Why the study?
Early identification of patients at risk of postoperative sleep disorders is needed to reduce surgical stress and improve enhanced recovery after surgery.
Can continuous HRV monitoring using a smart patch predict postoperative sleep disorders in patients undergoing radical surgery for gastrointestinal cancer?
Population
51 patients undergoing radical surgery for gastrointestinal cancer
Comparison
Patients with vs without postoperative sleep disorders
Design
Prospective cohort study
Follow-up
120 h
Key result
A risk factor prediction model established by continuous heart rate variability parameters successfully identified patients at risk for postoperative sleep disorders with an AUC of 0.815.
Authors
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May support HRV-based PSD risk stratification after GI cancer surgery; leaves open prospective validation before clinical use.
Cohort (n=51)
No
Can continuous HRV monitoring using a smart patch predict postoperative sleep disorders in patients undergoing radical surgery for gastrointestinal cancer?
Effect estimate: AUC 0.815 (95% CI 0.701-0.929)
p-value: p=<0.0001
Continuous HRV monitoring using a smart patch can effectively predict postoperative sleep disorders in patients undergoing gastrointestinal cancer surgery.
Fang et al. (2025) conducted a cohort in Postoperative sleep disorder (PSD) in gastrointestinal cancer surgery (n=51). Heart rate variability (HRV) monitoring via smart patch vs. Normal sleep (PSQI ≤ 5) was evaluated on Prediction of postoperative sleep disorder using a multi-factor HRV parameter model (AUC 0.815, 95% CI 0.701-0.929, p=<0.0001). A risk factor prediction model established by continuous heart rate variability parameters successfully identified patients at risk for postoperative sleep disorders with an AUC of 0.815.