Evaluation of a client questionnaire at diagnosing surgical site infections in an active surveillance system

• Published in: Veterinary surgery 2024-01, Vol.53 (1), p.184-193
• Main Authors: Glenn, Owen J., Faux, Ian, Pratschke, Kathryn M., Bowlt Blacklock, Kelly L.
• Format: Article
• Language: English
• Subjects: Algorithms; Animals; Bone surgery; Cat Diseases - diagnosis; Cats; Cohort Studies; Criteria; Data collection; Dehiscence; Dog Diseases - diagnosis; Dogs; Humans; Infectious diseases; Orthopedics; Pain perception; Prospective Studies; Questionnaires; Sensitivity; Soft tissues; Surgery; Surgical site infections; Surgical Wound Infection - diagnosis; Surgical Wound Infection - epidemiology; Surgical Wound Infection - veterinary; Surveillance; Surveillance systems; Surveys and Questionnaires; Watchful Waiting; Wound healing
• ISSN: 0161-3499; 1532-950X
• DOI: 10.1111/vsu.14011

Objective To report sensitivity, specificity, predictive values and accuracy of a client questionnaire at diagnosing surgical site infections (SSIs) and describe the impact of active surveillance on SSI detection. Study design Prospective, cohort study. Animals Dogs and cats undergoing soft tissue or orthopedic surgery over a 12‐month period at a referral hospital. Methods Clients were emailed a questionnaire 30 days postoperatively, or 90 days where an implant was used. Three algorithms were developed to diagnose SSIs using one or both of two criteria: (1) presence of any wound healing problems; (2) wound dehiscence or antibiotic prescription, and either purulent discharge or two or more clinical signs (redness, pain, heat, swelling, discharge). Algorithmic diagnoses were compared to gold standard diagnoses made by veterinarians. Results Of 754 surgical procedures, 309 responses were completed with 173 corresponding gold standard diagnoses. The most accurate algorithm determined “SSI” or “No SSI” from 90.2% of responses with 95.5% (92.4–98.6) accuracy, 82.6% (77–88.3) sensitivity, 97.7% (95.5–100) specificity, 86.4% (81.2–91.5) positive predictive value, and 97% (94.5–99.6) negative predictive value. “No SSI” was diagnosed in responses not meeting criterion 1, and “SSI” in responses meeting criteria 1 and 2. “Inconclusive” responses, comprising 9.8% of responses, met criterion 1 but not 2. Overall SSI rate was 62/754 (8.2%) and 12/62 (19.4%) SSIs were detected by active surveillance only. Conclusion Use of this client questionnaire accurately diagnosed SSIs; active surveillance increased SSI detection. Clinical significance Surveillance of SSIs should be active and can be simplified by using a client questionnaire and algorithmic diagnoses, allowing automated distribution, data collection and analysis.