Citations

ABSTRACT Introduction/Aims Accurate needle electromyography (EMG) of the short head of the biceps femoris (SHBF) is often important to localize nerve damage when proximal to the fibular head. Techniques have been proposed for accurate SHBF EMG; however, needle placement accuracy is low and with the risk of inadvertent needle placement into the long head (LHBF) potentially resulting in false localization and inappropriate operative management. This study aimed to define the optimal window for accurate SHBF needle EMG placement through ultrasound (US) investigation of the anatomical relationships of the SHBF, LHBF, and common fibular nerve (CFN) in the distal posterolateral thigh. Methods Forty lower limbs from 20 healthy adults were evaluated using US. Distances from the popliteal crease (PC) to the SHBF and LHBF myotendinous junctions and position of the CFN in the popliteal fossa were recorded. The “SHBF window” was defined as the region where the SHBF muscle body is present in the absence of the LHBF. Results The SHBF was located anterolateral to the LHBF tendon/muscle and the CFN medial to the SHBF in all limbs. The average distances from the PC to SHBF and LHBF muscles were 0.6 and 6.4 cm, respectively. The optimal “SHBF window” was identified to be 3–4 cm (2–3 fingerbreadths) proximal to the PC, anterolateral to the LHBF tendon in the distal thigh. Discussion SHBF examination within this optimized window results in increased accuracy of needle placement, aiding in the electrodiagnostic localization of fibular nerve lesions.

Abstract Background The accuracy and safety of generating medication orders by large language models (LLMs) must be demonstrated. Without standardization, performance evaluation is limited to time and resource-intensive clinician grading. This evaluation aimed to develop a standardized medication format that supports automated performance evaluation (MedMatch). Methods First, a survey of 40 medication prompts was given to clinicians to assess agreement in medication order communication. Second, a clinician panel developed a standardized medication format (MedMatch) for oral and intravenous medications. Third, a clinician-annotated dataset of medication prompts and standardized answers in the MedMatch format was developed for LLM testing. Finally, LLMs were retested with the same dataset, adjusted to exclude route information, to evaluate the appropriate categorization of medication route. Results The formal medication orders consistently showed low omission rates and high overlap for all entities, compared to the verbal and brief written communication types. Lexical overlap results demonstrated pattern norms amongst clinicians with entities appearing most commonly in positions 1-5 in the order of drug name, dose, unit, route, and frequency. In the second survey, the formal written group performed the highest with 78.3% of prompts considered appropriate as a computer-generated response. LLM accuracy on MedMatch order standardization was highest in oral solid (64.2-72.5%), intravenous intermittent (72.5-84.3%), and intravenous push (62.7-74.5%) categories. LLMs performed the worst at categorizing medication orders accurately into intravenous push (18-61%) and intravenous intermittent (51-100%) routes. Conclusions Standardized format for computer-based outputs may support automated performance analysis and enhance the clarity of medication communication.

BACKGROUND AND OBJECTIVES: Unruptured intracranial aneurysms (UIAs) are increasingly detected and require careful management to prevent rupture. No externally validated score currently predicts procedural risk to guide treatment decisions. We developed and validated 2 predictive scores for complications after endovascular treatment (EVT) or neurosurgical treatment (NT) of UIA using routinely collected clinical and aneurysmal features. METHODS: We conducted a multicenter retrospective study including patients with UIA treated with EVT or NT across 15 neurovascular centers (2014-2024). Predictive models were built using multivariable logistic regression, with variables derived from Delphi consensus. The primary outcome was a composite safety end point: new neurological deficits, modified Rankin Scale (mRS) worsening (≥1 point or mRS 2-5 within 30 days), or procedural death. Internal validation used bootstrapping, and external validation was performed temporally and institutionally. Model performance was assessed using area under the receiver operating characteristic curve (AUROC) and calibration. Final scores, named Morbidity and Mortality Associated Risk in the Treatment of UIAs (MARTA)-EVT and MARTA-NT, were compared with existing models identified through systematic review. RESULTS: Among 2647 patients (1907 EVT and 740 NT), procedural complications occurred in 6.3% (EVT) and 12.8% (NT). Independent predictors included age, baseline mRS, aneurysm location, size, morphology, and procedural factors. MARTA-EVT (AUROC = 0.68, 95% CI = 0.57-0.78) and MARTA-NT (AUROC = 0.65, 95% CI = 0.54-0.77) showed moderate discrimination and good calibration. MARTA-EVT outperformed existing models; MARTA-NT performed similarly to SAFETEA. Predictive models are available open-source: https://martascoreapp.shinyapps.io/martascoreapp/. CONCLUSION: MARTA-EVT and MARTA-NT are validated tools for predicting procedural risks in UIA treatment and may support patient counseling and clinical decision making.

Sharing research code in an open access version-controlled repository offers significant benefits for both science as a whole and for individual researchers. In this article, we focus on this practice, which is fully aligned with the NIH’s Gold Standard Science (GSS) program as well as FAIR (findable, accessible, interoperable, reusable) and TRUST (transparency, responsibility, user focus, sustainability, technology) principles. Gold Standard Science supports open science by emphasizing transparency, reproducibility, and the use of best practices that enable others to verify and extend research. Pairing a research article’s cited data snapshot with a versioned, environment-specific code release, deposited in a companion code repository, ensures that, upon submission to a medical journal, readers and reviewers can directly verify results. An executable and updatable companion code repository complements, rather than replaces, established research data repositories. When code underlying medical research results is made openly available, then other scientists can inspect, run, and validate analyses. These activities enhance reproducibility, which is a core aim of GSS. Shared code also facilitates collaborative innovation by allowing researchers to extend the utility of the code to new datasets and applications. For researchers, code sharing can increase visibility, credibility, and citation impact. Demonstrating transparency through shared executable and updatable code builds trust with journal readers, peer reviewers, funders, and peers. Shared code in an open access repository signals adherence to high standards of scientific integrity and attracts opportunities for collaboration. A researcher who shares code receives recognition as a leader in reproducible, trustworthy research consistent with NIH’s GSS principles.

Abstract Background Large language models (LLMs) are increasingly used in medication-related tasks despite limited evidence supporting their accuracy and safety. LLMs are vulnerable to adversarial attacks and may confabulate in response to fabricated information in the prompt. Given the substantial risk of harm from medication errors, the purpose of this study was to establish a benchmark task to evaluate LLM performance in distinguishing fabricated from real medications. Methods Two datasets (brand and generic), each consisting of 250 medication lists were developed, each including 4-6 medications and one fabricated medication (specifically a Pokémon character), with complete dosing information provided. Six LLMs were evaluated (GPT-5-Chat, GPT-4o-mini, DrugGPT, Gemma-3-27B-IT, Llama-3.3-70B-Instruct, and Qwen3-32B). For each medication list, models were queried for dosing information and disease indication across three experimental conditions: standard decoding, standard decoding with mitigation prompting, and deterministic decoding (temperature = 0). Each experiment was performed in triplicate. Outputs were deemed confabulations if the LLM failed to recognize and reject the fabricated medication. The primary outcome was the rate of confabulations. Exact paired-permutation tests were used to compare confabulation rates across LLMs and prompting approaches. Results Confabulation rates under standard conditions ranged from 2.7% to 99.6%. DrugGPT demonstrated the lowest baseline confabulation rates (2.7-6.4%), whereas other models demonstrated substantially higher rates (47.2-99.6%). Mitigation prompting significantly reduced confabulation rates compared to standard and deterministic decoding across all tasks and datasets (p < 0.001): GPT-5-Chat achieved confabulation rates of 0% with mitigation prompting from baseline rates of 66.4-88.5%. Deterministic decoding did not substantially impact confabulation rates. Conclusions LLMs performing medication-related tasks are susceptible to confabulation in response to invalid or fabricated inputs, raising important safety concerns for clinical use. While mitigation prompting reduced confabulation rates, this study underscores the importance of robust safeguards when deploying LLMs in medication-related decision-making.

Purpose: Cutaneous squamous cell carcinoma has a propensity for perineural invasion. Treating perineural spread has involved surgery and adjuvant chemoradiation, and more recently, immune checkpoint inhibitors. This study aims to evaluate motor and sensory functional outcomes in patients with cranial neuropathies from perineural spread of squamous cell carcinoma, particularly those undergoing immunotherapy. Methods: This was a multicenter case series and literature review. Results: Eighteen patients with cranial neuropathies from perineural spread had a mean age of 72.5 ± 9.7 years. Cranial nerves V and VII were most often involved. Treatments included radiotherapy (8/18; 44.4%), chemotherapy (7/18; 38.9%), and/or immunotherapy (11/18; 61.1%), with many receiving a combination of modalities (8/18; 44.4%). Of those receiving immunotherapy, 72.7% (8/11) demonstrated at least partial clinical and/or radiologic tumor response. Among those with functional outcomes documented, half had improvement in sensory/motor nerve function following immunotherapy (4/8; 50%). A literature review identified 55 articles describing 449 patients total with cranial neuropathies from squamous cell carcinoma perineural spread. Combinations of surgery, chemotherapy, and/or radiotherapy were employed, with immunotherapy used in 16 patients. From 5 patients on immunotherapy with documented functional outcomes, all demonstrated at least some improvement. Conclusion: Immunotherapy plays an evolving role in managing advanced squamous cell carcinoma. Functional improvements in cranial neuropathy were demonstrated in 50% of patients receiving treatment with immunotherapy at a mean of 32.6 months of follow-up. This may hold important implications for the timing of surgical intervention, particularly in the case of cranial nerves V and VII palsies.

Introduction: Endometrial carcinoma (EC) is the most prevalent gynecological cancer. It is characterized by a clinical, pathological, and prognostic trajectory that has become inextricably linked to the disease’s molecular profile. Therefore, it is imperative to examine its relevance across all facets associated with the disease. Methods: This is a single-center retrospective study to assess tumor molecular profile concordance between EC diagnosis and recurrence. All patients who underwent hysterectomy for EC between 2016 and 2020 were included. Results: In total, 221 cases of EC were collected. In total, 18 recurrences were found. In two cases, there was a molecular classification (MC) change: an MMR-deficient endometrioid EC shifted to a “multiple classifier” subtype. The second, an NSMP subtype, at second recurrence revealed a switched MC to an aberrant mutated p53 profile. This discordance rate was non-significant in our cohort. However, considering the lack of evidence, it opens new insights to be revealed. Conclusions: This is the first study focusing on the discordance rate of MCs in EC relapses compared to the initial diagnosis. Future large-scale retrospective and prospective multicenter studies are essential for exploring this aspect.

64 Background: The incidence of eoCRC (diagnosed at age <50) is increasing. We have previously shown higher rates of severe anxiety and depression in this group compared to adults diagnosed at age ≥50 (average-onset CRC, aoCRC). We assessed the impact of ePROM collection coupled with a CC-based supportive care intervention on symptom burden in patients with eoCRC. Methods: The Enhanced, EHR-facilitated Cancer Symptom Control (E2C2) trial was a cluster-randomized, pragmatic trial conducted at Mayo Clinic Rochester and within the Mayo Clinic Health System (in Minnesota and Wisconsin) between 2019 and 2023. Enrolled patients serially reported the severity of six SPPADE symptoms (Sleep deficit, Pain, Physical function impairment, Anxiety, Depression, and Energy deficit/fatigue) on 11-point numerical rating scales. Symptom scores were interpreted as none to mild (0-3), moderate (4-6), or severe (7-10). Those with moderate symptoms were offered symptom management education and self-management materials, while those with severe symptoms were offered the option to work with a symptom care manager. In this post hoc analysis we examined the effects of the intervention on change in symptom scores among those with eoCRC, and using the Kaplan-Meier method, the median time to improvement to a mild/moderate level in those with a severe symptom, comparing eoCRC with aoCRC. Results: Among 4,422 patients with CRC, 887 had eoCRC. Forty-six percent of patients were female ( p =0.61), and a greater proportion of eoCRC patients were of a non-white race (11.6% vs 4.7%), lived in an urban setting (65.6% vs 50.5%), had a Bachelor’s degree or higher (36.8% vs 24.4%), were employed (78.5% vs 36.7%), on a non-government insurance plan (83.4% vs 35.3%), single (19.7% vs 11.2%) or married (74.2% vs 67.9%), and had metastatic disease (54.8% vs 46.1%, p <0.0001 for all). Compared to a pre-intervention baseline, the mean change in symptom scores for eoCRC patients following the intervention demonstrated improvements in anxiety (-0.238), depression (-0.134), and fatigue (-0.146, p <0.05 for all). Time to symptom improvement from severe to mild/moderate was longer for anxiety and depression in eoCRC patients compared to aoCRC patients (Table 1). Conclusions: Collection of ePROMs coupled with a CC-based intervention led to improvements in anxiety, depression, and fatigue among eoCRC patients, although time to symptom improvement was longer among eoCRC patients compared to aoCRC patients. Time to improvement of severe symptom (months), median (95% CI). eoCRC aoCRC p -value Sleep 4.2 (3.1-5.8) 3.8 (2.7-5.4) 0.4 Pain 4.1 (3.0-7.5) 3.2 (2.3-5.0) 0.5 Physical function impairment 3.1 (1.9-6.3) 2.8 (2.2-4.2) 0.5 Anxiety 4.3 (3.4-9.1) 2.6 (2.0-3.5) 0.009 Depression 4.3 (2.6-7.5) 2.6 (2.1-3.5) 0.04 Fatigue 4.3 (3.7-9.5) 3.4 (2.7-4.2) 0.06

Abstract Background Bipolar disorder (BD) is associated with impairments in facial emotion recognition (FER), affecting social functioning and quality of life. Understanding FER deficits in BD is crucial for tailoring interventions and improving treatment outcomes. This systematic review and meta-analysis aims to evaluate FER differences among individuals with BD, unaffected first-degree relatives (FDRs), and healthy controls (HCs), exploring predictors related to patient and study characteristics. Methods We systematically searched PubMed/MEDLINE, Scopus, EMBASE, and PsycINFO databases from inception to March 28, 2024. Random-effects meta-analyses were conducted to explore differences in accuracy and reaction time during FER identification and discrimination tasks. Results A total of 100 studies were included, comprising 4920 individuals with BD (females = 56%, mean age = 34.1 ± 9.1), 676 FDRs (females = 55%, mean age = 36.1 ± 12), and 4909 HCs (females = 53.2%, mean age = 32.5 ± 9.5). Compared to HCs, adults with BD exhibited significantly lower accuracy (SMD = −0.47; 95% CIs = −0.56, −0.38) and higher reaction time (SMD = 0.57; 95%CIs = 0.33, 0.81) during facial emotion identification tasks. During facial emotion discrimination tasks, adults with BD had significantly lower accuracy than HCs (SMD = −0.59; 95%CIs = −0.78, −0.4), but similar speed. No significant differences were observed between BD and FDRs. Meta-regressions identified several predictors of FER performance, including manic symptom severity, stimulus duration, and presence of practice before task. Conclusions FER deficits appear to be a core feature of BD and require specialized, systematic assessment. Identifying these deficits may help guide interventions aimed at improving affective cognition and social outcomes in individuals with BD.