Dataset Information

Design and Validation of a Computer Application for Diagnosis of Shoulder Locomotor System Pathology.

ABSTRACT:

Objectives

To design and validate a computer application for the diagnosis of shoulder locomotor system pathology.

Methods

The 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).

Results

The 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 (p < 0.05).

Conclusions

The 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.

SUBMITTER: Bigorda-Sague A

PROVIDER: S-EPMC6517628 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Design and Validation of a Computer Application for Diagnosis of Shoulder Locomotor System Pathology.

Bigorda-Sague Albert A Trujillano Cabello Javier J Ariza Carrio Gemma G Campoy Guerrero Carmen C

Healthcare informatics research 20190430 2

<h4>Objectives</h4>To design and validate a computer application for the diagnosis of shoulder locomotor system pathology.<h4>Methods</h4>The 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 r ...[more]

PMID: 31131142

Similar Datasets

Project description:BackgroundThe premature loss of primary teeth is a common problem in pediatric dentistry, resulting in disruption of the arch integrity. Hence, space maintainers (SM) used for maintaining spaces are necessary. However, current methods of making removable space maintainers (RSM) have some limitations.MethodsDigital models of dentition defects were obtained by using a scanning technique coupled with laser medical image reconstruction. The digital RSMs were designed using the 3Shape software. They were manufactured using two methods: polyetheretherketone (PEEK), and conventional methods (20 RSMs per group). For qualitative evaluation, the Likert five-point scale was used by 10 experts to obtain a score for 40 RSMs. The spaces between the tissue surfaces of the RSMs and the models were replaced using silicone, and the maximum and mean distances, as well as the standard deviation, were measured. A three-dimensional variation analysis was used to measure these spaces. The student's t-test and Satterthwaite t-test were used to compare the differences in the spaces for the various materials.ResultsThe PEEK RSMs were found to fit the models well. In the qualitative assessment, the mean experts' scores for the PEEK and conventional groups were 1.80 ± 0.40 and 1.82 ± 0.40, and there was no significant difference between the two groups (p = 0.875). In the quantitative assessment, the mean spaces for the PEEK digital RSMs and the conventional RSMs were 44.32 ± 1.75 μm, and 137.36 ± 18.63 μm, respectively, and the differences were statistically significant (p < 0.001). In addition, there were significant differences in the maximum space and the standard deviation between the two groups.ConclusionDigitally designed and integrated RSMs were found to be superior to those produced using the conventional method. 3D variation analysis results showed that the mean distances and standard deviations of the PEEK groups were significantly smaller than those of conventional group (p < 0.01). A PEEK-manufactured RSM produced using CAD/CAM would be extremely suitable for clinical applications.

Dataset Information

Design and Validation of a Computer Application for Diagnosis of Shoulder Locomotor System Pathology.

Objectives

Methods

Results

Conclusions

Publications

Design and Validation of a Computer Application for Diagnosis of Shoulder Locomotor System Pathology.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets