Elgazar, Abdelhamed

Variability in novel inflammatory markers (HBP and SAA) post-surgery could indicate ongoing perioperative inflammation. This pilot cohort study collected blood from 99 patients undergoing elective cardiac surgery at baseline, 24 hours, 7 days, and 3 months post-surgery. Inflammatory markers (HBP, SAA, PCT, CRP, IL-6) were measured with a point-of-care device. Demographic and clinical data were extracted from health records. Serum SAA increased significantly in the acute postoperative phase (M e [IQR];SAA baseline =81.1[87] vs SAA 24hr= 232.65[88.02];U[72]=2343,p<0.0001), remained elevated at 7 days (Me 7d =252.6[88.56];U[57]=1484,p<0.0001) and were still more pronounced than baseline at t 3m (Me 3m =118.44[101.52];U[38]=448,p=0.0008). HBP showed a significant rise at seven days (HBP baseline =45[26;89] vs HBP 7d =121[69.75;224.5]; U[56]=805,p<0.0001) then returned to near baseline by t 3m (Me 3m =32.5[15.75;98.5]). Traditional inflammatory markers PCT, CRP, and IL-6 demonstrated a rapid increase at t 24h and plateaued at t 7d . None of the biomarkers showed variability at baseline or postoperatively with preoperative status or postoperative complications. Cluster analysis of the inflammatory markers at 24 hours (t 24h ) identified distinct subgroups. Cluster #1-patients with a modest increase in all markers; Cluster#2 characterized with a robust increase in IL-6; Cluster #3 showed increase in CRP and decline in HBP; Cluster #4 showed a modest increase in IL-6 and decline in HBP; Cluster #5 represented a decline in both CRP and SAA. Patients in these clusters differ with respect to age, pre-existing peripheral artery disease, and borderline differences in perioperative acetaminophen use. SAA and HBP remain elevated longer than IL-6, CRP, and PCT after surgery, suggesting that inflammation may persist beyond 3 months.

Abstract Rationale Clear and accurate communication is essential in critical care, yet patients with non-English language preferences (NELP) often face limited access to professional interpreters. Although machine translation has been explored in healthcare, most studies have focused on written translation. Their use in real-time, two-way interpretation specifically for high-stakes ICU conversations remains largely unexamined. To bridge this gap, we developed AI-TransLATE (AI-enhanced Transition to Language-Agnostic Transcultural Engagement), a voice-to-voice multilingual interpretation tool designed to support real-time interactions in critical care. Following successful initial validation, we evaluated clinicians’ perceptions of its usability in simulated ICU encounters and compared its performance with commercially available AI tools, including Gemini and ChatGPT. Methods We developed three standardized ICU role-play scenarios focused on shared decision-making regarding ECMO, tracheostomy, and comfort care, designed to encourage natural, unscripted dialogue. Clinicians were asked to use the AI translation tools during these encounters in Spanish, Chinese, or Arabic, while a bilingual research team member acted as the patient’s family member. After each simulation, participants completed a post-session survey evaluating communication quality, satisfaction (using a 5-point Likert scale), and usability through the System Usability Scale (SUS). Results Eighteen clinicians participated, including residents, fellows, and attending physicians with an average of 3.6 ± 1.2 years of postgraduate experience. Fifty-four post-simulation surveys were completed across Arabic, Chinese, and Spanish languages comparing AI-TransLATE, ChatGPT, and Google Gemini. Participants rated the simulation as realistic across all cases (ECMO = 3.94 ± 0.66; Tracheostomy = 4.22 ± 0.43; Comfort Care = 4.06 ± 0.42; p = 0.32). Satisfaction was highest for AI-TransLATE (4.11 ± 0.68) and ChatGPT (4.00 ± 0.69) but lowest for Gemini (2.06 ± 1.00; p &lt; 0.001). Willingness to use in real life followed the same trend. (AI-TransLATE = 4.00 ± 0.69, ChatGPT = 3.89 ± 0.96, Gemini = 2.00 ± 1.03 (p &lt; 0.001)). SUS scores supported these findings (AI-TransLATE = 71.25 ± 13.35; ChatGPT = 72.22 ± 15.57; Gemini = 40.28 ± 21.30; p &lt; 0.001), corresponding to good usability for AI-TransLATE and ChatGPT and poor usability for Gemini. Clinicians mentioned interruptions, uneven translation flow, and difficulty judging accuracy, but appreciated it when the AI-TransLATE conveyed tone and intonation, enabling smoother, more natural communication. Conclusion Overall, AI-TransLATE and ChatGPT demonstrated strong usability and satisfaction, showing promise as clinical communication tools; however, further validation in real-world ICU settings is warranted, and data privacy and confidentiality remain important considerations. This abstract is funded by: Critical care research committee mayo clinic

Background: Surgical trauma disrupts hormone networks, but the duration required for these systems to recover remains unclear. We hypothesize that significant perioperative stress would trigger protracted abnormalities of the thyroid axis extending past 28 days. Methods: This retrospective exploratory study analyzed opportunistically obtained thyroid-related laboratory values (free T3 [FT3], free T4 [FT4], and thyroid-stimulating hormone [TSH]) and serum albumin from electronic medical records of patients undergoing CABG, AVR, or PCI between 2017 and 2022. Preprocedural baseline values were compared with post-procedural serum levels measured during the acute peri-procedural period (0–30 days), early recovery (31–90 days), intermediate recovery (91–180 days), late recovery (181–365 days), medium-term follow-up (1–2 years), and long-term follow-up (>2 years). Results: Free T3 demonstrated early suppression across all procedures, most pronounced in CABG during the acute peri-procedural period, with partial recovery at later timepoints. AVR showed moderate suppression at early and long-term follow-up, while PCI demonstrated minimal and inconsistent changes. Free T4 remained relatively stable across procedures, with limited significant post hoc differences after adjustment. TSH showed significant temporal variability in CABG and AVR but not in PCI. Serum albumin demonstrated marked early decline, most pronounced in CABG, with partial recovery over time, whereas AVR showed delayed long-term suppression. Data availability declined substantially at later timepoints across all biomarkers. Conclusions: In this retrospective exploratory analysis, CABG was associated with the most pronounced early perturbations in thyroid and albumin trajectories, while PCI and AVR demonstrated more heterogeneous temporal patterns. These findings are hypothesis-generating and should be interpreted cautiously given non-protocolized laboratory follow-up, substantial missingness, and potential selection bias.

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.

Background/Objectives: Treating critically ill patients is complex and often subjective. This study investigates adherence to clinical guidelines for sepsis among different providers. Considering the strengths of the recommendations, we hypothesize that heterogeneity in the decision-making process will be low and independent of provider background and psychological makeup. Methods: This cohort study used two clinical vignettes of sepsis. Providers were given standardized treatment plans for 7 days, and their responses were recorded. Demographical, professional, and psychological (ambiguity tolerance, defensiveness, anxiety due to uncertainty, risk-taking behavior, decision styles, and optimism) variables were acquired. Results: Crystalloids were commonly used in both vignettes. Pressor engagement, especially norepinephrine, increased significantly after the third day. Providers recommended antibiotics and no provider stopped antibiotic therapy. Cluster analysis revealed no differences in therapy implementation among provider types, but some differences existed between the two vignettes. Cluster #1 was characterized by the implementation of early light bundle therapy combined with the use of pressors and a notable enhancement in therapies by the fifth day (Early Cluster). Cluster #2 (Minimalists) involved consistent engagement only in light bundle therapy throughout the treatment period. Cluster #3 (Escalation) comprised providers who rapidly escalated treatment using multiple different modalities. Cluster #3 stood out as most providers were female, non-MD, with significant ICU duties, and enhanced rational thinking. Conclusions: Providers differ in implementation styles of the sepsis treatment standard based on types of therapies selected not studied psychological variables.