Can a prediction model combining self-reported symptoms, sociodemographic and clinical features serve as a reliable first screening method for sleep apnea syndrome in patients with stroke?
| Field | Value |
|---|---|
| Model ID | 14-028-01 |
| Model Name | Aaronson 2014 |
| Pubmed ID | 24378806 |
| First Author | Aaronson |
| Journal | Archives of Physical Medicine and Rehabilitation |
| Year | 2014 |
| Title | Can a prediction model combining self-reported symptoms, sociodemographic and clinical features serve as a reliable first screening method for sleep apnea syndrome in patients with stroke? |
| Primary Index Condition | Stroke |
| Secondary Index Condition | N/A |
| Outcome | Sleep Apnea |
| Model Sample Size | 438 |
| Cohort Sample Size | 438 |
| Number of Events | 135 |
| Follow-Up Duration | Diagnosis |
| AUROC | 0.76 |
| Calibration Reported | 1 |
| Covariates | Intercept; Age; Sex; BMI; Apneas; Falling asleep |
| Mesh Terms | To be updated |
| Number of Validations | 0 |