Automated Capture of Intraoperative Adverse Events Using Artificial Intelligence: A Systematic Review and Meta-Analysis
, Marissa Maas 1, Abhishek Venkat 1, Sij Hemal 1, Mihir M. Desai 1, Andrew J. Hung 1, Teodor Grantcharov 2, Giovanni E. Cacciamani 1 and Mitchell G. Goldenberg 1,*
Round 1
Reviewer 1 Report
It is rather difficult to asses a study that focuses on finding “misses” and “near misses” in an operating room on account of the psychologic aspects that should be overcome in the surgeon’s mind (ie: I don’t make mistakes, what is the need for this system).
With that being said, the present article dives into a relatively tabu part of surgery and doses so using AI and rehearsing the AI’s merit in finding problems in OR. The quality of the presentation is good, the methodology is described accurately, and data processing is transparent. The article can be considered one of the first steps in analyzing the benefit of using AI in the detection of mishaps in the OR.
Author Response
Dear Reviewer 1, Thank you for reviewing our article and your thoughtful response. We agree that this is a relatively unknown aspect of surgery and we are excited to publish one of the first reviews on this topic. We appreciate your suggestion for a minor spell check and will conduct a thorough final review of the manuscript.Reviewer 2 Report
Interesting study and methodologically very well carried out.
The complexity of the study makes it difficult to read, although I doubt it can be improved upon.
I advise authors to add the MESH terms to the keywords: Adverse effects; Intraoperative Period
Author Response
Dear Reviewer 2, Thank you for reviewing our article and your thoughtful response. We appreciate your suggestion to incorporate the additional terms. We have added the suggested keywords to the manuscript. Thanks again for your time and consideration.