Knee Pain
Conditions
Keywords
Knee pain, map, questionnaire, survey
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.
Interventions
None listed
Sponsors
Brock Foster
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
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
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| The ability of the UCLA modeling software to predict diagnosis based on questionnaire answers | 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
| Measure | Time frame | Description |
|---|---|---|
| Accuracy of patient input diagnosis compared to orthopedic surgeon diagnosis | 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. |
Countries
United States
Outcome results
None listed