Craniofacial and Clinical Data for Predicting Sleep Apnea Treatment Pressure

Thays Crosara Abrahão Cunha's research dataset contains clinical and anthropometric measurements from 50 male patients with mild-to-moderate obstructive sleep apnea. The data includes polysomnographic, cephalometric, and upper airway assessments used to derive a predictive formula for optimal continuous positive airway pressure. The study was published on paperswithcode.

Use Cases

• Predict optimal continuous positive airway pressure based on mandibular length and atlas-jaw distance.
• Analyze correlations between Mallampati classification and required treatment pressure.
• Build regression models for clinical treatment planning using anthropometric and polysomnographic features.

Strengths

• Dataset is based on a study of 50 male patients with detailed clinical assessments.
• Includes specific predictive formula derived from mandibular length, atlas-jaw distance, and Mallampati classification.
• Data collection involved baseline and titration polysomnography, suggesting a structured methodology.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Data is limited to a specific demographic of 50 men with BMI ≤ 35 kg/m².

Provenance

Source

Thays Crosara Abrahão Cunha via paperswithcode

Collection Method

Clinical study involving polysomnography, cephalometric, and otolaryngological assessments.