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As part of the initiative known as the Intraoperative Complication Assessment and Reporting with Universal Standards (ICARUS) project, the investigators are working to develop a set of tools to aid in improving the homogenous reporting of intraoperative adverse events (iAEs). Accordingly, the investigators developed a web-based tool, known as the ICARUS Calculator, that integrates the 5 published iAE grading systems. We plan to compare the consistency of grading responses between the ICARUS Calculator and the individual grading systems as presented in their respective publications.
The purpose of this study is two-fold. First, the investigators hope to evaluate the utility of a web-based intraoperative adverse event (iAE) grading system known as the Intraoperative Complication Assessment and Reporting with Universal Standards (ICARUS) calculator. Second, the investigators plan to evaluate the difference in iAE grading outcomes of the ICARUS calculator compared with standard iAE grading.
Perioperative complications, especially intraoperative adverse events (iAEs), carry significant potential for long-term sequelae in a patient's postoperative course. Without consistent and homogenous reporting, these events represent a substantial gap in contemporary surgical literature and clinical practice. By definition, an iAE is any unplanned incident related to a surgical intervention occurring between skin incision and skin closure. Despite the availability of multiple intraoperative grading and classification systems, colloquiallary known as: EAUiaiC, iAE severity classification scheme, Modified Satava, EAES Grading system, and ClassIntra® (formerly CLASSIC) , the reporting of intraoperative adverse events remains exceedingly rare. Further, while most studies report postoperative adverse events, only a fraction of surgical publications report intraoperative complications as outcomes of interest.
As part of the initiative known as the Intraoperative Complication Assessment and Reporting with Universal Standards (ICARUS) project, the investigators are working to develop a set of tools to aid in improving the homogenous reporting of iAEs. Accordingly, the investigators developed a web-based tool, known as the ICARUS Calculator, that integrates the four aforementioned iAE grading systems. The investigators plan to compare the consistency of grading responses between the ICARUS Calculator and the individual grading systems as presented in their respective publications.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| ICARUS Calculator Raters (Intervention Group) | Surgeons and anesthesiologists will be asked to use the ICARUS Calculator to grade a subset of 10 clinical scenarios selected from a list of the clinical scenarios and examples from the publications of the 5iAE systems |
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| Cognitive Grading Raters (Control Group) | Surgeons and anesthesiologists will be asked to use the ICARUS Calculator to grade a subset of 10 clinical scenarios (same as the Intervention group) selected from a list of the clinical scenarios and examples from the publications of the 5iAE systems |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| ICARUS intraoperative adverse events calculator | Other | The ICARUS calculator is a web-based tool that uses answers to Boolean, yes/no questions to determine the iAE grade (appendix I). The calculator providers iAE grade outputs for the 5 iAE classification systems. Development of the ICARUS calculator was performed as follows: Referencing the 5 classification systems, we first assembled a list of Boolean questions based on the iAE grade descriptions. This list was distilled to the minimum number of questions necessary to represent all descriptions in the combined list of iAE grades. Next, these questions were used to independently establish the conditional logic required to determine iAE grade for each classification system. The questions and logic were translated into Hypertext Preprocessor (PHP), a server-side programming language, and JavaScript, a client-side scripting language. |
| Measure | Description | Time Frame |
|---|---|---|
| Evaluate the consistency and inter-rater reliability of the 5 iAEs grading systems in terms of Distribution of responses by count and percent | Primary data analysis will involve calculations to evaluate the consistency and inter-rater agreement for each grading system, as follows: -Distribution of responses by count and percent | 03-01-2022 to 03-15-2022 |
| Evaluate the consistency and inter-rater reliability of the 5 iAEs grading systems in terms of Percent agreement of grade | Primary data analysis will involve calculations to evaluate the consistency and inter-rater agreement for each grading system, as follows: -Percent agreement of grade | 03-01-2022 to 03-15-2022 |
| Evaluate the consistency and inter-rater reliability of the 5 iAEs grading systems using the Cohen's Kappa | Primary data analysis will involve calculations to evaluate the consistency and inter-rater agreement for each grading system, as follows: - Cohen's Kappa | 03-01-2022 to 03-15-2022 |
| Evaluate the consistency and inter-rater reliability of the 5 iAEs grading systems using the Intra-class correlation (ICC) with two-way, random effects to evaluate for consistency of grades | Primary data analysis will involve calculations to evaluate the consistency and inter-rater agreement for each grading system, as follows: -Intra-class correlation (ICC) with two-way, random effects to evaluate for consistency of grades | 03-01-2022 to 03-15-2022 |
| Evaluate theTime to complete grading (minutes) using the 5 iAEs grading systems | Primary data analysis will involve calculations i to evaluate the consistency and inter-rater agreement for each grading system, as follows: -Time to complete grading (minutes) |
| Measure | Description | Time Frame |
|---|---|---|
| Evaluation of the experience using the ICARUS calculator by System Usability Scale (SUS) questionnaire | Assess the physician satisfaction using a validated questionnaires System Usability Scale (SUS) questionnaire | 03-16-2022- to 06-01-2022 |
| Evaluation of the experience using the ICARUS calculator by using the Usefulness, Satisfaction and Ease of Use (USE) questionnaire. |
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Inclusion Criteria:
Exclusion Criteria:
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The study team will identify corresponding authors who have published articles at any point during 2019-2021 in key American and European scientific surgical journals. The study team plans to email up to 1500 authors from each of these journals - though, many of these journals will not likely have substantially fewer corresponding authors. Specifically, these journals will be associated with one or more of the following specialties:
Anesthesiology Interventional Radiology Interventional Cardiology Cardiothoracic Surgery Colon and rectal surgery General Surgery Gynecologic oncology Gynecology and obstetrics Neurological Surgery Ophthalmologic Surgery Oral and maxillofacial Surgery Orthopaedic Surgery Otorhinolaryngology Plastic Surgery Urology Vascular Surgery
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| Name | Affiliation | Role |
|---|---|---|
| Giovanni Cacciamani, MD | University of Southern California | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| University of Southern California | Los Angeles | California | 90005 | United States |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 31787430 | Background | Biyani CS, Pecanka J, Roupret M, Jensen JB, Mitropoulos D. Intraoperative Adverse Incident Classification (EAUiaiC) by the European Association of Urology ad hoc Complications Guidelines Panel. Eur Urol. 2020 May;77(5):601-610. doi: 10.1016/j.eururo.2019.11.015. Epub 2019 Nov 29. | |
| 24702887 | Background | Kaafarani HM, Mavros MN, Hwabejire J, Fagenholz P, Yeh DD, Demoya M, King DR, Alam HB, Chang Y, Hutter M, Antonelli D, Gervasini A, Velmahos GC. Derivation and validation of a novel severity classification for intraoperative adverse events. J Am Coll Surg. 2014 Jun;218(6):1120-8. doi: 10.1016/j.jamcollsurg.2013.12.060. Epub 2014 Feb 28. |
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| 03-01-2022 to 03-15-2022 |
| Evaluate the consistency and inter-rater reliability of the ICARUS Calculator in term of Distribution of responses by count and percent | Primary data analysis will involve calculations to evaluate the consistency and inter-rater agreement for each grading system, as follows: -Distribution of responses by count and percent | 03-16-2022- to 06-01-2022 |
| Evaluate the consistency and inter-rater reliability of the ICARUS Calculator in terms of Percent agreement of grade | Primary data analysis will involve calculations to evaluate the consistency and inter-rater agreement for each grading system, as follows: -Percent agreement of grade | 03-16-2022- to 06-01-2022 |
| Evaluate the consistency and inter-rater reliability of the ICARUS Calculator using Cohen's Kappa | Primary data analysis will involve calculations to evaluate the consistency and inter-rater agreement for each grading system, as follows: - Cohen's Kappa | 03-16-2022- to 06-01-2022 |
| Evaluate the consistency and inter-rater reliability of the ICARUS Calculator using Intra-class correlation (ICC) with two-way, random effects to evaluate for consistency of grades | Primary data analysis will involve calculations to evaluate the consistency and inter-rater agreement for each grading system, as follows: -Intra-class correlation (ICC) with two-way, random effects to evaluate for consistency of grades | 03-16-2022- to 06-01-2022 |
| Evaluate Time to complete grading (minutes)using the ICARUS Calculator | Primary data analysis will involve calculations to evaluate the consistency and inter-rater agreement for each grading system, as follows: -Time to complete grading (minutes) | 03-16-2022- to 06-01-2022 |
| Determination of benefit in efficiency, consistency, inter-rater reliability of the ICARUS Calculator compared to cognitively grading intraoperative adverse events | Determination of benefit in efficiency, consistency, inter-rater reliability of the ICARUS Calculator compared to cognitively grading intraoperative adverse events There will be 5 output groupings involving the grading systems:
| 03-16-2022- to 06-01-2022 |
| Determination of benefit in efficiency of the ICARUS Calculator compared to cognitively grading intraoperative adverse events | Determination of benefit in efficiency, consistency, inter-rater reliability of the ICARUS Calculator compared to cognitively grading intraoperative adverse events There will be 5 output groupings involving the grading systems:
| 03-16-2022- to 06-01-2022 |
| Determination of benefit in consistency of the ICARUS Calculator compared to cognitively grading intraoperative adverse events | Determination of benefit in efficiency, consistency, inter-rater reliability of the ICARUS Calculator compared to cognitively grading intraoperative adverse events There will be 5 output groupings involving the grading systems:
| 03-16-2022- to 06-01-2022 |
| Determination of benefit in inter-rater reliability of the ICARUS Calculator compared to cognitively grading intraoperative adverse events | Determination of benefit in efficiency, consistency, inter-rater reliability of the ICARUS Calculator compared to cognitively grading intraoperative adverse events There will be 5 output groupings involving the grading systems:
| 03-16-2022- to 06-01-2022 |
Assess the physician satisfaction using a validated questionnaires: Questionnaire for User Interaction Satisfaction (QUIS) and Usefulness, Satisfaction and Ease of Use (USE) questionnaire |
| 03-16-2022- to 06-01-2022 |
| Evaluation of the experience using the ICARUS calculator by using Questionnaire for User Interaction Satisfaction (QUIS) | Assess the physician satisfaction using a validated questionnaires: Questionnaire for User Interaction Satisfaction (QUIS) | 03-16-2022- to 06-01-2022 |
| 23762627 | Background | Kazaryan AM, Rosok BI, Edwin B. Morbidity assessment in surgery: refinement proposal based on a concept of perioperative adverse events. ISRN Surg. 2013 May 16;2013:625093. doi: 10.1155/2013/625093. Print 2013. |
| 32843333 | Background | Dell-Kuster S, Gomes NV, Gawria L, Aghlmandi S, Aduse-Poku M, Bissett I, Blanc C, Brandt C, Ten Broek RB, Bruppacher HR, Clancy C, Delrio P, Espin E, Galanos-Demiris K, Gecim IE, Ghaffari S, Gie O, Goebel B, Hahnloser D, Herbst F, Ioannidis O, Joller S, Kang S, Martin R, Mayr J, Meier S, Murugesan J, Nally D, Ozcelik M, Pace U, Passeri M, Rabanser S, Ranter B, Rega D, Ridgway PF, Rosman C, Schmid R, Schumacher P, Solis-Pena A, Villarino L, Vrochides D, Engel A, O'Grady G, Loveday B, Steiner LA, Van Goor H, Bucher HC, Clavien PA, Kirchhoff P, Rosenthal R. Prospective validation of classification of intraoperative adverse events (ClassIntra): international, multicentre cohort study. BMJ. 2020 Aug 25;370:m2917. doi: 10.1136/bmj.m2917. |
| 29435754 | Background | Francis NK, Curtis NJ, Conti JA, Foster JD, Bonjer HJ, Hanna GB; EAES committees. EAES classification of intraoperative adverse events in laparoscopic surgery. Surg Endosc. 2018 Sep;32(9):3822-3829. doi: 10.1007/s00464-018-6108-1. Epub 2018 Feb 12. |
| 34430764 | Background | Cacciamani G, Sholklapper T, Sotelo R, Desai M, Gill I. A Protocol for the Development of the Intraoperative Complications Assessment and Reporting With Universal Standards Criteria: The ICARUS Project. Int J Surg Protoc. 2021 Aug 6;25(1):160-164. doi: 10.29337/ijsp.155. eCollection 2021. |
| ID | Term |
|---|---|
| D007431 | Intraoperative Complications |
| ID | Term |
|---|---|
| D010335 | Pathologic Processes |
| D013568 | Pathological Conditions, Signs and Symptoms |
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