Are heart rate dynamics in the transition from rest to submaximal exercise related to maximal cardiorespiratory responses in COPD?

Abnormal heart rate responses to exercise in non-severe COPD: relationship with pulmonary vascular volume and ventilatory efficiency

BACKGROUND

Despite being a prognostic predictor, cardiac autonomic dysfunction (AD) has not been well investigated in chronic obstructive pulmonary disease (COPD). We aimed to characterise computed tomography (CT), spirometry, and cardiopulmonary exercise test (CPET) features of COPD patients with cardiac AD and the association of AD with CT-derived vascular and CPET-derived ventilatory efficiency metrics.

METHODS

This observational cohort study included stable, non-severe COPD patients. They underwent clinical evaluation, spirometry, CPET, and CT. Cardiac AD was determined based on abnormal heart rate responses to exercise, including chronotropic incompetence (CI) or delayed heart rate recovery (HRR) during CPET.

RESULTS

We included 49 patients with FEV1 of 1.2-5.0 L (51.1-129.7%), 24 (49%) had CI, and 15 (31%) had delayed HRR. According to multivariate analyses, CI was independently related to reduced vascular volume (VV; VV ≤ median; OR [95% CI], 7.26 [1.56-33.91]) and low ventilatory efficiency (nadir VE/VCO2 ≥ median; OR [95% CI], 10.67 [2.23-51.05]). Similar results were observed for delayed HRR (VV ≤ median; OR [95% CI], 11.46 [2.03-64.89], nadir VE/VCO2 ≥ median; OR [95% CI], 6.36 [1.18-34.42]).

CONCLUSIONS

Cardiac AD is associated with impaired pulmonary vascular volume and ventilatory efficiency. This suggests that lung blood perfusion abnormalities may occur in these patients. Further confirmation is required in a large population-based cohort.

Predicting Adverse Events During Six-Minute Walk Test Using Continuous Physiological Signals

Background and Objective: The 6-min walk test (6MWT) is a common functional assessment test, but adverse events during the test can be potentially dangerous and can lead to serious consequences and low quality of life. This study aimed to predict the occurrence of adverse events during 6MWT, using continuous physiological parameters combined with demographic variables.

Methods: 578 patients with respiratory disease who had performed standardized 6MWT with wearable devices from three hospitals were included in this study. Adverse events occurred in 73 patients (12.6%). ECG, respiratory signal, tri-axial acceleration signals, oxygen saturation, demographic variables and scales assessment were obtained. Feature extraction and selection of physiological signals were performed during 2-min resting and 1-min movement phases. 5-fold cross-validation was used to assess the machine learning models. The predictive ability of different models and scales was compared.

Results: Of the 16 features selected by the recursive feature elimination method, those related to blood oxygen were the most important and those related to heart rate were the most numerous. Light Gradient Boosting Machine (LightGBM) had the highest AUC of 0.874 ± 0.063 and the AUC of Logistic Regression was AUC of 0.869 ± 0.067. The mMRC (Modified Medical Research Council) scale and Borg scale had the lowest performance, with an AUC of 0.733 and 0.656 respectively.

Conclusion: It is feasible to predict the occurrence of adverse event during 6MWT using continuous physiological parameters combined with demographic variables. Wearable sensors/systems can be used for continuous physiological monitoring and provide additional tools for patient safety during 6MWT.

Brain-heart autonomic axis across different clinical status and severity of chronic obstructive pulmonary disease

PURPOSE

Impairment of cardiac autonomic integrity is common in chronic obstructive pulmonary disease (COPD) patients. The influence of the interaction between clinical and severity status on brain-heart autonomic axis (BHAA) is not well known. We aimed to investigate the BHAA function across different clinical status and severity of COPD.

METHODS

Cross-sectional study involving 77 COPD patients allocated into four groups according to clinical status [acute exacerbation (GAE) or stable (GST)] and severity [less (-) or more (+)]: 1) GAE-, n = 13; 2) GAE+, n = 20; 3) GST-, n = 23; and 4) GST+, n = 21. Heart rate variability (HRV) at rest and heart rate recovery (HRR) after 6-min walk test were markers of BHAA. Mean R-R, STDRR, RMSSD, RRtri, HF, LF, SD1, SD2, ApEn and SampEn were the HRV indexes and, HRR was obtained as: HR at 1st min of recovery minus peak HR.

RESULTS

A main effect of clinical status (p < 0.001) was found to vagal modulation in GAE-vs. GST- (RMSSD: 25.0 ± 14.8 vs. 12.6 ± 5.5 ms; SD1: 18.0 ± 10.6 vs. 8.9 ± 3.9 ms) and to GAE + vs. GST+ (RMSSD: 26.4 ± 15.2 vs. 15.4 ± 6.3 ms; SD1: 18.3 ± 11.2 vs. 10.9 ± 4.5 ms). An effect of clinical status (p = 0.032) and severity (p = 0.030) were found to HF (vagal) in GAE + compared to GAE- and GST+ (264.7 ± 239.0 vs. 134.7 ± 169.7 and 135.8 ± 139.7 ms²). Lower HRR was found in GAE-compared to GST- (8.0 ± 2.4 vs. 19.6 ± 2.4 bpm), p = 0.002.

CONCLUSION

In COPD patients, clinical status (AECOPD or stable) was more dominant than the severity on BHAA function. A more pronounced parasympathetic modulation was found in AECOPD patients with a lower HRR to exercise.