Flow-mediated skin fluorescence: A novel method for the estimation of sleep apnea risk in healthy persons and cardiac patients

BACKGROUND

A pilot study revealed a relationship between the results of flow mediated skin fluorescence (FMSF) and of ECG-Holter-based estimated apnea/hypopnea index (eAHI) in asymptomatic individuals. The aim of this study was to test whether the results of FMSF show a relationship with the eAHI in patients with coronary artery disease or aortic stenosis.

METHODS

Twenty-one patients (12 coronary disease, 9 aortic stenosis) and 37 healthy volunteers were included. FMSF was assessed before, during and after the pressure occlusion of the brachial artery, using a prototype device allowing the quantification of skin fluorescence. The values of FMSF expressed as baseline (BASE), maximum (MAX), and minimum (MIN) were analyzed. The percentages of ischemic response (IR) and hyperemic response (HR) were calculated. The eAHI was assessed from night ECG-Holter recordings. Differences between the groups and the relationships between the parameters were analyzed statistically.

RESULTS

Mean ± standard deviation of BASE, MAX, MIN and IR were not significantly different in both groups (p > 0.05). HR was significantly lower in cardiac patients (14.7 ± 7.5 vs. 11.8 ± 5.1; p = 0.048), whose eAHI was significantly higher (11.0 ± 7.4 vs. 36.3 ± 16.5; p < 0.01). Negative correlation for MAX and eAHI was found in volunteers and patients: r = -0.38, p = 0.02 and r = -0.47, p = 0.03, respectively. In volunteers, HR had a negative correlation with eAHI: r = -0.34, p = 0.04.

CONCLUSIONS

This pioneer study confirms that FMSF can be used to detect the negative correlation between MAX fluorescence and eAHI not only among healthy volunteers, but also among cardiac patients with coronary artery disease or aortic stenosis.

Detection of sleep-disordered breathing with ambulatory Holter monitoring

PURPOSE

Obstructive sleep apnea (OSA) syndrome is a common condition that can impact clinical outcomes among patients with cardiovascular disease. Screening all subjects with heart disease via polysomnography (PSG) is costly and resource-limited. We sought to compare a Holter monitor-based algorithm to detect OSA to in-laboratory polysomnography (PSG).

METHODS

Prospective cohort study of patients undergoing in-laboratory attended PSG for the evaluation of OSA. A standard 12-lead Holter monitor was attached to patients at the initiation of PSG. Holter-derived respiratory disturbance index (HDRDI) was extracted from the respiratory myogram, based on detecting skeletal muscle "noise" detected on the baseline. Apneic and hypopneic episodes were identified by comparing sudden changes in the myogram to abrupt increases in heart rate. The HDRDI was compared with the PSG-derived apnea-hypopnea index (PDAHI).

RESULTS

Thirty patients underwent simultaneous Holter monitoring and overnight diagnostic PSG. An ROC curve for peak HDRDI was 0.79 (95% CI 0.61, 0.97) for OSA, with sensitivity of 94.4% and specificity of 54.5%. A cutoff value of HDRDI < 10 appeared to identify those individuals without clinically significant sleep-disordered breathing.

CONCLUSION

Holter-derived respiration detected OSA comparable to PSG. Further study is warranted to determine its utility for screening and diagnosing OSA in appropriately selected patients.

Assessment of mean respiratory rate from ECG recordings for risk stratification after myocardial infarction

BACKGROUND

We recently reported that nocturnal respiratory rate (NRR) predicts non-sudden cardiac death in survivors of myocardial infarction (MI). Here, we present the details of the technique deriving NRR from ECG recordings.

METHODS

Continuous ECG and respiratory chest excursions were simultaneously recorded in 941 MI survivors who were followed-up for 5-years. Mean respiratory rate was derived from the ECG based on RR intervals, QRS amplitudes, and QRS vectors and compared to chest belt measurements. NRR was calculated from Holter-ECGs accordingly using the same ECG processing.

RESULTS

Directly-measured and ECG-derived respiratory rates were in good agreement. Areas under the ROC curve for 10-min-ECG- and Holter-derived respiratory rate were well in the confidence intervals of that of the chest belt measurement. The optimum dichotomy of NRR for the prediction of mortality was ≥18.6 breaths per minute.

CONCLUSIONS

The mean respiratory rate can be precisely derived from continuous ECGs.