This paper is in the following e-collection/theme issue:

Preoperative Measures for Prevention (37) Patient-Views on Cardiology Technology and Innovations (10) Perioperative Risk Assessment (21) Development and Evaluation of Research Methods, Instruments and Tools (571)

Published on in Vol 8 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/65805, first published .
Implementation of Brief Submaximal Cardiopulmonary Testing in a High-Volume Presurgical Evaluation Clinic: Feasibility Cohort Study

Implementation of Brief Submaximal Cardiopulmonary Testing in a High-Volume Presurgical Evaluation Clinic: Feasibility Cohort Study

Implementation of Brief Submaximal Cardiopulmonary Testing in a High-Volume Presurgical Evaluation Clinic: Feasibility Cohort Study

Authors of this article:

Zyad James Carr1, 2 Author Orcid Image ;   Daniel Agarkov1, 2 Author Orcid Image ;   Judy Li2 Author Orcid Image ;   Jean Charchaflieh1, 2 Author Orcid Image ;   Andres Brenes-Bastos1, 2 Author Orcid Image ;   Jonah Freund3 Author Orcid Image ;   Jill Zafar1 Author Orcid Image ;   Robert B Schonberger1 Author Orcid Image ;   Paul Heerdt1 Author Orcid Image
Article Authors Cited by Tweetations Metrics

    Original Paper

    1Department of Anesthesiology, Yale University, New Haven, CT, United States

    2School of Medicine, Yale University, New Haven, CT, United States

    3Syracuse University, Syracuse, NY, United States

    *these authors contributed equally

    Corresponding Author:

    Zyad James Carr, MD

    Department of Anesthesiology

    Yale University

    333 Cedar Street, TMP-3

    New Haven, CT, 06510

    United States

    Phone: 1 2037852802

    Email: zyad.carr@yale.edu


    Background: Precise functional capacity assessment is a critical component for preoperative risk stratification. Brief submaximal cardiopulmonary exercise testing (smCPET) has shown diagnostic utility in various cardiopulmonary conditions.

    Objective: This study aims to determine if smCPET could be implemented in a high-volume presurgical evaluation clinic and, when compared to structured functional capacity surveys, if smCPET could better discriminate low functional capacity (≤4.6 metabolic equivalents [METs]).

    Methods: After institutional approval, 43 participants presenting for noncardiac surgery who met the following inclusion criteria were enrolled: aged 60 years and older, a Revised Cardiac Risk Index of ≤2, and self-reported METs of ≥4.6 (self-endorsed ability to climb 2 flights of stairs). Subjective METs assessments, Duke Activity Status Index (DASI) surveys, and a 6-minute smCPET trial were conducted. The primary end points were (1) operational efficiency, based on the time of the experimental session being ≤20 minutes; (2) modified Borg survey of perceived exertion, with a score of ≤7 indicating no more than moderate exertion; (3) high participant satisfaction with smCPET task execution, represented as a score of ≥8 (out of 10); and (4) high participant satisfaction with smCPET scheduling, represented as a score of ≥8 (out of 10). Student's t test was used to determine the significance of the secondary end points. Correlation between comparable structured surveys and smCPET measurements was assessed using the Pearson correlation coefficient. A Bland-Altman analysis was used to assess agreement between the methods.

    Results: The mean session time was 16.9 (SD 6.8) minutes. The mean posttest modified Borg survey score was 5.35 (SD 1.8). The median patient satisfaction (on a scale of 1=worst to 10=best) was 10 (IQR 10-10) for scheduling and 10 (IQR 9-10) for task execution. Subjective METs were higher when compared to smCPET equivalents (extrapolated peak METs; mean 7.6, SD 2.0 vs mean 6.7, SD 1.8; t42=2.1; P<.001). DASI-estimated peak METs were higher when compared to smCPET peak METs (mean 8.8, SD 1.2 vs mean 6.7, SD 1.8; t42=7.2; P<.001). DASI-estimated peak oxygen uptake was higher than smCPET peak oxygen uptake (mean 30.9, SD 4.3 mL kg–1 min–1 vs mean 23.6, SD 6.5 mL kg–1 min–1; t42=7.2; P<.001).

    Conclusions: Implementation of smCPET in a presurgical evaluation clinic is both patient centered and clinically feasible. Brief smCPET measures, supportive of published reports regarding low sensitivity of provider-driven or structured survey measures for low functional capacity, were lower than those from structured surveys. Future studies will analyze the prediction of perioperative complications and cost-effectiveness.

    Trial Registration: ClinicalTrials.gov NCT05743673; https://clinicaltrials.gov/study/NCT05743673

    JMIR Perioper Med 2025;8:e65805

    doi:10.2196/65805

    Keywords

    preoperative evaluation; submaximal cardiopulmonary exercise test; risk stratification; perioperative medicine; anesthesiology 


    Background

    Assessment of functional capacity or exercise tolerance, as measured by self-reported metabolic equivalents (METs), remains a cornerstone of preoperative risk stratification. METs are defined as multiples of the basal metabolic rate (1 MET=3.5 mL kg–1 min–1), and self-reported ability to climb 1 flight of stairs has a general consensus of 4 METs [1]. A threshold of ≤4.6 METs (self-reported inability to climb 2 flights of stairs) has been associated with major adverse cardiac events, all-cause mortality, and increased perioperative complications [2-4]. Despite its importance, published reports have cast doubt on the accuracy of provider-driven and self-reported assessment of functional capacity [5,6]. Thus, reliable and efficient methods to precisely characterize functional capacity continue to be of importance in preoperative risk stratification.

    Cardiopulmonary exercise testing (CPET) precisely characterizes exercise tolerance by analyzing cellular respiration at rest and during exercise challenges. By measuring resting gas exchange followed by maximal exercise to expose pathophysiological impairments, CPET exploits a symptom-limited approach with a 3-minute resting stage, 3 minutes of unloaded cycling, and a 10- to 12-minute ramp stage with increasing resistance until terminated by the participant [7]. Abnormal CPET measures have been frequently associated with perioperative morbidity, with a peak oxygen uptake (VO2) of <15 mL kg–1 min–1 reported as a threshold for elevated cardiopulmonary risk after thoracic and major noncardiac surgery [8-12]. In addition, peak VO2 impairment predicts an increased risk of surgical site infection, postoperative respiratory failure, and critical care readmission [13]. However, CPET has not been widely adopted in preoperative testing, likely due to limited availability, required technical skills, necessity of maximal patient effort, complexity of task, and cost. Yet, conventional preoperative care, usually comprised of subjective or structured, survey-based, clinician estimation of preoperative functional capacity, has demonstrated poor sensitivity in the identification of patients with low functional capacity (≤4 METs), when compared to CPET [13,14].

    In contrast to a conventional symptom-limited approach, submaximal cardiopulmonary exercise testing (smCPET) uses a time-limited approach and predictive analytics to provide estimates of peak cardiopulmonary performance [7]. A maximal exercise effort is not required since it analyzes the VO2 efficiency slope to predict peak cardiopulmonary performance [15-17]. Of note, the VO2 efficiency slope has a strong correlation with peak VO2 (r=0.941), permitting effort-independent prediction of conventional CPET measures [16]. Brief smCPET has demonstrated diagnostic utility in predicting postoperative length of stay, complications, and prognosis in heart failure, pulmonary hypertension, and other conditions [18-23].

    Objectives

    These advantages suggest that time-limited smCPET may be useful for rapid preoperative assessment of exercise tolerance. Therefore, the primary objective was to determine the logistic feasibility of smCPET integration within a high-volume presurgical evaluation clinic. Our measured feasibility end points were (1) operational efficiency, based on the experimental session length being <20 minutes; (2) modified Borg survey of perceived exertion, with a score of ≤7 indicating no more than moderate exertion; (3) high participant satisfaction with smCPET task execution, with a score of >8 (out of 10); and (4) high patient satisfaction with smCPET scheduling, with a score of >8 (of 10). Our secondary objective was to determine if comparable smCPET measures were significantly different from structured survey findings. The secondary end points were a comparison of (1) self-reported subjective METs from a survey versus smCPET equivalents (extrapolated peak METs), (2) Duke Activity Status Index (DASI) [24] estimates versus smCPET equivalents (extrapolated peak METs), and (3) estimated DASI maximal oxygen consumption (estimated peak VO2) versus smCPET equivalents (extrapolated peak VO2). This study hypothesized that brief smCPET would achieve two objectives: first, meet feasibility end points indicating successful implementation, and second, similar to prior published reports regarding provider-driven functional capacity assessments, identify lower peak METs and VO2, when compared to structured surveys.


    Trial Design

    This is an ongoing prospective open-label clinical device study approved by the Yale University Institutional Review Board (IRB#2000033885; ClinicalTrials.gov: #NCT05743673 [25]; principal investigator: ZJC; date of registration: December 5, 2023). This clinical trial was registered prior to participant enrollment.

    Study Population

    Inclusion criteria for study enrollment included age of 60 years and older, a Revised Cardiac Risk Index (RCRI) [26] of ≤2, self-endorsed subjective METs of ≥4 (endorses reliably climbing 2 flights of stairs), and presenting for noncardiac surgery. The aim was to recruit 40 participants for the feThis number was estimated to be adequate to identify any study-related logistic process problems or patient-centered outcome deficiencies and to determine the operational efficiency of this novel system process. The RCRI≤2 criterion was selected given the novelty of smCPET in preoperative evaluation.

    Given that participants were screened prior to surgical procedures, exclusion criteria were adapted to maintain current standard-of-care practices in preoperative evaluation, which includes mandatory subspecialty evaluation of select cardiopulmonary conditions. Participants with recorded severe or critical heart valve disease, active exertional angina, nonambulation, gait abnormalities, end-stage renal disease, severe peripheral vascular disease, and neurological motor deficits were excluded. Additionally, non–English-speaking participants, those under legal guardianship, and participants documented to not have personal health care decision-making capacity were also excluded. After prescreening, a phone call was placed by a study team member, and eligible participants were invited for in-person written informed consent, preoperative evaluation, questionnaire assessment of METs, and a 6-minute smCPET experimental session.

    Testing Environment

    Testing was performed at the presurgical evaluation (PSE) clinic at Yale New Haven Hospital, which is responsible for more than 40,000 preoperative evaluations per year. On a daily basis, the PSE clinic is staffed by an anesthesiologist, 2 resident physicians, 3 certified nurse practitioners, and 6 nursing staff and contains 6 exam rooms.

    Study Apparatus

    The US Food and Drug Administration–approved Shape II is a compact, cardiopulmonary, breath-by-breath, exercise testing system that uses brief submaximal exercise effort (3 minutes) to generate multiple quantitative measures of actual and predicted peak cardiopulmonary performance measurements (Figure 1). Predicted peak exercise values are automatically calculated by the device using oxygen efficiency slope equations [16,17]. Furthermore, the device has been previously validated to conventional CPET measurements [27,28]. The compact design allows all the necessary equipment to be placed on a standard rolling cart and was deployed in a PSE clinic examination room (2.4 × 2.4 m). A stairstep (14-cm height) was used for the graded exercise portion. The graded exercise was performed with a device prompt (“begin exercise”), with auditory prompts at 1-minute intervals to increase step frequency if possible. A metronome is used to provide cadence. The device provides an option for either timed or symptom-limited assessment. The timed session was selected for all participants. The timed device session requires a total of 6 minutes: 2 minutes of seated baseline resting data, 3 minutes of escalating exercise using the stairstep, and 1 minute of seated recovery data to generate a variety of individual measures of cardiac and pulmonary physiological data (Multimedia Appendix 1).

    ‎
    Figure 1. Performance of submaximal cardiopulmonary exercise testing requires (A) 2 minutes of calibration data in the seated position with a disposal mouthpiece connected to the device, (B) 3 minutes of graded exercise using a stair step, and 1 minute of recovery data in the seated position. The submaximal cardiopulmonary device (white and blue box) is visible on the cart, attached to a laptop with calculation software. Coauthor JF gave express permission for the use of his likeness in this simulated participant session.

    Data Collection

    Participants received height, weight, and vital sign measurements (heart rate, blood pressure, and pulse oximetry). Informed written consent was performed, and participants were instructed on smCPET (approximately 5 minutes).

    Session time was measured from the beginning of pretest METs questionnaires until the termination of the smCPET recovery phase. A session time of ≤20 minutes would indicate that 24 high-risk participants could be screened per day per machine, permitting high-volume assessment. Session components included (1) a 7-question subjective METs assessment, (2) a 12-question DASI survey, and (3) a timed smCPET (6 minutes).

    The modified Borg survey of perceived exertion was performed at session termination. After study interventions, a standard preoperative evaluation was completed, and the participant was discharged. A 24-hour postexperiment survey of minor and major complications and patient satisfaction was performed by telephone (Multimedia Appendix 2). With the exception of the patient satisfaction survey, all survey instruments were adapted from prior publications [29-31]. DASI-estimated peak METs and peak VO2 were calculated from individual participants’ DASI scores using the recommended formula.

    Statistical Analysis

    End points were reported as continuous variables, described as mean (SD); ordinal variables, as median (IQR and range); and categorical variables, as number (%). Secondary end points were first analyzed using the Student t test (2-tailed) to compare differences in comparable measurements. Agreement between structured survey findings and smCPET comparable measurements was assessed using 2 approaches. First, a Pearson correlation coefficient was calculated to evaluate the strength and direction of the linear relationship, followed by a Bland-Altman analysis to assess agreement between methods, where differences between paired measurements were plotted against their means. Mean difference (MD) and 95% limits of agreement (LOAs) were calculated. All analyses were carried out on R (version 4.1.1; R Foundation for Statistical Computing). To reduce the introduction of bias, a complete case analysis for missing data was performed, where participants with missing data were excluded from the analysis of the respective end point. Similarly, dropouts were removed from the analysis. A P value of <.05 was accepted for significance.

    Ethical Considerations

    This study was performed in accordance with the principles of the Declaration of Helsinki. Approval was granted by the Yale University Institutional Review Board (IRB#2000033885). Informed consent was obtained from all participants included in the study. All provided data were deidentified prior to analysis to maintain participant privacy. No monetary compensation was provided to the participants. JF has given express written informed consent for the publication of his image in Figure 1.


    Participant Recruitment

    We identified 209 (61.6%) out of 339 potential participants that met eligibility criteria; 6 (1.8%) did not meet the inclusion criteria, 59 (17.4%) failed the prescreening criteria, and 98 (28.9%) declined study participation (Figure 2). Initially, 46 participants were enrolled but 3 (7%) were excluded (operator error: n=2; surgery cancellation: n=1), for a final cohort of 43 participants.

    ‎
    Figure 2. A flow diagram of participant enrollment.

    Baseline Characteristics

    Trial participants had a median age of 68 (IQR 66-73, range: 60-86 years), 20 (47%) of 43 were female, and the mean BMI was 27.5 (SD 6.0) kg/m2. Preoperative RCRI score was a median of 1 (IQR 1-1; range 1-2). Essential hypertension (22/43, 51%), hyperlipidemia (17/43, 39%), and solid tumor (25/43, 58%) were the most common premorbid conditions. A total of 22 (51%) out of 43 participants were former or active smokers. Major abdominal surgeries comprised 27 (63%) out of the 43 surgical procedures (Table 1).

    All participants completed the smCPET session components. The mean peak respiratory exchange ratio was 0.88 (SD 0.12), consistent with submaximal effort (respiratory exchange ratio<1.05). The ventilatory threshold was achieved in 22 (51%) of 43 participants (mean 227.9, SD 21.9 seconds in those that achieved ventilatory threshold).

    Table 1. Baseline demographical data of the study cohort (n=43).
    VariableValues
    Age (years), median (IQR; range)68 (66-73; 60-86)
    Sex, n (%)

    		Male23 (54)

    		Female20 (47)
    BMI (kg/m2), mean (SD)27.5 (6.0)
    Revised Cardiac Risk Index score, median (IQR; range)1 (1-1; 1-2)
    Preoperative comorbidities, n (%)

    		Essential hypertension22 (51)

    		Hyperlipidemia17 (40)

    		Ventricular dysrhythmia1 (2)

    		Congestive heart failure1 (2)

    		Myocardial infarction3 (7)

    		Cerebrovascular disease1 (2)

    		Chronic obstructive pulmonary disease3 (7)

    		Asthma4 (9)

    		Obstructive sleep apnea3 (7)

    		History of prior lung resection1 (2)

    		Diabetes mellitus7 (16)

    		Thyroid disorders7 (16)

    		Solid tumor25 (58)

    		Anemia1 (2)
    Social history, n (%)

    		Smoking


    		Ever22 (51)



    		Active4 (9)



    		Former18 (42)


    		Never21 (49)

    		Marijuana use (active)4 (9)

    		Alcohol use


    		Active24 (56)


    		Former16 (37)


    		Never3 (7)
    Cardiovascular medication use, n (%)

    		Beta-blocker14 (33)

    		Calcium channel antagonist9 (21)

    		ACE/ARBa antagonist16 (37)

    		Diuretic12 (28)
    Surgical categories, n (%)

    		Abdominal major27 (63)

    		Musculoskeletal major4 (9)

    		Neurosurgical major2 (5)

    		Thoracic major5 (12)

    		Other major5 (12)

    aACE/ARB; angiotensin converting enzyme inhibitor/angiotensin receptor blockers.

    Primary End Points

    The mean experimental session time was 16.9 (SD 6.8) minutes. The modified Borg survey score after experimental sessions was mean 5.35 (SD 1.8), corresponding to moderate perceived exertion. All 43 participants were reached for the 24-hour postexperiment survey. The median patient satisfaction (on a scale of 1=worst to 10=best) was 10 (IQR 10-10) for scheduling and 10 (IQR 9-10) for task execution. No major or minor complications associated with study testing were reported by participants. Operational efficiency was achieved within 15 experimental sessions among 4 study team members (3 physicians and 1 undergraduate researcher).

    Secondary End Points

    Average self-reported peak METs were higher when compared to smCPET equivalents (extrapolated peak METs; mean 7.6, SD 2.0 vs mean 6.7, SD 1.8; t42=2.1; P<.001). DASI-estimated peak METs were higher when compared to the smCPET equivalents (extrapolated peak METs; mean 8.8, SD 1.2 vs mean 6.7, SD 1.8; t42=7.2; P<.001). DASI-estimated peak VO2 was higher than the smCPET equivalent (extrapolated peak VO2; mean 30.9, SD 4.3 mL kg–1 min–1 vs mean 23.6, SD 6.5 mL kg–1 min–1; t42=2.1; P<.001). Figure 3 provides a comparison of values obtained from smCPET compared to structured survey–estimated peak METs and DASI-estimated peak METs.

    ‎
    Figure 3. Comparison of elicited METs from 2 structured survey instruments (subjective METs and DASI) compared to predicted peak METs from submaximal cardiopulmonary exercise testing (dotted line represents 4.7 METs). DASI: Duke Activity Status Index; MET: metabolic equivalent.

    To analyze the congruency between the 3 study instruments, correlation and Bland-Altman analyses were performed. DASI-estimated METs showed a moderate positive correlation versus subjective METs (r=0.63; P<.001). Weaker correlations were observed with smCPET-derived extrapolated peak METs versus DASI and subjective METs (r=0.29; P=.06 and r=0.144; P=.36, respectively). DASI versus subjective METs showed an MD of 1.1 (SD 1.49; 95% LOAs –1.82 to 4.02) METs, while DASI versus smCPET-derived extrapolated peak METs showed larger discrepancies with an MD of 2.07 (SD 1.86; 95% LOAs –1.58 to 5.73) METs. The comparison between subjective METs and smCPET-derived extrapolated peak METs showed intermediate systematic bias with the widest LOAs (MD 0.97, SD 2.43 METs; 95% LOAs –3.80 to 5.75). When comparing DASI and smCPET-derived extrapolated peak VO2 values, a positive MD was observed, indicating that DASI estimates were consistently higher (MD 7.23, SD 6.54 mL kg–1 min–1; 95% LOA –8.11 to 21.12) and showed poor agreement (r=0.28; Multimedia Appendix 3).


    Principal Findings

    Integration of brief smCPET in a high-volume PSE clinic was feasible as measured by the primary end points of session time, patient satisfaction with smCPET task execution, perceived exertion, and session scheduling. The operational efficiency of study team members was acceptable within 15 experimental sessions. Finally, smCPET measures of peak METs and VO2 were significantly lower, when compared to comparable structured survey results.

    Mean session time, which included the subjective METs survey, DASI, and 6-minute smCPET session, was 16.9 (SD 6.8) minutes, with progressive improvement over the study time period as operators (n=4) became facile with the study instrument (Multimedia Appendix 4). It is important to note that smCPET comprised 6 minutes of the session time, shorter than reported times with conventional CPET (15-20 min/session) [32]. In high-volume PSE, this may be advantageous, as patients are often seen on short notice for preoperative evaluation. Participants were able to flexibly arrange smCPET around other clinic appointments, decreasing study participants’ time constraints. This likely enhanced our high satisfaction score for scheduling. High patient satisfaction was observed with task execution and perceived exertion during smCPET. The tested device uses a stationary stairstep for graded exercise, which was frequently familiar to participants. The short duration of graded exercise (3 minutes) was not perceived by any participant as maximum exertion by the Borg survey, likely contributing to the high level of patient satisfaction. Second, the Borg score of <7 after smCPET suggests a reasonable probability of success when transitioning its use to patients with more severe comorbidities, or preoperative deconditioning. It is important to note that the ventilatory threshold, or anaerobic threshold, was not measurable in 50% of our cohort, suggesting that the brief graded exercise contributed to the reported exertion level and high participant satisfaction.

    One of the goals of smCPET is to make precise cardiopulmonary evaluation more widely available and patient centered, advantages that are acknowledged by its increasing adoption in the routine assessment of heart failure and pulmonary hypertension. Consistent with large-scale CPET application in cardiovascular clinical trials, smCPET did not result in findings of major or minor complications despite encouraging participants to safely provide their best effort within the timed and graded exercise component [33]. This is reassuring, as early termination of preoperative CPET trials, due to participant fatigue, safety, or other considerations, has been reported to be approximately 11% [13]. However, we purposefully selected functionally independent participants with self-reported ≥4.6 METs, and expansion to patients who are less functionally independent may result in higher smCPET session failure rates. Regardless, the safety of smCPET has been suggested by its routine application to high-risk and frail populations with severe cardiopulmonary disease, suggesting that a wide spectrum of preoperative populations can be safely tested using smCPET [20,22,34].

    The structured survey estimated METs were, on average, significantly higher than their smCPET equivalents. Using the subjective METs structured survey, 8 (19%) of 43 participants reported peak METs within 10% of smCPET extrapolated peak METs, 12 (28%) were underestimated by >10%, and 23 (53%) were overestimated by >10%, when compared to smCPET values. Brief smCPET identified that 8 (19%) out of 43 study participants had ≤4.6 extrapolated peak METs (peak VO2 equivalent: 14 mL kg–1 min–1), corresponding to a METs threshold associated with higher perioperative cardiovascular risk [1,4]. Furthermore, smCPET identified 9 (21%) out of 43 participants with an age-adjusted peak VO2 of less than 20 mL kg–1 min–1, corresponding to poor aerobic capacity, and 2 (5%) with an extrapolated peak VO2 less than 15 mL kg–1 min–1, a measure frequently associated with higher perioperative risk [35]. These findings support prior descriptions of provider-driven and structured survey overestimation bias, highlighting the challenge of obtaining an accurate preoperative functional capacity assessment. Clinicians, when compared to CPET, had a 19.2% sensitivity in identifying low functional capacity (≤4 METs) [13,36]. Other investigations have also observed that preanesthesia evaluation calculation of self-reported METs overestimate functional capacity when compared to CPET assessment [6]. DASI was also found to poorly predict participants with lower peak VO2 [13,24,36]. In a cohort of participants that would not necessarily receive extensive preoperative assessment, given that 100% reported the ability to reliably climb 2 flights of stairs, this may suggest opportunities to identify and preemptively optimize unexpected cardiopulmonary impairments prior to surgical intervention.

    Worldwide, value-based health care has been a significant priority, and conventional preoperative evaluation may increase overall testing costs without improving perioperative outcomes [37-39]. Implementing brief smCPET for individualized preoperative cardiovascular evaluation may improve the precision of preoperative cardiovascular risk assessment and may potentially curb excess preoperative cardiovascular testing commonly associated with older age and patients with higher comorbidities [40-42]. However widespread adoption of this technology in the perioperative space will require (1) further evidence of smCPET predictive validity for perioperative outcomes, (2) characterization of optimal system processes for patient selection, and (3) justification of cost-benefit.

    Study Limitations

    Several study limitations limit generalizability to other populations. Selection bias should be acknowledged given that participants who volunteered for the study are likely to be more health-conscious than usual patients who undergo PSE. A measurement bias may be introduced into the study given that researchers may unconsciously influence participant performance on smCPET or interpret results differently based on unconscious expectations. Similarly, a recall bias is often introduced when using structured, interview-style questionnaires such as those used in our study. Instrument bias may similarly impact smCPET findings; however, this is substantially reduced by routine device calibration.

    Confounding factors are similar, where participants with higher fitness levels would find it easier to adapt to the stairstep exercise challenge. Our inclusion criteria purposely selected participants with lower comorbidities to ensure successful participation rates for this feasibility study. We acknowledge that certain premorbid conditions and chronic medication usage may influence smCPET participants’ performance, but we did not balance this factor in this exploratory study. Although CPET and smCPET predictive performance with cardiovascular perioperative morbidity and mortality has been previously published, our cohort is not yet powered for the assessment of perioperative outcomes with this device [19,23,43,44]. Finally, the finding of no device-related adverse events should be cautiously interpreted given the small sample size and the possibility of rare exercise-induced adverse events.

    Conclusions

    In summary, we observed that smCPET implementation was well accepted into the workflow of a high-volume PSE clinic. Operator efficiency with the smCPET instrument was rapid and achieved relative parity at 15 participant sessions. smCPET, when compared to usual session times for conventional CPET of 15-20 minutes, uses less than half the time (6 minutes), making it attractive for the purposes of precise but time-efficient preoperative evaluation of exercise tolerance. This feasibility analysis has (1) reinforced the operational integrity of our active study protocol assessing smCPET findings with perioperative outcomes and (2) affirmed satisfactory patient-centered outcomes with study procedures. Studies should further expand smCPET predictive validity to postoperative cardiopulmonary complications, assess cost-effectiveness, and develop optimal system processes for patient selection.

    Acknowledgments

    The authors would like to acknowledge the work of Rayna Lewoc, Elizabeth Womack, Elizabeth Cozza, Gwendolyn Burkett, and the staff of the Yale New Haven Hospital’s presurgical evaluation clinic. This study was partially supported by Shape Medical Systems, Inc.

    Data Availability

    The datasets generated or analyzed during this study are available from the corresponding author on reasonable request.

    Authors' Contributions

    Study conception and design were performed by ZJC, PH, and RBS. The first draft of the manuscript was performed by ZJC, JC, JZ, and ABB. Data collection was performed by ZJC, JF, JL, and DA. Statistical analysis was performed by ZJC. Further manuscript editing was performed by all coauthors. All authors read and approved the final manuscript.

    Conflicts of Interest

    ZJC receives partial funding from Shape Medical Systems, Inc related to this work. RBS reports owning stock in Johnson and Johnson unrelated to this work. RBS reports that Yale University has received funding from Merck for a study in which he was involved, unrelated to this work. PH reported receiving research support grants from Edwards Lifesciences and consulting and/or royalty fees from Baudax Bio, Fire1Foundry, Cardiage LLC, and Edwards Lifesciences. All other authors have no competing interests.

    Multimedia Appendix 1

    A detailed description of the submaximal cardiopulmonary exercise testing device and its measures.

    DOCX File , 18 KB
    Multimedia Appendix 2

    Adapted subjective METs survey questions and 24 hour postsession minor and major adverse events survey. MET: metabolic equivalent.

    PDF File (Adobe PDF File), 237 KB
    Multimedia Appendix 3

    Bland-Altman plots for the compared measures: (A) subjective METs versus smCPET-extrapolated peak METs showed a mean difference of 0.97 METs but the widest LOAs; (B) DASI–estimated peak METs versus smCPET-extrapolated peak METs showed a mean difference of 2.07 METs, the largest discrepancy; (C) DASI-estimated peak METs versus subjective METs showed a mean difference of 1.1 METs but narrower LOAs; and (D) DASI-estimated peak VO2 versus smCPET-extrapolated peak VO2 showed that DASI had consistently higher estimates, with a mean difference of 6.5 mL kg–1 min–1. DASI: Duke Activity Status Index; LOA: limit of agreement; mean diff: mean difference; MET: metabolic equivalent; smCPET: submaximal cardiopulmonary exercise testing; VO2: peak oxygen uptake.

    PDF File (Adobe PDF File), 136 KB
    Multimedia Appendix 4

    Operator efficiency as a function of session time (y-axis), defined as performance of two structured functional capacity survey instruments and submaximal cardiopulmonary exercise testing, versus session number (x-axis).

    PNG File , 98 KB
    1. Fleisher LA, Fleischmann KE, Auerbach AD, Barnason SA, Beckman JA, Bozkurt B, et al. 2014 ACC/AHA guideline on perioperative cardiovascular evaluation and management of patients undergoing noncardiac surgery: a report of the American College of Cardiology/American Heart Association Task Force on practice guidelines. J Am Coll Cardiol. 2014;64(22):e77-137. [FREE Full text] [CrossRef] [Medline]
    2. Lurati Buse GAL, Puelacher C, Gualandro DM, Genini AS, Hidvegi R, Bolliger D, et al. Association between self-reported functional capacity and major adverse cardiac events in patients at elevated risk undergoing noncardiac surgery: a prospective diagnostic cohort study. Br J Anaesth. 2021;126(1):102-110. [FREE Full text] [CrossRef] [Medline]
    3. Reilly DF, McNeely MJ, Doerner D, Greenberg DL, Staiger TO, Geist MJ, et al. Self-reported exercise tolerance and the risk of serious perioperative complications. Arch Intern Med. 1999;159(18):2185-2192. [CrossRef] [Medline]
    4. Biccard BM. Relationship between the inability to climb two flights of stairs and outcome after major non-cardiac surgery: implications for the pre-operative assessment of functional capacity. Anaesthesia. 2005;60(6):588-593. [FREE Full text] [CrossRef] [Medline]
    5. Weinstein AS, Sigurdsson MI, Bader AM. Comparison of preoperative assessment of patient's metabolic equivalents (METs) estimated from history versus measured by exercise cardiac stress testing. Anesthesiol Res Pract. 2018;2018:5912726. [FREE Full text] [CrossRef] [Medline]
    6. Nieves-Alonso JM, Méndez Hernández RM, Ramasco Rueda F, Planas Roca A. Estimated metabolic equivalents of task do not correlate with the maximal oxygen consumption of patients undergoing lung resection surgery. Rev Esp Anestesiol Reanim. 2022;69(7):437-441. [CrossRef] [Medline]
    7. Glaab T, Taube C. Practical guide to cardiopulmonary exercise testing in adults. Respir Res. 2022;23(1):9. [FREE Full text] [CrossRef] [Medline]
    8. Loewen GM, Watson D, Kohman L, Herndon JE, Shennib H, Kernstine K, et al. Preoperative exercise Vo2 measurement for lung resection candidates: results of Cancer and Leukemia Group B Protocol 9238. J Thorac Oncol. 2007;2(7):619-625. [FREE Full text] [CrossRef] [Medline]
    9. Benzo R, Kelley GA, Recchi L, Hofman A, Sciurba F. Complications of lung resection and exercise capacity: a meta-analysis. Respir Med. 2007;101(8):1790-1797. [FREE Full text] [CrossRef] [Medline]
    10. Hartley RA, Pichel AC, Grant SW, Hickey GL, Lancaster PS, Wisely NA, et al. Preoperative cardiopulmonary exercise testing and risk of early mortality following abdominal aortic aneurysm repair. Br J Surg. 2012;99(11):1539-1546. [CrossRef] [Medline]
    11. Older P, Hall A, Hader R. Cardiopulmonary exercise testing as a screening test for perioperative management of major surgery in the elderly. Chest. 1999;116(2):355-362. [CrossRef] [Medline]
    12. Argillander TE, Heil TC, Melis RJF, van Duijvendijk P, Klaase JM, van Munster BC. Preoperative physical performance as predictor of postoperative outcomes in patients aged 65 and older scheduled for major abdominal cancer surgery: a systematic review. Eur J Surg Oncol. 2022;48(3):570-581. [FREE Full text] [CrossRef] [Medline]
    13. Wijeysundera DN, Pearse RM, Shulman MA, Abbott TEF, Torres E, Ambosta A, et al. Assessment of functional capacity before major non-cardiac surgery: an international, prospective cohort study. Lancet. 2018;391(10140):2631-2640. [CrossRef] [Medline]
    14. Struthers R, Erasmus P, Holmes K, Warman P, Collingwood A, Sneyd JR. Assessing fitness for surgery: a comparison of questionnaire, incremental shuttle walk, and cardiopulmonary exercise testing in general surgical patients. Br J Anaesth. 2008;101(6):774-780. [FREE Full text] [CrossRef] [Medline]
    15. Ferguson M, Shulman M. Cardiopulmonary exercise testing and other tests of functional capacity. Curr Anesthesiol Rep. 2022;12(1):26-33. [FREE Full text] [CrossRef] [Medline]
    16. Baba R, Nagashima M, Goto M, Nagano Y, Yokota M, Tauchi N, et al. Oxygen uptake efficiency slope: a new index of cardiorespiratory functional reserve derived from the relation between oxygen uptake and minute ventilation during incremental exercise. J Am Coll Cardiol. 1996;28(6):1567-1572. [FREE Full text] [CrossRef] [Medline]
    17. Hollenberg M, Tager IB. Oxygen uptake efficiency slope: an index of exercise performance and cardiopulmonary reserve requiring only submaximal exercise. J Am Coll Cardiol. 2000;36(1):194-201. [FREE Full text] [CrossRef] [Medline]
    18. Snowden CP, Prentis JM, Anderson HL, Roberts DR, Randles D, Renton M, et al. Submaximal cardiopulmonary exercise testing predicts complications and hospital length of stay in patients undergoing major elective surgery. Ann Surg. 2010;251(3):535-541. [CrossRef] [Medline]
    19. Prentis JM, Manas DMD, Trenell MI, Hudson M, Jones DJ, Snowden CP. Submaximal cardiopulmonary exercise testing predicts 90-day survival after liver transplantation. Liver Transpl. 2012;18(2):152-159. [FREE Full text] [CrossRef] [Medline]
    20. Oakland HT, Joseph P, Elassal A, Cullinan M, Heerdt PM, Singh I. Diagnostic utility of sub-maximum cardiopulmonary exercise testing in the ambulatory setting for heart failure with preserved ejection fraction. Pulm Circ. 2020;10(4):2045894020972273. [FREE Full text] [CrossRef] [Medline]
    21. Joseph P, Savarimuthu S, Zhao J, Yan X, Oakland HT, Cullinan M, et al. Noninvasive determinants of pulmonary hypertension in interstitial lung disease. Pulm Circ. 2023;13(1):e12197. [FREE Full text] [CrossRef] [Medline]
    22. Bernstein EJ, Mandl LA, Gordon JK, Spiera RF, Horn EM. Submaximal heart and pulmonary evaluation: a novel noninvasive test to identify pulmonary hypertension in patients with systemic sclerosis. Arthritis Care Res. 2013;65(10):1713-1718. [FREE Full text] [CrossRef] [Medline]
    23. Woods PR, Bailey KR, Wood CM, Johnson BD. Submaximal exercise gas exchange is an important prognostic tool to predict adverse outcomes in heart failure. Eur J Heart Fail. 2011;13(3):303-310. [FREE Full text] [CrossRef] [Medline]
    24. Hlatky MA, Boineau RE, Higginbotham MB, Lee KL, Mark DB, Califf RM, et al. A brief self-administered questionnaire to determine functional capacity (the Duke Activity Status Index). Am J Cardiol. 1989;64(10):651-654. [CrossRef] [Medline]
    25. A feasibility study of the SHAPE™ test of aerobic fitness in older adults presenting for moderate to high-risk surgery. ClinicalTrials.gov. 2023. URL: https://clinicaltrials.gov/study/NCT05743673 [accessed 2025-01-21]
    26. Ford MK, Beattie WS, Wijeysundera DN. Systematic review: prediction of perioperative cardiac complications and mortality by the revised cardiac risk index. Ann Intern Med. 2010;152(1):26-35. [CrossRef] [Medline]
    27. Miller AD, Woods PR, Olson TP, Hulsebus ML, O'Malley KA, MacCarter D, et al. Validation of a simplified, portable cardiopulmonary gas exchange system for submaximal exercise testing. Open Sport Med J. 2010;4(1):34-40. [CrossRef]
    28. Kim CH, Hansen JE, MacCarter DJ, Johnson BD. Algorithm for predicting disease likelihood from a submaximal exercise test. Clin Med Insights Circ Respir Pulm Med. 2017;11:1179548417719248. [FREE Full text] [CrossRef] [Medline]
    29. Borg GA. Psychophysical bases of perceived exertion. Med Sci Sports Exerc. 1982;14(5):377-381. [Medline]
    30. McAuley P, Myers J, Abella J, Froelicher V. Evaluation of a specific activity questionnaire to predict mortality in men referred for exercise testing. Am Heart J. 2006;151(4):890.e1-890897. [CrossRef] [Medline]
    31. Bell EC, Cox NS, Goh N, Glaspole I, Westall GP, Watson A, et al. Oxygen therapy for interstitial lung disease: a systematic review. Eur Respir Rev. 2017;26(143):160080. [FREE Full text] [CrossRef] [Medline]
    32. Albouaini K, Egred M, Alahmar A, Wright DJ. Cardiopulmonary exercise testing and its application. Heart. 2007;93(10):1285-1292. [FREE Full text] [CrossRef] [Medline]
    33. O'Connor CM, Whellan DJ, Lee KL, Keteyian SJ, Cooper LS, Ellis SJ, et al. Efficacy and safety of exercise training in patients with chronic heart failure: HF-ACTION randomized controlled trial. JAMA. 2009;301(14):1439-1450. [FREE Full text] [CrossRef] [Medline]
    34. Woods PR, Frantz RP, Taylor BJ, Olson TP, Johnson BD. The usefulness of submaximal exercise gas exchange to define pulmonary arterial hypertension. J Heart Lung Transplant. 2011;30(10):1133-1142. [FREE Full text] [CrossRef] [Medline]
    35. Kaminsky LA, Arena R, Myers J, Peterman JE, Bonikowske AR, Harber MP, et al. Updated reference standards for cardiorespiratory fitness measured with cardiopulmonary exercise testing: data from the Fitness Registry and the Importance of Exercise National Database (FRIEND). Mayo Clin Proc. 2022;97(2):285-293. [FREE Full text] [CrossRef] [Medline]
    36. Wijeysundera DN, Beattie WS, Hillis GS, Abbott TEF, Shulman MA, Ackland GL, Measurement of Exercise Tolerance before Surgery Study Investigators, et al. Integration of the Duke Activity Status Index into preoperative risk evaluation: a multicentre prospective cohort study. Br J Anaesth. 2020;124(3):261-270. [FREE Full text] [CrossRef] [Medline]
    37. World Economic Forum. Value in Healthcare: Laying the Foundation for Health System Transformation. Geneva, Switzerland. World Economic Forum; 2017.
    38. Mahajan A, Esper SA, Cole DJ, Fleisher LA. Anesthesiologists' role in value-based perioperative care and healthcare transformation. Anesthesiology. 2021;134(4):526-540. [CrossRef] [Medline]
    39. Beckerleg W, Kobewka D, Wijeysundera DN, Sood MM, McIsaac DI. Association of preoperative medical consultation with reduction in adverse postoperative outcomes and use of processes of care among residents of Ontario, Canada. JAMA Intern Med. 2023;183(5):470-478. [FREE Full text] [CrossRef] [Medline]
    40. Ellenbogen MI, Drmanovic A, Segal JB, Kapoor S, Wagner PC. Patient, provider, and system-level factors associated with preoperative cardiac testing: a systematic review. J Hosp Med. 2023;18(11):1021-1033. [CrossRef] [Medline]
    41. Kumar M, Wilkinson K, Li YH, Masih R, Gandhi M, Saadat H, et al. Association of a novel electronic form for preoperative cardiac risk assessment with reduction in cardiac consultations and testing: retrospective cohort study. JMIR Perioper Med. 2024;7:e63076. [FREE Full text] [CrossRef] [Medline]
    42. Ferré F, Laurent R, Furelau P, Doumard E, Ferrier A, Bosch L, et al. Perioperative risk assessment of patients using the MyRISK digital score completed before the preanesthetic consultation: prospective observational study. JMIR Perioper Med. 2023;6:e39044. [FREE Full text] [CrossRef] [Medline]
    43. Bédat B, Koliakos E, Demarchi MS, Perentes J, Licker MJ, Triponez F, et al. Ventilatory efficiency slope is associated with cardiopulmonary complications after thoracoscopic anatomical lung resection. Interact Cardiovasc Thorac Surg. 2022;35(1):ivac039. [FREE Full text] [CrossRef] [Medline]
    44. Kallianos A, Rapti A, Tsimpoukis S, Charpidou A, Dannos I, Kainis E, et al. Cardiopulmonary exercise testing (CPET) as preoperative test before lung resection. In Vivo. 2014;28(6):1013-1020. [FREE Full text] [Medline]

    ‎
    CPET: cardiopulmonary exercise testing
    DASI: Duke Activity Status Index
    LOA: limit of agreement
    MD: mean difference
    MET: metabolic equivalent
    PSE: presurgical evaluation
    RCRI: Revised Cardiac Risk Index
    smCPET: submaximal cardiopulmonary exercise testing
    VO2: oxygen uptake

    Edited by T Aslanidis; submitted 26.08.24; peer-reviewed by DJ Elmer, N Agnew; comments to author 18.12.24; revised version received 21.12.24; accepted 08.01.25; published 17.02.25.

    Copyright

    ©Zyad James Carr, Daniel Agarkov, Judy Li, Jean Charchaflieh, Andres Brenes-Bastos, Jonah Freund, Jill Zafar, Robert B Schonberger, Paul Heerdt. Originally published in JMIR Perioperative Medicine (http://periop.jmir.org), 17.02.2025.

    This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Perioperative Medicine, is properly cited. The complete bibliographic information, a link to the original publication on http://periop.jmir.org, as well as this copyright and license information must be included.