Abstract: FR-PO0453
Prevalence of Sleep Apnoea Using Different Detection Methods in People Receiving Haemodialysis
Session Information
- Dialysis: Measuring and Managing Symptoms and Syndromes
November 07, 2025 | Location: Exhibit Hall, Convention Center
Abstract Time: 10:00 AM - 12:00 PM
Category: Dialysis
- 801 Dialysis: Hemodialysis and Frequent Dialysis
Authors
- Mowles, Patrick John, University of Leicester Medical School, Leicester, England, United Kingdom
- Burton, James, NIHR Leicester Biomedical Research Centre, Leicester, England, United Kingdom
- Hall, Andrew Peter, University Hospitals of Leicester NHS Trust, Leicester, England, United Kingdom
- Hull, Katherine Leigh, NIHR Leicester Biomedical Research Centre, Leicester, England, United Kingdom
- Pallett, Edward J, University Hospitals of Leicester NHS Trust, Leicester, England, United Kingdom
- Quann, Niamh, NIHR Leicester Biomedical Research Centre, Leicester, England, United Kingdom
- Worboys, Hannah, University of Leicester College of Life Sciences, Leicester, England, United Kingdom
- March, Daniel Scott, NIHR Leicester Biomedical Research Centre, Leicester, England, United Kingdom
Background
People with end stage kidney disease receiving haemodialysis (HD) have a high cardiovascular risk and sleep apnoea (SA) may be associated with this. SA is neglected in this population and formal diagnosis requires overnight polysomnography. The STOP-Bang questionnaire and oxygen desaturation index (ODI) are suggested screening tools for SA in the general population but have not been widely assessed in the HD population. This study assessed the likelihood of SA using STOP-Bang and ODI in a HD population. Agreement between the tools was evaluated and their associated factors.
Methods
Adults receiving prevalent HD completed the STOP-Bang and were offered overnight home oximetry. The STOP-Bang categorised risk of SA as low, intermediate or high using a score of 0-8. ODI grouped users into mild (0-15), moderate (>15-30) or severe (>30). ODI was defined as the number of dips per hour, ≥3% from baseline oxygen saturation. The cut-offs for likely SA were ODI>15 and intermediate STOP-Bang risk. Mean scores were calculated and weighted Cohen’s Kappa established agreement between each tool. Univariate and multivariate ordinal logistic regression on each tool was performed, adjusting for collected demographic, clinical and HD data.
Results
Fifty-nine adults (39 male, age: 61.5±13.4 years, BMI: 27.9±5.7 kg/m2, HD vintage: 31.0±34.2 months) completed the STOP-Bang, 23 wore an oximeter. Diabetes was present in 42.4% and prior transplant in 20.3% of participants. The mean STOP-Bang score was 4.1±1.6, and mean ODI was 30.4±27.9. The STOP-Bang assigned 86.4% to intermediate-high risk and 65.2% had moderate-severe ODI. There was fair agreement between STOP-Bang risk and ODI severity groupings (k=0.395, p=0.022). Univariate and adjusted models yielded diabetes as a significant predictor of elevated STOP-Bang risk (b= 1.387, p=0.016) and increased BMI was significantly associated with greater ODI severity (b=0.419, p=0.027).
Conclusion
STOP-Bang and nocturnal oximetry perceive a high burden of SA in this HD population, with oximetry providing a more conservative estimate. Agreement between the tools is modest but not concordant, and they have different associated factors, indicating a complimentary relationship between the tools.