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Related Experiment Video

Updated: May 4, 2026

Non-invasive Assessment of Microvascular and Endothelial Function
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Microvascular errors of technique: a systematic review.

Victor Esanu1,2, Elisa Marziali2, Oana Gaspar2

  • 1Erasmus MC, Rotterdam, Netherlands.

Acta Neurochirurgica
|March 8, 2026
PubMed
Summary
This summary is machine-generated.

Identifying and correcting microvascular anastomosis errors is crucial for surgical training. This review categorizes errors across operative phases to improve skill acquisition and patient outcomes.

Keywords:
Cerebrovascular bypassMicrovascular anastomosisTechnique errors

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Area of Science:

  • Surgical Training and Education
  • Microsurgery
  • Medical Error Analysis

Background:

  • Microvascular procedures require high precision, with technical errors impacting outcomes.
  • Error-based learning is vital for improving performance in microsurgical training.
  • Systematic identification and correction of errors accelerate skill acquisition.

Purpose of the Study:

  • To systematically review and categorize all reported microsurgical errors.
  • To analyze the impact of errors on anastomotic outcomes, particularly patency.
  • To provide a structured taxonomy of errors for enhanced surgical training.

Main Methods:

  • Conducted a systematic literature search across Medline, Embase, and Web of Science.
  • Included studies evaluating microvascular anastomoses (<2 mm diameter) detailing errors and outcomes.
  • Utilized a Synthesis Without Meta-analysis (SWiM) narrative synthesis approach.

Main Results:

  • 34 studies met inclusion criteria; errors classified into pre-operative, intra-operative, and post-operative phases.
  • Intra-operative errors were most frequent, with back-wall stitches, uneven lumens, and excessive suture tension linked to reduced patency.
  • Validated tools (ALI, MARS10, OSATS) effectively quantify errors and guide feedback.

Conclusions:

  • Microsurgical anastomosis errors occur throughout all operative phases and affect success rates.
  • A structured taxonomy of errors is essential for effective microsurgical training programs.
  • Standardized error classification accelerates skill acquisition and improves clinical outcomes.