Clinical Validation of a Computer-Aided Diagnosis (CAD) System Utilizing Artificial Intelligence Algorithms for Continuous and Remote Monitoring of Patient Condition Severity in an Objective and Stable Manner. (LEGIT_COVIDX_EVCDAO_2022.)

Study type

• Study type:
  Non-interventional study
• Data collection methods:
  Combined primary data collection and secondary use of data

Non-interventional study

• Non-interventional study design:
  Cohort

Population studied

• Short description of the study population:
  Patients diagnosed with any of the specified chronic dermatological conditions that meet the inclusion criteria. These patients are attended at the Dermatology Department of the Hospital Universitario de Torrejón. It encompassed a diverse patient cohort with a range of chronic dermatologic pathologies, providing a comprehensive representation of the population affected by these conditions.
• Age groups:
  Adults (18 to < 46 years)

  Adults (46 to < 65 years)

  Adults (65 to < 75 years)

  Adults (75 to < 85 years)

  Adults (85 years and over)
• Estimated number of subjects:
  160

Study design details

• Main study objective:
  This study aims to: Evaluate the effectiveness of the device in remotely monitoring the severity of chronic dermatologic pathologies. Assess patient satisfaction with the device for remote monitoring.
• Outcomes:
  Primary Analyses - Clinical Utility Questionnaire Specialists found the device easy to use, optimized consultation time, and enhanced data collection. General satisfaction was high, with an overall mean score of 71.39. Statistical Analysis A one-sample Student's t-test suggested no substantial evidence to reject the hypothesis, aligning the observed sample mean with a population mean of 80, Data Utility Questionnaire: Specialists unanimously agreed on app usefulness. Mean scores revealed strong preferences for app functionalities, with some variations. System Usability Scale Questionnaire: Specialists found the device easy to use, with positive feedback on integration. Discrepancies encountered indicated areas for improvement.
• Data analysis plan:
  For the purpose of estimating mean responses and their variability, we calculated the mean and standard deviation for all questions. Additionally, to evaluate the hypothesis concerning the CUS value, we conducted a one-sample Student's t-test to determine the statistical significance and either accept or reject the hypothesis based on the test results.

Documents

Study, other information

CEIm_LEGIT_COVIDX_EVCDAO_2022_TRJON-8abc0f12d828135f5b5e7bf93985ee24

Study publications

Clinical Validation of a Computer-Aided Diagnosis (CAD) System Utilizing Artifi…