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

This study has been terminated.
Sponsor:
Information provided by (Responsible Party):
Brock Foster, University of California, Los Angeles
ClinicalTrials.gov Identifier:
NCT01492244
First received: December 6, 2011
Last updated: March 26, 2012
Last verified: March 2012

December 6, 2011
March 26, 2012
December 2011
Not Provided
The ability of the UCLA modeling software to predict diagnosis based on questionnaire answers [ Time Frame: One year ] [ Designated as safety issue: No ]
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.
Same as current
Complete list of historical versions of study NCT01492244 on ClinicalTrials.gov Archive Site
Accuracy of patient input diagnosis compared to orthopedic surgeon diagnosis [ Time Frame: One Year ] [ Designated as safety issue: No ]
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.
Same as current
Not Provided
Not Provided
 
Validation of an Online Knee Pain Map and Questionnaire: A Probabilistic Diagnostic Tool
Alidation of an Online Knee Pain Map and Questionnaire: A Probabilistic Diagnostic Tool

"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.

Not Provided
Observational
Observational Model: Cohort
Time Perspective: Prospective
Not Provided
Not Provided
Non-Probability Sample

Patients older than 18 years old with knee pain that contains a known diagnosis for their pain.

Knee Pain
Not Provided
Patients with knee pain and a known diagnosis
Not Provided

*   Includes publications given by the data provider as well as publications identified by ClinicalTrials.gov Identifier (NCT Number) in Medline.
 
Terminated
1000
Not Provided
Not Provided

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
Both
18 Years and older
No
Contact information is only displayed when the study is recruiting subjects
United States
 
NCT01492244
11-003024
Yes
Brock Foster, University of California, Los Angeles
Brock Foster
Not Provided
Not Provided
University of California, Los Angeles
March 2012

ICMJE     Data element required by the International Committee of Medical Journal Editors and the World Health Organization ICTRP