Overcoming language barriers in pediatric care: a multilingual, AI-driven curriculum for global healthcare education.

Background: Online medical education often faces challenges related to communication and comprehension barriers, particularly when the instructional language differs from the healthcare providers' and caregivers' native languages. Our study addresses these challenges within pediatric healthcare by employing generative language models to produce a linguistically tailored, multilingual curriculum that covers the topics of team training, surgical procedures, perioperative care, patient journeys, and educational resources for healthcare providers and caregivers. Methods: An interdisciplinary group formulated a video curriculum in English, addressing the nuanced challenges of pediatric healthcare. Subsequently, it was translated into Spanish, primarily emphasizing Latin American demographics, utilizing OpenAI's GPT-4. Videos were enriched with synthetic voice profiles of native speakers to uphold the consistency of the narrative. Results: We created a collection of 45 multilingual video modules, each ranging from 3 to 8 min in length and covering essential topics such as teamwork, how to improve interpersonal communication, "How I Do It" surgical procedures, as well as focused topics in anesthesia, intensive care unit care, ward nursing, and transitions from hospital to home. Through AI-driven translation, this comprehensive collection ensures global accessibility and offers healthcare professionals and caregivers a linguistically inclusive resource for elevating standards of pediatric care worldwide. Conclusion: This development of multilingual educational content marks a progressive step toward global standardization of pediatric care. By utilizing advanced language models for translation, we ensure that the curriculum is inclusive and accessible. This initiative aligns well with the World Health Organization's Digital Health Guidelines, advocating for digitally enabled healthcare education.

Paediatric sleep apnea event prediction using nasal air pressure and machine learning.

Sleep-disordered breathing is an important health issue for children. The objective of this study was to develop a machine learning classifier model for the identification of sleep apnea events taken exclusively from nasal air pressure measurements acquired during overnight polysomnography for paediatric patients. A secondary objective of this study was to differentiate site of obstruction exclusively from hypopnea event data using the model. Computer vision classifiers were developed via transfer learning to either normal breathing while asleep, obstructive hypopnea, obstructive apnea or central apnea. A separate model was trained to identify site of obstruction as either adeno-tonsillar or tongue base. In addition, a survey of board-certified and board-eligible sleep physicians was completed to compare clinician versus model classification performance of sleep events, and indicated very good performance of our model relative to human raters. The nasal air pressure sample database available for modelling comprised 417 normal, 266 obstructive hypopnea, 122 obstructive apnea and 131 central apnea events derived from 28 paediatric patients. The four-way classifier achieved a mean prediction accuracy of 70.0% (95% confidence interval [67.1-72.9]). Clinician raters correctly identified sleep events from nasal air pressure tracings 53.8% of the time, whereas the local model was 77.5% accurate. The site of obstruction classifier achieved a mean prediction accuracy of 75.0% (95% confidence interval [68.7-81.3]). Machine learning applied to nasal air pressure tracings is feasible and may exceed the diagnostic performance of expert clinicians. Nasal air pressure tracings of obstructive hypopneas may "encode" information regarding the site of obstruction, which may only be discernable by machine learning.

Aspiration does not mean the end of a breast-feeding relationship.

OBJECTIVE: Breastfeeding is widely recommended as optimal nutrition for infants. However, there are no known publications on the impact of prandial aspiration of breast milk fed infants with dysphagia. The goal of this study was to assess pulmonary outcomes in infants with dysphagia who were given medical clearance for intake of breast milk. METHODS: This retrospective cohort study included review of 80 infants examined between August 2016 to March 2021. Patients were evaluated by an interdisciplinary team of providers in a tertiary pediatric aerodigestive center. Patient inclusion criteria included a VFSS with documented aspiration or penetration with thin liquids. Participants met inclusion criteria if given medical clearance for intake of breast milk despite aspiration risk. Pulmonary health was monitored for three months following medical clearance for the consumption of breast milk. Pulmonary illness was defined as development of bronchiolitis, wheezing, unexplained stridor during feeding, croup, pneumonia, or persistent bacterial bronchitis requiring medical intervention. RESULTS: Forty-three males (54%) and 37 females (46%) enrolled in the study with an age range of 1 month-6 months corrected age. Mean age at initial VFSS was 3.6 months. Twenty-six out of 80 (32.5%) had a report of a mild cough but did not require intervention. Eight out of 80 (10%) received a diagnosis of a pulmonary illness. Seventy-two out of 80 (90%) did not report pulmonary illness. CONCLUSION: This pilot study reveals that the majority (90%) of this single institution, small sample size cohort of breast milk fed infants with documented oropharyngeal dysphagia remained healthy despite continued intake of breast milk. Prospective investigation is warranted to follow pulmonary health outcomes longitudinally and a head to head comparative study would be helpful to identify whether there were indeed significant changes to pulmonary health according to differential feeding regimens offered and followed.

A quality study of family-centered care coordination to improve care for children undergoing tracheostomy and the quality of life for their caregivers.

IMPORTANCE: Approximately 4000 U.S. children undergo tracheostomy yearly [1], and these surgeries often result in hospital re-admissions that have definite cost and caregiver burdens due to complications that are avoidable with proper training and support. OBJECTIVE: To assess the impact of a Family-Centered Care Coordination (FCCC) program on the quality of care received by children undergoing tracheostomy and their caregivers. DESIGN: Caregivers of children undergoing tracheostomies from January 2012 to January 2013 and then a different set of caregivers of children undergoing tracheostomies from January 2015 to January 2016 completed both the Pediatric Tracheostomy Health Status Instrument (PTHSI) 1 month after discharge and the Medical Complications Associated with Pediatric Tracheostomy (MCAT) questionnaire 6 months after initial tracheostomy. To assess complication rates, these same sets of caregivers were asked to complete the MCAT and only those who provided complete medical data for all 6 months were included for comparative analysis. SETTING: The PTHSI and MCAT were administered at Massachusetts Eye and Ear in a hospital setting. PARTICIPANTS: Ten caregivers of children undergoing tracheostomies completed the PTHSI before FCCC program implementation and12 caregivers then completed the PTHSI after FCCC implementation. For each of the 2 groups, 5 caregivers provided complete data on the MCAT questionnaires. EXPOSURES: FCCC is a collection of programs, policies, and tools designed to ensure safe transition home for children undergoing tracheostomies, reduce re-admission rates, and minimize "caregiver burden". MAIN OUTCOMES AND MEASURES: The PTHSI is a validated caregiver quality of life instrument that was supplemented by the MCAT which records post-discharge medical issues following tracheostomy that relate specifically to the tracheotomy placement. RESULTS: The time to first follow-up appointment decreased from 6.4 weeks (SD = 1.52) to 6 days (SD = 0.18) with FCCC implementation. The total MCAT scores decreased from 15.2 (SD = 1.1) to 1.3 (SD = 1.3) (Wilcoxon sum rank test: P < 0.016) whereas neither PTHSI scores (P = 0.32) nor the specific caregiver burden domain (P = 0.18) demonstrated a significant change. CONCLUSIONS: and Relevance: By reducing the time to first follow-up after tracheostomy and by optimizing caregiver tracheostomy tube care and teaching, children's quality of care and caregiver burden can be significantly improved.