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
Study Overview
Status
Status
Conditions
Conditions
Study Type
Study Type
Enrollment (Anticipated)
Enrollment
Contacts and Locations
Study Locations
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California
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Los Angeles, California, United States, 90095
- UCLA
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Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Genders Eligible for Study
Sampling Method
Study Population
Description
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
Study Plan
How is the study designed?
Design Details
Number of groups / cohorts
Cohorts and Interventions
Group / CohortGroup / Cohort |
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Patients with knee pain and a known diagnosis
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What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
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The ability of the UCLA modeling software to predict diagnosis based on questionnaire answers
Time Frame: One year
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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.
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One year
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Secondary Outcome Measures
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
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Accuracy of patient input diagnosis compared to orthopedic surgeon diagnosis
Time Frame: One Year
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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.
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One Year
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Collaborators and Investigators
Sponsor
Sponsor
Study record dates
Study Major Dates
Study Start
Study Start
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Estimate)
First Posted
Study Record Updates
Last Update Posted (Estimate)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Keywords
Other Study ID Numbers
Other Study ID Numbers
- 11-003024
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