Patient-reported outcomes have become standard in facial skin cancer surgery, yet clinicians currently lack validated tools to predict postoperative appearance satisfaction from preoperative patient characteristics. We developed and internally validated a prediction model for appearance satisfaction three months after facial skin cancer reconstruction. A prospective cohort study enrolled 287 patients at a tertiary referral center (2017-2018); 111 patients with complete data were included in the primary analysis. Patients completed the FACE-Q Skin Cancer Module preoperatively and at three months postoperatively. Our multivariable linear regression model incorporated age, sex, comorbidities, smoking status, and baseline appearance satisfaction. The model explained 23.0% of variance in postoperative appearance satisfaction (R2 = 0.23; adjusted R2 = 0.19; p < 0.001). Baseline appearance satisfaction (B = 0.48; 95% CI 0.28-0.68; p < 0.001) and female sex (B = -7.16; 95% CI -12.52 to -1.81; p = 0.009) emerged as independent predictors. Bootstrap resampling (500 iterations) yielded an optimism-corrected R2 of 0.17, supporting acceptable internal validity. Mean appearance satisfaction remained stable from baseline (54.8 +/- 13.8) to three months (57.0 +/- 16.4; p = 0.27). Baseline appearance satisfaction and female sex independently predict postoperative appearance satisfaction following facial skin cancer reconstruction. External validation in independent cohorts is warranted before clinical implementation.
WearBCI Dataset: Understanding and Benchmarking Real-World Wearable Brain-Computer Interfaces Signals
arXiv:2604.09649v1 Announce Type: cross Abstract: Brain-computer interfaces (BCIs) have opened new platforms for human-computer interaction, medical diagnostics, and neurorehabilitation. Wearable BCI systems, which typically employ


