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August 1, 2025British journal of surgery

36 Design of an algorithm for the semi-automated detection of surgical site infections in elective colorectal surgery

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Authors

JBJulia Castells BouDCDaniel Casanova-PortolésJPJose Uriel Perez

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Overview

Prospective analysis shows increased diagnostic accuracy in surgical site infection detection, indicating potential for reduced manual workload.

Key Points

  • The proposed algorithm achieved a sensitivity of 86.77% and specificity of 73.17% in detecting surgical site infections.
  • Among a sample of 1213 cases, 118 events were accurately predicted, highlighting its diagnostic precision.
  • Algorithm performance was evaluated using receiver operating characteristic curves to maximize sensitivity and specificity.
  • Application of this semi-automated approach may reduce manual workloads by up to 70%, supporting infection control efforts.

Cite This Study

Bou et al. (2025) studied this question.

synapsesocial.com/papers/68af409acf1dd9ea359ec758https://doi.org/10.1093/bjs/znaf159.008
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 121 The burden of surgical site infection following colorectal surgery in England: a population-based analysis using linked hospital and primary care data sets2025
  2. 217 Artificial intelligence for the detection of surgical site infection on wound images. A systematic review and meta-analysis2025
  3. 312 Evaluation of ChatGPT-4 for the detection of surgical site infections from electronic health records after colorectal surgery: a pilot diagnostic study2025
  4. 4Effectiveness of Surveillance in Reducing Reoperations in Spinal Surgery2025
  5. 5Dual Surveillance of Surgical Site Infections Using CDC and ASEPSIS Criteria: Clinical and Economic Outcomes in Colorectal and Small Bowel Surgery2025