ArticleHealthcare informatics research2019
Design and Validation of a Computer Application for Diagnosis of Shoulder Locomotor System Pathology.
Article in Healthcare informatics research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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4 authors at 1 institution in 1 country.
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Abstract
objectivesTo design and validate a computer application for the diagnosis of shoulder locomotor system pathology.
methodsThe first phase involved the construction of the application using the Delphi method. In the second phase, the application was validated with a sample of 250 patients with shoulder pathology. Validity was measured for each diagnostic group using sensitivity, specificity, and positive and negative likelihood ratio (LR(+) and LR(-)). The correct classification ratio (CCR) for each patient and the factors related to worse classification were calculated using multivariate binary logistic regression (odds ratio, 95% confidence interval).
resultsThe mean time to complete the application was 15 ± 7 minutes. The validity values were the following: LR(+) 7.8 and LR(-) 0.1 for cervical radiculopathy, LR(+) 4.1 and LR(-) 0.4 for glenohumeral arthrosis, LR(+) 15.5 and LR(-) 0.2 for glenohumeral instability, LR(+) 17.2 and LR(-) 0.2 for massive rotator cuff tear, LR(+) 6.2 and LR(-) 0.2 for capsular syndrome, LR(+) 4.0 and LR(-) 0.3 for subacromial impingement/rotator cuff tendinopathy, and LR(+) 2.5 and LR(-) 0.6 for acromioclavicular arthropathy. A total of 70% of the patients had a CCR greater than 85%. Factors that negatively affected accuracy were massive rotator cuff tear, acromioclavicular arthropathy, age over 55 years, and high pain intensity (
conclusionsThe developed application achieved an acceptable validity for most pathologies. Because the tool had a limited capacity to identify the full clinical picture in the same patient, improvements and new studies applied to other groups of patients are required.
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