Citations

Abstract Pain medicine triage plays a crucial role in ensuring patients receive timely and appropriate care by scheduling them to the most suitable treatment path. However, the absence of standardized triage protocols in pain medicine often leads to inefficiencies, including delay of care and wastage of healthcare resources. This study aims to develop a rule-based automated referral triage system leveraging information from patients' medical notes for scheduling patients to specific procedures in the pain medicine department. The proposed triage system, grounded in the knowledge and expertise of clinical providers, processed referral order comments and referring provider notes by iteratively refining the Natural Language Processing (NLP) rules and post-processing rules through intensively reviewing 76 patients. A post-processing regression model was incorporated to further enhance the accuracy. To ensure alignment with real-world practices, the system was integrated into an electronic health record (EHR) platform for real-time application, streamlining scheduling workflows and enhancing usability in daily clinical settings. After three iterations, the proposed NLP and post-processing rules improved accuracy from 76.3 to 80.3% compared to machine learning (ML) approaches in the preliminary study. The post-processing model further increased accuracy to 84.2%. The implementation accuracy of 200 cases for the first 3 months was consistent with our prediction at 83.5%, which concluded that the improvement over ML models (p-value = 0.018) was statistically significant at 95% significance level. This study demonstrates the feasibility and benefits of a knowledge-driven approach to referral triage in specialized medical fields. It lays a foundation for others in building similar triaging solutions to other specialties.

Abstract Effective communication in the intensive care unit (ICU) is essential, particularly for patients with non-English language preference, yet timely access to professional interpreters remains limited. While artificial intelligence (AI)-based translation tools have been explored in outpatient and nonacute care settings, studies evaluating their use in acute care, environments such as the ICU remain limited. To address this gap, we developed AI-TransLATE (AI-enhanced Transition to Language-Agnostic Transcultural Engagement), a speech-based translation tool designed for multilingual communication in critical care settings. This study aimed to assess the interpretation quality of AI-TransLATE across four languages—Spanish, Chinese, Arabic, and Turkish—using scripted ICU scenarios. We created ICU communication scripts and recorded bilingual research team members simulating clinical interactions. Two independent bilingual evaluators assessed interpretation quality using a 5-point Likert scale across fluency, adequacy, meaning preservation, and severity of errors. Clarity and cultural appropriateness were also rated. Percentage agreement was used to assess interrater agreement. AI-TransLATE achieved acceptable composite scores (≥16/20) across all languages. Spanish and Turkish performed consistently well; Chinese and Arabic showed variability due to omissions and terminology errors. AI-TransLATE shows promise as a clinical communication tool, but further evaluation in real-world, unscripted ICU settings is needed.

Hypoplastic left heart syndrome (HLHS) is the most lethal congenital heart disease (CHD) whose genetic basis remains elusive, likely due to oligogenic complexity. To identify regulators of cardiomyocyte (CM) proliferation relevant to HLHS, we performed a genome-wide siRNA screen in human iPSC-derived CMs, revealing ribosomal protein (RP) genes as the most prominent effectors of CM proliferation. Whole-genome sequencing of 25 HLHS proband–parent trios similarly showed enrichment of rare RP gene variants, including a damaging RPS15A promoter variant shared in a familial CHD case. Cross-species functional analyses demonstrated that perturbation of RP genes impairs cardiac growth: knockdown of RPS15A, RPS17, RPL26L1, RPL39, or RPS15 reduced CM proliferation, caused cardiac malformations in Drosophila , and produced hypoplastic or dysfunctional hearts in zebrafish. Genetic interactions between RP genes and key cardiac transcription factors (TBX5 and NKX2–7) further support their developmental role. Importantly, p53 suppression or Hippo activation partially rescued RP deficiency phenotypes. Together, these findings implicate RP genes as critical regulators of cardiogenesis and candidate contributors to HLHS.

Abstract Preiser's disease (PD), or idiopathic avascular necrosis of the scaphoid, is a debilitating condition leading to wrist pain, dysfunction, and pan-carpal arthritis. While impaired scaphoid vascularity is central to its pathogenesis, identifying individuals at risk is challenging due to the morphological distortion of the scaphoid as the disease progresses. This study aims to investigate the association between a novel capitate morphology classification, scaphoid morphology, and their impact on PD prevalence and characteristics. We also re-evaluate negative ulnar variance (NUV) as a potential risk factor for PD. This retrospective case–control study included 34 PD patients and 340 age-matched controls. Capitate morphology was classified into Type I/II on anteroposterior (AP) radiographs based on capitotrapezoid–scaphocapitate (CT–SC) joint line angle and ratio. Scaphoid morphology was assessed via the waist index on contralateral healthy wrists. Radiographic measurements of ulnar variance and PD staging were also performed. Statistical analyses compared morphological prevalence and risk factors between groups. Type II capitate was significantly more prevalent in the PD group (35.3%) than in controls (17.1%, p = 0.018). Similarly, NUV was significantly higher in PD patients (29%) compared with controls (6.8%, p < 0.001). We found a strong correlation between Type II capitate and slender (Type II) scaphoid morphology in healthy wrists. No significant differences in age, gender, or affected side were observed. Interobserver and intraobserver agreements for capitate classification were substantial (kappa ≥0.882). Our study introduces a reliable radiographic method for classifying capitate morphology, which strongly correlates with intrinsic scaphoid shape and potential vascular vulnerability. Both Type II capitate morphology and NUV are significant predisposing factors for PD. These findings offer valuable insights for identifying at-risk individuals and improving understanding of PD's multifactorial etiology. Diagnostic Level III.

Intravascular lipomas are rare benign tumors composed of adipose tissue that originate from the walls of blood vessels. They most commonly arise from veins, are typically asymptomatic, and rarely occur in the lower extremities. When large, these tumors can cause symptoms related to venous obstruction, such as swelling and pain. We report a case of a 75-year-old man with an intravascular lipoma in the right common femoral vein, identified during evaluation of lower extremity swelling and poorly healing ulcers. Surgical resection was ultimately required. This case contributes to the few published reports of pathologically proven symptomatic intravascular lipomas involving the lower extremity veins. Comprehensive preoperative imaging played a critical role in characterizing the lesion. The case facilitates a discussion of key differential diagnoses, such as atypical lipomatous tumors/well-differentiated liposarcoma and leiomyosarcoma.