Objective:

To characterize comorbid circadian rhythm sleep-wake disorders (CRSWDs) in patients with chronic fatigue syndrome (CFS), identify factors independently associated with CRSWDs, and develop a risk prediction model for early screening and sleep health management.

Approach:

• Study Design: Retrospective study including 610 patients with CFS, divided into training (n = 427) and validation (n = 183) cohorts.
• Data Analysis: Univariable and multivariable logistic regression analyses were performed, and a nomogram was developed based on the final model.
• Model Evaluation: Discriminative ability, calibration, and public health usefulness were evaluated using ROC analysis, Hosmer-Lemeshow test, and decision curve analysis.

Key Findings:

• Among the 427 patients in the training cohort, 208 (48.7%) had comorbid CRSWDs.
• Factors significantly associated with CRSWDs included gender, BMI, fatigue severity (Fatigue Scale-14, FS-14), slow-wave sleep (SWS, N3%), duration of screen use before bedtime, and shift-work schedule type.
• Multivariable analysis identified 12-hour rotating shifts (OR = 6.981, 95% CI: 2.603-18.720), 24-hour shifts (OR = 5.316, 95% CI: 2.197-12.863), 8-hour rotating shifts (OR = 3.982, 95% CI: 1.698-9.339), fatigue severity (OR = 1.984, 95% CI: 1.442-2.728), and female sex (OR = 1.892, 95% CI: 1.178-3.037) as independently associated with increased CRSWDs.
• Increased slow-wave sleep (N3%) was associated with decreased odds of CRSWDs (OR = 0.982, 95% CI: 0.971-0.992).
• The model demonstrated good performance with AUCs of 0.808 in the training cohort and 0.767 in the validation cohort.

Interpretation:

The study identifies key factors associated with CRSWDs in CFS patients and presents a risk prediction model.

Limitations:

• The study is retrospective and may be subject to selection bias.
• Data were collected from a single center, which may limit generalizability.

Conclusion:

The model may be useful for early screening and risk stratification, aiding in sleep hygiene education and health management for individuals at elevated risk.