Citations

AbstractBackgroundPrimary cutaneous γδ T‐cell lymphoma (CGD‐CTL) is a rare malignancy that classically exhibits an aggressive clinical phenotype.ObjectivesReview cases of mycosis fungoides with a γδ phenotype that demonstrated an indolent clinical course.MethodsRetrospective review of patients diagnosed with MF with a γδ phenotype and an indolent clinical course between 2018 and 2022 treated at the University of Utah.ResultsFive patients ages 4‐81 years old were identified. All presented with clinically persistent patch or plaque‐stage disease, and histopathology showed primarily epidermotropic infiltrates positive for TCR delta via immunostaining. None of these patients have required aggressive treatment with multiagent chemotherapy.ConclusionsThere exists a subset of indolent CGD‐TCL patients who are clinicopathologically distinct from classic CGD‐CTL and clinically resembling indolent MF. Therefore, we prefer the term “MF with γδ phenotype” for these rare cases.

Abstract Objective SNOMED CT provides a standardized terminology for clinical concepts, allowing cohort queries over heterogeneous clinical data including Electronic Health Records (EHRs). While it is intuitive that missing and inaccurate subtype (or is-a) relations in SNOMED CT reduce the recall and precision of cohort queries, the extent of these impacts has not been formally assessed. This study fills this gap by developing quantitative metrics to measure these impacts and performing statistical analysis on their significance. Material and Methods We used the Optum de-identified COVID-19 Electronic Health Record dataset. We defined micro-averaged and macro-averaged recall and precision metrics to assess the impact of missing and inaccurate is-a relations on cohort queries. Both practical and simulated analyses were performed. Practical analyses involved 407 missing and 48 inaccurate is-a relations confirmed by domain experts, with statistical testing using Wilcoxon signed-rank tests. Simulated analyses used two random sets of 400 is-a relations to simulate missing and inaccurate is-a relations. Results Wilcoxon signed-rank tests from both practical and simulated analyses (P-values < .001) showed that missing is-a relations significantly reduced the micro- and macro-averaged recall, and inaccurate is-a relations significantly reduced the micro- and macro-averaged precision. Discussion The introduced impact metrics can assist SNOMED CT maintainers in prioritizing critical hierarchical defects for quality enhancement. These metrics are generally applicable for assessing the quality impact of a terminology’s subtype hierarchy on its cohort query applications. Conclusion Our results indicate a significant impact of missing and inaccurate is-a relations in SNOMED CT on the recall and precision of cohort queries. Our work highlights the importance of high-quality terminology hierarchy for cohort queries over EHR data and provides valuable insights for prioritizing quality improvements of SNOMED CT's hierarchy.

AbstractQuantitative susceptibility mapping (QSM) is a tool for mapping tissue susceptibility. Using QSM for functional brain mapping, it is possible to directly quantify blood‐oxygen‐level‐dependent (BOLD) susceptibility changes. This study presents a submillimeter functional QSM (fQSM) approach compared to BOLD fMRI from data acquired with 3D gradient‐echo echo planar imaging (EPI) at ultra‐high field. Complex EPI data were acquired in nine healthy subjects with varying temporal and spatial resolutions and used for BOLD fMRI and for fQSM. Right‐hand finger tapping experiments were performed as well as one measurement with intentional subject movement. Susceptibility maps were computed using 3D path‐based unwrapping, the variable‐kernel sophisticated harmonic artifact reduction for phase data, and the streaking artifact reduction for QSM algorithm. Functional data analysis included general linear modeling and computation of z‐scores. Submillimeter data were denoised using NOise reduction with DIstribution Corrected (NORDIC), which improved z‐scores in the motor cortex for fQSM and fMRI. An expected increase in BOLD fMRI signal and corresponding decrease in magnetic susceptibility was observed in sensorimotor areas during active periods. For all experiments, fQSM showed smaller activation regions compared with fMRI. The percentage of high negative t‐values localized in the cortex was higher for fQSM (52%) than for positive or negative t‐values for fMRI (45%). For the scans with intentional motion, movement exceeded the size of a voxel, but paradigm dependent signal evolution could be recovered using motion correction. In conclusion, this study demonstrates the feasibility of submillimeter whole‐brain fQSM with voxel volume of 0.53 μL. In comparison to traditional BOLD fMRI, fQSM provided improved localization of brain activation within the cortex, especially in submillimeter 3D EPI sequences.

Abstract Background: HPV vaccine is an effective measure to prevent and control the diseases caused by Human Papillomavirus (HPV). This study addresses the development of VaxBot-HPV, a chatbot aimed at improving health literacy and promoting vaccination uptake by providing information and answering questions about the HPV vaccine; Methods: We constructed the knowledge base (KB) for VaxBot-HPV, which consists of 451 documents from biomedical literature and web sources on the HPV vaccine. We extracted 202 question-answer pairs from the KB and 39 questions generated by GPT-4 for training and testing purposes. To comprehensively understand the capabilities and potential of GPT-based chatbots, three models were involved in this study : GPT-3.5, VaxBot-HPV, and GPT-4. The evaluation criteria included answer relevancy and faithfulness; Results: VaxBot-HPV demonstrated superior performance in answer relevancy and faithfulness compared to baselines (Answer relevancy: 0.85; Faithfulness: 0.97) for the test questions in KB, (Answer relevancy: 0.85; Faithfulness: 0.96) for GPT generated questions; Conclusions: This study underscores the importance of leveraging advanced language models and fine-tuning techniques in the development of chatbots for healthcare applications, with implications for improving medical education and public health communication.

PURPOSE Imlunestrant is a next-generation oral selective estrogen receptor (ER) degrader designed to deliver continuous ER target inhibition, including in ESR1- mutant breast cancer. This phase Ia/b trial determined the recommended phase II dose (RP2D), safety, pharmacokinetics, and efficacy of imlunestrant, as monotherapy and in combination with targeted therapy, in ER-positive (ER+) advanced breast cancer (ABC) and endometrial endometrioid cancer. The ER+/human epidermal growth factor receptor 2–negative (HER2–) ABC experience is reported here. METHODS An i3+3 dose-escalation design was used, followed by dose expansions of imlunestrant as monotherapy or in combination with abemaciclib with or without aromatase inhibitor (AI), everolimus, or alpelisib. Imlunestrant was administered orally once daily and with the combination partner per label. RESULTS Overall, 262 patients with ER+/HER2– ABC were treated (phase Ia, n = 74; phase Ib, n = 188). Among patients who received imlunestrant monotherapy (n = 114), no dose-limiting toxicities or discontinuations occurred. At the RP2D (400 mg once daily), patients (n = 51) reported grade 1-2 nausea (39.2%), fatigue (39.2%), and diarrhea (29.4%). Patients at RP2D had received previous cyclin-dependent kinase 4/6 inhibitor (CDK4/6i; 92.2%), fulvestrant (41.2%), and chemotherapy (29.4%) for ABC and achieved a median progression-free survival (mPFS) of 7.2 months (95% CI, 3.7 to 8.3). Among patients who received imlunestrant + abemaciclib (n = 42) and imlunestrant + abemaciclib + AI (n = 43), most (69.4%) were treatment-naïve for ABC; all were CDK4/6i-naïve. Patients treated with imlunestrant + everolimus (n = 42)/alpelisib (n = 21) had received previous CDK4/6i (100%), fulvestrant (34.9%), and chemotherapy (17.5%) for ABC. No new safety signals or interactions with partnered drugs were observed. The mPFS was 19.2 months (95% CI, 13.8 to not available) for imlunestrant + abemaciclib and was not reached for imlunestrant + abemaciclib + AI. The mPFS with imlunestrant + everolimus/alpelisib was 15.9 months (95% CI, 11.3 to 19.1)/9.2 months (95% CI, 3.7 to 11.1). Antitumor activity was evident regardless of ESR1 mutation status. CONCLUSION Imlunestrant, as monotherapy or in combination with targeted therapy, had a manageable safety profile with evidence of preliminary antitumor activity in ER+/HER2– ABC.

Abstract Objective In acupuncture therapy, the accurate location of acupoints is essential for its effectiveness. The advanced language understanding capabilities of large language models (LLMs) like Generative Pre-trained Transformers (GPTs) and Llama present a significant opportunity for extracting relations related to acupoint locations from textual knowledge sources. This study aims to explore the performance of LLMs in extracting acupoint-related location relations and assess the impact of fine-tuning on GPT’s performance. Materials and Methods We utilized the World Health Organization Standard Acupuncture Point Locations in the Western Pacific Region (WHO Standard) as our corpus, which consists of descriptions of 361 acupoints. Five types of relations (“direction_of”, “distance_of”, “part_of”, “near_acupoint”, and “located_near”) (n = 3174) between acupoints were annotated. Four models were compared: pre-trained GPT-3.5, fine-tuned GPT-3.5, pre-trained GPT-4, as well as pretrained Llama 3. Performance metrics included micro-average exact match precision, recall, and F1 scores. Results Our results demonstrate that fine-tuned GPT-3.5 consistently outperformed other models in F1 scores across all relation types. Overall, it achieved the highest micro-average F1 score of 0.92. Discussion The superior performance of the fine-tuned GPT-3.5 model, as shown by its F1 scores, underscores the importance of domain-specific fine-tuning in enhancing relation extraction capabilities for acupuncture-related tasks. In light of the findings from this study, it offers valuable insights into leveraging LLMs for developing clinical decision support and creating educational modules in acupuncture. Conclusion This study underscores the effectiveness of LLMs like GPT and Llama in extracting relations related to acupoint locations, with implications for accurately modeling acupuncture knowledge and promoting standard implementation in acupuncture training and practice. The findings also contribute to advancing informatics applications in traditional and complementary medicine, showcasing the potential of LLMs in natural language processing.

ABSTRACTIntroductionLow body weight in patients with COPD is associated with a poor prognosis and more comorbidities. However, the impact of increased body weight in patients with COPD remains controversial. The aim of this study was to explore the clinical features of overweight patients with AECOPD.MethodsIn this multicenter cross‐sectional study, a total of 647 AECOPD patients were recruited. Finally, 269 normal weight and 162 overweight patients were included. Baseline characteristics and clinical and laboratory data were collected. The least absolute shrinkage and selection operator (LASSO) regression was performed to determine potential features, which were substituted into binary logistic regression to reveal overweight‐associated clinical features. The nomogram and its associated curves were established to visualize and verify the logistic regression model.ResultsSix potential overweight‐associated variables were selected by LASSO regression. Subsequently, a binary logistic regression model identified that the rates of type 2 diabetes (T2DM) and hypertension and levels of lymphocytes (LYM)%, and alanine aminotransferase (ALT) were independent variables of overweight in AECOPD patients. The C‐index and AUC of the ROC curve of the nomogram were 0.671 and 0.666, respectively. The DCA curve revealed that the nomogram had more clinical benefits if the threshold was at a range of 0.22~0.78.ConclusionsCollectively, we revealed that T2DM and hypertension were more common, and LYM% and ALT were higher in AECOPD patients with overweight than those with normal weight. The result suggests that AECOPD patients with overweight are at risk for additional comorbidities, potentially leading to worse outcomes.