Lipedema Screening Questionnaire and Predictive Model Data

A lipedema screening questionnaire and predictive model data developed to address underdiagnosis of the condition. The dataset likely contains responses from 109 female patients, used to build models achieving correct diagnosis probabilities of 91.2% and 86.15%. The work was authored by Alexandre Campos Moraes Amato and is available via Open Access.

Use Cases

• Training a binary classification model for lipedema based on questionnaire scores.
• Developing a clinical decision support system based on the described predictive model.
• Analyzing symptom patterns associated with lipedema based on the questionnaire items.

Strengths

• Model performance is quantified, with an individual-question model achieving 91.2% correct diagnosis probability.
• Questionnaire was validated on a patient sample, with all 109 participants reported to have understood the questions.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown beyond the 109 participants mentioned, which may limit suitability assessment.
• Data may reflect demographic bias inherent to the study sample, which consisted entirely of female patients.

Provenance

Source

Alexandre Campos Moraes Amato

Collection Method

A simplified questionnaire was constructed and administered to a sample of patients with and without lipedema.