Citations

Primary care is a language-intensive environment where clinicians frequently synthesize, document, and communicate large amounts of information. Given the amount of information in primary care, large language models (LLMs) have emerged as tools to support primary care clinician workflows, aiming to reduce administrative burden and augment patient care. LLMs are artificial intelligence tools that can generate text and assist with chart summarization, message drafting, and clinical decision support. However, because LLMs are probabilistic, identical inputs may yield inconsistent responses. The LLMs output can be significantly improved through prompt engineering. Prompt engineering is the intentional design of text entered into the LLM to help produce better LLM results. Prompting is best approached as an iterative process where a clinician defines the task, the LLM generates output, and the clinician critically reviews and refines the results. Low-quality prompts are often vague and produce generic or misleading responses. High-quality prompts are specific, context-rich, and well-structured. Using structured prompting frameworks can improve the LLMs response. Including core elements, such as the LLMs role, the clinical context, the requested task, and the desired output formatting, can help improve the LLMs response by providing situational background and framing response formatting. Additional frameworks, such as Ask-Context-Expectation and PICO+O, can be utilized for specific patient circumstances and cases. However, despite their promise, LLMs have important limitations. They may generate inaccurate or hallucinated information and produce inconsistent results. Given these limitations, LLMs should not be viewed as knowledge authorities but rather as cognitive assistants. Thoughtful prompt design can help reduce these limitations and improve response accuracy, always keeping in mind that LLMs should not replace human judgment or clinical reasoning. As LLMs continue to be integrated into primary care, prompt engineering will become an increasingly important clinical skill. Careful prompt design and critical appraisal of LLM responses will be key to maintaining excellent patient care in the AI era.

Interest in using gene therapy to treat osteoarthritis (OA) is growing and a number of clinical trials have been initiated. This commentary identifies three intersecting areas that need to be addressed for the field to move forward expeditiously. The first relates to lowering the cost of manufacturing clinical grade viral vectors, addressing various aspects of their deployment, and overcoming immune barriers to dosing and re-dosing. The second area requires an improved understanding of the pathophysiology of OA, including its stratification by endotype and phenotype. Coupled to the development of reliable biomarkers, this will enable the creation of personalized gene therapies, facilitate patient selection, and aid the identification of additional molecular targets. Moreover, progress in the early diagnosis of OA will enable administration of gene therapeutics at a stage when they are most likely to be successful. Finally, important issues with regard to financing and regulation are discussed. Top line data from two pivotal Phase III clinical trials are expected to be released this year. The findings from these trials will exercise considerable influence on the future development of the field.

ABSTRACT Patients requiring permanent pacing after tricuspid valve intervention present challenges due to the need to cross tricuspid valve prostheses. We report three cases of successful dual coronary sinus (CS) lead implantation for biventricular pacing following a range of tricuspid interventions—surgical tricuspid annuloplasty, transcatheter edge‐to‐edge repair, and transcatheter tricuspid valve replacement. The approach avoided tricuspid valve traversal, was technically feasible and resulted in satisfactory pacing performance without procedural complications. Dual CS lead configurations were individualized based on CS anatomy and pacing characteristics. The degree of QRS narrowing achieved varied according to lead location and ventricular activation patterns, highlighting the importance of individualized lead placement strategies and device programming. Dual CS lead pacing may represent a viable alternative for biventricular pacing in selected patients with prior tricuspid valve interventions. Larger studies are needed to evaluate long‐term outcomes and define the optimal role of this approach among available pacing strategies in this patient population.

Study Design. Post hoc analysis of prospectively-collected data. Objective. To identify factors predicting the most (and least) satisfaction following surgery for cervical spondylotic myelopathy (CSM). Summary of Background Data. Patient satisfaction affects long-term outcomes after surgery but the preoperative factors that influence postoperative satisfaction have not been well studied in patients with CSM. Methods. We conducted a post hoc analysis of prospectively-collected data from the Quality Outcomes Database (QOD) CSM registry cohort. Baseline and surgical characteristics were compared for patients with CSM reporting the most [North American Spine Society Satisfaction Score (NASS) 1] and least (NASS 4) satisfaction 24 months postoperatively. A multivariable logistic regression model was constructed using backward stepwise elimination to determine significant predictors of most versus least satisfaction. Twenty-four-month patient-reported outcomes (PROs) were compared. Results. Overall, 1141 patients were prospectively enrolled with 948 (83.1%) reaching 24-month follow-up. Of these, 699 met prespecified inclusion criteria: 610 (87.3%) were most satisfied and 89 (12.7%) were least satisfied. Though there were mean improvements in all 24-month PROs for the most satisfied cohort ( P <0.001), there were no significant improvements in 24-month PROs for the least satisfied cohort ( P >0.05). Using multivariable logistic regression modeling, a preoperative symptom of upper extremity weakness (OR=2.5, P =0.003), subjective myelopathy (OR=2.0, P =0.04), absence of numbness complaints (OR=2.2, P =0.003), symptom duration under 12 months (OR=1.6, P =0.047), Caucasian race (OR=2.3, P =0.001), participation in activities outside of the home (OR=2.0, P =0.04), anterior approach (OR=2.3, P <0.001), and higher baseline quality of life (OR=4.0, P =0.01) were predictive of the most satisfaction. Conclusion. Compared with the least satisfied, those most satisfied following surgery for CSM more often had a preoperative symptom of arm weakness, subjective myelopathy, the absence of numbness complaints, symptom duration under 12 months, higher baseline quality of life, and participation in activities outside of the home. Compared with a posterior approach, an anterior approach was associated with the most satisfaction. Taken together, early surgical treatment--before myelopathic symptoms significantly impact one's quality of life--may be considered to optimize patient satisfaction following CSM surgery.

Patients with plasma cell leukemia (PCL) are generally excluded from pivotal T-cell redirecting bispecific antibody (BsAb) trials. We evaluated real-world outcomes in a multicenter retrospective study of 122 patients with primary or secondary PCL across 15 academic centers, categorized as 'active' (≥5% circulating plasma cells within 30 days of BsAb initiation) or 'historical'. In a heavily pretreated population, patients received teclistamab (37%), elranatamab (11%), talquetamab as a line of therapy (Tal LOT, 42%), or talquetamab as bridging therapy to CAR-T (Tal Bridge, 11%). Cytokine release syndrome (CRS) was grade 1-2 in 56% and grade 3-4 in 4%, whereas neurotoxicity was grade 1-2 in 16% and grade 3-4 in 5%. Among 110 evaluable patients, the overall response rate (ORR) was 55%, including 61% with Tal LOT, 58% with Tal Bridge, 46% with elranatamab, and 33% with teclistamab. With a median follow-up of 8.3 months, talquetamab demonstrated superior survival. Tal LOT showed a median progression-free survival (mPFS) of 5.5 months and a median overall survival (mOS) of 11.5 months, and both were unreached in the Tal Bridge cohort. In contrast, teclistamab and elranatamab showed a mPFS of 1.2 and 1.6 months and mOS of 8.1 and 3.6 months, respectively (P=0.007, P=0.023). In active PCL, Tal LOT achieved mPFS/mOS of 6.9/12.2 months versus 0.7/1.4 months with teclistamab and 1.0/3.1 months with elranatamab, respectively (P&lt;0.001, P=0.002). Multivariable analysis associated active PCL with worse survival and Tal LOT with improved outcomes. BsAbs were safe in PCL, with talquetamab showing superior outcomes compared with BCMA-directed BsAbs.

PURPOSE Incorporation of structured data elements within the electronic health record generates real-time data for many potential uses. However, this requires a change in documentation practices, which may increase documentation effort. The best strategies to support structured documentation interventions have not been thoroughly investigated. Herein, we report the results of extending a data capture tool across multiple disease sites and practice locations. METHODS A note-based data capture tool was developed to collect five data elements using minimum common oncology data elements language. Soft-stop close visit validation (CVV), offloading of data entry tasks to allied health staff, group education, individualized e-mails, and one-on-one assistance were used to support utilization. Baseline and follow-up surveys were collected. For each provider, we compared data capture in the 6 months before and after their CVV go-live. RESULTS Forty-five providers participated (31 physicians, 14 nurse pracationers and physician assistants [NPPAs]), resulting in 23,274 encounters pre-CVV go-live and 23,146 post-CVV go-live visits. Median percentage of all data elements captured increased from 69.5% to 82.6% across all providers. The effect of CVV was immediate and sustained. When surveyed, most respondents agreed with the value propositions of understanding practice population, outcomes, selecting trials to open, and identifying patients for trial enrollment. Most respondents (15/20, 75%) felt the soft stop was a helpful reminder. CONCLUSION Structured data can be successfully collected in provider notes with >80% data capture. Personalized assistance incorporating the structured data elements into users' preexisting templates and soft-stop CVV, along with monitoring the results of implementation and personalized follow-up, was used to support the structured data capture intervention.

Dynamic gadopiclenol-enhanced nodal and pedal MR lymphangiography was safe, with no adverse events, and feasible for imaging peripheral and central conducting lymphatic anatomy.

Abstract Rationale Idiopathic Pulmonary Fibrosis (IPF) is characterized by chronic progressive pulmonary fibrosis and high mortality. Genetic markers, summarized into a polygenic risk score (PRS), associate with IPF in well-phenotyped research cohorts. Objectives To evaluate the performance of the PRS using real-world data from routinely captured electronic healthcare records. Methods We conducted an observational study evaluating the association of a PRS for IPF with electronic healthcare record diagnosis of IPF as well as lung transplant-free survival in four independent cohorts; the Mass General Brigham Biobank (MGBB), Mayo Clinic Biobank (MCBB), Mayo Clinic Tapestry Cohort (Tapestry), and U.K. Biobank (UKBB). We used multivariable logistic regression and multivariable Cox proportional hazards models adjusting for age, gender, and principal components of ancestry. The cohorts then underwent fixed and random effects meta-analysis. Measurements and Main Results Of 37,709; 44,195; 43,202; and 447,422 participants from MGBB, MCBB, Tapestry and UKBB respectively, 1,015 (2.7%) 2,879 (6.5%), 1,310 (3.0%), and 2,742 (0.6%) participants had an IPF diagnosis. Meta-analysis demonstrated a high-risk PRS associated with IPF diagnosis, OR 2.88 (95%CI 2.41-3.44) compared to all other individuals. A high-risk PRS also associated with the composite endpoint of mortality or lung transplant among those with an IPF diagnosis, HR 1.23(95%CI 1.11-1.35) compared to all other individuals. Conclusions A PRS can identify those at risk for an IPF diagnosis and mortality in biobank-scale data, which may have implications for clinical decisions. Further work is necessary to evaluate the utility of adding genetics in clinical settings.

ABSTRACT Introduction Chronic gastroduodenal disorders remain challenging to manage, and new diagnostic approaches are needed to better delineate underlying causes and guide therapeutic decisions. Body Surface Gastric Mapping (BSGM) technologies combine high‐resolution gastric myoelectrical activity measurements with symptom and psychological profiling to provide mechanistic insights into gastric motor and sensory dysfunction. An International Working Group convened to derive the first consensus classification of BSGM phenotypes (the “Auckland Classification”). Methods A Technical Group conducted a systematic literature and clinical database review to identify objective test biomarkers and candidate disease mechanisms. Evidence was synthesized across 50 studies (primarily in gastroparesis, chronic nausea and vomiting, and functional dyspepsia), and BSGM phenotypes were mapped to existing treatment guidelines. Subsequently, iterative review and development of consensus was performed by a Consensus Group composed of international clinical experts familiar with BSGM. Eleven statements underlying the classification were then derived and circulated as a final survey to establish agreement. Results Six BSGM phenotypes were endorsed: three defined by myoelectrical abnormalities (Dysrhythmic, High Frequency, and Low Meal Response) and three by characteristic symptom associations (Sensorimotor, Continuous, and Delayed Onset Symptoms). Published studies plausibly linked these phenotypes to mechanisms including interstitial cell of Cajal depletion, vagal impairment, hypomotility, visceral hypersensitivity, gut‐brain dysregulation, and small bowel dysfunction. Phenotypes were also mapped to existing mechanism‐based treatment guidelines. Ten out of the eleven statements had > 80% agreement. Conclusions The Auckland Classification, derived by international consensus, presents a structured framework for BSGM‐defined patient phenotypes. Evidence and mechanism‐based treatment options are suggested for each phenotype to provide a foundation for research, further validation, and a pathway for integrating BSGM into clinical care.