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Validation of an Online Knee Pain Map and Questionnaire: A Probabilistic Diagnostic Tool

This study has been terminated.
Information provided by (Responsible Party):
Brock Foster, University of California, Los Angeles Identifier:
First received: December 6, 2011
Last updated: March 26, 2012
Last verified: March 2012
"Blank" has designed a medical diagnostic system in the form of an unvalidated online questionnaire and drawing tool used to describe and identify the location of knee pain, respectively. A component of the survey includes the patient inputting their diagnosis as the etiology of their knee pain. Dr. Ivo Dinov's team has used the data from 100,000 patient surveys to construct a probabilistic model to diagnose those who fill out the questionnaire and knee pain map but do not have a diagnosis. However, the validity of the online survey and the accuracy of the probabilistic model has not been confirmed in patients with known diagnoses. Therefore, the purpose of this study will be to recruit patients with knee pain at UCLA orthopedic clinics to complete the online survey which will then be applied to the probabilistic model to output possible diagnoses. The results will be compared to the actual diagnosis assigned to that patient in the clinic. If validated, the online survey may serve as a tool for diagnostic and research purposes.

Knee Pain

Study Type: Observational
Study Design: Observational Model: Cohort
Time Perspective: Prospective
Official Title: Alidation of an Online Knee Pain Map and Questionnaire: A Probabilistic Diagnostic Tool

Further study details as provided by Brock Foster, University of California, Los Angeles:

Primary Outcome Measures:
  • The ability of the UCLA modeling software to predict diagnosis based on questionnaire answers [ Time Frame: One year ]
    UCLA has developed modeling software that may be accurate at predicting diagnoses depending on the answers given by patients to an online questionnaire and knee pain drawing map. The accuracy of the software has not been tested or validated. This study will determine the accuracy of this software by comparing UCLA orthopedic surgeon input diagnosis to that output by the modeling software following completion of the questionnaire by study participants.

Secondary Outcome Measures:
  • Accuracy of patient input diagnosis compared to orthopedic surgeon diagnosis [ Time Frame: One Year ]
    Patients may inaccurately input "known diagnoses" into the online questionnaire because they were diagnosed inaccurately by their doctor, input the wrong diagnosis into the questionnaire by accident, or were never diagnosed with a condition but they input a diagnosis. Therefore, because the modeling software is contingent on accurate patient input diagnoses, determining if patients accurately input their diagnoses into the questionnaire by comparing surgeon input diagnosis to patient input diagnosis may be helpful in elucidating modeling inaccuracy.

Estimated Enrollment: 1000
Study Start Date: December 2011
Patients with knee pain and a known diagnosis


Ages Eligible for Study:   18 Years and older   (Adult, Senior)
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   No
Sampling Method:   Non-Probability Sample
Study Population
Patients older than 18 years old with knee pain that contains a known diagnosis for their pain.

Inclusion Criteria:

  • patients with knee pain and a known diagnosis for their pain
  • patients older than 18 years old

Exclusion Criteria:

  • patients that are unable or unwilling to complete the online survey.
  • patients who do not have a diagnosis for their knee pain
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Please refer to this study by its identifier: NCT01492244

United States, California
Los Angeles, California, United States, 90095
Sponsors and Collaborators
Brock Foster
  More Information

Responsible Party: Brock Foster, Mr., University of California, Los Angeles Identifier: NCT01492244     History of Changes
Other Study ID Numbers: 11-003024
Study First Received: December 6, 2011
Last Updated: March 26, 2012

Keywords provided by Brock Foster, University of California, Los Angeles:
Knee pain
survey processed this record on May 25, 2017