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Robotic oncologic complexity score - a new tool for predicting complications in computer-enhanced oncologic surgery.
Olivia Sgarbura1,2, Victor Tomulescu1,3, Irinel Popescu1,3
1Department of Surgery, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania.
Summary
The robotic oncologic complexity score (ROCS) aids in comparing robotic surgeries and predicting complications. A score over 4 indicates a higher risk of major complications, improving surgical outcome analysis.
Area of Science:
- Surgical Oncology
- Robotic Surgery
- Medical Informatics
Background:
- Robotic surgery offers advancements but lacks tools for performance comparison.
- A validated complexity score is needed for objective assessment in robotic surgery.
Purpose of the Study:
- To develop and validate the Robotic Oncologic Complexity Score (ROCS).
- To assess ROCS's ability to predict major complications in oncologic robotic surgery.
Main Methods:
- Developed ROCS based on identified risk factors.
- Validated the score on 400 robotic oncologic surgery cases.
- Assessed correlation between ROCS and complications, operating time, and length of stay.
Main Results:
- Mean ROCS was 3.3 (+/-1.4).
- ROCS correlated significantly with major complications (r=0.42), Clavien grade (r=0.5), and length of stay (r=0.47).
- A ROCS >4 demonstrated optimal specificity and sensitivity for predicting major complications (P<0.05).
Conclusions:
- ROCS shows potential for predicting complications and hospital length of stay.
- ROCS can assist in classifying oncologic robotic surgical interventions.
- The score may facilitate center-to-center performance comparisons in robotic surgery.
