Background: Feline Dermatitis Extent and Severity Index (FEDESI) and Scoring Feline Allergic Dermatitis (SCORFAD) are scales used to assess lesion severity in cats with allergic dermatitis. Interobserver reliability has not been assessed for either.
Hypothesis And Objectives: To determine interobserver reliability for FEDESI and SCORFAD, and the relationship between lesion scores and pruritus.
Animals: Thirty-eight cats presenting for pruritus.
Methods And Materials: Each cat's lesions were scored by two observers at each visit using both FEDESI and SCORFAD (n = 117 paired observations). Spearman's rho was calculated to assess correlation between scales and between each scale and the owner-reported pruritus Visual Analog Scale (pVAS). Concordance correlation coefficients were calculated between observers for each scale, and Bland-Altman plots were used to visually represent the relationship between paired scores.
Results: FEDESI and SCORFAD were strongly positively correlated with one another (rho = 0.84, P < 0.001). Each scale showed fair correlation with pVAS (rho = 0.42, P < 0.001; rho = 0.38, P < 0.001, respectively). There was good concordance between observers for both scales, with a correlation coefficient of 0.77 for FEDESI and 0.80 for SCORFAD [intraclass correlation coefficient (ICC) 95%, confidence interval (CI) 0.69-0.83; ICC 95%, CI 0.72-0.86, respectively]. Median lesion score was low (FEDESI 20; SCORFAD 4), which may improve interobserver reliability.
Conclusions And Clinical Importance: There is good interobserver reliability for both FEDESI and SCORFAD. FEDESI and SCORFAD are positively correlated with one another and with pVAS. These findings support use of both scales in clinical research and assessment.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1111/vde.13003 | DOI Listing |
J Clin Med
January 2025
Radiology, Multizonal Unit of Rovereto and Arco, APSS Provincia Autonoma Di Trento, 38123 Trento, Italy.
The assessment of lymph node (LN) involvement with clinical imaging is a key factor in cancer staging. Node Reporting and Data System 1.0 (Node-RADS) was introduced in 2021 as a new system specifically tailored for classifying and reporting LNs on computed tomography (CT) and magnetic resonance imaging scans.
View Article and Find Full Text PDFJ Clin Med
December 2024
Faculty of Medicine, Wroclaw University of Science and Technology, 50-370 Wroclaw, Poland.
Abdom Radiol (NY)
January 2025
Department of Radiology, Peking University People's Hospital, Beijing, China.
Purpose: Correctly classifying uterine fibroids is essential for treatment planning. The objective of this study was to assess the accuracy and reliability of the FIGO classification system in categorizing uterine fibroids via organ-axial T2WI and to further investigate the factors associated with uterine compression.
Methods: A total of 130 patients with ultrasound-confirmed fibroids were prospectively enrolled between March 2023 and May 2024.
Sci Rep
January 2025
Robotics Institute, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA, 15213, USA.
Patient-specific templating (PST), which is a sister procedure to patient-specific instrumentation (PSI) but hospital-based, is relatively less complex and less expensive than robotics and navigation. However, there are some concerns about the PST including the process of preoperative planning, 3D printing and material, positioning of PST intraoperatively, availability, and clinical value. The purpose of this study was to validate the technical accuracy and reliability of the PST technique in the lab and to report the outcomes of clinical application.
View Article and Find Full Text PDFOral Maxillofac Surg
January 2025
Department of Oral and Maxillofacial Surgery, University Hospital Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Germany.
Purpose: This study aimed to clarify the applicability of smartphone-based three-dimensional (3D) surface imaging for clinical use in oral and maxillofacial surgery, comparing two smartphone-based approaches to the gold standard.
Methods: Facial surface models (SMs) were generated for 30 volunteers (15 men, 15 women) using the Vectra M5 (Canfield Scientific, USA), the TrueDepth camera of the iPhone 14 Pro (Apple Inc., USA), and the iPhone 14 Pro with photogrammetry.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!