Prognostic Value of Cardiopulmonary Exercise Test in Patients with Acute Myocardial Infarction after Percutaneous Coronary Intervention

doi:10.21203/rs.3.rs-4316606/v1

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Prognostic Value of Cardiopulmonary Exercise Test in Patients with Acute Myocardial Infarction after Percutaneous Coronary Intervention

https://doi.org/10.21203/rs.3.rs-4316606/v1

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published 14 Jul, 2024

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Objectives: To determine the independent risk factors of cardiopulmonary exercise test (CPET) parameters related to adverse prognostic events within 5 years in patients undergoing percutaneous coronary intervention (PCI) for acute myocardial infarction (AMI) and establish a prediction model for the occurrence of adverse events within 5 years to provide a reference for cardiac rehabilitation training.

Methods: From August 2015 to December 2021, patients who underwent PCI for AMI and completed CPET within 1–2 weeks after surgery before discharge from the Department of Cardiovascular Medicine of Zhengzhou Central Hospital Affiliated to Zhengzhou University, Henan Provincial Hospital of Traditional Chinese Medicine, and Anyang District Hospital were selected as participants. Univariate and multivariate analyses were used to screen for independent risk factors associated with 5-year adverse events. Feature importance was interpreted using SHapley Additive exPlanations (SHAP), and a logistic regression model was established for prediction. A receiver operating characteristic (ROC) curve was constructed to evaluate the performance of the prediction model. Calibration was assessed by the Hosmer-Lemeshow test and the calibration curve.

Results: In total, 375 patients met the inclusion criteria, including 53 in the event group and 322 in the non-event group, according to whether adverse events occurred during the 5-year follow-up period. Peak oxygen uptake (peakVO₂), carbon dioxide ventilation equivalent slope (VE/VCO₂slop), and peak end-tidal carbon dioxide partial pressure (PETCO₂) were three independent risk factors for re-acute myocardial infarction (re-AMI), heart failure (HF), and even death after PCI for AMI (P < 0.05). The SHAP plots demonstrated that the significant contributors to model performance were related to peakVO₂, VE/VCO₂slop, and PETCO₂. The risk of adverse events was significantly reduced when the peakVO₂ was ≥ 20 ml/kg/min and the VE/VCO₂slop was < 33. The ROC curves of the three models were drawn, including the no-event and event groups, re-AMI group, and HF group, which performed well, with AUC of 0.894, 0.760, and 0.883, respectively. The Hosmer-Lemeshow test showed that the three models were a good fit (P > 0.05). The calibration curve of the three models was close to the ideal diagonal lines.

Conclusions: CPET parameters can predict the prognosis of adverse events within 5 years after PCI in patients with AMI and provide a theoretical basis for cardiac rehabilitation training.

Health sciences/Medical research/Experimental models of disease

Health sciences/Medical research/Outcomes research

AMI

PCI

CPET

prediction model

risk factors

Acute myocardial infarction (AMI) is a serious form of myocardial ischemia and necrosis caused by acute coronary artery stenosis or occlusion. AMI is a major cardiovascular disease that poses a serious threat to human health and is characterized by high prevalence, rapid progression, and high mortality, all of which seriously affect the quality of life of patients and aggravate their medical burden[1,2]. Although percutaneous coronary intervention (PCI) can improve the in-hospital survival rate of patients with myocardial infarction, the incidence of in-stent restenosis remains at 5%, and there are a series of cardiac remodeling evolutions that can lead to re-myocardial infarction, heart failure (HF), or even death. Therefore, managing the adverse outcomes after AMI and way of life has become a concern in cardiac rehabilitation.

Previous studies have shown that cardiopulmonary exercise test (CPET) parameters have an extremely good predictive value for the prognosis of patients with cardiovascular disease[3,4]. Nadruz et al.[5] showed that peakVO₂ and the VE/VCO₂ slop can provide prognostic value for patients with HF; another study has shown that PETCO₂ has a greater prognostic ability than peakVO₂ for adverse events in patients undergoing cardiac resynchronization therapy (CRT)[6]. Moreover, Nakade et al.[7] showed that pulse pressure differences in exercise tests can accurately predict cardiovascular death in patients with HF. In addition, the trajectory of oxygen uptake in an exercise test[8] and the size of the oscillatory ventilation ring[9] can predict the prognosis of patients with HF. The latest research in China used CPET indicators to predict the prognosis of patients with anxiety after PCI for coronary heart disease[10]. However, to date, only a few studies have investigated the rate of re-acute myocardial infarction (re-AMI) and the risk of HF and death in patients with AMI after PCI, which need to be further studied.

Therefore, this study aimed to observe and analyze the predictive ability of CPET parameters for the re-AMI rate, incidence of HF after AMI, and death in patients with AMI after PCI to provide a reference for the postoperative management and rehabilitation of patients with AMI.

1.1 Study Design and Participants

Patients who underwent PCI for AMI and completed CPET within 1–2 weeks after surgery at the Department of Cardiology, Zhengzhou Central Hospital Affiliated to Zhengzhou University, Henan Province Hospital of Traditional Chinese Medicine, and Anyang District Hospital from July 2015 to December 2021 were analyzed. Modeling data were obtained from Zhengzhou Central Hospital Affiliated to Zhengzhou University, Henan Province Hospital of Traditional Chinese Medicine, and Anyang Regional Hospital. The specific inclusion criteria were as follows: (i) meeting the diagnostic criteria of the 2018 AMI general definition (fourth edition) guide and (ii) aged 18–80 years. The exclusion criteria were as follows: (i) ejection fraction < 50% and (ii) AMI combined with a malignant tumor, pulmonary hypertension, and other diseases affecting the patient’s life. The study complies with the Declaration of Helsinki.

Overall, this study included 375 patients who met the inclusion criteria, with an average follow-up duration of 5 years (2, 7). The modeling data were divided into 269 patients in the no-event group and 41 patients in the event group, including seven patients with re-AMI complicated with HF, 13 patients with re-AMI, 18 patients with HF, and three deaths (see Fig. 1), including one due to a car accident and two due to cardiovascular death.

1.2 Ethics Approval

This study was approved by the Zhengzhou Central Hospital Affiliated to Zhengzhou University (approval number: 202462). Informed consent was obtained from all the participants for primary data collection. All research data were anonymous or de-identified to protect the participants’ privacy. We did not provide any remuneration to participants who provided complete and valid responses.

1.3 CPET

All participants in this study were informed of the relevant precautions before CPET and signed an informed consent form. The CPET was performed after a professional cardiovascular physician evaluated the patient’s physical condition. Cardiopulmonary function was assessed using the power bicycle ramp protocol. Before the first test, after the tester was restarted, the gas flow rate sensor and gas analyzer were calibrated to measure oxygen and carbon dioxide. The patient was connected to the test system after wearing the device and began to pedal after resting for 3 min. The baseline metabolic and static cardiopulmonary function data were collected. Subsequently, the patient performed a 3 min no-load warm-up exercise at 55–65 r/min and then entered an incremental exercise. Based on the patient’s age, height, weight, medical history, and exercise habits, different incremental loads (ranging from 10 to 25w) were selected until the test was terminated, according to the scientific statement of the American Heart Association. Finally, the patient continued to exercise for approximately 2–3 min during recovery at 30–40 r/min. The system automatically records heart rate, blood pressure, and heart and lung data at rest, each exercise stage, and peak exercise and evaluates the degree of conscious exertion at the end of the test (Borg score 6–20 points).

The CPET parameters included the peak heart rate (HRmax), peak oxygen uptake (peakVO₂), peak metabolic equivalent (METmax), anaerobic threshold oxygen uptake (AT), peak end-tidal carbon dioxide partial pressure (PETCO₂), heart rate reserve (HRR; the difference between the maximum heart rate and rest heart rate), carbon dioxide ventilation equivalent slope (VE/VCO₂slop), percentage of peakVO₂ to predicted value (%pred), peak ventilation (VE), peak workload, peak respiratory reserve, peak oxygen pulse, oxygen uptake efficiency slope, and Borg score. The key criterion for selecting the anaerobic threshold is the oxygen uptake at the lowest value of the VO₂ ventilation equivalent when the VCO₂ ventilation equivalent is constant, METmax = peakVO₂/3.5, and other data are directly obtained or calculated by the cardiopulmonary system of COSMED in Italy.

1.4 Collection and Follow-Up of Clinical Data

This was a multicenter retrospective study. The patient’s medical information was obtained by consulting the patient’s medical records and follow-up records, and the participants were determined. Medical information included demographic characteristics, medical examination results, smoking and drinking history, history of hypertension and diabetes, and CPET results. To record the outcome, we conducted follow-ups every 6 months after the patient was discharged from the hospital. If death occurred during this period, follow-up was terminated. Follow-up was conducted via telephone or case review. The follow-up was conducted until August 15, 2023. All-cause death is caused by obvious cardiac events, unexplained sudden death, or noncardiac causes.

In the adverse event group of 53 patients (14.13%), the first case of re-AMI occurred 122 days after surgery, and the last case occurred 2250 days after surgery. The first case of HF after AMI occurred 62 days after surgery, and the last case occurred 1460 days after surgery. The first death occurred on day 525, and the last on day 2555. Seven patients developed HF after re-AMI.

1.5 Statistical Analysis

Descriptive statistics were used to describe the baseline data and CPET parameters of the patients, including the mean, standard deviation, number of people, and percentage. The chi-squared test and independent sample t-test were used to compare the variables between the no-event and event groups and the re-AMI and HF groups. IBM SPSS software of IBM was used for all analyses. All statistical tests were two-sided, and a P-value < 0.05 was regarded as statistically significant.

The data were divided into modeling (82%) and validation (18%) data. According to the results of single factor analysis, the factors with P < 0.5 were included in the logistic regression, and the logistic regression equation was established. Furthermore, we used SHapley Additive exPlanations (SHAP) to explain and visualize the effect of predictors based on the risk of adverse outcomes after PCI for AMI.

The verification data was used for external verification, and the receiver operating characteristic (ROC) curve was drawn for detection. It was considered that the area under the curve (AUC) ˃ 0.5 had a predictive value, while the AUC ˃ 0.75 had a relatively high predictive value. An overall flowchart of the analysis is shown in Fig. 2.

2.1 Comparison of Clinical Data Between the No-Event and Event Groups

The results revealed no significant differences in sex, age, body mass index, left ventricular ejection fraction, clinical diagnosis, blood biochemical data, smoking and drinking history, diabetes history, hypertension history, in-hospital medication (e.g., calcium channel blockers, antiplatelet aggregation drugs, β-blockers, and statins), and intervention data between the two groups (P > 0.05) (Table 1).

2.2 Comparison of CPET Parameters Between the No-Event and Event Groups and re-AMI and HF Groups

The HRmax, peakVO₂, METmax, AT, PETCO₂, HRR, and %predicted in the no-event group were significantly higher than those in the event group (P < 0.05). The VE/VCO₂slop in the no-event group was significantly lower than that in the event group (P < 0.01). The peakVO₂, METmax, VE/VCO₂slop, and %predicted were significantly different between the no-event and re-AMI groups (P < 0.05). The peakVO₂, METmax, VE/VCO₂slop, AT, PETCO₂, and HRmax were significantly different between the no-event and HF groups (P < 0.05). However, there were no statistically significant differences in the other parameters, as shown in Table 2.

MET is based on energy consumption in a quiet environment and the sitting position and expresses the common index of relative energy metabolism level in various activities, 1MET = oxygen consumption 3.5 ml/ (kg·min).

2.3 Independent Factors Leading to Adverse Events after PCI for AMI

According to the results of the above two groups of single factor analysis with or without events, the independent variables with P < 0.05 were included in the binary logistic multivariate regression, and the indices included in the binary logistic multivariate regression were selected as the HRmax, peakVO₂, AT, PETCO₂, HRR, VE/VCO₂slop, and %pred. The forward likelihood ratio method was used to screen variables, and the peakVO₂ (P < 0.01, OR: 0.724, 95% CI: 0.568–0.924) and VE/CO₂slop (P < 0.01, OR: 1.169, 95% CI: 1.064–1.284) were identified as independent risk factors for adverse events after PCI for AMI (Table 3).

Based on the results of the univariate analysis of AMI with or without re-AMI after PCI, the independent variables with P < 0.05 were included in the binary logistic multivariate regression analysis. The indicators included in the binary logistic multivariate regression were peakVO₂, VE/VCO₂slop, and %pred. VE/CO₂slop (P < 0.05, OR: 1.140, 95% CI: 1.047–1.242) was an independent risk factor for re-AMI after PCI for AMI (Table 3).

Based on the results of the univariate analysis of AMI with or without HF after PCI, the independent variables with P < 0.05 were included in the binary logistic multivariate regression, and the indicators included in the binary logistic multivariate regression were selected. The HRmax, peakVO₂, AT, PETCO₂, and VE/VCO₂slop were selected for binary logistic multivariate regression. The variables were screened by the forward likelihood ratio method. The peakVO₂ (P < 0.05, OR: 0.705, 95% CI: 0.527–0.944), PETCO₂ (P < 0.05, OR: 1.21, 95% CI: 1.028–1.424), and VE/VCO₂slop (P < 0.01, OR: 1.232, 95% CI: 1.091–1.391) were independent risk factors for HF after PCI in patients with AMI (Table 3).

2.4 Analysis of the Importance of Model Factors

According to the American Medical Association cardiopulmonary function diagnostic criteria, the peakVO₂ was divided into four levels according to ≥ 25, ≥ 20–< 25, ≥ 15–< 20, and < 15 ml/min/kg[11]. The VE/CO₂slop was divided into four levels, comprising < 30.0, 30.0–35.9, 36.0–44.9, and ≥ 45, according to the scientific statement of the European Association for the Prevention and Rehabilitation of Cardiovascular Disease and American Heart Association in 2012[12]. The PETCO₂ was divided into four levels, including ≥ 37, 30–36, 20–29, and < 20 mmHg. The SHAP model factor importance analysis and single-factor partial dependence were performed on the grouped database.

SHAP value analysis shows that peakVO₂ was the most important factor in the entire model, where the higher the peakVO₂ value, the lower the probability of an event (Fig. 3). When peakVO₂ ≥ 20 ml/min/kg (Fig. 4A), the incidence of adverse events was significantly reduced, and the patient prognosis was better. The second most important was the VE/CO₂slop (Fig. 3), where the higher the value of VE/CO₂slop, the higher the probability of the occurrence of events. When the VE/CO₂slop was > 33 (Fig. 4B), the incidence of adverse events increased significantly.

2.5 Establishment of the Logistic Model

The regression coefficients of peakVO₂, VE/VCO₂slop, and PETCO₂ were established according to the results of the logistic multivariate regression analysis of the three groups. r is the probability of predicting the occurrence of adverse events, and its value is (0–1). The greater the r value, the greater the possibility of adverse events. The regression equation was as follows:

With or without event groups: Logit (r) = − 2.415 − 0.17 peakVO₂ + 0.1 VE/VCO₂slop

With or without re-AMI groups: Logit (r) = − 7.765 + 0.157 VE/VCO₂slop

With or without HF groups: Logit (r) = − 9.942–0.231peakVO₂ + 0.182 VE/VCO₂slop + 0.148 PETCO₂

2.6 Evaluation of the Prediction Models

The ROC curve was used to evaluate the discriminant ability of the three prediction models. The occurrence of adverse events, re-infarction, and HF after myocardial infarction were used as state variables. According to the established model, the prognostic indices of patients with coronary heart disease after PCI for AMI in this study (data source: the Henan Provincial Hospital of Traditional Chinese Medicine and Anyang Regional Hospital Chest Pain Center) were calculated, and ROC curves were drawn (Fig. 5).

Prediction model 1: The area under the ROC of the no-event and event groups was 0.894 > 0.75, 95% CI: 0.746–1.000, and the discrimination was very good; Prediction model 2: The area under the ROC of the no-event and re-AMI groups was 0.76 > 0.75, 95% CI: 0.545–0.976, and the discrimination was good; Prediction model 3: The area under the ROC of the no-event and HF groups after AMI was 0.883 > 0.75, 95% CI: 0.690–1.000, and the discrimination was very good. The fitness of the prediction model was evaluated by the Hosmer-Lemeshow goodness-of-fit test. The results showed that the P values of the three models were 0.255, 0.974, and 0.064 > 0.05, respectively, and the calibration curve was close to the ideal diagonal line (Fig. 6). The prediction models had a good fit and good working effect.

A risk prediction model is a statistical model based on a series of characteristics used to estimate the probability of individual risks or clinical outcomes. In clinical practice, a risk prediction model is primarily used to stratify disease severity and predict disease risk or prognosis. Compared to traditional imaging examinations and noninvasive stress imaging, CPET has great advantages in terms of economy and objective accuracy[13]. More importantly, CPET can be used to obtain a series of parameters closely related to cardiopulmonary function and prognosis[14]. Anuradha Lala et al.[3] reported that many CPET parameters have a clear predictive value for death in patients with heart disease and rehospitalization in patients with HF.

In this study, we found that the CPET parameters of peakVO₂, PETCO₂, and VE/VCO₂slop were important factors in predicting the prognosis of patients with AMI after PCI. SHAP was used to analyze the importance of the modeling factors, which confirmed that the peakVO₂, PETCO₂, and VE/VCO₂slop had clear predictive values for the recurrence of AMI, HF, hospitalization, and death of patients after PCI. Moreover, peakVO₂ ≥ 20 ml/min/kg and VE/VCO₂slop < 33 significantly reduced the risk of adverse prognosis. The ROC curves of the three logistic models were drawn using the verification set, and the results showed that they had good differentiation, a high fit, and a good working effect. The results of internal and external verification showed that the model has good stability and clinical practicability and can be used to predict the prognosis of patients with AMI after PCI.

In 2016, the American medical community officially listed cardiorespiratory fitness (CRF) as a “clinical vital sign.” PeakVO₂, as an important indicator for evaluating CRF, has become an important parameter for clinical evaluation of patient status, rehabilitation treatment effect, and prediction of life and health. Matsumura et al.[15] found that the New York Heart Association (NYHA) classification has a good correlation with peakVO₂ and AT, indicating that HF symptoms are closely related to the body’s ability to transport oxygen. Based on the peakVO₂ and AT values, Weber and Janicki[16] more objectively divided the cardiac function of patients with HF into four levels. Most scholars believe that peakVO₂ and AT are more reliable and independent predictors of survival in HF than the NYHA classification or left ventricular ejection fraction[17–19]. Our results also showed that peakVO₂ was an independent factor affecting the prognosis of AMI after PCI, and a peakVO₂ ≥ 20 ml/min/kg significantly reduced the incidence of adverse events and improved the prognosis of patients. Therefore, patients with AMI after PCI should initiate aerobic exercises as soon as possible to improve their functional abilities. Functional capacity can be used as a risk factor for predicting death. For every 1 MET increase in functional capacity (3.5 ml/kg/minVO₂), the risk of death can be reduced by 13–35%[20]. However, improvements in functional ability are mainly achieved by increasing the peakVO₂ value through aerobic exercise.

The VE/VCO₂slop is an indicator of the gas exchange efficiency. Ferreira et al.[21] found that VE/VCO₂slop ≥ 43 is an ideal cut-off value for judging the presence of HF; indeed, compared to the classical peakVO₂-based criteria, it can accurately reclassify 18.3% of HF. Patients with HF with VE/VCO₂slop ≥ 45 and peakVO₂ < 10.0 ml/min/kg have a very poor prognosis in the next 4 years[22]. Studies have shown that aerobic exercise capacity and ventilation efficiency are important reference indicators in evaluating the prognosis of patients with mild obstructive hypertrophic cardiomyopathy[23]. This evidence suggests that the VE/VCO₂slop can predict the prognosis of patients with cardiovascular diseases. This study also found that the VE/VCO₂ slope was an independent factor affecting the prognosis of patients with AMI after PCI, where the higher the value, the higher the risk of adverse events. Several studies have confirmed that the ventilation efficiency of patients with coronary heart disease improves after exercise training[24–30]. Additionally, the VE/VCO₂slop was reduced by 6–23% in patients with chronic HF after the exercise training program. In this regard, Gademan et al.[27] showed improvements in the ventilation efficiency of patients with HF after exercise (VE/VCO₂slop, before training = 35.8 ± 3.9 vs. after training = 31.0 ± 6.1, decreased by 14%). In summary, patients with AMI after PCI should start cardiac rehabilitation exercises as soon as possible after achieving a stable condition to increase peakVO₂ and improve ventilation efficiency.

PETCO₂ is the end-tidal carbon dioxide partial pressure that reflects pulmonary ventilation and pulmonary blood flow. Arena et al. showed that ventilation efficiency (especially VE/VCO₂slop) and PETCO₂ peak during exercise are related to pulmonary hypertension caused by late diastolic dysfunction of left ventricular hypertrophy and that PETCO₂ is an important predictor of cardiac-related events in patients with HF[31]. A previous study suggested that PETCO₂AT is superior to peakVO₂ in the prognosis of adverse events in patients undergoing CRT[6]. Moreover, Matsumoto et al.[32] found that in a group of patients with HF, PETCO₂ at the ventilation threshold was significantly correlated with cardiac output during peak exercise. The sensitivity and specificity of PETCO₂ (< 38.5 mmHg) in predicting low cardiac output during exercise (cardiac index < 5.11 L/min/m² at peak exercise) were 76.5% and 75.0%, respectively. Tanabe et al.[33] also reported a significant correlation between PETCO₂ and cardiac index during peak exercise in patients with HF. The results showed that PETCO₂ can better reflect the cardiac output response during exercise and has a diagnostic value. Thus, this study found that PETCO₂ is an independent predictor of HF during follow-up in patients with AMI after PCI and reported that the risk of HF is 1.21 times higher for every unit increase in PETCO₂. In summary, PETCO₂ is not only a prognostic predictor of patients with HF but also a predictor of HF after AMI.

This study has some limitations that warrant discussion. First, this is a retrospective cohort study, and some patients were not included in the analysis because of data loss. Second, during the CPET, some patients did not reach the maximum exercise level owing to the symptom-restricted exercise strategy adopted by individual patients; thus, the HRmax could not be obtained. Lastly, the study participants included patients who underwent CPET in tertiary hospitals, which may not represent the entire AMI population, limiting the generalizability of our results at the grassroots level.

Our results revealed that CPET can well predict the prognosis of adverse events after PCI in patients with AMI and that the risk of adverse events was significantly reduced when peakVO₂ ≥ 20 ml/min/kg and VE/VCO₂slop < 33. Therefore, patients with AMI should start aerobic rehabilitation training as soon as possible to promote cardiac function recovery, improve oxygen uptake and ventilation efficiency, reduce the incidence of re-AMI and HF, and improve prognosis.

Table 1

Comparison of clinical data (x ± s)
Item	No-event group (n = 269)	Event group (n = 41)
Age (years)	56.53 ± 10.94	59.27 ± 12.79
Sexuality	M 230 (85%) F 40 (15%)	M 36 (88%) F 5 (12%)
BMI (kg/m²)	25.47 ± 3.57	25.95 ± 3.35
LVEF (%)	60.1 ± 4.94	58.56 ± 5.02
Clinical diagnosis
STEMI	135 (50%)	28 (68%)
NSTEMI	134 (50%)	13 (32%)
Laboratory examination
Hemoglobin (g/L)	137.75 ± 17.36	137.68 ± 15.35
BNP (pg/ml)	100.87 ± 135.14	134.06 ± 146.25
Total cholesterol (mmol/L)	4.12 ± 1.10	3.78 ± 1.20
Triglyceride (mmol/L)	1.85 ± 2.20	1.74 ± 0.94
Low-density lipoprotein (mmol/L)	2.40 ± 1.50	2.16 ± 0.90
High-density lipoprotein (mmol/L)	1.03 ± 0.33	1.04 ± 0.24
Serum creatinine (µmol/L)	66.79 ± 27.26	65.71 ± 23.06
Troponin (µg/L)	2.66 ± 6.90	1.09 ± 2.06
Creatine kinase-MB (U/L)	1.43 ± 2.88	1.25 ± 1.12
Smoking history
Never or have quit smoking	159 (59.1%)	21 (51.2%)
Smoking	110 (40.9%)	20 (48.8%)
Drinking history
Never or have quit drinking	188 (70%)	25 (61%)
Drinking	81 (30%)	16 (39%)
Case history
Diabetes	60 (22%)	10 (24%)
Hypertension	128 (47.6%)	25 (61%)
Medication
Antiplatelet aggregation drugs	269 (100%)	41 (100%)
Calcium channel blockers	128 (47.6%)	27 (65.9%)
Atorvastatin	255 (94.8%)	41 (100%)
β-blockers	229 (85.1%)	36 (87.8%)
Coronary artery disease
Triple vessel disease ≥ 50%	66 (24.5%)	12 (29.3%)
LAD ≥ 50%	189 (70.3%)	35 (85.4%)
LCX ≥ 50%	128 (47.6%)	15 (36.6%)
RCA ≥ 50%	134 (49.8%)	20 (48.8%)
LMCA ≥ 50%	8 (3.0%)	3 (7.3%)
Number of brackets	1.27 ± 0.56	1.24 ± 0.74

Count data in the table represent [number of cases (%)]. Compared to the no-event group. *P < 0.05, **P < 0.01. BMI: body mass index, LVEF: left ventricular ejection fraction, STEMI: acute ST-segment elevation myocardial infarction, NSTEMI: non-acute ST-segment elevation myocardial infarction, BNP: brain natriuretic peptide, LAD: left anterior descending branch, LCX: left circumflex branch, RCA: right coronary artery, LMCA: left main coronary artery.

Table 2

Comparison of CPET parameters (x ± s)
Item	No-event group (n = 269)		Event group (n = 41)	re-AMI group (n = 20)	HF group (n = 25)
HRmax (time/min)	109.51 ± 18.00		102.51 ± 15.29*	102.35 ± 11.96	101.76 ± 16.48*
Peak workload (W)	97.39 ± 30.38		89.12 ± 30.28	93.6 ± 20.80	88.20 ± 30.79
METmax	5.04 ± 1.05		4.22 ± 0.86**	4.42 ± 0.73*	4.13 ± 0.85**
PeakVO₂ (ml/kg/min)	17.64 ± 3.67		14.73 ± 2.99**	15.37 ± 2.48**	14.44 ± 2.98**
AT (ml/kg/min)	14.73 ± 3.29	12.84 ± 2.54**		13.29 ± 2.49	12.67 ± 2.64**
VE (L/min)	44.28 ± 13.29		41.87 ± 11.95	44.85 ± 10.48	41.64 ± 13.08
Peak oxygen pulse (ml/beat)	11.40 ± 2.86		10.94 ± 2.80	11.90 ± 2.27	10.60 ± 2.86
VE/VCO₂slop	30.43 ± 4.99		36.10 ± 8.94**	35.78 ± 8.23**	37.83 ± 9.34**
PETCO₂ (mmHg)	35.77 ± 4.62		33.78 ± 5.39*	34.10 ± 4.23	33.48 ± 5.55**
BR (%)	62.51 ± 9.34		64.07 ± 9.20	64.93 ± 7.48	62.58 ± 10.80
OUES (ml/min/L/min)	1858.71 ± 449.32		1765.73 ± 512.70	1875.50 ± 409.60	1709.32 ± 513.46
Borg	14.86 ± 0.99		15.12 ± 0.93	15.00 ± 1.03	15.04 ± 0.98
HRR (time/min)	38.68 ± 14.76		32.85 ± 13.52*	32.60 ± 10.95	33.36 ± 13.28
%pred	61.71 ± 13.27		55.95 ± 15.53*	53.00 ± 12.81**	58.20 ± 17.84

Compared to the no-event group: *P < 0.05, **P < 0.01.

HRmax: peak heart rate, HRrest: rest heart rate, peakVO₂: peak oxygen uptake, METmax: peak metabolic equivalent, AT: anaerobic threshold oxygen uptake, PETCO₂: peak end-tidal carbon dioxide partial pressure, VE/VCO₂slop: carbon dioxide ventilation equivalent slope, %pred: percentage of peak oxygen uptake to predicted value, VE: peak ventilation, BR: peak respiratory reserve, OUES: oxygen uptake efficiency slope, HRR: HRmax-HRrest.

Table 3

Logistic multivariate regression of the three groups
Group	Item	OR	95% CI:		P
Group	Item	OR	Lower limit	Upper limit	P
No-event group and event group	PeakVO₂	0.724	0.568	0.924	0.009
	VE/CO₂slop	1.169	1.064	1.284	0.001
	Constant	0.000			0.054
No-event group and re-AMI group	VE/CO₂slop	1.140	1.047	1.242	0.030
No-event group and re-AMI group	Constant	0.013			0.073
No-event group and HF group	PeakVO₂	0.705	0.527	0.944	0.019
	VE/CO₂slop	1.232	1.091	1.391	0.001
	PETCO₂	1.210	1.028	1.424	0.022
	Constant	0.000			0.016

peakVO₂: peak oxygen uptake, PETCO₂: peak end-tidal carbon dioxide partial pressure, VE/VCO₂slop: carbon dioxide ventilation equivalent slope.

Funding:

The study was supported by: The project of Henan Medical Science and Technology Project(2018010047, LHGJ20220865).

Acknowledgments

Thanks to all participants for their contributions to this study, and we appreciate the reviewers’ valuable comments.

Conflict of Interest

The authors declare no conflict of interest related to this work. This study is retrospective and has passed ethical review

Data availability statement

The data supporting this comprehensive analysis comes from Department of Cardiovascular Medicine of Zhengzhou Central Hospital Affiliated to Zhengzhou University, Henan Provincial Hospital of Traditional Chinese Medicine, and Anyang District Hospital.Please contact the correspondding author DW.W if needed.

Author Contributions

LM.L, ZY.L and DW.W are responsible for the research direction and specific content design. YC.G and YF.W consult and search the literature. BC.F, ZY.L, DW.W, LM.L, YC.H,HM.R participated in the formulation of inclusion criteria and exclusion criteria. Data extraction for this study was undertaken by two independent authors (ZY.L and YC.G). BC.F and ZY.L contributed to statistical analysis. ZY.L and JC.B, YC.H, DW.W, and HM.R contributed to the quality assessment. ZY.L participated in data analysis, discussion and drafting of the manuscript. LM.L , DW.W and BC.F participated in the interpretation of data and critical revision of the manuscript. All authors had read and approved the manuscript before submission.

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No competing interests reported.

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Prognostic Value of Cardiopulmonary Exercise Test in Patients with Acute Myocardial Infarction after Percutaneous Coronary Intervention

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Journal Publication

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Abstract

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Introduction

1. Methods

1.2 Ethics Approval

1.3 CPET

1.4 Collection and Follow-Up of Clinical Data

1.5 Statistical Analysis

2. Results

2.1 Comparison of Clinical Data Between the No-Event and Event Groups

2.3 Independent Factors Leading to Adverse Events after PCI for AMI

2.4 Analysis of the Importance of Model Factors

2.5 Establishment of the Logistic Model

2.6 Evaluation of the Prediction Models

3. Discussion

Declarations

References

Additional Declarations

Status:

Journal Publication

Version 1