2020 journal article

Development of a checklist for the detection of degenerative joint disease-associated pain in cats

Journal of Feline Medicine and Surgery, 22(12), 1137–1147.

By: M. Enomoto n, B. Lascelles n & M. Gruen n

co-author countries: United States of America 🇺🇸
author keywords: Osteoarthritis; pain; checklist; musculoskeletal disease; degenerative joint disease; screening; behavioral change
MeSH headings : Animals; Cat Diseases / diagnosis; Cats; Checklist; Cross-Sectional Studies; Female; Joint Diseases / diagnosis; Joint Diseases / veterinary; Male; Pain / diagnosis; Pain Measurement / methods; Pain Measurement / veterinary; Sensitivity and Specificity
Source: ORCID
Added: March 3, 2020

Objectives The aim of this study was to develop an evidence-based, clinically expedient checklist to identify cats likely to have degenerative joint disease (DJD)-associated pain. Methods Data were compiled from previously conducted studies that employed a standardized subjective outcome measure consisting of a series of questions. These studies included a prevalence study (with DJD non-informed owners) and therapeutic trials (with DJD-informed owners). For each cat, and each question, response scores were converted to ‘impaired’ and ‘unimpaired’. Cats were categorized as ‘DJD pain’ and ‘non-DJD’ based on orthopedic pain and radiographic DJD scores. These binary data were compared between cat phenotypes (non-DJD and DJD pain) for each question. Sensitivity and specificity of each question were calculated using the binary data; based on this, potential questions for the checklist were selected. Sensitivity and specificity across this group of questions were calculated, and questions sequentially removed to optimize length, sensitivity and specificity. Finally, the proposed checklist was applied to a novel data set to evaluate its ability to identify cats with DJD pain. Results In total, 249 DJD pain cats and 53 non-DJD cats from five studies were included. Nine questions with adequate sensitivity and specificity were initially identified. Following sequential removal of questions, a checklist with six binary questions was proposed. Based on the data from the cohorts of DJD-informed and DJD non-informed owners, the sensitivity and specificity of the proposed checklist were approximately 99% and 100%, and 55% and 97%, respectively. Conclusions and relevance The proposed checklist represents a data-driven approach to construct a screening checklist for DJD pain in cats. This checklist provides a clinically expedient tool likely to increase veterinarians’ ability to screen for DJD pain in cats. The identified behaviors comprising the checklist may further provide a foundation for increasing awareness of DJD pain among cat owners.