GAPS phase II: development and pilot results of the global assessment in pediatric surgery, an evidence-based pediatric surgical capacity assessment tool for low-resource settings.

PURPOSE: Pediatric surgical care in low- and middle-income countries is often hindered by systemic gaps in healthcare resources, infrastructure, training, and organization. This study aims to develop and validate the Global Assessment of Pediatric Surgery (GAPS) to appraise pediatric surgical capacity and discriminate between levels of care across diverse healthcare settings. METHODS: The GAPS Version 1 was constructed through a synthesis of existing assessment tools and expert panel consultation. The resultant GAPS Version 2 underwent international pilot testing. Construct validation categorized institutions into providing basic or advanced surgical care. GAPS was further refined to Version 3 to include only questions with a > 75% response rate and those that significantly discriminated between basic or advanced surgical settings. RESULTS: GAPS Version 1 included 139 items, which, after expert panel feedback, was expanded to 168 items in Version 2. Pilot testing, in 65 institutions, yielded a high response rate. Of the 168 questions in GAPS Version 2, 64 significantly discriminated between basic and advanced surgical care. The refined GAPS Version 3 tool comprises 64 questions on: human resources (9), material resources (39), outcomes (3), accessibility (3), and education (10). CONCLUSION: The GAPS Version 3 tool presents a validated instrument for evaluating pediatric surgical capabilities in low-resource settings.

Exploring the digital divide: results of a survey informing mobile application development.

Introduction: Mobile health apps risk widening health disparities if they overlook digital inclusion. The digital divide, encompassing access, familiarity, and readiness, poses a significant barrier to medical interventions. Existing literature lacks exploration of the digital divide's contributing factors. Hence, data are needed to comprehend the challenges in developing inclusive health apps. Methods: We created a survey to gauge internet and smartphone access, smartphone familiarity, and readiness for using mobile health apps among caregivers of pediatric patients in tertiary care. Open-ended questions solicited feedback and suggestions on mobile health applications. Responses were categorized by similarity and compared. Developed with patient partners, the survey underwent cognitive testing and piloting for accuracy. Results: Data from 209 respondents showed that 23% were affected by the digital divide, mainly due to unfamiliarity with digital skills. Among 49 short text responses about health app concerns, 31 mentioned security and confidentiality, with 7 mentioning the impersonal nature of such apps. Desired features included messaging healthcare providers, scheduling, task reminders, and simplicity. Conclusions: This study underscores a digital divide among caregivers of pediatric patients, with nearly a quarter affected primarily due to a lack of digital comfort. Respondents emphasized user-friendliness and online security for health apps. Future apps should prioritize digital inclusion by addressing the significant barriers and carefully considering patient and family concerns.

Implementation of a Global Pediatric Trauma Course in an Upper Middle-Income Country: A Pilot Study.

INTRODUCTION: Over 90% of pediatric trauma deaths occur in low- and middle-income countries (LMICs), yet pediatric trauma-focused training remains unstandardized and inaccessible, especially in LMICs. In Brazil, where trauma is the leading cause of death for children over age 1, we piloted the first global adaptation of the Trauma Resuscitation in Kids (TRIK) course and assessed its feasibility. METHODS: A 2-day simulation-based global TRIK course was hosted in Belo Horizonte in October 2022, led by one Brazilian and four Canadian instructors. The enrollment fee was $200 USD, and course registration sold out in 4 d. We administered a knowledge test before and after the course and a postcourse self-evaluation. We recorded each simulation to assess participants' performance, reflected in a team performance score. Groups received numerical scores for these three areas, which were equally weighted to calculate a final performance score. The scores given by the two evaluators were then averaged. As groups performed the specific simulations in varying orders, the simulations were grouped into four time blocks for analysis of performance over time. Statistical analysis utilized a combination of descriptive analysis, Wilcoxon signed-rank tests, Kruskal-Wallis tests, and Wilcoxon rank-sum tests. RESULTS: Twenty-one surgeons (19 pediatric, one trauma, one general) representing four of five regions in Brazil consented to study participation. Women comprised 76% (16/21) of participants. Overall, participants scored higher on the knowledge assessment after the course (68% versus 76%; z = 3.046, P < 0.001). Participants reported improved knowledge for all tested components of trauma management (P < 0.001). The average simulation performance score increased from 66% on day 1% to 73% on day 2, although this increase was not statistically significant. All participants reported they were more confident managing pediatric trauma after the course and would recommend the course to others. CONCLUSIONS: Completion of global TRIK improved surgeons' confidence, knowledge, and clinical decision-making skills in managing pediatric trauma, suggesting a standardized course may improve pediatric trauma care and outcomes in LMICs. We plan to more closely address cost, language, and resource barriers to implementing protocolized trauma training in LMICs with the aim to improve patient outcomes and equity in trauma care globally.

Essential surgery delivery in the Northern Kivu Province of the Democratic Republic of the Congo.

INTRODUCTION: Surgical services are an essential part of a functional healthcare system, but the Lancet Commission of Global Surgery (LCoGS) indicators of surgical capacity such as perioperative workforce and surgical volume are unknown in many low- and middle-income countries (LMICs) including the Democratic Republic of Congo (DRC). We aimed to determine the surgical capacity and its associated factors within the DRC. METHODS: Hospitals were assessed in the North Kivu province of the DRC. Hospital characteristics and surgical rates were determined using the WHO-PGSSC hospital assessment tool and operating room (OR) registries. The primary outcome of interest was the number of Bellwether operations (i.e. Caesarean sections, laparotomies, and external fixation for bone fractures) per 100,000 people. Univariate and multiple linear regressions were performed. Primary predictors were the number of trained surgeons, anaesthesiologists, and obstetricians (SAOs) and the number of perioperative providers (including clinical officers and nurse anaesthetists) per 100,000 people. RESULTS: Twenty-eight hospitals in North Kivu were assessed over one year in 2021; 24 (86%) were first-level referral health centres while 4 (14%) were second-level referral hospitals. In total, 11,176 Bellwether procedures were performed in the region in one year. Rates per 100,000 people were 1,461 Bellwether surgical interventions, 1.05 SAOs, and 13.1 perioperative providers. In univariate linear regression analysis, each additional SAO added 239 additional cases annually (p = 0.023), while each additional perioperative provider added 110 cases annually (p < 0.001). In our multiple regression analysis adjusting for other hospital services, the association between workforce and Bellwether surgeries was no longer significant. CONCLUSIONS: The surgical workforce in DRC did not meet the LCoGS benchmark of 20 SAOs per 100,000 people but was not an independent predictor of surgical capacity. Major investment is needed to simultaneously bolster healthcare facilities and increase surgical workforce training.

The Impact of Educational Materials on Parental Anxiety and Productivity: A Clinical Trial in Pediatric Appendicitis.

OBJECTIVES: There is limited literature on how acute appendicitis, the most common acute children's surgical illness, affects the family. We conducted a prospective study to assess the impact of educational materials on parents' anxiety and productivity during the child's illness. METHODS: A quasi-experimental clinical trial was conducted among parents of children undergoing laparoscopic appendectomy. In Phase I, parents received the standard explanations at diagnosis and throughout the postoperative period. In Phase II, parents also received a comprehensive educational brochure on pediatric appendicitis at diagnosis. The primary outcome, parental preoperative anxiety, was assessed using the Amsterdam Preoperative Anxiety and Information Scale (APAIS). The secondary outcome, parental productivity, was evaluated through a post-recovery online questionnaire based on the Productivity and Disease Questionnaire (PRODISQ). Baseline characteristics and outcomes were compared between the two cohorts using t-tests, Mann-Whitney, chi-square, or Fischer's exact test as appropriate. RESULTS: Phases I and II included 67 and 66 families, respectively. Patient demographics and disease severity were similar between both groups. Of the 53 parents (80.3%) in Phase II who answered the postoperative questionnaire, most recommended the booklet (96.2%), as it decreased their stress (78.0%) and enhanced their understanding of appendicitis (94.1%). However, the two groups showed similar preoperative anxiety levels and postoperative productivity loss. CONCLUSIONS: Educational materials increased satisfaction with surgical care but did not mitigate the high parental preoperative anxiety levels and postoperative productivity loss. Additional research is required to elucidate interventions that may improve these important patient and family-centered outcomes. TYPE OF STUDY: Non-Randomized Clinical Trial. LEVEL OF EVIDENCE: II.

ChatGPT: What Every Pediatric Surgeon Should Know About Its Potential Uses and Pitfalls.

ChatGPT - currently the most popular generative artificial intelligence system - has been revolutionizing the world and healthcare since its release in November 2022. ChatGPT is a conversational chatbot that uses machine learning algorithms to enhance its replies based on user interactions and is a part of a broader effort to develop natural language processing that can assist people in their daily lives by understanding and responding to human language in a useful and engaging way. Thus far, many potential applications within healthcare have been described, despite its relatively recent release. This manuscript offers the pediatric surgical community a primer on this new technology and discusses some initial observations about its potential uses and pitfalls. Moreover, it introduces the perspectives of medical journals and surgical societies regarding the use of this artificial intelligence chatbot. As ChatGPT and other large language models continue to evolve, it is the responsibility of the pediatric surgery community to stay abreast of these changes and play an active role in safely incorporating them into our field for the benefit of our patients. LEVEL OF EVIDENCE: V.

Adaptation, Translation, and Validation of a Patient-Reported Experience Measure for Children and Young People for the Canadian Context.

BACKGROUND: Patient-reported experience measures (PREMs) evaluate children's and young people's (CYP) perceptions of care. An important PREM developed with and for children was created in London, UK. Given the absence of similar North American instruments, we aimed to adapt, translate, and linguistically validate this instrument for use in a Canadian pediatric outpatient setting. METHODS: A qualitative design was used, involving CYP and their parents/caregivers. Phase 1 entailed the English survey adaptation using think-aloud testing, revision, and cognitive testing. Phase 2 involved translation into French, revision and back-translation, and cognitive testing. Phase 3 encompassed a cross-validation of the English and French versions of the adapted instrument. RESULTS: Fifty-five children in 3 age groups (8-11y, 12-13y, 14-16y) participated in creating the Canadian PREM. In Phases 1 and 2, 41 children participated in reviewing and updating specific questions in the instrument, resulting in adjustments and revisions based on their feedback. In Phase 3, 14 bilingual children linguistically validated the PREM instrument. CONCLUSIONS: This study reports the development of the first Canadian PREM specifically tailored to children. By incorporating the perspectives and preferences of CYP in clinical practice, this approach has the potential to amplify the delivery of patient-centered care for this vulnerable population and ensure that the needs and voices of CYP are acknowledged. LEVEL OF EVIDENCE: V, Therapeutic.

Improving Pediatric Trauma Education by Teaching Non-technical Skills: A Randomized Controlled Trial.

BACKGROUND: Pediatric trauma is a significant cause of child mortality, and the absence of non-technical skills (NTS) among health providers is linked with errors in patients' care. In this study, we evaluate the effectiveness of a structured debriefing protocol in enhancing NTS during pediatric trauma simulation. METHODS: A total of 45 medical students were successfully recruited from two medical schools, one in Brazil and one in Canada. Medical students were assigned to a control (N = 20) or intervention group (N = 25) in a randomized control trial. Following simulated scenarios, participants in the intervention group underwent NTS debriefing, while the control received standard debriefing based on the Advanced Trauma Life Support (ATLS) protocol. Students' confidence, NTS level, and performance were measured through self-assessment surveys, the Non-Technical Skills for Surgeons (NOTSS) score, and adherence to the trauma protocol, respectively. Baseline characteristics and outcomes were compared using t-tests, Mann-Whitney, Wilcoxon signed-rank Kruskal-Wallis, ANOVA, and a repeated-measures ANCOVA. A significance level was set at p < 0.05. RESULTS: The workshop increased students' confidence in leading trauma resuscitation regardless of their assignment to condition. While controlling for covariates, students in the intervention group significantly improved their overall NOTSS compared to those in the control and in all categories: situational awareness, decision-making, communication and teamwork, and leadership. The intervention teams also demonstrated a significant increase in completing trauma protocol steps. CONCLUSION: Implementing structured debriefing focusing on NTS enhanced these skills and improved adherence to protocol among medical students managing pediatric trauma-simulated scenarios. These findings support integrating NTS training in pediatric trauma education. LEVEL OF EVIDENCE: I.

Using Artificial Intelligence to Label Free-Text Operative and Ultrasound Reports for Grading Pediatric Appendicitis.

PURPOSE: Data science approaches personalizing pediatric appendicitis management are hampered by small datasets and unstructured electronic medical records (EMR). Artificial intelligence (AI) chatbots based on large language models can structure free-text EMR data. We compare data extraction quality between ChatGPT-4 and human data collectors. METHODS: To train AI models to grade pediatric appendicitis preoperatively, several data collectors extracted detailed preoperative and operative data from 2100 children operated for acute appendicitis. Collectors were trained for the task based on satisfactory Kappa scores. ChatGPT-4 was prompted to structure free text from 103 random anonymized ultrasound and operative records in the dataset using the set variables and coding options, and to estimate appendicitis severity grade from the operative report. A pediatric surgeon then adjudicated all data, identifying errors in each method. RESULTS: Within the 44 ultrasound (42.7%) and 32 operative reports (31.1%) discordant in at least one field, 98% of the errors were found in the manual data extraction. The appendicitis grade was erroneously assigned manually in 29 patients (28.2%), and by ChatGPT-4 in 3 (2.9%). Across datasets, the use of the AI chatbot was able to avoid misclassification in 59.2% of the records including both reports and extracted data approximately 40 times faster. CONCLUSION: AI chatbot significantly outperformed manual data extraction in accuracy for ultrasound and operative reports, and correctly assigned the appendicitis grade. While wider validation is required and data safety concerns must be addressed, these AI tools show significant promise in improving the accuracy and efficiency of research data collection. LEVELS OF EVIDENCE: Level III.

Patient-Centered Surgical Care for Children in Low and Lower-Middle Income Countries (LMICs) - A Systematic Scoping Review of the Literature.

PURPOSE: Studies exploring patient-centered care (PCC) in pediatric surgery have been disproportionately concentrated in high-income countries. This review aims to characterize the adoption of key PCC domains in low and lower-middle income countries (LMICs). METHODS: Seven databases were searched from inception until January 2023 to retrieve relevant articles in pediatric surgery in LMICs. We focused on six key PCC domains: patient-reported outcomes (PROs), patient-reported experiences (PREs), shared decision-making (SDM), patient/parent education, patient/parent satisfaction, and informed consent. RESULTS: Of 8050 studies screened, 230 underwent full-text review, and 48 were finally included. Most were single-center (87.5%), cross-sectional studies (41.7%) from the South-East Asian (35.4%) and Eastern Mediterranean regions (33.3%). Studies most frequently focused on postoperative care (45.8%) in pediatric general surgery (18.8%), and included 1-3 PCC domains. PREs (n = 30), PROs (n = 16) and patient/parent satisfaction (n = 16) were most common. Informed consent (n = 2) and SDM (n = 1) were least studied. Only 13 studies directly elicited children's perspectives. Despite all studies originating in LMICs, 25% of first and 17.8% of senior authors lacked LMIC affiliations. CONCLUSION: The adoption of PCC in LMICs appears limited, focusing predominantly on PROs and PREs. Other domains such as informed consent and SDM are rarely addressed, and the voice of children and young people is rarely heard in their care. Opportunities to enhance PCC in LMICs abound, with the potential to improve the surgical care of children in resource-limited settings. LEVEL OF EVIDENCE: III.

The State of Artificial Intelligence in Pediatric Surgery: A Systematic Review.

BACKGROUND: Artificial intelligence (AI) has been recently shown to improve clinical workflows and outcomes - yet its potential in pediatric surgery remains largely unexplored. This systematic review details the use of AI in pediatric surgery. METHODS: Nine medical databases were searched from inception until January 2023, identifying articles focused on AI in pediatric surgery. Two authors reviewed full texts of eligible articles. Studies were included if they were original investigations on the development, validation, or clinical application of AI models for pediatric health conditions primarily managed surgically. Studies were excluded if they were not peer-reviewed, were review articles, editorials, commentaries, or case reports, did not focus on pediatric surgical conditions, or did not employ at least one AI model. Extracted data included study characteristics, clinical specialty, AI method and algorithm type, AI model (algorithm) role and performance metrics, key results, interpretability, validation, and risk of bias using PROBAST and QUADAS-2. RESULTS: Authors screened 8178 articles and included 112. Half of the studies (50%) reported predictive models (for adverse events [25%], surgical outcomes [16%] and survival [9%]), followed by diagnostic (29%) and decision support models (21%). Neural networks (44%) and ensemble learners (36%) were the most commonly used AI methods across application domains. The main pediatric surgical subspecialties represented across all models were general surgery (31%) and neurosurgery (25%). Forty-four percent of models were interpretable, and 6% were both interpretable and externally validated. Forty percent of models had a high risk of bias, and concerns over applicability were identified in 7%. CONCLUSIONS: While AI has wide potential clinical applications in pediatric surgery, very few published AI algorithms were externally validated, interpretable, and unbiased. Future research needs to focus on developing AI models which are prospectively validated and ultimately integrated into clinical workflows. LEVEL OF EVIDENCE: 2A.