Literature DB >> 34343174

Changes and prognostic value of cardiopulmonary exercise testing parameters in elderly patients undergoing cardiac rehabilitation: The EU-CaRE observational study.

Thimo Marcin1, Prisca Eser1, Eva Prescott2, Leonie F Prins3, Evelien Kolkman3, Wendy Bruins4, Astrid E van der Velde4, Carlos Peña Gil5, Marie-Christine Iliou6, Diego Ardissino7, Uwe Zeymer8, Esther P Meindersma4,9, Arnoud W J Van't Hof4,10,11, Ed P de Kluiver4, Matthias Wilhelm1.   

Abstract

OBJECTIVE: We aimed 1) to test the applicability of the previously suggested prognostic value of CPET to elderly cardiac rehabilitation patients and 2) to explore the underlying mechanism of the greater improvement in exercise capacity (peak oxygen consumption, VO2) after CR in surgical compared to non-surgical cardiac patients.
METHODS: Elderly patients (≥65 years) commencing CR after coronary artery bypass grafting, surgical valve replacement (surgery-group), percutaneous coronary intervention, percutaneous valve replacement or without revascularisation (non-surgery group) were included in the prospective multi-center EU-CaRE study. CPETs were performed at start of CR, end of CR and 1-year-follow-up. Logistic models and receiver operating characteristics were used to determine prognostic values of CPET parameters for major adverse cardiac events (MACE). Linear models were performed for change in peak VO2 (start to follow-up) and parameters accounting for the difference between surgery and non-surgery patients were sought.
RESULTS: 1421 out of 1633 EU-CaRE patients performed a valid CPET at start of CR (age 73±5.4, 81% male). No CPET parameter further improved the receiver operation characteristics significantly beyond the model with only clinical parameters. The higher improvement in peak VO2 (25% vs. 7%) in the surgical group disappeared when adjusted for changes in peak tidal volume and haemoglobin.
CONCLUSION: CPET did not improve the prediction of MACE in elderly CR patients. The higher improvement of exercise capacity in surgery patients was mainly driven by restoration of haemoglobin levels and improvement in respiratory function after sternotomy. TRIAL REGISTRATION: Netherlands Trial Register, Trial NL5166.

Entities:  

Year:  2021        PMID: 34343174      PMCID: PMC8330933          DOI: 10.1371/journal.pone.0255477

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


Introduction

Improving physical fitness is a cornerstone of modern cardiac rehabilitation (CR) [1] and a lack of improvement is associated with worse outcome [2-6]. The American Heart Association has recently emphasized functional physical capacity as a principal endpoint for therapies oriented to older adults with cardiovascular disease [7]. There is evidence that elderly CR patients are able to improve their physical fitness with CR, although the improvement seems to be attenuated with increasing age [8-10]. We previously reported that elderly cardiac patients after surgery have a lower physical fitness than patients with only minimal or no invasive procedure when commencing CR [11] and that they recover to the same level over the time course of one year [12]. A higher improvement in patients after coronary artery bypass graft (CABG) has also been shown in previous studies [13, 14], however, the underlying mechanisms of the recovery process has not been fully investigated to date. Peak oxygen consumption (VO2) measured by cardiopulmonary exercise testing (CPET) is the gold standard for measuring physical fitness. Additionally, CPET provides a tool to characterise exercise limitation and differentiate between respiratory and circulatory patterns [15]. Besides peak VO2, CPET provides additional parameters with prognostic value, namely the oxygen uptake efficiency slope (OUES), ventilation to carbon dioxide (VE/CO2) slope, VO2/workload slope and the ventilatory thresholds (VT1 and VT2) [16]. Combining CPET parameters to a risk score has been shown to improve the prediction of adverse events in heart failure patients and coronary artery disease patients [16-18], but the predictive value for major cardiovascular adverse events (MACE) in elderly CR patients is unclear. The study aims were 1) to determine prognostic values of CPET parameters for MACE after 1-year follow up in elderly patients commencing CR and 2) to identify respiratory and circulatory factors explaining the greater peak VO2 improvement in surgical compared non-surgical patients from start of CR to 1-year follow-up.

Materials and methods

The European Cardiac Rehabilitation in Elderly (EU-CaRE) study was a prospective cohort study performed from 2016 to 2019, with the aim to assesses the (cost-)effectiveness, sustainability and participation levels in current CR programs of eight cardiac rehabilitation centres in seven European countries (Denmark, France, Germany, the Netherlands, Italy, Spain and Switzerland) [19]. The study was approved by the lead ethics committee (Medisch Ethische Toetsingscommissie at Isala, Netherlands) and all relevant medical ethics committees of all participating centres: Landesärztekammer Rheinland Pfalz, Germany (Nr. 837.341.15, (10109)) Comission Nationale de l’Informatique et de Libertés, France (DR-2016-021) Secretario do Comité de Ética da Investigación de Santiago-Lugo, Spain (2015/486) Comitato Ethico per Parma, Italy (34360) Videnskabsetiske Komite C for Region Hovedstaden, Denmark (593) Kantonale Ethikkomission Bern, Switzerland (290/15). The study was registered at trialregister.nl (NTR5306). The participants gave written informed consent before they were included in the study.

Study population

Patients with an age of ≥65 commencing CR after coronary artery bypass grafting, surgical valve replacement (surgery-group), percutaneous coronary intervention, percutaneous valve replacement or without revascularisation (non-surgery group) were consecutively included from January 2016 –January 2018. Patients with a contraindication to CR, mental impairment leading to inability to cooperate, severe impaired ability to exercise, signs of severe cardiac ischemia and/or a positive exercise testing on severe cardiac ischemia, insufficient knowledge of the native language and an implanted cardiac device were excluded.

Data collection and processing

Demographic, socioeconomic and cardiovascular risk factors as well as comorbidities were recorded through hospital records, interviewing, questionnaires and clinical assessments. Clinical assessments included CPET, anthropometric measurements, spirometry and resting heart rate. Haemoglobin was recorded if it was routinely determined in the clinical work up. CPETs were performed on a cycle with an individualized ramp protocol aiming to achieve voluntary exhaustion within 8 to 12 min of ramp duration. CPET parameters were determined at the core lab in Bern by an automated procedure on raw data files using MATLAB (vers. R2017b, MathWorks®, United States), as describe previously [11, 20]. One experienced operator (TM) performed extensive visual quality control using Wassermann’s 9-panel plot and in case of doubtful quality, a second operator (MW) was consulted. Data from the gas exchange measurements were excluded from the analysis in case of suspected mask leakage or equipment failure, as well as if the ramp duration was less than 3 min. Peak values from the CPET were determined as the highest value of a 30 s moving average and included peak VO2, VE, breathing frequency (BF), tidal volume (TV) and oxygen pulse. The following submaximal gas measures were determined: VE/VCO2 slope, VO2/workload slope, the OUES, which represents the ratio of the log VE to VO2. All ventilatory thresholds (VT1 and VT2) were visually determined by one single investigator (TM). Interrater reliability was determined in a random subset of 200 CPETs, in which thresholds were determined by a second experienced investigator (MW) blinded also to patients and centres as well as to thresholds set by the other investigator [20]. The respiratory exchange ratio (RER) as measure for exertion was determined by dividing VCO2 by VO2. Besides gas measures, further exercise parameters such as maximal workload, peak heart rate (HR), HR reserve (difference between peak and resting HR) and HR recovery after 60 s were recorded. Adverse events, which were the primary outcome for this sub-study, were recorded by monthly telephone calls and assessed individually by an independent Clinical Event Committee. Major Adverse Cardiac Event (MACE) were defined as composite endpoint of all-cause and cardiovascular mortality, acute coronary syndrome, aborted sudden cardiac death and cardiovascular intervention/surgery, hospital admission or emergency visits between T0 and T2.

Statistical analyses

All statistics were performed with R (Version 3.5.1, R Core Team, 2017). Mixed logistic regression models (lme4 package) adjusted for age, sex, PCI, time between index event and start of CR as fixed, centre as random intercept and baseline CPET parameters added individually to the model were performed to determine the associations of CPET characteristics with MACE. Existing cut-off values (peak VO2 <18ml/kg/min, OUES <1550, VE/CO2 slope >31.5) were used to compare the risk of MACE between patients with and without impaired CPET characteristics at start of CR [16]. Additionally, optimal specific cut-offs for peak VO2, OUES and VE/CO2 slope were determined for our surgery and non-surgery patients using receiver operator characteristics (ROC) and Youden’s index with 95% confidence intervals (CI) calculated by bootstrapping (Cutpointr package). We compared the area under the curve (AUC) of each model including the CPET parameter in question to the model without any CPET parameters using bootstrap test for two ROC curves (pROC package). CPET characteristics were compared between surgery and non-surgery patients using t-tests for T0 and T2. Improvement in percent and Cohen’s D effect sizes were calculated to compare changes (Δ) between the CPET parameters. Additionally, linear models robust for outliers (package robustbase) were performed to explore whether the difference in Δpeak VO2 between surgery and non-surgery patients may be explained by respiratory (ΔTV, ΔBF) or circulatory/peripheral changes (ΔHR reserve, Δhaemoglobin, ΔVT1). We performed available case analyses. Alpha was set at 0.01 for all analyses instead of 0.05 to adjust somewhat for multiple testing. Residual plots were used to check model assumptions (normality, variance homogeneity and linearity) in the linear robust models and deviance statistics assessed for the logistic models.

Results and discussion

1421 out of 1633 EU-CaRE patients performed a CPET with acceptable test quality before start of CR and 1178 as well at one-year follow-up (Fig 1).
Fig 1

Flow-chart of the patients included for the analyses of MACE and changes in CPET characteristics.

T0, start of CR; T2, 1-year follow-up.

Flow-chart of the patients included for the analyses of MACE and changes in CPET characteristics.

T0, start of CR; T2, 1-year follow-up. Main characteristics of the 1178 patients are presented in Table 1. The characteristics of the comparable full EU-CaRE population has been reported elsewhere [20-23]. From the 1421 patients, 195 (14%) reported a MACE within a mean (SD) follow up time of 340 (112) days, namely 14 (1%) all-cause-mortality, 11 (1%) CV-mortality, 1 (0%) aborted sudden cardiac death, 26 (2%) acute coronary syndrome, 121 (9%) CV hospitalisations, 107 (8%) CV emergency visits and 123 (9%) CV interventions.
Table 1

Baseline characteristics.

VariableAllSurgeryNon-surgery
N = 1178n = 423n = 755
Age [y]72.5 (5.3)72.6 (4.9)72.41 (5.49)
Male Sex957 (81%)372 (88%)581 (77%)
Ejection Fraction [%]
 >55614 (58%)241 (64%)373 (54%)
 45–55291 (27%)98 (26%)193 (28%)
 35–44123 (12%)30 (8%)93 (13.5%)
 <3536 (3%)6 (1.6%)30 (4.3%)
Acute Coronary Syndrome654 (56%)80 (19%)573 (76%)
Procedure
 PCI653 (55%)
 Chronic CAD without revascularization78 (7%)
 Percutaneous valve replacement101 (2%)
 Surgical valve replacement79 (7%)
 CABG344 (29%)
Diabetes mellitus270 (23%)96 (23%)174 (23%)
COPD68 (6%)21 (5%)47 (6%)

Values are meand (SD) and counts (percentage) as appropriate. SD, standard deviation; PCI, percutaneous coronary intervention; CABG, coronary artery bypass grafting; COPD, chronic obstructive pulmonary disease.

Values are meand (SD) and counts (percentage) as appropriate. SD, standard deviation; PCI, percutaneous coronary intervention; CABG, coronary artery bypass grafting; COPD, chronic obstructive pulmonary disease. Higher peak VO2, OUES, VE/CO2-slope at baseline was associated with lower risk for MACE in one-year follow-up, when adjusted for age, sex, PCI and time from index to start of CR (Table 2).
Table 2

Multiple logistic mixed models for major adverse cardiac events.

CPET PredictorsaOR99% CIAUC [%]Specifity [%]bSensitivity [%] bp-valuec
Peak VO2 [per SD]0.73(0.57; 0.93)*64.6149.1075.900.08
VE/VCO2-Slope [per SD]1.23(1.01; 1.52)*63.4961.0463.070.62
OUES [per SD]0.75(0.59; 0.95)*63.8665.5857.440.53
VE/VCO2slope/VO2 [per SD]1.31(1.07; 1.60)*64.9048.7776.970.25
VT1 [per SD]0.90(0.70; 1.19)65.5345.6376.170.58
O2-pulse [per SD]0.75(0.59; 0.96)63.6369.3752.810.65
HR recovery [per SD]0.84(0.66; 1.07)63.3652.7469.400.64
HR reserve [per SD]0.90(0.70; 1.13)63.3968.9055.380.32
CPET RISK SCOREc (reference 0)11.90(0.89; 4.06)64.8957.5367.690.33
22.20(1.02; 4.76)*
33.06(1.42; 6.62)*

a adjusted for age, sex, timelag of CR uptake, PCI as fixed, centre as random factor and the respective CPET parameter.

b Best classification threshold according to Youden-Index.

c bootstrap test for two correlated R curves (model with vs. model without CPET parameter).

d Number of values below cut-off in peak VO2 <18ml/kg/min, OUES <1.55 and VE/CO2 slope >31.5 [16].

CPET, cardiopulmonary exercise testing; OR, Odds Ratio; CI, Confidence Interval; VO2, oxygen consumption; VE, ventilation; OUES, oxygen uptake efficency slope; VCO2, carbon dioxid output; HR, heart rate.

a adjusted for age, sex, timelag of CR uptake, PCI as fixed, centre as random factor and the respective CPET parameter. b Best classification threshold according to Youden-Index. c bootstrap test for two correlated R curves (model with vs. model without CPET parameter). d Number of values below cut-off in peak VO2 <18ml/kg/min, OUES <1.55 and VE/CO2 slope >31.5 [16]. CPET, cardiopulmonary exercise testing; OR, Odds Ratio; CI, Confidence Interval; VO2, oxygen consumption; VE, ventilation; OUES, oxygen uptake efficency slope; VCO2, carbon dioxid output; HR, heart rate. Patients with impaired values in all three variables had the highest risk of MACE. The cut-offs with 95% CI derived from our own study population for the non-surgery and surgery group were as follow: peak VO2, 15.7 [11.8–18.1] ml/kg/min and 12.5 [9.8–15.7]; OUES, 1.75 [1.2–2.1] and 1.35 [0.58–2.26]; VE/CO2-slope, 50.1 [27.4–58.6] and 34.2 [31.5–38.2]. Using our own cut-offs did not significantly improve the prediction of MACE (AUC = 66.99, specificity = 52.86, sensitivity = 73.84) compared to the established cut-offs (Table 2) [16]. Additionally, impaired oxygen pulse and VE/CO2-slope standardised for peak VO2 were associated with an increased risk of MACE. Overall, no single CPET parameter significantly improve the AUC compared to the multivariate logistic model without the respective CPET parameter. From the potentially confounding factors included in the model, only PCI as indication for CR was associated with MACE (Odds ratio ≈ 1.7)x, probably driven by the great proportion of patients with PCI after an acute coronary syndrome. Age, sex or time lag of CR uptake did not significantly predict cardiac events (full output shown in S1 Table). Analysis of deviance did not indicate a lack of fit in any of the performed logistic models. S1 Fig in the supplemental information shows the survival curves for MACE in patients after surgery and non-surgery and patients with the CPET risk score 1–4 based on our own cut-offs, illustrating the distribution of MACE over time. Fig 2 shows the comparison of the CPET characteristics (including resting HR and haemoglobin as additional CPET related parameters) between the surgery and non-surgery patients for T0 and T2 and the changes between the two time-points. At start of CR, most CPET parameters differed significantly between the two groups. In contrast, there were no significant differences at 1-year follow-up, except for peak Watt, absolute peak VO2 [L/min] and peak VE [L/min].
Fig 2

CPET characteristics in surgery and non-surgery patients.

Shown are mean and standard deviation of all CPET and exercise related parameters at start of CR (T0) and 1 year follow-up (T2) as well the changes as standardised effect size (cohen’s D). Cohen’s Ds of 0.2 indicate a weak, 0.4 a medium and 0.8 a large effect size. VO2, oxygen consumption; VE, ventilation; BF, breathing frequency; TV, tidal volume; RER, respiratory exchange ratio; OUES, oxygen uptake efficiency slope; VT, ventilatory threshold; HR, heart rate.

CPET characteristics in surgery and non-surgery patients.

Shown are mean and standard deviation of all CPET and exercise related parameters at start of CR (T0) and 1 year follow-up (T2) as well the changes as standardised effect size (cohen’s D). Cohen’s Ds of 0.2 indicate a weak, 0.4 a medium and 0.8 a large effect size. VO2, oxygen consumption; VE, ventilation; BF, breathing frequency; TV, tidal volume; RER, respiratory exchange ratio; OUES, oxygen uptake efficiency slope; VT, ventilatory threshold; HR, heart rate. Mean changes (T2-T0) of the CPET characteristics are illustrated as Cohen’s D effect size (mean/standard deviation) with 99% confidence interval (CI) in Fig 2. Changes in submaximal parameters, namely the OUES, VE/CO2-slope or the VT1 were only slightly lower than changes in peak exercise variables such as peak VO2 and peak Workload. HR reserve and HR recovery improved most with 41 and 42% in surgery patients and 13 and 8% in non-surgery whereas the effect size was largest in haemoglobin (ΔHb) due to the relatively low standard deviation. Mean improvement in peak VO2 was 0.25 l/min higher in surgery patients compared to non-surgery patients. However, the difference declined when adjusting for ΔHb, ΔVT1 or ΔHR reserve, was more than halved when adjusted for Δpeak TV and disappeared almost completely when adjusted for ΔHb and Δpeak TV variables (Fig 3). Adding change in RER to the model in order to account for the potential confounding effect of submaximal CPETs did not influence the results. Model diagnostic did not indicate violation of model assumptions in any of the performed robust linear model.
Fig 3

Mean differences (99%CI) in Δpeak VO2 [ml/kg/min] between surgery and non-surgery patients when adjusted for respiratory and circulatory/peripheral CPET parameters.

adj., adjusted; VO2, oxygen consumption; TV, tidal volume; Hb, haemoglobin; VT, ventilatory threshold; HRres, heart rate reserve.

Mean differences (99%CI) in Δpeak VO2 [ml/kg/min] between surgery and non-surgery patients when adjusted for respiratory and circulatory/peripheral CPET parameters.

adj., adjusted; VO2, oxygen consumption; TV, tidal volume; Hb, haemoglobin; VT, ventilatory threshold; HRres, heart rate reserve.

Discussion

Patients with an impaired VE/CO2slope, peak VO2 and OUES and oxygen pulse at start of CR were at higher risk of developing a major cardiac adverse event within one year. However, no single CPET parameter significantly improved the prediction of a multivariate logistic model including presence of PCI and age. Nevertheless, the present study provides a detailed insight into the CPET characteristics of 1178 elderly cardiac patients participating in current European CR programmes. Our data suggests that the greater improvement in peak VO2 in surgery compared to non-surgery patients was mainly driven by changes in peak TV and Hb, and based on their lower pre-CR values.

Major adverse cardiac events

In a previous study, combining CPET parameters has been found to add prognostic information, namely patients with an OUES<1550, a VE/VCO2 slope >31.5 and VO2 peak <18.3 ml/kg/min were more likely to develop MACE compared to patients with a normal values or bad performance in only one or two of these variables [16]. Similarly in our study, patients with a value below these cut-offs showed a 3.14 fold risk of MACE in the one-year follow-up compared to patients with values above the cut-offs. However, the patients of the present study were older and most likely weaker than in the study from Coeckelberghs et al [16]. Hence, the cut-offs were probably not appropriate and the predictive value correspondingly underestimated. We therefore calculated cut-off values based on our own elderly cohort, nonetheless, these cut-offs did not significantly improve the discriminative performance compared to the established cut-offs. The 95% CI of our own cut-offs were wide and may therefore not be applicable for other cohorts. Overall, the models were poor in predicting MACE indicated by a very low AUC (<65). Guazzi et al. found an improved prediction of survival in chronic heart failure patients when the VE/CO2-slope was normalised for peak VO2 [24], however, neither this index nor any other CPET parameter significantly improved the discriminative performance for MACE in our elderly CR patients. In our study, the follow-up period may have been too short and the definition of MACE too wide to obtain a valuable prediction of MACE.

Changes in CPET characteristics

Patients after open chest surgery, namely CABG and surgical valve replacement, are generally more deconditioned at start of CR than patients after percutaneous intervention or without revascularization as reported elsewhere [25]. This is also reflected by the overall deteriorated CPET characteristics as shown in the present study (Fig 2). Maximal exercise parameters were significantly reduced in surgery patients despite similar level of exertion (peak RER). Submaximal parameters related to exercise capacity (VT1, VT2) and ventilatory efficiency (OUES, VE/CO2slope) were also reduced. Surgery patients showed overall a larger improvement in the CPET characteristics (medium to large effect size) and differences to non-surgery were mostly abolished at one-year follow-up (Fig 2). Similar findings were reported by Lan et. al who observed lower baseline values and greater improvements of peak VO2 and VT1 in CABG patients compared to PCI patients [26]. There is likely a greater spontaneous recovery in surgery patients than non-surgery patients. This recovery process may be enhanced by CR, however the evidence is weak and the beneficial effect may only account for patients with reduced ventricular function [27]. A randomized trial found similar improvements in peak VO2 in the CR group and the control group [28]. As shown in Fig 2, the higher improvement in peak VO2 in surgery patients could be explained by the larger improvement in peak TV and Hb whereas chronotropic changes (HR reserve) contributed only little to the differences in peak VO2. It has been shown that patients after sternotomy suffer from an impaired lung volume capacity and reduced respiratory muscle strength 6 days postoperative [29], but recover their respiratory muscle function 2 months after surgery [30]. Exercise training has shown to improve ventilatory pattern by improving the rapidness and depth of breathing during exercise in patients with heart disease [31]. Similarly, postoperative inspiratory muscle training in patients undergoing cardiac surgery has been found to improve maximal inspiratory pressure, tidal volume and peak expiratory flow [29]. Inspiratory muscle training may therefore be used in the CR of cardiac surgery patients in order to improve their exercise capacity, but also in elderly fragile non-surgery patients unable to exercise. A recent study assigned a contributing role of autonomic function to the peak VO2 improvements in coronary artery disease patients undergoing CR [32]. They found an improvement in the chronotropic response in the responder group (Δ peak VO2 >2.6ml/kg/min) but no improvements in the non-responder group (Δ peak VO2 ≤ 2.6ml/kg/min). In this study, surgery patients improved their HR reserve much more than non-surgery patients (40% vs. 13%) but the larger improvement in HR reserve did not explain the larger improvement in peak VO2. In contrast to respiratory function, improvement in chronotropic response seemed to have a lower impact on changes in exercise capacity. In accordance to a prior study that found a significant association of ΔHb and improvements in peak VO2 in CABG patients [33], we found that in surgery patients Hb largely recovered (Cohen’s D > 1.5) within one year. Given these results, it is not surprising that ΔHb explained partly the higher improvement in peak VO2 of the surgery patients. Early onset of the anaerobic threshold (reflected by early VT1) occurs in anaemic as well as patients with muscular deconditioning [34], and an improvement in the threshold may reflect circulatory and/or peripheral improvements. As ΔHb explained as much as ΔVT1 of the difference in Δpeak VO2 between these groups, it is likely that exercise capacity in elderly surgery patients improves via restoration of Hb levels and improved respiratory function, and less by circulatory or peripheral improvement.

Strengths

This is a large multi-centre study of a commonly underrepresented elderly cardiac patient population. All CPET data have been automatically analysed in the Core Lab of Bern. Reporting the CPET characteristics as outcomes of CR allows a more comprehensive assessment of exercise performance and enables to discriminate between respiratory and circulatory/peripheral changes.

Limitations

The present study is part of the EU-CaRE study that primarily aimed to compare the Δpeak VO2 between the participating rehabilitation centres. Therefore, the presented analyses are of explorative nature and the associations cannot infer causality. Not all included patients performed a high quality CPET, and in a considerably large proportion (19%) of patients the VT1 could not be determined. However, CPET duration was on average 7.75 min (SD 2.7) at baseline and 9.0 min (SD 2.8) at 1-year follow up and therefore of acceptable test duration. In addition, the effect of peak VO2 on MACE was not altered when the logistic model was adjusted for RER. Further, Hb was not routinely assessed in all centres and ΔHb was therefore missing in 62% of the included patients. However, the ΔVO2peak was comparable between patients with and without missing values. Nevertheless, patients without CPET data tended to have a higher risk for MACE (OR 1.58, p = 0.0432).

Conclusion

CPET parameters did not add to the prediction of major adverse cardiovascular events within one year in this large elderly cohort. Submaximal as well as maximal CPET parameters improved significantly more in patients after open chest surgery compared to patients with no or minimally invasive intervention. The higher improvement of exercise capacity in elderly surgery patients was mainly driven by restoration of haemoglobin levels and improvement in respiratory function after sternotomy. In clinical studies on peak VO2, the potentially large confounding effect of haemoglobin should be considered. Supportive respiratory muscle training may be beneficial in elderly cardiac surgery patients.

Kaplan-Meier curves for major adverse cardiovascular events within 365 days after cardiac rehabilitation entry.

Panel A shows patients after cardiac surgery and no surgery. Panel B shows patients by CPET risk score (reduced peak VO2, VE to VCO2 slope and/or OUES based on the cut-offs derived from this study). VO2, oxygen uptake; VE, ventilation; VCO2, carbon dioxide ouput; OUES, oxygen uptake efficency slope. (DOCX) Click here for additional data file.

Multiple logistic mixed models for major adverse cardiac events.

(DOCX) Click here for additional data file. (PDF) Click here for additional data file. (PDF) Click here for additional data file. 11 Feb 2021 PONE-D-20-37659 Changes and prognostic value of cardiopulmonary exercise testing parameters in elderly patients undergoing cardiac rehabilitation: the EU-CaRE observational study PLOS ONE Dear Dr. Marcin, Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. Please submit your revised manuscript by Mar 22 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. 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Please see our Supporting Information guidelines for more information: http://journals.plos.org/plosone/s/supporting-information. [Note: HTML markup is below. Please do not edit.] Reviewers' comments: Reviewer's Responses to Questions Comments to the Author 1. Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: Yes Reviewer #2: Partly ********** 2. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes Reviewer #2: No ********** 3. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #1: No Reviewer #2: No ********** 4. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: Yes Reviewer #2: Yes ********** 5. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: PONE-D-20-37659: statistical review SUMMARY. This is a longitudinal study that (1) tests whether parameters of cardiopulmonary exercise testing (CPET) are significant predictors of major cardiovascular adverse events (MACE) in elderly patients who commence cardiac rehabilitation and (2) seeks factors that explain the greater peak VO2 improvement in surgical compared non-surgical patients. Overall, the statistical analysis seems appropriate, but the authors should describe additional details about the exploited methods (see major issues 1 and 2 below). Furthermore, model diagnostics should be provided (major issue 3). MAJOR ISSUES 1. The statistical analysis that addresses aim (1) appropriately relies on a mixed effects logistic model. However, Table 2 does not display the parameters of the random effect distribution. I was therefore unable to understand the specific random effect correlation structure that has been chosen for this analysis. The authors should add details about this correlation structure and display the estimated parameters in Table 2. 2. The analysis of the factors that explain VO2 improvements is based on "robust linear models". However, it is not clear what kind of model has been used by the authors. After all, robustness has many aspects! Robustness with respect to outliers? Robustness with respect to variance assumptions? This should be clarified. 3. It seems (last paragraph of the statistical analysis) that traditional model diagnostics have been performed, which is a good idea. However, these results are not displayed nor commented. At least, the results of the diagnostics should be summarized in a supplementary file. Reviewer #2: The study had two objectives: 1) to test the applicability of the previously suggested prognostic value of CPET to elderly cardiac rehabilitation (CR) patients. 2) to explore the underlying mechanism of the greater improvement in exercise capacity (peak oxygen consumption, VO2) after CR in surgical compared to non-surgical cardiac patients. Cardiopulmonary exercise tests (CPET) were performed at the start of CR, end of CR, and 1-year follow-up. Patients were divided into two groups. - Surgery group: after coronary artery bypass grafting, surgical valve replacement. - Non-surgery group: percutaneous coronary intervention, percutaneous valve replacement, or without revascularization. Adverse Cardiac Event (MACE) was defined as a composite endpoint of all-cause and cardiovascular mortality, acute coronary syndrome, aborted sudden cardiac death, cardiovascular intervention/surgery, hospital admission, or emergency visits between T0 and T2. Results No CPET parameter further improved the receiver operation characteristics significantly with the model, including only clinical parameters. The higher improvement in peak VO2 (25% vs. 7%) in the surgical group disappeared when adjusted for peak tidal volume and hemoglobin changes. Conclusion CPET did not improve the prediction of MACE in elderly CR patients. The more significant improvement of exercise capacity in surgery patients was mainly driven by the restoration of hemoglobin levels and improvement in respiratory function after sternotomy. My considerations about the article: It is an interesting paper about cardiovascular rehabilitation (CR) on elderly patients (age 73±5,4, 81% male), with a good number of participants (1,421 for prognostic evaluation and 1,178 for modification on CPET) and multicentric (eight centers in seven countries). 1) Although the CPET aimed a duration of 8-12 minutes, exclusion criteria excluded a protocol duration shorter than 3 minutes. Were CPET with a duration of 3 to 8 minutes included for analyses? These CPETs with short duration (mainly those with less than 5-6 minutes) may have limited the measured variables' utilization and, therefore, the prognostic value. CPET duration (mean and SD) was not shown in Figure 2 or described in the article. 2) Existing cut-off values (peak VO2 <18 ml/kg/min, OUES <1550, VE/CO2 slope >31.5) were used to compare the risk of MACE between patients with and without impaired CPET characteristics at the start of CR. [Ref. 16] [16] Coeckelberghs E, Buys R, Goetschalckx K, Cornelissen VA, Vanhees L. Prognostic value of the oxygen uptake efficiency slope and other exercise variables in patients with coronary artery disease. European journal of preventive cardiology 2016;23(3):237–44. These cut-offs values were determined by a previous study with a younger population (60,7±9,9 years), all patients with CAD, and a higher peak VO2 (19,5±5,6 ml/kg/min), compared to the surgery group of the presented manuscript (15,3±4,0 ml/kg/min). Peak RER were also higher than surgery or non-surgery group (1,20±0,11 versus 1,07±0,13 or 1,08±0,11). It is expected that these cut-off values would not apply to the present study due to the study population's characteristic differences and a higher proportion of submaximal CPET. As shown in Table 2, more than half of the patients were below the cut-off values, especially the peak VO2 values. peak VO2 <18ml/kg/min 75,9% of patients OUES <1550 57,4% of patients VE/CO2 slope >31.5 63,1% of patients This limitation is described in the Discussion: present study were older and most likely weaker than in the study from Coeckelberghs et al.[16] Hence, the cut-offs were probably not appropriate and the predictive value correspondingly underestimated. So, the present article should focus on new cut-off values and not the previous. Prognostic cut-off values are always linked to population characteristics. . The cut-offs with 95% CI derived from the study population for the non-surgery and surgery group were as follow: peak VO2, 15.7 [11.8 – 18.1] ml/kg/min and 12.5 [9.8 – 15.7]; OUES, 1.75 [1.2 – 2.1] and 1.35 [0.58 –2.26]; VE/CO2-slope, 50.1 [27.4 – 58.6] and 34.2 [31.5 – 38.2]. The cut-off values were different from the previous study and between the study groups (surgery or non-surgery).” “The 95% CI of our own cut-offs were wide and may therefore not be applicable for other cohorts.” Agree. A limited submaximal CPET might have influenced it at T0 for some patients. 3) On the abstract, there is information that CPET was performed at the start of CR (T0), end of CR (T1), and 1-year follow-up (T2), but analyses included only T0 and T2 time points. No results were available for T1. Why? Analysis should be performed within the 3 CPET groups (T0, T1, and T2). When treating patients with more severe disease or after procedures, an initial submaximal CPET is expected, so a second CPET (first maximal) is necessary to evaluate these patients better. Carvalho T, Milani M, Ferraz AS, Silveira AD, Herdy AH, Hossri CAC, et al. Brazilian Cardiovascular Rehabilitation Guideline – 2020. Arq Bras Cardiol. 2020;114(5):943-987.https://doi.org/10.36660/abc.20200407. Therefore, logistic regression models should include T1 results, besides or instead of T0 results. 4) Table 1 presents an age average of 72.5 (5.3), while the abstract is 73±5.4. Could you please explain its difference? 5) Table 1 has only the baseline characteristics of the overall group. It should also include group characteristics (and possible differences) among surgery and non-surgery groups. It would be even better if patients’ characteristics were described for each procedure: PCI, No revascularization; Percutaneous valve replacement, surgical valve replacement, and CABG. Possible doubts and bias: - Had the surgery group patients more diabetes or lower ejection fraction? - Had PCI patients more acute coronary syndrome? - Were percutaneous valve replacement patients older? - Had percutaneous valve replacement patients more COPD? Or were patients older? -What exactly is a "No revascularization patient? Stable CAD? Heart failure? Acute coronary syndrome patient not suitable for revascularization? This is not clear in the article. 6) In the article: “ Mixed logistic regression models adjusted for age, sex, PCI, time between index event and the start of CR as fixed, centre as random factor and baseline CPET parameters added individually to the model were performed to determine the associations of CPET characteristics with MACE.” Why was the only PCI included in the regression model? Why were not other procedures included? Why was acute coronary syndrome not included? As described in Table 1: PCI 653 (55%); No revascularization 78 (7%); Percutaneous valve replacement 101 (2%); Surgical valve replacement 79 (7%); CABG 344 (29%). The manuscript states that "PCI as an indication for CR was associated with MACE (Odds ratio ≈ 1.7)”. This is because of PCI, or those patients were mainly the ones with the acute coronary syndrome and, consequently, had a higher probability of short-term MACE? This can be a critical bias of the analysis, and this information needs to be more precise. Possibly there is a requirement to modify and reanalyze the logistic regression models. 7) What was the period between the index event and the CR start? This data was not described in the article. CPET completed at a short period after the surgical intervention has limited clinical use and, even more, limited prognostic utility. There can be a risk of complications (bleeding, infection) related to the procedure and not related to baseline diseases. Esternal pain, exercise discomfort, or even fear to exercise can lead to a submaximal evaluation. The mean peak RER was 1,07 at T0 on the surgery group. So, more than half of the initial CPET were submaximal. Also, as shown by the actual and previous article, lower hemoglobin levels and limited ventilation response can impact peak VO2 at initial CPET (T0). That is why I missed the information of CPET at T1, after the end of CR. A CPET performed 6 to 8 or 12 weeks after the event or procedure could better predict prognosis than an initial limited submaximal CPET in some patients, as previously discussed. 8) What was the duration of CR? There is no information about it. CR duration affected prognosis. Was it evaluated? 9) MACE reported: 195 patients (14%) within a mean (SD) follow-up time of 340 (112) days. 14 (1%) allcause-mortality, 11 (1%) CV-mortality 1 (0%) aborted sudden cardiac death. 26 (2%) acute coronary syndromes 121 (9%) CV hospitalizations 107 (8%) CV emergency visits 123 (9%) CV interventions. I missed a visual graphic of MACE versus time on both study groups. (Kaplan-Meier). Follow-up was short, as written in Discussion. “In our study, the follow-up period may have been too short, and the definition of MACE too wide to obtain a valuable prediction of MACE.” Agree. Maybe longer follow-up can provide better results. Hospitalizations, emergency visits, and interventions could be higher in short-term follow-ups of surgical patients and after acute coronary syndrome. There is a need for more detailed information about MACE reported. 10) “Mean improvement in peak VO2 was 0.25 l/min higher in surgery patients compared to non-surgery patients. However, the difference declined when adjusting for ΔHb, ΔVT1, or ΔHR reserve was more than halved when adjusted for Δpeak TV and disappeared almost completely when adjusted for ΔHb and Δpeak TV variables (Figure 3).” Was the Δpeak RER adjust performed? Peak RER was different between T0 e T2. A submaximal CPET at T0 might have been compared with a maximal CPET at T2 in the same cases. This could have influenced differences in peak VO2. 15) Using our own cut-offs did not significantly improve the prediction of MACE (AUC = 66.99, specificity = 52.86, sensitivity = 73.84) compared to the established cut-offs (Table 4) Table 4 was not available in the document for Review. Conclusions: It is promising but needs to be clearly described and provide more detailed information, as described previously. Maybe it is necessary to change the logistic regression models. A longer follow-up may be necessary. The definition of MACE was too broad and may include short term procedure complications. Focus on new cut-off values may be better than using previous values derived from a different population. ********** 6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy. Reviewer #1: No Reviewer #2: No [NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.] While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step. 1 Jun 2021 We thank the reviewers for their constructive comments and hope we have addressed them accordingly. Please find below our responses to the reviewers’ comments in the uploaded word document "Response to Reviewers". Submitted filename: Response to Reviewers.docx Click here for additional data file. 19 Jul 2021 Changes and prognostic value of cardiopulmonary exercise testing parameters in elderly patients undergoing cardiac rehabilitation: the EU-CaRE observational study PONE-D-20-37659R1 Dear Dr. Marcin, We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements. Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication. An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org. If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org. Kind regards, Gerson Cipriano Jr., PT, MsC, Ph.D. Academic Editor PLOS ONE Additional Editor Comments (optional): Reviewers' comments: Reviewer's Responses to Questions Comments to the Author 1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation. Reviewer #1: All comments have been addressed Reviewer #2: All comments have been addressed ********** 2. Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: (No Response) Reviewer #2: Yes ********** 3. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: (No Response) Reviewer #2: Yes ********** 4. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #1: (No Response) Reviewer #2: Yes ********** 5. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: (No Response) Reviewer #2: Yes ********** 6. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: (No Response) Reviewer #2: I enjoyed the new version of the manuscript and several aspects that were previously commented were addressed, and modifications or justifications were made. The research still has several limitations that reduces external validation, but they were reported in the appropriate section. Congratulations for the research and my final recommendation was approval for publication. ********** 7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy. Reviewer #1: No Reviewer #2: No 26 Jul 2021 PONE-D-20-37659R1 Changes and prognostic value of cardiopulmonary exercise testing parameters in elderly patients undergoing cardiac rehabilitation: the EU-CaRE observational study Dear Dr. Marcin: I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department. If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org. If we can help with anything else, please email us at plosone@plos.org. Thank you for submitting your work to PLOS ONE and supporting open access. Kind regards, PLOS ONE Editorial Office Staff on behalf of Professor Gerson Cipriano Jr. Academic Editor PLOS ONE
  31 in total

Review 1.  Cardiopulmonary exercise testing in the clinical evaluation of patients with heart and lung disease.

Authors:  Ross Arena; Kathy E Sietsema
Journal:  Circulation       Date:  2011-02-15       Impact factor: 29.690

2.  A randomized comparison of exercise training in patients with normal vs reduced ventricular function.

Authors:  U Goebbels; J Myers; G Dziekan; P Muller; M Kuhn; R Ratte; P Dubach
Journal:  Chest       Date:  1998-05       Impact factor: 9.410

3.  Predictors of pre-rehabilitation exercise capacity in elderly European cardiac patients - The EU-CaRE study.

Authors:  Thimo Marcin; Prisca Eser; Eva Prescott; Nicolai Mikkelsen; Leonie F Prins; Evelien K Kolkman; Óscar Lado-Baleato; Carmen Cardaso-Suaréz; Wendy Bruins; Astrid E van der Velde; Carlos Peña Gil; Marie Christine Iliou; Diego Ardissino; Uwe Zeymer; Esther P Meindersma; Arnoud Wj Van't Hof; Ed P de Kluiver; Matthias Wilhelm
Journal:  Eur J Prev Cardiol       Date:  2019-12-18       Impact factor: 7.804

4.  Cardiac rehabilitation of elderly patients in eight rehabilitation units in western Europe: Outcome data from the EU-CaRE multi-centre observational study.

Authors:  Eva Prescott; Prisca Eser; Nicolai Mikkelsen; Annette Holdgaard; Thimo Marcin; Matthias Wilhelm; Carlos Peña Gil; José R González-Juanatey; Feriel Moatemri; Marie Christine Iliou; Steffen Schneider; Eike Schromm; Uwe Zeymer; Esther P Meindersma; Antonio Crocamo; Diego Ardissino; Evelien K Kolkman; Leonie F Prins; Astrid E van der Velde; Arnoud Wj Van't Hof; Ed P de Kluiver
Journal:  Eur J Prev Cardiol       Date:  2020-02-26       Impact factor: 7.804

Review 5.  Pre- and postoperative inspiratory muscle training in patients undergoing cardiac surgery: systematic review and meta-analysis.

Authors:  Mansueto Gomes Neto; Bruno P Martinez; Helena Fc Reis; Vitor O Carvalho
Journal:  Clin Rehabil       Date:  2016-07-10       Impact factor: 3.477

6.  Improvement of cardiorespiratory function after percutaneous transluminal coronary angioplasty or coronary artery bypass grafting.

Authors:  Ching Lan; Ssu-Yuan Chen; Chen-Jung Hsu; Shu-Fen Chiu; Jin-Shin Lai
Journal:  Am J Phys Med Rehabil       Date:  2002-05       Impact factor: 2.159

7.  Effect of physical training on ventilatory patterns during exercise in patients with heart disease.

Authors:  Tetsuya Taguchi; Hitoshi Adachi; Hiroshi Hoshizaki; Shigeru Oshima; Masahiko Kurabayashi
Journal:  J Cardiol       Date:  2014-07-08       Impact factor: 3.159

8.  Cardiovascular fitness and mortality after contemporary cardiac rehabilitation.

Authors:  Billie-Jean Martin; Ross Arena; Mark Haykowsky; Trina Hauer; Leslie D Austford; Merril Knudtson; Sandeep Aggarwal; James A Stone
Journal:  Mayo Clin Proc       Date:  2013-05       Impact factor: 7.616

9.  Determinants of the effects of physical training and of the complications requiring resuscitation during exercise in patients with cardiovascular disease.

Authors:  Luc Vanhees; An Stevens; Dirk Schepers; Johan Defoor; Frank Rademakers; Robert Fagard
Journal:  Eur J Cardiovasc Prev Rehabil       Date:  2004-08

10.  Clinical outcomes after cardiac rehabilitation in elderly patients with and without diabetes mellitus: The EU-CaRE multicenter cohort study.

Authors:  Prisca Eser; Thimo Marcin; Eva Prescott; Leonie F Prins; Evelien Kolkman; Wendy Bruins; Astrid E van der Velde; Carlos Peña-Gil; Marie-Christine Iliou; Diego Ardissino; Uwe Zeymer; Esther P Meindersma; Arnoud W J Van'tHof; Ed P de Kluiver; Markus Laimer; Matthias Wilhelm
Journal:  Cardiovasc Diabetol       Date:  2020-03-19       Impact factor: 9.951

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