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Abstract: FR-PO558

Glycosylated Hemoglobin A1c as a Predictive Marker of Poor Sleep in ESRD Population

Session Information

Category: Health Maintenance, Nutrition, and Metabolism

  • 1302 Health Maintenance, Nutrition, and Metabolism: Clinical

Authors

  • Fouda, Tarek Ahmed, Hamad medical cooporation, Doha, Qatar
  • Elshirbeny, Mostafa Fottoh, HMC, Doha, Qatar
  • Kaddourah, Ahmad, Hamad Medical Corporation, Doha, Qatar
  • Hamad, Abdullah, Hamad Medical Corporation, Doha, Qatar
  • Mohamed, Mohamed Yahya, Hamad Medical Corporation, Doha, Qatar
  • Ibrahim, Rania Abdelaziz, Hamad Medical Corporation, Doha, Qatar
  • Al-Ali, Fadwa S., Hamad Medical Corporation, Doha, Qatar
Background

Patients on dialysis experience higher rates of sleep disorders compared to general population. Self-directed questionnaires can help to diagnose sleep disorders. We aim in this study to describe the epidemiology of sleep disorders in ESRD population and determine the clinical and laboratory biomarkers that can predict it.

Methods

We conducted a prospective cross-sectional study in ESRD patients on dialysis in the main dialysis unit in the state of Qatar. All adult patients on dialysis for at least one month were eligible. Enrolled patients underwent sleep disorder screening using the Pittsburgh Sleep Quality Index (PSQI), a validated questionnaire to measure the quality and patterns of sleep in adults. PSQI score >5 indicates poor sleep. Logistic and regression models were employed to evaluate the association between poor sleep scores and different commonly used clinical and laboratory markers.

Results

253 patients on dialysis (62% on hemodialysis and 38% on peritoneal dialysis) were enrolled. 115 (44.6%) were male. Median PSQI score was 10 (interquartilerange(IQR): 6-18). Diabetic patients had significantly higher median score of PSQI of 10 (IQR: 7-18.75) compared to non-diabetics (Median 9, IQR: 5-16.5) (P=0.02). 84% of diabetics had PSQI ≥ 5 compared to 73% in non-diabetic (P=0.03). Using univariate linear regression model, PSQI scores correlated significantly with Hb1AC levels (β1= 0.9, P=0.006) (even after adjusting for BMI (β1= 0.6, P=0.03)). For every 0.9 unit increase in Hb1AC, the PSQI increases by 1. The receiver operating characteristic (ROC) using Hb1AC as a predictor for sleep disorder showed AUC of 0.65. Utilizing a cut-off value of 5.1, the predictive diagnostic utility of Hb1AC was 80% for sensitivity and 89% specificity.
Univariate analysis of other clinical markers including hemoglobin level, anemia, PTH, KT/v, hypertension, and phosphorus revealed no statistical correlation with PSQI scores.

Conclusion

Our data shows high prevalence of sleep disorders in ESRD population and diabetic patients are at higher risk. Utilizing Hb1AC in diabetics with ESRD can predict patients at increased risk of sleep disorder. Our statistical models suggest that controlled diabetes is associated with better sleep quality, however, further investigational work is needed.