New Tool Effectively Monitors Sleep Quality in Parkinson’s Patients, Researchers Say

A new tool called cardiopulmonary coupling could be used to effectively evaluate sleep quality in Parkinson’s disease patients, who often experience sleep disorders, according to a study.

The study, “Assessment of sleep quality using cardiopulmonary coupling analysis in patients with Parkinson’s disease,” was published in Brain and Behavior.

Disturbances in sleep — such as insomnia, sleep apnea, excessive daytime sleepiness, and rapid eye movement sleep behavior disorder — affect between 40 percent and 98 percent of Parkinson’s patients.

The most common strategy to assess sleep disorders is by polysomnography, also called a sleep study — a test that records brain waves, levels of oxygen in the blood, heart rate, and breathing, as well as eye and leg movements.

But this type of approach has some limitations that can interfere with getting an accurate estimate of sleep staging and quality.

Researchers are now testing cardiopulmonary coupling (CPC) as a new method of evaluating sleep quality. The tool works by analyzing the connection between heart rate variability and respiratory volume variability.

CPC calculates the percentage of stable sleep, presented as high-frequency coupling, or unstable sleep, presented as very low-frequency coupling. Wake and rapid eye movement sleep exhibit very low-frequency coupling.

The study included 42 Parkinson’s disease patients — 18 men and 24 women — treated with levodopa or dopamine agonists, and 30 healthy individuals used as controls.

Researchers used CPC as well as the Pittsburgh Sleep Quality Index (PSQI) to assess and compare sleep quality. The PSQI is a self-reported questionnaire based on seven individual scores — subjective sleep quality, sleep latency, duration, sleep efficiency, sleep disturbances, use of sleep medications, and daytime dysfunction. The overall score ranges from zero to 21, with higher scores corresponding to increasingly impaired sleep.

Researchers defined subjective sleep quality based on the PSQI score, where a score of less than 10 was considered “good” sleep and score of 10 or higher was considered “poor” sleep.

PSQI scores were higher in Parkinson’s patients — a median score of 9 — than in the control group, who registered a median score of 6.27.

CPC analysis showed that stable sleep and sleep efficiency were significantly lower in Parkinson’s patients than in healthy controls — 31.6% vs. 36.37%, respectively. In contrast, unstable sleep and sleep latency were higher among this population — 37.62% vs 32.37%, respectively.

Parkinson’s patients had an overall sleep efficiency of 72.81%, compared with 76.06% in healthy individuals. Wake and rapid eye movement sleep was also significantly higher in Parkinson’s patients than in healthy controls.

The team also measured the frequency of nocturia — the excessive need to wake and urinate during the night — which, along with the severity of Parkinson’s disease, was found to affect sleep quality in these patients.

“Our study reflects a poor overall sleep quality in patients with PD [Parkinson’s disease] based on both, CPC analysis and PSQI scores,” the researchers concluded. “Additionally, we observed that CPC analysis reflects the subjective sleep quality of patients with PD. CPC analysis can serve as a novel sleep monitoring tool to screen patients with ‘good’ and ‘poor’ sleep quality.”