Patient-Representing Population's Perceptions of GPT-Generated Versus Standard Emergency Department Discharge Instructions: Randomized Blind Survey Assessment.

BACKGROUND: Discharge instructions are a key form of documentation and patient communication in the time of transition from the emergency department (ED) to home. Discharge instructions are time-consuming and often underprioritized, especially in the ED, leading to discharge delays and possibly impersonal patient instructions. Generative artificial intelligence and large language models (LLMs) offer promising methods of creating high-quality and personalized discharge instructions; however, there exists a gap in understanding patient perspectives of LLM-generated discharge instructions. OBJECTIVE: We aimed to assess the use of LLMs such as ChatGPT in synthesizing accurate and patient-accessible discharge instructions in the ED. METHODS: We synthesized 5 unique, fictional ED encounters to emulate real ED encounters that included a diverse set of clinician history, physical notes, and nursing notes. These were passed to GPT-4 in Azure OpenAI Service (Microsoft) to generate LLM-generated discharge instructions. Standard discharge instructions were also generated for each of the 5 unique ED encounters. All GPT-generated and standard discharge instructions were then formatted into standardized after-visit summary documents. These after-visit summaries containing either GPT-generated or standard discharge instructions were randomly and blindly administered to Amazon MTurk respondents representing patient populations through Amazon MTurk Survey Distribution. Discharge instructions were assessed based on metrics of interpretability of significance, understandability, and satisfaction. RESULTS: Our findings revealed that survey respondents' perspectives regarding GPT-generated and standard discharge instructions were significantly (P=.01) more favorable toward GPT-generated return precautions, and all other sections were considered noninferior to standard discharge instructions. Of the 156 survey respondents, GPT-generated discharge instructions were assigned favorable ratings, "agree" and "strongly agree," more frequently along the metric of interpretability of significance in discharge instruction subsections regarding diagnosis, procedures, treatment, post-ED medications or any changes to medications, and return precautions. Survey respondents found GPT-generated instructions to be more understandable when rating procedures, treatment, post-ED medications or medication changes, post-ED follow-up, and return precautions. Satisfaction with GPT-generated discharge instruction subsections was the most favorable in procedures, treatment, post-ED medications or medication changes, and return precautions. Wilcoxon rank-sum test of Likert responses revealed significant differences (P=.01) in the interpretability of significant return precautions in GPT-generated discharge instructions compared to standard discharge instructions but not for other evaluation metrics and discharge instruction subsections. CONCLUSIONS: This study demonstrates the potential for LLMs such as ChatGPT to act as a method of augmenting current documentation workflows in the ED to reduce the documentation burden of physicians. The ability of LLMs to provide tailored instructions for patients by improving readability and making instructions more applicable to patients could improve upon the methods of communication that currently exist.

The effects of double-filtration plasmapheresis on coagulation profiles and the risk of bleeding.

BACKGROUND/PURPOSE: Double-filtration plasmapheresis (DFPP) can be used to remove circulating pathogenic molecules. By reclaiming filtered albumin, DFPP reduces the need for albumin and plasma replacement. Large proteins, such as fibrinogen, are removed. Our institution adopts a DFPP treatment protocol consisting of active surveillance of coagulation profiles and prophylactic supplementation of blood products containing fibrinogen. This study aims to investigate the effects of consecutive DFPP treatments on serial coagulation profiles and the risk of bleeding under this protocol. METHODS: Serial laboratory data and bleeding events at a single tertiary medical center were prospectively collected. Prophylactic transfusion of cryoprecipitate or fresh frozen plasma (FFP) was instituted if significant coagulopathy or a clinically evident bleeding event was observed. RESULTS: After the first treatment session, plasma fibrinogen levels decreased from 332 ± 106 mg/dL to 96 ± 44 mg/dL in the 37 study patients. In the following sessions, plasma fibrinogen levels were maintained at around 100 mg/dL under prophylactic transfusion. No major bleeding events were recorded, but five (14%) patients experienced minor bleeding. CONCLUSION: DFPP treatment might be performed safely along with active monitoring of coagulation profiles and prophylactic transfusion of cryoprecipitate or FFP.

Low levels of mouse sperm chromatin fragmentation delay embryo development.

We previously demonstrated that MnCl2 induces double-stranded DNA breaks in sperm in a process that we term as sperm chromatin fragmentation. Here, we tested if the levels of double-stranded DNA breaks were corelated to the concentration of MnCl2, and we compared this to another agent that causes single-stranded DNA breaks, H2O2. We found that both methods have the advantage of inducing DNA breaks in a concentration-dependent manner. Mouse sperm were treated with varying concentrations of either H2O2 or MnCl2, and the DNA damage was assessed by pulse-field gel electrophoresis, and the alkaline and neutral comet assays. Oocytes were injected with either treated sperm and the resulting embryos analyzed with an embryoscope to detect subtle changes in embryonic development. We confirmed that H2O2 treatment induced primarily single-stranded DNA breaks and MnCl2 induced primarily double-stranded DNA breaks, indicating different mechanisms of damage. These sperm were injected into oocytes, and the development of the resulting embryos followed with an embryoscope equipped with time lapse recording. We found that aberrations in early embryonic development by day 2 with even the lowest levels of DNA damage and that the levels of embryonic aberrations correlated to the concentration of either H2O2 or MnCl2. Low levels of H2O2 caused significantly more aberrations in embryonic development than low levels of MnCl2 even though the levels of DNA damage as measured by comet assays were similar. These data demonstrate that even low levels of sperm DNA damage cause delays and arrests in embryonic development.

Comparison of euploid blastocyst expansion with subgroups of single chromosome, multiple chromosome, and segmental aneuploids using an AI platform from donor egg embryos.

PURPOSE: This retrospective observational study compares how different classes of blastocyst genotypes from egg donor cycles differentially blastulate and expand using a standard assay. METHODS: Quantitative measurements of expansion utilized a customized neural network that segments all sequential time-lapse images during the first 10 h of expansion. RESULTS: Analyses were performed using two developmental time perspectives using time-lapse imaging. The first was the time to blastocyst formation (tB), which broadly reflects variations in developmental rate. Euploidy peaked at 100-115 h from fertilization. In contrast, aneuploidy peaks flanked this interval bi-modally. These distributions limit ploidy discrimination based upon traditional standard grading features when assessed in real time. In contrast, from the second perspective of progressive blastocyst expansion that is normalized to each individual blastocyst's tB time, euploidy was significantly increased at expansion values > 20,000µ2 across all tB intervals studied. A Cartesian coordinate plot graphically summarizes information useful to rank order blastocysts within cohorts for transfer. Defined aneuploidy subgroups, distinguished by the number and complexity of chromosomes involved, also showed distributive differences from both euploids and from each other. A small subset of clinically significant trisomies did not show discriminating features separating them from other euploids. CONCLUSION: A standard assay of blastocyst expansion normalized to each individual blastocyst's time of blastocyst formation more usefully discriminates euploidy from aneuploidy than real-time expansion comparisons using absolute developmental time from fertilization.

Angiopoietin-2 inhibition attenuates kidney fibrosis by hindering chemokine C-C motif ligand 2 expression and apoptosis of endothelial cells.

Plasma levels of angiopoietin-2 are increased in patients with chronic kidney disease (CKD). Moreover, mouse models of progressive kidney disease also demonstrate increased angiopoietin-2 in both plasmas and kidneys. The role of dysregulated angiopoietins in the progression of kidney disease has not been thoroughly investigated. Here, we found in a cohort of 319 patients with CKD that plasma angiopoietin-2 and angiopoietin-2/angiopoietin-1 ratios were positively associated with the development of kidney failure. In mice with progressive kidney disease induced by either ureteral obstruction or ischemia-reperfusion injury, overexpression of human angiopoietin-1 in the kidney tubules not only reduced macrophage infiltration in the initial stage post-injury but also attenuated endothelial cell apoptosis, microvascular rarefaction, and fibrosis in the advanced disease stage. Notably, angiopoietin-1 attenuated chemokine C-C motif ligand 2 (CCL2) expression in the endothelial cells of the fibrosing kidneys, and these protective effects led to attenuation of functional impairment. Mechanistically, angiopoietin-1 reduced CCL2-activated macrophage migration and protected endothelial cells against cell apoptosis induced by angiopoietin-2 and Wnt ligands. Based on this, we applied L1-10, an angiopoietin-2 inhibitor, to the mouse models of progressive kidney disease and found inhibitory effects on macrophage infiltration, microvascular rarefaction, and fibrosis. Thus, we defined the detrimental impact of increased angiopoietin-2 on kidney survival of patients with CKD which appears highlighted by angiopoietin-2 induced endothelial CCL2-activated macrophage infiltration and endothelial cell apoptosis in their kidneys undergoing fibrosis.

Spectrum of cancer patients receiving renal biopsy.

BACKGROUND: The frontier of onco-nephrology, particularly renal complications of cancer and treatment, remains unexplored. We revisit the fundamental tool of diagnosing kidney disease, renal biopsy, in cancer patients with renal manifestation. METHODS: Patients who received renal biopsy from July 2015 to July 2019 were analyzed. Primary outcomes included end-stage renal disease (ESRD), mortality, and catastrophic outcome defined as either ESRD or mortality. A Cox proportional hazards model and Kaplan-Meier technique were used to assess the association with outcome measurements and survival analyses. Immunosuppression after renal biopsy and response to the treatment were evaluated. RESULTS: Among the 77 patients, the median age was 66 years (interquartile range [IQR] 59-73 years) and 46 (59.7%) were male. At the time of renal biopsy, 57 patients (74%) had various degrees of renal insufficiency. Tubulointerstitial damage score, quantified by renal pathology, were associated with higher hazards of ESRD (hazard ratio [HR], 1.77; 95% confidence interval [95% CI], 1.20 to 2.61; P = 0.004) and catastrophic outcome (HR, 1.30; 95% CI, 0.99 to 1.70; P = 0.058). The response rate to immunosuppression was lower in those diagnosed with tubulointerstitial nephritis (1 of 4 patients, 25%) than those with glomerulopathy (10 of 20 patients, 50%). CONCLUSION: Renal biopsy may improve diagnostic accuracy and assist in treatment guidance of cancer patients with renal manifestation. Renal biopsy should be encouraged with clinical indication. Collaboration between oncologists and nephrologists is of paramount importance to provide more comprehensive care for caner patients.

Deep learning neural network analysis of human blastocyst expansion from time-lapse image files.

RESEARCH QUESTION: Can artificial intelligence (AI) discriminate a blastocyst's cellular area from unedited time-lapse image files using semantic segmentation and a deep learning optimized U-Net architecture for use in selecting single blastocysts for transfer? DESIGN: This platform was retrospectively applied to time-lapse files from 101 sequentially transferred single blastocysts that were prospectively selected for transfer by their highest expansion ranking within cohorts using a 10 h expansion assay rather than standard grading. RESULTS: The AI platform provides expansion curves and raw data files to classify and compare blastocyst phenotypes within both cohorts and populations. Of 35 sequential unbiopsied single blastocyst transfers, 23 (65.7%) resulted in a live birth. Of 66 sequential single euploid blastocyst transfers, also selected for their most robust expansion, 49 (74.2%) resulted in live birth. The AI platform revealed that the averaged expansion rate was significantly (P = 0.007) greater in euploid blastocysts that resulted in live births compared with those resulting in failure to give a live birth. The platform further provides a framework to analyse fragmentation phenotypes that can test new hypotheses for developmental regulation during the preimplantation period. CONCLUSIONS: AI can be used to quantitatively describe blastocyst expansion from unedited time-lapse image files and can be used to quantitatively rank-order blastocysts for transfer. Early clinical results from such single blastocyst selection suggests that live birth rates without biopsy may be comparable to those found using single euploid blastocysts in younger, good responder patients.

Pacemaker use for the treatment of reflex-mediated syncope: 40-year experience at a single paediatric institution.

INTRODUCTION: Reflex-mediated syncope occurs in 15% of children and young adults. In rare instances, pacemakers are required to treat syncopal episodes associated with transient sinus pauses or atrioventricular block. This study describes a single centre experience in the use of permanent pacemakers to treat syncope in children and young adults. MATERIALS AND METHODS: Patients with significant pre-syncope or syncope and pacemaker implantation from 1978 to 2018 were reviewed. Data collected included the age of presentation, method of diagnosis, underlying rhythm disturbance, age at implant, type of pacemaker implanted, procedural complications and subsequent symptoms. RESULTS: Fifty patients were identified. Median age at time of the first syncopal episode was 10.2 (range 0.3-20.4) years, with a median implant age of 14.9 (0.9-34.3) years. Significant sinus bradycardia/pauses were the predominant reason for pacemaker implant (54%), followed by high-grade atrioventricular block (30%). Four (8%) patients had both sinus pauses and atrioventricular block documented. The majority of patients had dual-chamber pacemakers implanted (58%), followed by ventricular pacemakers (38%). Median follow-up was 6.7 (0.4-33.0) years. Post-implant, 4 (8%) patients continued to have syncope, 7 (14%) had complete resolution of their symptoms, and the remaining reported a decrease in their pre-syncopal episodes and no further syncope. Twelve (24%) patients had complications, including two infections and eight lead malfunctions. CONCLUSIONS: Paediatric patients with reflex-mediated syncope can be treated with pacing. Complication rates are high (24%); as such, permanent pacemakers should be reserved only for those in whom asystole from sinus pauses or atrioventricular block has been well documented.

Using next-generation sequencing to redefine BRCAness in triple-negative breast cancer.

BRCAness is considered a predictive biomarker to platinum and poly(ADP-ribose) polymerase (PARP) inhibitors. However, recent trials showed that its predictive value was limited in triple-negative breast cancer (TNBC) treated with platinum. Moreover, tumors with mutations of DNA damage response (DDR) genes, such as homologous recombination (HR) genes, could be sensitive to platinum and PARP inhibitors. Thus, we aim to explore the relationship between mutation status of DDR genes and BRCAness in TNBC. We sequenced 56 DDR genes in 120 TNBC and identified BRCAness by array comparative genomic hybridization. The sequencing results showed that 13, 14, and 14 patients had BRCA, non-BRCA HR, and non-HR DDR gene mutations, respectively. Array comparative genomic hybridization revealed that BRCA-mutated and HR gene-mutated TNBC shared similar BRCAness features, both having higher numbers and longer length of large-scale structural aberration (LSA, >10 Mb) and similar altered chromosomal regions of LSA. These suggested non-BRCA HR gene-mutated TNBC shared similar characteristics with BRCA-mutated TNBC, indicating non-BRCA HR gene-mutated TNBC sensitive to platinum and PARP inhibitors. Among tumors with mutation of non-HR DDR genes, 3 PTEN and 1 MSH6 mutation also contained significant LSAs (BRCAness); however, they had different regions of genomic alteration to BRCA and HR gene-mutated tumors, might explain prior findings that PTEN- and MSH6-mutated cancer cells not sensitive to PARP inhibitors. Therefore, we hypothesize that the heterogeneous genomic background of BRCAness indicates different responsiveness to platinum and PARP inhibitors. Direct sequencing DDR genes in TNBC should be applied to predict their sensitivity toward platinum and PARP inhibitors.

Early blastocyst expansion in euploid and aneuploid human embryos: evidence for a non-invasive and quantitative marker for embryo selection.

RESEARCH QUESTION: How can the kinetics of human blastocyst expansion be used to evaluate an embryo's ploidy identified using preimplantation genetic testing for aneuploidy (PGT-A)? DESIGN: This was a retrospective observational study of 188 autologous blastocysts from 34 sequential treatment cycles using PGT-A and blastocyst biopsy. Using time-lapse imaging, blastocyst expansion was evaluated using a quantitative standardized expansion assay (qSEA). Trophectoderm cell division was examined in selected, unbiopsied embryos (n = 7) to evaluate the contribution of mitosis to the expansion rate. RESULTS: The averaged euploid blastocyst expansion rate was significantly (52.8%) faster than in aneuploid blastocysts (P = 0.0041). Scatterplots, representing 'expansion maps', revealed that both populations showed a similarly overlapping distribution of blastocyst formation times at 80-140 h from fertilization. Euploidy and aneuploidy were better distinguished in regions of higher and lower expansion, respectively, in expansion maps. Based upon the expansion slopes, rank-ordering of individual embryos within cohorts resulted in more than 90% euploid embryos in the first two ranks in patients less than 35 years of age. Additional detailed time-lapse image analysis provided evidence that rapid expansion was associated with robust, integrative cellular mitosis in trophectoderm cells. CONCLUSIONS: The kinetics of human blastocyst expansion are related to an embryo's ploidy. These preliminary observations describe a new quantitative, non-invasive approach to embryo assessment that may be useful to identify single blastocysts for transfer, particularly in younger patient groups. However, this approach may also be useful for euploid embryo selection after PGT-A. The results support the hypothesis that aneuploidy universally impairs general cellular processes, including cell division, in differentiated cells.

A multidisciplinary approach to designing and evaluating Electronic Medical Record portal messages that support patient self-care.

We describe a project intended to improve the use of Electronic Medical Record (EMR) patient portal information by older adults with diverse numeracy and literacy abilities, so that portals can better support patient-centered care. Patient portals are intended to bridge patients and providers by ensuring patients have continuous access to their health information and services. However, they are underutilized, especially by older adults with low health literacy, because they often function more as information repositories than as tools to engage patients. We outline an interdisciplinary approach to designing and evaluating portal-based messages that convey clinical test results so as to support patient-centered care. We first describe a theory-based framework for designing effective messages for patients. This involves analyzing shortcomings of the standard portal message format (presenting numerical test results with little context to guide comprehension) and developing verbally, graphically, video- and computer agent-based formats that enhance context. The framework encompasses theories from cognitive and behavioral science (health literacy, fuzzy trace memory, behavior change) as well as computational/engineering approaches (e.g., image and speech processing models). We then describe an approach to evaluating whether the formats improve comprehension of and responses to the messages about test results, focusing on our methods. The approach combines quantitative (e.g., response accuracy, Likert scale responses) and qualitative (interview) measures, as well as experimental and individual difference methods in order to investigate which formats are more effective, and whether some formats benefit some types of patients more than others. We also report the results of two pilot studies conducted as part of developing the message formats.

Fully programmable spectrum sliced chirped microwave photonic filter.

A novel chirped microwave photonic filter (MPF) capable of achieving a large radio frequency (RF) group delay slope and a single passband response free from high frequency fading is presented. The design is based upon a Fourier domain optical processor (FD-OP) and a single sideband modulator. The FD-OP is utilized to generate both constant time delay to tune the filter and first order dispersion to induce the RF chirp, enabling full software control of the MPF without the need for manual adjustment. An optimized optical parameter region based on a large optical bandwidth >750 GHz and low slicing dispersion < ± 1 ps/nm is introduced, with this technique greatly improving the RF properties including the group delay slope magnitude and passband noise. Experimental results confirm that the structure simultaneously achieves a large in-band RF chirp of -4.2 ns/GHz, centre frequency invariant tuning and independent reconfiguration of the RF amplitude and phase response. Finally, a stochastic study of the device passband noise performance under tuning and reconfiguration is presented, indicating a low passband noise <-120 dB/Hz.

Big data in Earth science: Emerging practice and promise.

Improvements in the number and resolution of Earth- and satellite-based sensors coupled with finer-resolution models have resulted in an explosion in the volume of Earth science data. This data-rich environment is changing the practice of Earth science, extending it beyond discovery and applied science to new realms. This Review highlights recent big data applications in three subdisciplines-hydrology, oceanography, and atmospheric science. We illustrate how big data relate to contemporary challenges in science: replicability and reproducibility and the transition from raw data to information products. Big data provide unprecedented opportunities to enhance our understanding of Earth's complex patterns and interactions. The emergence of digital twins enables us to learn from the past, understand the current state, and improve the accuracy of future predictions.

Correction: How Does ChatGPT Perform on the United States Medical Licensing Examination (USMLE)? The Implications of Large Language Models for Medical Education and Knowledge Assessment.

[This corrects the article DOI: 10.2196/45312.].

Identifying incarceration status in the electronic health record using large language models in emergency department settings.

Background: Incarceration is a significant social determinant of health, contributing to high morbidity, mortality, and racialized health inequities. However, incarceration status is largely invisible to health services research due to inadequate clinical electronic health record (EHR) capture. This study aims to develop, train, and validate natural language processing (NLP) techniques to more effectively identify incarceration status in the EHR. Methods: The study population consisted of adult patients (≥ 18 y.o.) who presented to the emergency department between June 2013 and August 2021. The EHR database was filtered for notes for specific incarceration-related terms, and then a random selection of 1,000 notes was annotated for incarceration and further stratified into specific statuses of prior history, recent, and current incarceration. For NLP model development, 80% of the notes were used to train the Longformer-based and RoBERTa algorithms. The remaining 20% of the notes underwent analysis with GPT-4. Results: There were 849 unique patients across 989 visits in the 1000 annotated notes. Manual annotation revealed that 559 of 1000 notes (55.9%) contained evidence of incarceration history. ICD-10 code (sensitivity: 4.8%, specificity: 99.1%, F1-score: 0.09) demonstrated inferior performance to RoBERTa NLP (sensitivity: 78.6%, specificity: 73.3%, F1-score: 0.79), Longformer NLP (sensitivity: 94.6%, specificity: 87.5%, F1-score: 0.93), and GPT-4 (sensitivity: 100%, specificity: 61.1%, F1-score: 0.86). Conclusions: Our advanced NLP models demonstrate a high degree of accuracy in identifying incarceration status from clinical notes. Further research is needed to explore their scaled implementation in population health initiatives and assess their potential to mitigate health disparities through tailored system interventions.

Automated HEART score determination via ChatGPT: Honing a framework for iterative prompt development.

Objectives: This study presents a design framework to enhance the accuracy by which large language models (LLMs), like ChatGPT can extract insights from clinical notes. We highlight this framework via prompt refinement for the automated determination of HEART (History, ECG, Age, Risk factors, Troponin risk algorithm) scores in chest pain evaluation. Methods: We developed a pipeline for LLM prompt testing, employing stochastic repeat testing and quantifying response errors relative to physician assessment. We evaluated the pipeline for automated HEART score determination across a limited set of 24 synthetic clinical notes representing four simulated patients. To assess whether iterative prompt design could improve the LLMs' ability to extract complex clinical concepts and apply rule-based logic to translate them to HEART subscores, we monitored diagnostic performance during prompt iteration. Results: Validation included three iterative rounds of prompt improvement for three HEART subscores with 25 repeat trials totaling 1200 queries each for GPT-3.5 and GPT-4. For both LLM models, from initial to final prompt design, there was a decrease in the rate of responses with erroneous, non-numerical subscore answers. Accuracy of numerical responses for HEART subscores (discrete 0-2 point scale) improved for GPT-4 from the initial to final prompt iteration, decreasing from a mean error of 0.16-0.10 (95% confidence interval: 0.07-0.14) points. Conclusion: We established a framework for iterative prompt design in the clinical space. Although the results indicate potential for integrating LLMs in structured clinical note analysis, translation to real, large-scale clinical data with appropriate data privacy safeguards is needed.

GLP-1 receptor agonists' impact on cardio-renal outcomes and mortality in T2D with acute kidney disease.

Previous studies have explored the effects of glucagon-like peptide-1 receptor agonists (GLP-1 RAs) in reducing cardiovascular events in type 2 diabetes. Here we show that GLP-1 RAs are associated with lower risks of mortality, major cardiovascular events (MACEs), and major adverse kidney events (MAKEs) in type 2 diabetes patients with acute kidney disease (AKD). Utilizing global data from the TriNetX database (2002/09/01-2022/12/01) and propensity score matching, we compare 7511 GLP-1 RAs users to non-users among 165,860 AKD patients. The most common causes of AKI are sepsis (55.2%) and cardiorenal syndrome (34.2%). After a median follow-up of 2.3 years, GLP-1 RAs users exhibit reduced risks of mortality (adjusted hazard ratio [aHR]: 0.57), MACEs (aHR: 0.88), and MAKEs (aHR: 0.73). External validation in a multicenter dataset of 1245 type 2 diabetes patients with AKD supports the favorable outcomes. These results emphasize the potential of GLP-1 RAs in individualized treatment for this population.

Identifying signs and symptoms of urinary tract infection from emergency department clinical notes using large language models.

BACKGROUND: Natural language processing (NLP) tools including recently developed large language models (LLMs) have myriad potential applications in medical care and research, including the efficient labeling and classification of unstructured text such as electronic health record (EHR) notes. This opens the door to large-scale projects that rely on variables that are not typically recorded in a structured form, such as patient signs and symptoms. OBJECTIVES: This study is designed to acquaint the emergency medicine research community with the foundational elements of NLP, highlighting essential terminology, annotation methodologies, and the intricacies involved in training and evaluating NLP models. Symptom characterization is critical to urinary tract infection (UTI) diagnosis, but identification of symptoms from the EHR has historically been challenging, limiting large-scale research, public health surveillance, and EHR-based clinical decision support. We therefore developed and compared two NLP models to identify UTI symptoms from unstructured emergency department (ED) notes. METHODS: The study population consisted of patients aged ≥ 18 who presented to an ED in a northeastern U.S. health system between June 2013 and August 2021 and had a urinalysis performed. We annotated a random subset of 1250 ED clinician notes from these visits for a list of 17 UTI symptoms. We then developed two task-specific LLMs to perform the task of named entity recognition: a convolutional neural network-based model (SpaCy) and a transformer-based model designed to process longer documents (Clinical Longformer). Models were trained on 1000 notes and tested on a holdout set of 250 notes. We compared model performance (precision, recall, F1 measure) at identifying the presence or absence of UTI symptoms at the note level. RESULTS: A total of 8135 entities were identified in 1250 notes; 83.6% of notes included at least one entity. Overall F1 measure for note-level symptom identification weighted by entity frequency was 0.84 for the SpaCy model and 0.88 for the Longformer model. F1 measure for identifying presence or absence of any UTI symptom in a clinical note was 0.96 (232/250 correctly classified) for the SpaCy model and 0.98 (240/250 correctly classified) for the Longformer model. CONCLUSIONS: The study demonstrated the utility of LLMs and transformer-based models in particular for extracting UTI symptoms from unstructured ED clinical notes; models were highly accurate for detecting the presence or absence of any UTI symptom on the note level, with variable performance for individual symptoms.

Sodium-Glucose Cotransport Protein 2 Inhibitors in Patients With Type 2 Diabetes and Acute Kidney Disease.

Importance: Sodium-glucose cotransport protein 2 inhibitors (SGLT-2is) have demonstrated associations with positive kidney-related and cardiovascular outcomes in patients with type 2 diabetes. However, the association of SGLT-2is with outcomes among patients with type 2 diabetes and acute kidney disease (AKD) remains unclear. Objective: To examine the long-term associations of SGLT-2is with mortality, major adverse kidney events (MAKEs), and major adverse cardiovascular events (MACEs) in patients with type 2 diabetes and AKD. Design, Setting, and Participants: This cohort study used global health care data (the TriNetX database) spanning from September 30, 2002, to September 30, 2022. Propensity score matching was used to select a cohort of patients, and follow-up was conducted with a maximum duration of 5 years (completed on September 30, 2022) or until the occurrence of an outcome or death. Intervention: The use of SGLT-2is. Main Outcomes and Measures: The primary outcomes measured were mortality, MAKEs, and MACEs. Adjusted hazard ratios (AHR) with 95% CIs were calculated to compare the risks between SGLT-2i users and nonusers, representing the mean treatment effect among the treated patients. Results: A total of 230 366 patients with AKD (mean [SD] age, 67.1 [16.4] years; 51.8% men and 48.2% women) were enrolled in the study, which had a median follow-up duration of 2.3 (IQR, 1.2-3.5) years. Among these, 5319 individuals (2.3%) were identified as SGLT-2i users. Among nonusers, the incidence of mortality was 18.7%, the incidence of MAKEs was 21.0%, and the incidence of MACEs was 25.8%. After propensity score matching, the absolute differences between SGLT-2i users and nonusers for incidence of mortality, MAKEs, and MACEs were 9.7%, 11.5%, and 12.3%, respectively. Based on the treated population, SGLT-2i use was associated with a significantly lower risk of mortality (AHR, 0.69 [95% CI, 0.62-0.77]), MAKEs (AHR, 0.62 [95% CI, 0.56-0.69]), and MACEs (AHR, 0.75 [95% CI, 0.65-0.88]) compared with nonuse. External validation using a multicenter cohort data set of 1233 patients with AKD patients who were SGLT-2i users confirmed the observed beneficial outcomes. Notably, the risk reduction associated with SGLT-2is remained significant even among patients without hypertension, those with advanced chronic kidney disease, and those not receiving other hypoglycemic agents. Conclusions and Relevance: In this cohort study of patients with type 2 diabetes and AKD, administration of SGLT-2is was associated with a significant reduction in all-cause mortality, MAKEs, and MACEs when compared with nonuse, underscoring the importance of SGLT-2is in care after acute kidney injury. These findings emphasize the potential benefits of SGLT-2is in managing AKD and mitigating the risks of major cardiovascular and kidney diseases.