Citations

OBJECTIVE Glucagon-like peptide-1 (GLP-1) agonists are established therapeutics for weight loss that are increasingly used for BMI optimization prior to spine surgery. However, emerging evidence has suggested that GLP-1 agonists might reduce bone mineral density (BMD), increasing the risk of postoperative biomechanical complications. CT-based Hounsfield units (HUs) have gained popularity as a method for measuring spinal BMD. The aim of this study was to evaluate the effects of GLP-1 agonist–induced weight loss on spinal BMD as measured by opportunistic CT-based HUs. METHODS Patients who were treated with any GLP-1 agonist (2017–2022) for > 3 months were retrospectively identified. Patient body weight (BW), BMI, and HU measurements in the L1 vertebral body were measured before and after GLP-1 therapy. Patients were grouped according to the percentage of weight loss during GLP-1 therapy. One-way ANOVA was used to compare the mean changes in spinal HUs across the groups. RESULTS Among the 102 included patients, the mean ± standard error of the mean BW reduction was 14.5 ± 2.5 kg over 15.9 ± 1.2 months of GLP-1 agonist therapy. Of these, 7 patients (6.9%) lost > 20% BW (mean decrease of 31.9 ± 7.0 HU, p = 0.011), 14 (13.7%) lost 15%–20% BW (mean decrease of 19.1 ± 8.3 HU, p = 0.038), 14 (13.7%) lost 10%–15% BW (mean decrease of 12.2 ± 5.1 HU, p = 0.036), 24 (23.5%) lost 5%–10% BW (mean decrease of 15.7 ± 3.3 HU, p < 0.0001), 26 (25.5%) lost < 5% BW (mean decrease of 14.7 ± 6.0 HU, p = 0.022), and 17 (16.7%) gained BW during GLP-1 therapy (mean decrease of 6.3 ± 5.0 HU, p = 0.229). One-way ANOVA testing did not show a significant difference in HU reduction across the weight loss groups (F = 1.12, p = 0.355). In addition, there was a significant correlation between the decrease in L1 HUs and the duration of GLP-1 therapy (r = −0.38, p = 0.0001) but not the amount of weight loss (r = −0.18, p = 0.070). In the multivariate analysis, the duration of GLP-1 therapy (p = 0.032) was a significant independent predictor of vertebral HU reduction, but the amount of weight loss (p = 0.664) was not. CONCLUSIONS Despite similar pretreatment BW and HU measurements, all weight loss groups had significant decreases in vertebral HUs following GLP-1 agonist therapy, with a significant correlation observed between HU reduction and treatment duration. This suggests that long-term GLP-1 agonist therapy can significantly diminish spinal BMD regardless of the amount of weight loss achieved.

OBJECTIVE Achieving submillimetric accuracy in stereotactic neurosurgery remains critical for safely targeting deep brain structures. Current workflows rely on intraoperative CT to register stereotactic frames to preoperative imaging, but this introduces additional radiation exposure, cost, and workflow complexity. Three-dimensional surface scanning (3DSS) potentially offers a fast radiation-free alternative capable of capturing detailed craniofacial anatomy and frame geometry. Therefore, the aim of this cadaveric study was to evaluate the feasibility, accuracy, and navigational compatibility of integrating 3DSS into stereotactic workflows as a potential replacement for intraoperative CT. METHODS A human cadaveric head was imaged with both thin-slice CT and structured-light 3DSS after mounting stereotactic frame components. CT, 3DSS, and computer-aided design (CAD) models were registered using a multistep point cloud alignment pipeline involving the fast point feature histogram, the random sample consensus method, and the iterative closest point algorithm. Accuracy was assessed using surface deviation error, root mean square error (RMSE), and fiducial registration error within a commercial neuronavigation platform. RESULTS Fusion of the 3D facial scan with CT provided a mean surface deviation error of approximately 0.4 mm. Registration of the 3DSS-derived N-bar localizer to its CAD reference model produced a frame alignment RMSE of 1.3 mm. Within the navigation system, the 3DSS-based workflow achieved a mean fiducial registration error of 0.14 mm (range 0.02–0.20 mm), outperforming the conventional CT-based method (mean error 0.20 mm, range 0.09–0.40 mm). CONCLUSIONS The 3DSS-based method enabled precise submillimetric stereotactic registration without the need for intraoperative CT, reducing radiation exposure and operative complexity. This workflow is fully compatible with existing navigation systems and could serve as a practical radiation-free alternative in stereotactic neurosurgery. Future work will focus on automating frame detection, incorporating artificial intelligence–driven fusion methods, and validating this approach in live surgical settings.

OBJECTIVE The aim of this study was to compare 3 electrode designs—a novel 22-contact circular grid, standard 6-contact strip, and high-density (HD) grid between 32 and 64 contacts—for the detection of epileptiform activity during awake craniotomy. METHODS This study included patients who underwent functional brain mapping with and without direct electrical stimulation during awake craniotomy. Demographic, clinical, and electrocorticography (ECoG) data were collected. RESULTS A total of 194 patients were included, with 264 instances of electrode use: 113 circular grid, 96 strip electrode, and 55 HD grid. The HD grid (15%) was used less to record ECoG during direct electrical stimulation than the circular grid (80%, p < 0.001) and strip electrodes (69%, p < 0.001). Sporadic interictal epileptiform activity was better detected with circular (45%, p < 0.001) and HD (40%, p = 0.006) grids compared with strip electrodes (16%). Spontaneous seizures were recorded more frequently with the circular grid (16%, p = 0.018) compared with the strip electrode (9.4%) and HD grid (1.8%). Afterdischarges were more frequently detected by the circular grid (69%, p = 0.031) and with circular and HD grids (combined) compared with strip electrodes (67% vs 48%, p = 0.024), at lower median intensity (3 mA vs 5 mA, p < 0.001). Multivariable analyses demonstrated circular grids (p < 0.001) to be more sensitive in detecting spontaneous epileptiform activity than strip and HD grid electrodes, and grids (circular and HD) to be better in recording stimulus-induced epileptiform activity (p = 0.01). CONCLUSIONS This study demonstrates a higher rate of detection of epileptiform activity with circular and standard grids when compared with strip electrodes. The standard HD grid was used less during electrical stimulation, demonstrating the importance of both the number of contacts and design array when considering optimal conditions for ECoG and functional brain mapping.

Background: Generative AI and synthetic media have enabled realistic human Embodied Conversational Agents (ECAs) or avatars. A subset of this technology replicates faces and voices to create realistic likenesses. When combined with avatars, these methods enable the creation of “digital twins” of physicians, offering patients scalable, 24/7 clinical communication outside the immediate clinical environment. This study evaluated surgical patient perceptions of an AI-generated surgeon avatar for postoperative education. Methods: We conducted a pilot feasibility study with 30 plastic surgery patients at Mayo Clinic, USA (July–August 2025). A bespoke interactive surgeon avatar was developed in Python using the HeyGen IV model to reproduce the surgeon’s likeness. Patients interacted with the avatar through natural voice queries, which were mapped to predetermined, pre-recorded video responses covering ten common postoperative topics. Patient perceptions were assessed using validated scales of usability, engagement, trust, eeriness, and realism, supplemented by qualitative feedback. Results: The avatar system reliably answered 297 of 300 patient queries (99%). Usability was excellent (mean System Usability Scale score = 87.7 ± 11.5) and engagement high (mean 4.27 ± 0.23). Trust was the highest-rated domain, with all participants (100%) finding the avatar trustworthy and its information believable. Eeriness was minimal (mean = 1.57 ± 0.48), and 96.7% found the avatar visually pleasing. Most participants (86.6%) recognized the avatar as their surgeon, although many still identified it as artificial; voice resemblance was less convincing (70%). Interestingly, participants with prior exposure to deepfakes demonstrated consistently higher acceptance, rating usability, trust, and engagement 5–10% higher than those without prior exposure. Qualitative feedback highlighted clarity, efficiency, and convenience, while noting limitations in realism and conversational scope. Conclusions: The AI-generated physician avatar achieved high patient acceptance without triggering uncanny valley effects. Transparency about the synthetic nature of the technology enhanced, rather than diminished, trust. Familiarity with the physician and institutional credibility likely played a key role in the high trust scores observed. When implemented transparently and with appropriate safeguards, synthetic physician avatars may offer a scalable solution for postoperative education while preserving trust in clinical relationships.

Background: Fixed drug eruption (FDE) is a non-immediate, CD8+ T cell–mediated hypersensitivity reaction characterized by well-demarcated erythematous–violaceous plaques that recur at the same site after re-exposure to the causative drug. Although NSAIDs and antibiotics are the most common triggers, various other medications may induce FDE, and genetic susceptibility has been linked to specific HLA alleles. Methods: We conducted a clinical evaluation supported by patch testing, oral drug provocation, and assessment of therapeutic alternatives to identify the causative agent and confirm delayed-type hypersensitivity. Results: We report the case of a 53-year-old woman with essential hypertension, autoimmune thyroiditis, and renal lithiasis who developed well-demarcated erythematous plaques with central vesiculation and moderate pruritus on the dorsal hand and posterior calf approximately 8 h after ingestion of a 60 mg etoricoxib tablet. Patch testing was negative, while oral challenge confirmed etoricoxib-induced FDE; celecoxib was subsequently evaluated as a potential safe alternative. Conclusions: This case underscores the importance of an integrated diagnostic approach—including careful history, clinical examination, and confirmatory testing—to accurately diagnose delayed cutaneous drug reactions and to identify safe therapeutic options for patients.

Background: Interstitial lung disease (ILD) involves numerous chronic pulmonary conditions that damage the lung parenchyma and alveolar interstitium. ILD has overlapping clinical and radiological features with other commonly seen cardiac and respiratory conditions. If not identified and treated in a timely manner, it may lead to irreversible fibrosis and a poor prognosis in the patient. The current diagnostic methods are either invasive or reliant on imaging or specialist interpretation, which can lead to diagnostic delay, increased radiation exposure, and healthcare costs. Lung crackles, often under-recognized as a non-specific feature of ILD, may serve as an important diagnostic clue in identifying not only the early stages of ILD but also its subtypes. This review explores the potential of analyzing the lung sounds in ILD through AI-based auscultation. Objective: To provide a comprehensive analysis of the pathophysiological stages of lung injury in ILD, the specific acoustic features, and the location associated with each ILD subtype and to evaluate the current state-of-the-art non-AI and AI methodologies that are used to diagnose ILD. This review aims to analyze the limitations associated with the current modalities and to envision AI-integrated auscultation as a powerful, cost-effective, non-invasive, radiation-free screening tool for early detection of ILD and its subtypes. Content Overview: The review begins with a detailed analysis of the lung sound pathophysiology, exploring the two-stage mechanism of alveolar epithelial injury and fibrosis formation. Existing hypotheses explaining the mechanism behind crackle production and the role of structural anatomy and surface tension in the generation of pathological lung sounds are examined. A tabulated summary of common ILD subtypes is provided, including their inciting events, pathogenesis, anatomical auscultation locations, and prognostic implications. Current diagnostic modalities for ILD, both non-AI and AI-based, are summarized along with their limitations, emphasizing the need for improved diagnostic tools. Discussion: Existing studies suggest that AI-based auscultation can match or exceed the current modalities in its sensitivity and specificity for detecting ILD-related crackles. Clinicians can identify the specific sound pattern and then correlate it with the ILD subtype and understand the prognosis in real time, thereby providing timely intervention to the patient. Additionally, AI-based auscultation can be used in resource-limited settings and can potentially reduce dependence on pulmonology expertise and radiation-based imaging for monitoring the condition. Conclusions: This literature review highlights the clinical potential of AI-based auscultation for early and accurate diagnoses of ILD. Understanding the associated pathological sounds, biomarkers, and genetic mutations linked to different subtypes opens avenues for future development of non-invasive diagnostic panels for ILD in clinical practice.

Importance The 2007 US Food and Drug Administration (FDA) Amendments Act (FDAAA) expanded its safety-related regulatory authorities, including enhanced postmarketing safety surveillance and new clinical study requirements. However, whether FDAAA has been associated with differences in the frequency and timing of postmarket safety-related actions remains poorly understood. Objectives To assess whether FDAAA was associated with differences in time to first FDA postmarket drug safety−related action, and to assess whether therapeutic and regulatory characteristics were associated with differences in time to these actions post-FDAAA implementation. Design and Setting This was a cross-sectional study of all novel therapeutics approved by FDA between January 1, 2001, and December 31, 2019, and followed up through December 31, 2024. Approvals were categorized as pre- or post-FDAAA (before or after March 25, 2008). Post-FDAAA therapeutic and regulatory characteristics included drug class, therapeutic area, orphan status, special regulatory pathway, and presence of a boxed warning or FDAAA-mandated postmarket study requirement at approval. Main Outcomes and Measures Time to first FDA postmarket drug safety−related action, a composite of withdrawals due to safety concerns, incremental boxed warnings, and safety-related communications. Results Of the 560 novel therapeutics approved, FDA took postmarket safety-related actions for 130 (23.2%) during a median (IQR) follow-up of 12.1 (7.8-18.2) years. These comprised actions within 5 years of approval for 34 of 164 therapeutics (20.7%) approved pre-FDAAA, and 57 of 396 (14.4%) approved post-FDAAA (rate ratio, 0.69; 95% CI, 0.47-1.02; P = .06). Compared to pre-FDAAA approvals, after accounting for therapeutic and regulatory characteristics, there was no statistically significant difference in time to first postmarket safety-related action for post-FDAAA approvals (time ratio, 0.40; 95% CI, 0.15-1.07; P = .07). However, among therapeutics with postmarket safety-related actions within 5 years of approval, median time to first action was shorter post-FDAAA (median [IQR], 3.1 (2.0-4.2) years for pre-FDAAA vs 1.8 [1.3-2.5] years post-FDAAA; P = .004). Among 260 novel therapeutics approved post-FDAAA, after the October 2013 enactment of breakthrough therapy designation, the following therapeutic and regulatory characteristics were associated with time to first postmarket safety-related action: small molecule type (time ratio, 0.24; 95% CI, 0.07-0.81; P = .02), orphan designation (time ratio, 8.29; 95% CI, 2.43-28.27; P &amp;lt; .001), fast track (time ratio, 0.22; 95% CI, 0.08-0.64; P = .005), breakthrough therapy designation (time ratio, 0.10; 95% CI, 0.03-0.32; P &amp;lt; .001), prolonged regulatory review time (&amp;gt;400 days; time ratio, 0.16; 95% CI, 0.03-0.73; P = .02), and FDAAA-mandated postmarket study requirements at approval (time ratio, 0.35; 95% CI, 0.15-0.80; P = .01). Conclusions and Relevance This cross-sectional analysis found that the enhanced safety-related regulatory authorities of FDAAA were not associated with differences in time to first postmarket safety-related action. However, among therapeutics with postmarket safety-related actions within 5 years of approval, median time to first action was shorter post-FDAAA implementation.