NCT01492244

Brief Summary

"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.

Trial Health

35
At Risk

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Enrollment
1,000

participants targeted

Target at P75+ for all trials

Geographic Reach
1 country

1 active site

Status
terminated

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

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Study Timeline

Key milestones and dates

Study Start

First participant enrolled

December 1, 2011

Completed
5 days until next milestone

First Submitted

Initial submission to the registry

December 6, 2011

Completed
8 days until next milestone

First Posted

Study publicly available on registry

December 14, 2011

Completed
Last Updated

March 27, 2012

Status Verified

March 1, 2012

First QC Date

December 6, 2011

Last Update Submit

March 26, 2012

Conditions

Keywords

Knee painmapquestionnairesurvey

Outcome Measures

Primary Outcomes (1)

  • The ability of the UCLA modeling software to predict diagnosis based on questionnaire answers

    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.

    One year

Secondary Outcomes (1)

  • Accuracy of patient input diagnosis compared to orthopedic surgeon diagnosis

    One Year

Study Arms (1)

Patients with knee pain and a known diagnosis

Eligibility Criteria

Age18 Years+
Sexall
Healthy VolunteersNo
Age GroupsAdult (18-64), Older Adult (65+)
Sampling MethodNon-Probability Sample
Study Population

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

You may qualify if:

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

You may not qualify if:

  • patients that are unable or unwilling to complete the online survey.
  • patients who do not have a diagnosis for their knee pain

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (1)

UCLA

Los Angeles, California, 90095, United States

Location

Study Design

Study Type
observational
Observational Model
COHORT
Time Perspective
PROSPECTIVE
Sponsor Type
OTHER
Responsible Party
SPONSOR INVESTIGATOR
PI Title
Mr.

Study Record Dates

First Submitted

December 6, 2011

First Posted

December 14, 2011

Study Start

December 1, 2011

Last Updated

March 27, 2012

Record last verified: 2012-03

Locations