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Glenn et al: Evaluation of a client questionnaire at diagnosing surgical site infections in an active surveillance system
Veterinary Surgery 1, 2024

🔍 Key Findings Summary

  • Population: 754 soft tissue or orthopedic procedures in dogs and cats
  • SSI Rate: 62/754 (8.2%)
  • Algorithms Evaluated:
    • Algorithm 1: Highest sensitivity (87.1%) → best for "rule-out"
    • Algorithm 2: Highest specificity (97.9%) → best for "rule-in"
    • Algorithm 3: Highest overall accuracy (95.5%)
  • Active vs. Passive Surveillance:
    • Active surveillance detected 12 additional SSIs (19.4%) missed by passive
    • Active surveillance increased detection rate by 24%
  • Timing: Most SSIs occurred within 30 days; late infections (after 90 days) were rare and implant-related
  • Conclusion: Client questionnaires are a valid and scalable tool for SSI detection; active surveillance improves outcomes

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← Articles

Glenn et al: Evaluation of a client questionnaire at diagnosing surgical site infections in an active surveillance system
Veterinary Surgery 1, 2024

🔍 Key Findings Summary

  • Population: 754 soft tissue or orthopedic procedures in dogs and cats
  • SSI Rate: 62/754 (8.2%)
  • Algorithms Evaluated:
    • Algorithm 1: Highest sensitivity (87.1%) → best for "rule-out"
    • Algorithm 2: Highest specificity (97.9%) → best for "rule-in"
    • Algorithm 3: Highest overall accuracy (95.5%)
  • Active vs. Passive Surveillance:
    • Active surveillance detected 12 additional SSIs (19.4%) missed by passive
    • Active surveillance increased detection rate by 24%
  • Timing: Most SSIs occurred within 30 days; late infections (after 90 days) were rare and implant-related
  • Conclusion: Client questionnaires are a valid and scalable tool for SSI detection; active surveillance improves outcomes

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Multiple Choice Questions on this study

In Glenn 2024 et al., on questionnaire specificity, which algorithm had the highest specificity for SSI detection?

A. Algorithm 1
B. Algorithm 2
C. Algorithm 3
D. All equal
E. None reported

Answer: Algorithm 2

Explanation: Algorithm 2 had the highest specificity (97.9%) and is preferred when false positives must be minimized.
In Glenn 2024 et al., on infection timing, what was the most common time frame for diagnosed SSIs?

A. <7 days post-op
B. 8–14 days post-op
C. 15–30 days post-op
D. >30 days post-op
E. >90 days post-op

Answer: 15–30 days post-op

Explanation: Most SSIs were identified within 15–30 days of surgery, consistent with CDC surveillance periods.
In Glenn 2024 et al., on algorithm performance, which algorithm had the highest sensitivity for identifying SSIs?

A. Algorithm 1
B. Algorithm 2
C. Algorithm 3
D. Manual chart review
E. Passive surveillance

Answer: Algorithm 1

Explanation: Algorithm 1 had the highest sensitivity (87.1%), making it the best for screening or ruling out SSIs.
In Glenn 2024 et al., on overall diagnostic performance, which algorithm had the highest accuracy?

A. Algorithm 1
B. Algorithm 2
C. Algorithm 3
D. Chart review
E. Passive system

Answer: Algorithm 3

Explanation: Algorithm 3 had the highest overall accuracy (95.5%), balancing sensitivity and specificity.
In Glenn 2024 et al., on comparative surveillance methods, how did active surveillance affect SSI detection rate?

A. Increased by 10%
B. Increased by 18%
C. Increased by 24%
D. No effect
E. Decreased slightly

Answer: Increased by 24%

Explanation: Active surveillance increased detection rate by 24% over passive surveillance alone.

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