Detection of Sleep-Disordered Breathing in Patients with Spinal Cord Injury Using a Smartphone.

Area of Science:

• Neurology
• Pulmonology
• Biomedical Engineering

Background:

• Spinal cord injury (SCI) patients face elevated risks for sleep-disordered breathing (SDB).
• SDB in SCI can exacerbate comorbidities and hinder patient recovery and quality of life.
• Current diagnostic methods for SDB are often impractical for SCI patients due to cost and complexity.

Purpose of the Study:

• To evaluate a novel smartphone system for non-invasive SDB monitoring in SCI patients.
• To assess the feasibility and effectiveness of using smartphone-derived data for SDB detection.

Main Methods:

• Overnight recordings of pulse oximetry, acoustic, and accelerometer data were collected using a smartphone.
• Data were gathered from 19 SCI patients and 19 able-bodied controls.
• Automatic algorithms analyzed signals to detect desaturation, apnea, hypopnea events, and monitor sleep position.

Main Results:

• SCI patients exhibited a significantly higher apnea-hypopnea index (AHI) compared to controls (25 ± 15 vs. 9 ± 7, p < 0.001).
• 63% of SCI patients presented with moderate-to-severe SDB (AHI ≥ 15), versus 21% in the control group.
• While most SCI patients slept supine, increased SDB events in this position were noted in only a subset.

Conclusions:

• This study underscores the significant prevalence of SDB in the SCI population.
• The developed smartphone system offers a simple, cost-effective tool for SDB detection in SCI patients.
• This technology can aid in the improved detection, understanding, and management of SDB within this vulnerable group.