Proof of Concept of the Aiinane Preoperative Risk Assessment Tool.

BACKGROUND: Each year, over 13,000 patients in Catalonia and more than 4 million worldwide experience last-minute surgery cancellations (LMC) due to preoperative inefficiencies. As anaesthesia services struggle to meet surgical demands, thorough preoperative evaluations become challenging. Current resource-intensive pre-anaesthetic assessments are undermined by high demand, causing inefficiency. However, proper assessment identifies that most patients (\>70%) are low-risk and ensures high-risk patients are adequately prepared by analyzing risk profiles, health status, medical history, treatment, and lab results. RATIONALE: Previous attempts to improve preoperative risk assessment have mainly relied on self-administered questionnaires to detect at-risk patients. The investigators have identified a care model that enhances quality by adding value to preoperative risk assessment. By combining anaesthesiology expertise with AI techniques, the investigators developed an automated digital environment to detect risks, optimize visits, avoid cancellations, and reduce postoperative complications. This system uses parameterized medical knowledge to verify responses and objectively assess patient risk by integrating multiple data sources. The investigators have developed a Class IIa active diagnostic and monitoring product, a Medical Device Software (MDSW, EMDN V92), to support clinical decision-making in an automated digital preoperative environment. It helps assess patients and flags low-risk from medium/high-risk individuals, reporting personalized needs to the medical team. The software was developed exclusively by independent researchers from Bellvitge University Hospital and the Bellvitge Biomedical Research Institute (IDIBELL). HYPOTHESIS: The tool has been tested successfully on fictitious patients in controlled preclinical scenarios. The aim now is a proof-of-concept study to verify its performance with real patients in uncontrolled, real-world settings. This is a Clinical Performance Research Study, aligned with MDSW Clinical Evaluation Guidelines (MDR, MDCG 2020-1) for (EU) 2017/745, and authorized by the Spanish Agency of Medicines and Medical Devices (AEMPS) and the local Ethics Committee. MAIN OBJECTIVE: The clinical trial aims to verify that the software (aiinane), supporting preanesthetic assessment and preoperative risk estimation, is fit for its intended purpose and performs as expected under normal conditions of use. This is an observational, non-interventional, single-center, prospective, longitudinal adult cohort study. The target population is any adult (\>18 years) of any gender undergoing breast cancer surgery.

Sex

All

Minimum age

18 Years

Inclusion Criteria:

* Adult patients (age ≥18 years) of both sexes. Although breast neoplasia is a pathology with high prevalence in the female biological gender, we do not rule out recruiting patients of male biological gender.
* Who have been indicated for breast surgery to resolve breast cancer pathology.
* Who will undergo a pre-anesthetic evaluation during the inclusion period..
* Subjects must understand the nature of the study procedures and provide written informed consent prior to any study-related procedures.

Exclusion Criteria:

* Surgery scheduled for \<7 days from enrollment
* Inability to participate in the study, in the opinion of the investigator, due to, for example, severe brain damage, language barrier, dementia, or other clinically significant or unstable conditions.
* Subject's participation in any other clinical study.
* Subjects dependent (as employee or relative) of the promoter or researcher.
* Subjects placed in an institution by virtue of an order issued by either judicial or administrative authorities.
* Limited legal capacity or incapacity.
* Pregnancy.

• BACKGROUNDAl Talalwah N, McIltrot KH. Cancellation of Surgeries: Integrative Review. J Perianesth Nurs. 2019 Feb;34(1):86-96. doi: 10.1016/j.jopan.2017.09.012. Epub 2018 Apr 17. PMID 29678319
• BACKGROUNDGlazener C, Boachie C, Buckley B, Cochran C, Dorey G, Grant A, Hagen S, Kilonzo M, McDonald A, McPherson G, Moore K, N'Dow J, Norrie J, Ramsay C, Vale L. Conservative treatment for urinary incontinence in Men After Prostate Surgery (MAPS): two parallel randomised controlled trials. Health Technol Assess. 2011 Jun;15(24):1-290, iii-iv. doi: 10.3310/hta15240. PMID 21640056
• BACKGROUNDFinegan BA, Rashiq S, McAlister FA, O'Connor P. Selective ordering of preoperative investigations by anesthesiologists reduces the number and cost of tests. Can J Anaesth. 2005 Jun-Jul;52(6):575-80. doi: 10.1007/BF03015765. PMID 15983141
• BACKGROUNDRogers G. Using Telemedicine for Pediatric Preanesthesia Evaluation: A Pilot Project. J Perianesth Nurs. 2020 Feb;35(1):3-6. doi: 10.1016/j.jopan.2019.07.001. Epub 2019 Sep 11. PMID 31521494
• BACKGROUNDKramer S, Lau A, Kramer M, Wendler OG, Muller-Lobeck L, Scheding C, Klarhofer M, Schaffartzik W, Neumann T, Krampe H, Spies C. [Web-based for preanesthesia evaluation record: a structured, evidence-based patient interview to assess the anesthesiological risk profile]. Anasthesiol Intensivmed Notfallmed Schmerzther. 2011 Oct;46(10):694-8. doi: 10.1055/s-0031-1291948. Epub 2011 Oct 21. German. PMID 22020575
• BACKGROUNDSchoen DC, Prater K. Role of Telehealth in Pre-anesthetic Evaluations. AANA J. 2019 Feb;87(1):43-49. PMID 31587743
• BACKGROUNDGonzalez-Arevalo A, Gomez-Arnau JI, delaCruz FJ, Marzal JM, Ramirez S, Corral EM, Garcia-del-Valle S. Causes for cancellation of elective surgical procedures in a Spanish general hospital. Anaesthesia. 2009 May;64(5):487-93. doi: 10.1111/j.1365-2044.2008.05852.x.