total of 179 patients with CPET data were initially included. After excluding 5 cases due to missing values, 174 patients with matched CFS and CPET data were analysed. The descriptive statistics are presented in

Table 1. Patient demographics and comorbidities, n = 174.

Domain	Median (IQR)
Age	73.8 (69.0–79.0)
Male	70% (n = 121)
Ischaemic heart disease	18% (n = 32)
Atrial fibrillation	14% (n = 25)
Stroke/TIA	8% (n = 14)
Diabetes	23% (n = 40)
Heart failure	7% (n = 12)
COPD	16% (n = 27)
Hypertension	45% (n = 79)

and

Table 2. Surgical procedure, n = 174.

Surgery Type	(n)
Cystectomy	76
Nephrectomy
	35
Bowel resection
	36
Lung resection
	8

. The mean Clinical Frailty Scale (CFS) score was 3 (range: 1–5). The CPET-derived variables showed a mean VO₂ peak of 15.9 mL/kg/min (range: 5.7–28.0, SD: 3.51), a mean anaerobic threshold of 12.7 mL/kg/min (range: 4.8–22.0, SD: 2.8), and a mean ventilatory equivalent slope of 35.6 (range: 18–61, SD: 6.2).

3.1. CFS Score and CPET Values

Spearman’s rank correlation analysis revealed a weak association between the CFS score and the CPET results. The correlation coefficients for the VO₂ peak and the anaerobic threshold were −0.34 (p < 0.001) and −0.36 (p < 0.001), respectively. A weak positive correlation was observed between the CFS score and the ventilatory equivalents, with a coefficient of 0.31 (p < 0.001).

Linear regression modelling showed a significant negative association between the Clinical Frailty Scale (CFS) scores and the CPET variables. For every unit increase in the CFS score, the VO₂ peak decreased by 1.22 (p < 0.001), and the anaerobic threshold (AT) decreased by 1.70 (p < 0.001). In contrast, the ventilatory equivalents (VE/VCO₂) demonstrated a significant positive association, increasing by 2.74 per unit increase in the CFS score (p < 0.001). The adjusted R² values for the models were 0.13, 0.10, and 0.10, respectively. The linear regression plots are presented in Figure 1.

Ordinal logistic regression modelling of the CPET variables to predict the CFS demonstrated negative coefficients for the VO₂ peak (−0.22) and the AT (−0.24), both with p < 0.001. The ventilatory equivalents showed a weak positive coefficient (0.10, p < 0.001). For the VO₂ peak and AT as predictors of the CFS, the thresholds shifted from negative to positive between CFS scores of 4 and 5. A similar shift occurred between CFS scores of 2 and 3 for the ventilatory equivalents.

In the subgroup analysis of those patients who proceeded to surgery at the host site, (n = 59), the mean length of stay was 12 days (SD 22.8). The CFS score demonstrated no correlation with the length of stay (coefficient = 0.037).

3.2. One-Year Mortality Data

At 1 year, 19 deaths were recorded (10.9%). The CFS score showed a weak positive correlation with the 1-year mortality (coefficient 0.11), which did not reach statistical significance (p = 0.17). The logistic regression analysis indicated that each unit increase in the CFS score was associated with an odds ratio of 1.4 for the 1-year mortality; however, this result was not statistically significant (p = 0.22).

4. Discussion

This retrospective cohort analysis, representing a typical perioperative population in terms of CPET values [13], compared a clinician-assessed measure of patients’ frailty, the CFS, with the gold-standard method of preoperative risk stratification, CPET. CPET is complex, time-consuming, and costly for the provider and patient, whereas CFS scoring is simple, quick, and non-invasive, offering a potential avenue for the improvement of the process of patient risk stratification prior to major surgery.

Whilst it is intuitive that the functional status of a patient may correlate with CPET performance, there is currently a paucity of research available to support this. One study by O’Mahoney et al. [12] demonstrated a weak association between the CPET and CFS scores, similar to the findings of this study, but beyond this, there has been little investigation of the use of CFS status as a potential surrogate for formal CPET.

This study found a weak correlation between the CFS scores and the CPET variables. However, the relatively low adjusted R² values (0.13, 0.10, and 0.10 for the VO₂ peak, AT, and ventilatory equivalents, respectively) suggest that the models account for only a small proportion of the variability in the outcomes. This indicates that other unmeasured or unaccounted-for factors may be influencing these variables, highlighting the potential for additional predictors to improve the explanatory power of the models. Future studies will be strengthened by fully assessing the impact of confounders (such as age, gender) and including data for other unmeasured confounders in this study (such as socioecomic data, index of multiple deprivation).

The ordinal regression analysis revealed that CFS categories 1–4 exhibited an increasing probability of transitioning to a higher category as both the anaerobic threshold (AT) and VO₂ peak decreased. This linear relationship supports the weak overall association observed. This pattern continued up to categories 4–5, suggesting that CFS category 4 may represent a threshold beyond which further reductions in CPET values have minimal impact on CFS scoring. Similarly, the mortality data exhibited a weak positive association, with increasing mortality observed as the CFS scores rose. However, the linear regression analysis showed a non-significant coefficient, indicating insufficient evidence to conclude that the CFS score alone is a significant predictor of 1-year mortality in this cohort.

Whilst the presented study provides further investigation of the relationship between a frailty assessment and CPET performance, there are limitations. CFS scoring, by nature, is subjective. While scoring in this study was completed by a set of experienced clinicians, as a regular component of their usual practice, the standardisation of scoring did not occur.

Due to resource constraints, the study cohort was relatively small, potentially affecting the strength of association between the two variables. The retrospective nature placed this study at risk of selection bias and unmeasured confounders. In addition, the highest CFS score observed was 5, and the mean was 3, which may have been because those with high CFS scores were deemed too high-risk for surgery and therefore not referred for CPET. Regardless, this limited the ability of the study to assess the correlation between CFS and CPET in the frailest patients. Finally, although understanding the relationship between CFS scoring and CPET performance may be of academic interest, the successful adoption of CFS scoring as a surrogate for CPET would rely on CFS scoring providing an accurate estimation of perioperative risk itself (including perioperative complications), rather than a correlation with another risk prediction tool. Whilst there is emerging evidence [14] that increased frailty (as assessed using CFS scoring) is associated with worsened post-surgical outcomes, in our cohort, we were unable to demonstrate an association between CFS and length of hospital stay and only a weak association with the 1-year mortality.

The authors assert that, despite the findings presented in this study, the ongoing assessment of the Clinical Frailty Score (CFS) continues to add value to perioperative risk profiling and will remain an integral component of routine perioperative assessment. Future prospective cohort studies with a larger sample size will thus be required to assess the predictive power of frailty scoring of CPET variables and perioperative outcomes, thereby strengthening the role of CFS within perioperative care.

5. Conclusions

Our data suggest a statistically significant weak link between CFS score and CPET results, as evidenced by the correlation and regression coefficients. The R² values presented suggest significant unmeasured confounders. Further investigation with a larger prospective cohort is required to explore the merit of CFS as a surrogate for CPET, its use as an independent predictor for perioperative outcomes, and address the major limitations of this study. This study supports the limited literature available on this subject.