Advances in pediatric perioperative care using artificial intelligence.

PURPOSE OF THIS REVIEW: This article explores how artificial intelligence (AI) can be used to evaluate risks in pediatric perioperative care. It will also describe potential future applications of AI, such as models for airway device selection, controlling anesthetic depth and nociception during surgery, and contributing to the training of pediatric anesthesia providers. RECENT FINDINGS: The use of AI in healthcare has increased in recent years, largely due to the accessibility of large datasets, such as those gathered from electronic health records. Although there has been less focus on pediatric anesthesia compared to adult anesthesia, research is on- going, especially for applications focused on risk factor identification for adverse perioperative events. Despite these advances, the lack of formal external validation or feasibility testing results in uncertainty surrounding the clinical applicability of these tools. SUMMARY: The goal of using AI in pediatric anesthesia is to assist clinicians in providing safe and efficient care. Given that children are a vulnerable population, it is crucial to ensure that both clinicians and families have confidence in the clinical tools used to inform medical decision- making. While not yet a reality, the eventual incorporation of AI-based tools holds great potential to contribute to the safe and efficient care of our patients.

Use of artificial intelligence in paediatric anaesthesia: a systematic review.

Objectives: Although the development of artificial intelligence (AI) technologies in medicine has been significant, their application to paediatric anaesthesia is not well characterised. As the paediatric operating room is a data-rich environment that requires critical clinical decision-making, this systematic review aims to characterise the current use of AI in paediatric anaesthesia and to identify barriers to the successful integration of such technologies. Methods: This review was registered with PROSPERO (CRD42022304610), the international registry for systematic reviews. The search strategy was prepared by a librarian and run in five electronic databases (Embase, Medline, Central, Scopus, and Web of Science). Collected articles were screened by two reviewers. Included studies described the use of AI for paediatric anaesthesia (<18 yr old) within the perioperative setting. Results: From 3313 records identified in the initial search, 40 were included in this review. Identified applications of AI were described for patient risk factor prediction (24 studies; 60%), anaesthetic depth estimation (2; 5%), anaesthetic medication/technique decision guidance (2; 5%), intubation assistance (1; 2.5%), airway device selection (3; 7.5%), physiological variable monitoring (6; 15%), and operating room scheduling (2; 5%). Multiple domains of AI were discussed including machine learning, computer vision, fuzzy logic, and natural language processing. Conclusion: There is an emerging literature regarding applications of AI for paediatric anaesthesia, and their clinical integration holds potential for ultimately improving patient outcomes. However, multiple barriers to their clinical integration remain including a lack of high-quality input data, lack of external validation/evaluation, and unclear generalisability to diverse settings. Systematic review protocol: CRD42022304610 (PROSPERO).

Near-peer tutoring: an effective adjunct for virtual anatomy learning.

With recent shifts in medical education to the virtual setting during the COVID-19 pandemic, previous methods of teaching anatomy have been challenged. As such, we created the Medical Students' Society Anatomy Club (MAC), a student-led near-peer tutoring initiative providing virtual anatomy learning opportunities through interactive large and small group sessions using cadaveric prosection images and models. Sessions had high attendance rates and satisfaction among students. This pilot project demonstrated that near-peer teaching in a virtual learning environment can be an effective adjunct to traditional medical anatomy curricula.

Avec la récente transition vers l'enseignement virtuel pendant la pandémie de COVID-19, les méthodes traditionnelles d'enseigner l'anatomie devront être mises en question. À ce titre, nous avons créé le Medical Students' Society Anatomy Club (MAC), une initiative de tutorat par les pairs qui fournit des ressources d'apprentissage via des séances virtuelles interactives, en petits et en grands groupes, utilisant des images de dissections cadavériques et des modèles. Les séances ont démontré des taux de participation et de satisfaction élevés parmi les étudiants. Ce projet pilote montre que l'enseignement par les pairs dans un cadre virtuel peut être un complément très efficace aux programmes d'anatomie médicale traditionnels.

The Impact of Randomized Family-Centered Interventions on Family-Centered Outcomes in the Adult Intensive Care Unit: A Systematic Review.

Objective: To review the literature for randomized family-centered interventions with family-centered outcomes in the adult intensive care unit (ICU). Data Sources: We searched MEDLINE, EMBASE, PsycINFO, CINAHL, and the Cochrane Library database from inception until February 2023. Study Selection: We included articles involving randomized controlled trials (RCTs) in the adult critical care setting evaluating family-centered interventions and reporting family-centered outcomes. Data Extraction: We extracted data on author, year of publication, setting, number of participants, intervention category, intervention, and family-centered outcomes. Data Synthesis: There were 52 RCTs included in the analysis, mostly involving communication and receiving information (38%) and receiving care and meeting family member needs (38%). Nearly two-thirds of studies (N = 35; 67.3%) found improvements in at least 1 family-centered outcome. Most studies (N = 24/40; 60%) exploring the impact of family-centered interventions on mental health outcomes showed improvement. Improvements in patient-centered outcomes (N = 7/17; 41%) and healthcare worker outcomes (N = 1/5; 20%) were less commonly found. Conclusions: Family-centered interventions improve family-centered outcomes in the adult ICU and may be beneficial to patients and healthcare workers.

Understanding the effectiveness of consent processes and conversations in pediatric surgery: A systematic-scoping review.

BACKGROUND: The consent conversation in pediatric surgery is an essential part of pre-operative care which, when inadequate, can lead to significant adverse consequences for the child, parents, surgeon, other healthcare workers and the healthcare system. We reviewed the published literature on what key stakeholders perceive are the components of effective and ineffective consenting processes in pediatric surgery. METHODS: A medical librarian searched seven databases to retrieve articles looking at the informed consenting process in surgical care for the pediatric population. Two independent reviewers screened all publications and categorized them by stakeholder perspectives (patient/family, surgical team, other healthcare team, and hospital administration or policy maker). General study characteristics, interventions to improve consent and features of effective and ineffective consent conversations were extracted. RESULTS: 5079 titles and abstracts were screened, resulting in 88 full-text studies and 43 articles included in the final review. Most publications (51%) discussed informed consent only from the patient/family perspective, while 21% added surgeon's perspective. No study approached the consenting process from the perspective of all stakeholder groups. Effective consent components identified included use of multimedia, presence of multiple conversations prior to surgery, and individualized communication catered to unique family knowledge and needs. In contrast, ineffective conversations did not include a clear assessment of parental understanding, delivered too much information, and did not address parental anxiety. CONCLUSIONS: The literature on the consenting process in pediatric surgery is narrow in stakeholder perspectives. Our findings highlight gaps in the literature and opportunities to improve the informed consent processes prior to pediatric surgery.

The use of artificial intelligence and virtual reality in doctor-patient risk communication: A scoping review.

OBJECTIVES: While the development of artificial intelligence (AI) and virtual reality (VR) technologies in medicine has been significant, their application to doctor-patient communication is limited. As communicating risk is a challenging, yet essential, component of shared decision-making (SDM) in surgery, this review aims to explore the current use of AI and VR in doctor-patient surgical risk communication. METHODS: The search strategy was prepared by a medical librarian and run in 7 electronic databases. Articles were screened by a single reviewer. Included articles described the use of AI or VR applicable to surgical risk communication between patients, their families, and the surgical team. RESULTS: From 4576 collected articles, 64 were included in this review. Identified applications included decision support tools (15, 23.4%), tailored patient information resources (13, 20.3%), treatment visualization tools (17, 26.6%) and communication training platforms (19, 29.7%). Overall, these technologies enhance risk communication and SDM, despite heterogeneity in evaluation methods. However, improvements in the usability and versatility of these interventions are needed. CONCLUSIONS: There is emerging literature regarding applications of AI and VR to facilitate doctor-patient surgical risk communication. PRACTICE IMPLICATIONS: AI and VR hold the potential to personalize doctor-patient surgical risk communication to individual patients and healthcare contexts.