Proof of Concept of the Aiinane Preoperative Risk Assessment Tool.

NCT07021235 | Completed DMC

• 1 other identifier: ICPS033/24
• Study Type: observational
• Target: 30
• Locations: 1 country
• Sites: 1

Brief Summary

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.

Conditions

Breast Neoplasms; Surgery Scheduled; Surgery Related Complications Rate; Preanesthetic Medication; Preoperative Patients; Preoperative Planning; Risk Assesment

Keywords

pre-anesthetic assessment; perioperative risk; artificial intelligence; Robotic Process Automation

Outcome Measures

Primary Outcomes (1)

• The aiinane tool is able to create a final report/document with the clinical information required for preoperative assessment

  The present clinical trial aims to verify that the software (hereinafter aiinane) for the support of pre-anesthetic assessment in the estimation of preoperative risk, is adequate for its established purposes and offers the expected performance under normal conditions of use. Therefore the outcome measure is the total number of complete anesthesia reports generated.

  From enrollment to 2 weeks after surgery has been performed.

Secondary Outcomes (4)

• Patient Satisfaction

  From enrollment to 2 weeks after surgery

• Clinical usefulness

  From enrollment to 2 weeks after surgery

• clinical significance

  From enrollment to 2 weeks after surgery

• usefulness of risk stratification

  From enrollment to 2 weeks after surgery

Study Arms (1)

Breast cancer surgery

Adult patients diagnosed with breast cancer that require surgery as part of their treatment plan and have planed surgery in the following weeks.

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Target population: patients who will undergo preanesthetic evaluation at Bellvitge University Hospital for breast cancer surgery. An internal analysis performed on all types of surgical procedures in 2019 (2020 to 2022 skewed due to the COVID-19 pandemic) identified 4 types of surgery with 80% of patients categorized preoperatively as ASA I-II (low risk). From those, breast cancer surgery was the only one with a short intervention period between diagnosis, surgical indication and surgery. Patients who will undergo breast cancer surgery go through multiple visits, tests and treatments between diagnosis and surgery. Sparing them visits generates a high impact on their emotional state.

You may qualify if:

• 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.
• Subjects must understand the nature of the study procedures and provide written informed consent prior to any study-related procedures.

You may not qualify if:

• 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.

Sponsors & Collaborators

• Ancor Serrano: lead
• Hospital Universitari de Bellvitge: collaborator
• Institut d'Investigació Biomèdica de Bellvitge: collaborator

Study Sites (1)

Bellvitge University Hospital. ,

L'Hospitalet de Llobregat, Barcelona, 08907, Spain

Location

Related Publications (13)

• Al 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 BACKGROUND

• Glazener 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 BACKGROUND

• Finegan 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 BACKGROUND

• Rogers 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 BACKGROUND

• Kramer 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 BACKGROUND

• Schoen DC, Prater K. Role of Telehealth in Pre-anesthetic Evaluations. AANA J. 2019 Feb;87(1):43-49.

  PMID: 31587743 BACKGROUND

• Gonzalez-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.

  PMID: 19413817 BACKGROUND

• Seim AR, Fagerhaug T, Ryen SM, Curran P, Saether OD, Myhre HO, Sandberg WS. Causes of cancellations on the day of surgery at two major university hospitals. Surg Innov. 2009 Jun;16(2):173-80. doi: 10.1177/1553350609335035. Epub 2009 May 21.

  PMID: 19460816 BACKGROUND

• Connor CW. Artificial Intelligence and Machine Learning in Anesthesiology. Anesthesiology. 2019 Dec;131(6):1346-1359. doi: 10.1097/ALN.0000000000002694.

  PMID: 30973516 BACKGROUND

• Vetter TR, Boudreaux AM, Ponce BA, Barman J, Crump SJ. Development of a Preoperative Patient Clearance and Consultation Screening Questionnaire. Anesth Analg. 2016 Dec;123(6):1453-1457. doi: 10.1213/ANE.0000000000001532.

  PMID: 27529323 BACKGROUND

• Manso M, Schmelz J, Aloia T. ERAS-Anticipated outcomes and realistic goals. J Surg Oncol. 2017 Oct;116(5):570-577. doi: 10.1002/jso.24791. Epub 2017 Sep 5.

  PMID: 28873504 BACKGROUND

• Committee on Standards and Practice Parameters; Apfelbaum JL, Connis RT, Nickinovich DG; American Society of Anesthesiologists Task Force on Preanesthesia Evaluation; Pasternak LR, Arens JF, Caplan RA, Connis RT, Fleisher LA, Flowerdew R, Gold BS, Mayhew JF, Nickinovich DG, Rice LJ, Roizen MF, Twersky RS. Practice advisory for preanesthesia evaluation: an updated report by the American Society of Anesthesiologists Task Force on Preanesthesia Evaluation. Anesthesiology. 2012 Mar;116(3):522-38. doi: 10.1097/ALN.0b013e31823c1067. No abstract available.

  PMID: 22273990 BACKGROUND

• Sabate S, Gomar C, Canet J, Castillo J, Villalonga A; Grupo ANESCAT. [Survey of anesthetic techniques used in Catalonia: results of the analysis of 23,136 anesthesias (2003 ANESCAT study)]. Rev Esp Anestesiol Reanim. 2008 Mar;55(3):151-9. doi: 10.1016/s0034-9356(08)70533-4. Spanish.

  PMID: 18401989 BACKGROUND

Related Links

• Population statistics published by the Statistical Agency of the Generalitat de Catalunya (g
• Institut Catalan de la Salut's 2018 activity report.

MeSH Terms

Conditions

Breast Neoplasms

Condition Hierarchy (Ancestors)

Neoplasms by Site; Neoplasms; Breast Diseases; Skin Diseases; Skin and Connective Tissue Diseases

Study Officials

• Ancor Serrano Afonso, MD, PhD

  Bellvitge University Hospital

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Target Duration: 2 Weeks
• Sponsor Type: OTHER
• Responsible Party: SPONSOR INVESTIGATOR
• PI Title: MD, PhD,. Principal Investigator, Senior Consultant in Anesthesiology.

Study Record Dates

• First Submitted: May 28, 2025
• First Posted: June 13, 2025
• Study Start: March 3, 2025
• Primary Completion: July 25, 2025
• Study Completion: July 25, 2025
• Last Updated: July 31, 2025

Record last verified: 2025-07

Locations

ES (1)