Citations

Biparietal osteodystrophy, also known as bilateral parietal calvarium bone thinning, is a rare calvarial condition characterized by loss of diploic bone within the parietal region. Although historically described in anthropologic and radiologic literature, current understanding of its epidemiology, pathogenesis, clinical relevance, and management remains fragmented. This review synthesizes current evidence and highlights emerging studies on biparietal osteodystrophy. Epidemiologic reports indicate that biparietal osteodystrophy affects a broad age range but appears most frequently in older adults, with several series suggesting a slight female predominance. Prevalence is difficult to estimate due to incidental detection, though modern imaging has increased recognition of the condition. Histologically and anatomically, biparietal osteodystrophy is marked by thinning of the outer table and loss of the diploic space, with little osteoblastic or osteoclastic remodeling. Proposed pathogenic mechanisms include chronic degenerative change, impaired vascular supply to the diploë, and other theories, although no single explanation fully accounts for its complete presentation. Clinically, most patients remain asymptomatic, with complications such as calvarial fractures and traumatic brain injury being rare but highlighting the structural vulnerability associated with severe thinning. Management strategies are not standardized, and the use of anti-osteoporotic drugs and cranioplasty has been reported to offer benefit in select cases, although no treatment has been formally validated for biparietal osteodystrophy. As the understanding of biparietal osteodystrophy continues to evolve, future research is needed to clarify its natural history, identify potential etiologic pathways, and establish evidence-based management guidelines.

Objective Meaningful assessments of how large language models (LLMs) incorporate clinical guidelines require large-scale testing over many queries. Here, we evaluate the prevalence of clinical guideline omissions and hallucinations in a large sample of diagnostic LLM outputs. Methods We used simulated case vignettes and zero-shot prompting to generate diagnostic outputs and rationales from GPT-4.1 and DeepSeek-V3. English case vignettes were created for hypercholesterolaemia and type-2 diabetes mellitus. Each vignette contained identical medical information, while sociodemographic characteristics varied in terms of sex, ethnicity and location. We calculated the prevalence of existing and hallucinated clinical guidelines in LLM outputs across disease, LLM and sociodemographic characteristics. Results We analysed a total of 12 197 LLM outputs, which quantifies three hazard areas: omissions (up to 97% for DeepSeek-V3 and 46% for GPT-4.1), hallucinations (up to 9%) and inconsistencies (guideline citation rate ranging from 0% to 78.39% across sociodemographic vignettes). Omission and hallucination rates were generally similar across vignettes with different sex or ethnicity data, yet were particularly sensitive to patient location. Discussion This study highlights significant variability in clinical guideline prediction across two different diseases, three different sociodemographic variables and two LLMs, even when the LLMs were instructed by identical prompts, establishing clinical guideline prediction in LLM outputs as a stochastic event. Conclusion The stochastic nature of LLMs creates a unique challenge for evidence generation and clinical deployment. Being able to measure and capture this stochasticity within high-quality research designs will be a prerequisite to advancing the responsible deployment of LLMs in healthcare.

Chimeric antigen receptor (CAR) T-cell therapy is an effective treatment for hematologic malignancies. However, it is limited by high costs, risk of severe toxicities such as cytokine release syndrome and neurotoxicity, and heterogeneous patient responses. The current therapy monitoring depends largely on subjective symptom assessment, routine laboratory tests, and basic vital signs, without real-time, quantitative evaluation of CAR T-cell expansion or activation in clinical practice. This lack of timely immune monitoring hampers individualized care and contributes to increased treatment costs. To address this need, we present a proof-of-concept, label-free rapid optical imaging (ROI) biosensor with automated machine learning analysis for direct quantification of CAR T-cells from whole blood. This microfluidic platform integrates red blood cell (RBC) removal, CAR T-cell capture, and imaging-based quantification on a single chip, eliminating the need for centrifugation, staining, and operator-dependent interpretation. For validation, 50 μL whole blood samples spiked with Jurkat cells expressing CD19 CARs underwent RBC depletion by agglutination and microfiltration. The remaining blood components were then incubated on a sensor chip functionalized with recombinant CD19 protein. Captured CAR T-cells were imaged by brightfield microscopy and automatically enumerated using a machine learning algorithm trained on fluorescence-validated cells. The CD-19 cells’ capture performance was validated by flow cytometry and fluorescence imaging. The trained machine learning model validated at 88% sensitivity and 96% specificity. Buffer and whole blood calibration curves were established across clinically relevant concentrations (1–1000 cells/µL) with triple replicates. The results showed high correlation (0.975 and 0.990 R2) between the spiked concentration and the detected CAR T-cells, with a 95% certainty limit of detection (LOD) and quantification (LOQ) of 0.6 and 1.1 cells/µL for spiked buffer, and 14 and 67 cells/µL for spiked whole-blood, respectively.

Abstract Objective To evaluate the short- and long-term clinical outcomes of transcatheter aortic valve replacement (TAVR) among participants with RA and aortic stenosis compared with those without RA, using real-world data from a large multicentre registry. Methods Using the TriNetX Research Network, participants with aortic stenosis undergoing TAVR with (RA+) vs without (RA−) RA were identified. Odds ratios (ORs) with 95% CIs estimated 30-day all-cause mortality, permanent pacemaker implantation, ischaemic stroke, acute kidney injury, myocardial infarction, cardiogenic shock, major vascular complications, and major or life-threatening bleeding were evaluated. Five-year outcomes included all-cause mortality, ischaemic stroke, myocardial infarction and all-cause hospitalization. Cox regression was used to estimate hazard ratios (HRs) with 95% CIs. Results A total of 1414 RA+ (4.3%) and 39 004 RA− participants were eligible. After matching, 1374 were included in each cohort. At 30 days, outcomes did not differ between RA+ and RA− groups; mortality was 2.0% vs 1.5% (OR 1.29; 95% CI 0.73–2.29), with no significant differences in other endpoints. Over 5 years, mortality was 23.8% vs 20.5% (OR 1.12; 95% CI 0.97–1.31), and stroke, myocardial infarction and hospitalization were similar; HRs were concordant with OR estimates. In sex-based analyses of RA patients, outcomes did not differ by sex. Conclusion In this large observational study, TAVR was not associated with excess short- or long-term risk in patients with RA. These findings support TAVR as a safe therapeutic option in RA patients with aortic stenosis.

Abstract Background Isocitrate dehydrogenase (IDH)-mutant gliomas are infiltrative tumors with limited treatment options at recurrence. Early studies suggest IDH inhibition has therapeutic activity. We evaluated clinical outcomes associated with IDH-1 inhibitor ivosidenib in recurrent IDH-1-mutant gliomas and molecular predictors of response. Methods We retrospectively analyzed adults treated with ivosidenib from January 2021 to August 2025 with predominantly recurrent, pretreated CNS WHO grade 2-4 astrocytoma IDH-mutant or grade 2-3 oligodendroglioma, IDH-mutant and 1p/19q codeleted. Prior anticancer treatments, toxicities, enhancement status at ivosidenib initiation, and genomic alterations were collected. The primary endpoint was progression-free survival (PFS); secondary analyses evaluated associations between PFS, genomic complexity, and CDKN2A/B homozygous deletion. Results Ninety-two adults, median age 43, were included: 61 astrocytomas and 31 oligodendrogliomas, mostly grade 2. Before ivosidenib, 69 had surgery, 64 chemotherapy, and 64 radiation. Median time from diagnosis to ivosidenib was 4.8 years, with median of two prior progressions. Median treatment duration was 5.8 months. Median PFS was 15.2, 4.6, and 2.1 months for astrocytoma grades 2-4, 14.0 and 6.9 months for oligodendroglioma grades 2-3. Increasing genomic complexity was associated with shorter PFS in univariate analysis. Patients without CDKN2A/B homozygous deletion had median PFS of 19.2 months. Two patients with homozygous deletion had median PFS of 0.6 months. Conclusions In this retrospective analysis of predominantly recurrent IDH-1-mutant glioma, ivosidenib was associated with longer PFS in lower-grade, non-enhancing tumors that received little or no prior anticancer treatment and less complex genomic profiles. These findings support a context-dependent benefit of IDH inhibition in recurrent disease.

Abstract Background Knowing the prevalence of patent foramen ovale (PFO) and the increasing number of people who inject drugs (PWID) with right-sided infective endocarditis (RSIE), we aimed to better characterize the syndrome of injection drug use, RSIE, and PFO with systemic embolic events. Method A systematic search across multiple databases was independently screened using predefined criteria (from inception until September 2025). Published cases of adult PWID diagnosed with RSIE and ischemic stroke or other systemic embolic event were included, provided they had PFO assessment. Individuals were excluded if they had cardiac implantable electronic device (CIED) infections or any other conditions associated with systemic or paradoxical embolism. Results The review identified 13 studies with 14 young patients, mostly without comorbidities, predominantly infected with Staphylococcus aureus. In most cases, echocardiography revealed large tricuspid valve vegetations. Neuroimaging confirmed multiple ischemic infarcts, while 5 patients showed emboli outside the central nervous system (4 of them as the only systemic embolism). At least 11 (79%) patients had echocardiographic evidence of right-to-left shunting. Management included cardiac surgery in 6 cases that involved valve replacement or repair, percutaneous PFO closure in 2 cases, and percutaneous mechanical aspiration in 1 case. Three patients (21%) died during hospitalization, and only 27.3% patients had outpatient follow-up. Conclusions RSIE with systemic embolism in PWID with PFO has rarely been reported, affects younger patients without sex predominance, and was usually due to S. aureus with large tricuspid vegetations. Right-to-left shunting was characteristic, and outcomes were poor despite combined medical, surgical, and interventional therapies.

Background/Objectives: Characterizing spinal cord multiple sclerosis (MS) lesions in MRI is critical for diagnosis, monitoring, and treatment evaluation. However, current automated approaches for lesion detection and segmentation are typically designed for specific MRI contrasts or acquisition sites, limiting their generalizability in real-world clinical settings where imaging protocols vary widely. This work proposes a robust multi-site, multi-contrast segmentation framework for spinal cord lesions. Methods: The segmentation model was trained and evaluated on a large-scale dataset comprising 4428 annotated images from 1849 persons with MS across 23 imaging centers, encompassing six MRI contrasts (T1w, T2w, T2*w, PSIR, STIR, and UNIT1) acquired at 1.5 tesla (T), 3 T, and 7 T. Results: Likert-type assessment performed by neuroradiologist ratings demonstrated superior generalization of the model compared to existing contrast-specific pipelines ( p < 0.01). Additional experiments evaluated robustness across spinal levels, acquisition resolutions, binarization thresholds, and quantitative evaluation on external labeled datasets. Conclusions: The proposed model can achieve accurate and reliable spinal cord MS lesion segmentation across heterogeneous MRI data, addressing a key barrier to clinical translation. The model is available in the Spinal Cord Toolbox v7.2 and higher. Code repository: https://github.com/ivadomed/seg-sc-ms-lesion-multicontrast