Citations

Background and objectives To evaluate the safety and clinical efficacy of efgartigimod in adults with severe generalized myasthenia gravis (MG) exacerbations requiring ventilatory or enteral support. Methods Prospective, single-arm, open-label study conducted between November 2024 and April 2025. Sixteen consecutive adults with AChR- or MuSK-antibody-positive generalized MG requiring invasive or non-invasive ventilatory support or enteral feeding were enrolled; all met 2016 MG Guidelines criteria for impending myasthenic crisis. MGFA classification included Class IIIb (n=14), IIIa (n=1), and IVb (n=1). The primary endpoint was clinically meaningful improvement (CMI) in MG Activities of Daily Living (MG-ADL), defined as ≥2-point reduction from baseline at weeks 4 and 8. Results All 16 participants (mean age 58.5±17.4 years; 8 women) completed eight weeks of follow-up. At week 8, 12 patients (75%; 95% CI 47–91%) achieved the primary endpoint. Median MG-ADL decreased from 11 (IQR 9–13) to 7 (IQR 6–9) (median change −5 points; p=0.003). Median QMG decreased from 21 (IQR 19–23) to 13 (IQR 11–16) (median change −7.5 points; p<0.001), with 56% meeting QMG-CMI by week 1. Among 12 participants receiving corticosteroids (mean starting dose 21.2 mg/day), 50% reduced or discontinued by week 8. No treatment-related serious adverse events occurred. Discussion Efgartigimod produced rapid, clinically meaningful improvement in severe MG exacerbations without safety concerns. FcRn blockade may represent a practical alternative to plasma exchange or IVIG in acute care settings. Findings are limited by the absence of a control arm, which precludes definitive attribution of clinical improvement to efgartigimod alone. Clinical trials registration NCT06688253.

ABSTRACT Background Long‐term health effects of thymectomy in adults remain uncertain. Previous reports suggested associations with increased mortality, cancer incidence, and autoimmune disease, although these findings may reflect differences in patient selection, surgical indication, or follow‐up duration. We aimed to examine long‐term outcomes following adult thymectomy. Methods We performed a propensity score‐matched retrospective study of patients who underwent thymectomy or comparator cardiothoracic procedures, with follow‐up extending to 10 years. Primary outcomes were all‐cause mortality, new‐onset malignancy, and autoimmune disease. Findings were compared with those reported in a recent study that has raised caution regarding thymic excision. Results We identified 425 patients who underwent thymectomy and 5401 controls who underwent coronary artery bypass or valve surgery. After matching, 398 patients remained in each group. Thymectomy was not associated with increased mortality at 5 years ( HR = 0.63; 95% CI , 0.38–1.04) or 10 years ( HR = 0.78; 95% CI , 0.54–1.13). Excluding reclassified thymic cancers, 5‐year extrathymic malignancy incidence was 2.3% versus 1.8% ( p = 0.54); no significant differences were observed in immune‐related disease. Mortality was higher among patients with thymic malignancy. Among MG patients, only one event occurred, precluding reliable estimation. Conclusions Thymectomy was not associated with excess mortality or malignancy at 10 years compared with matched cardiothoracic controls. Indication‐stratified analyses within the thymectomy cohort showed higher mortality for thymic malignancy, with insufficient events to assess outcomes in MG patients. These findings do not support a generalized survival penalty from thymectomy, though caution is warranted for incidental thymic removal.

Abstract Chronic headache is a common complication after mild traumatic brain injury (mTBI), which affects close to 70 million individuals annually worldwide. This study aims to test the utility of a unique, early predictive magnetic resonance imaging (MRI)-based classification model using structural brain MRI scans, a rarely used approach to identify high-risk individuals for post-mTBI chronic pain. We recruited 227 patients with mTBI after a vehicle collision, between March 30, 2016 and December 30, 2019. T1-weighted brain MRI scans from 128 patients within 72 hours postinjury were included and served as input for a pretrained 3D ResNet-18 deep learning model. All patients had initial assessments within the first 72 hours after the injury and performed follow-ups for 1 year. Chronic pain was reported in 43% at 12 months postinjury; remaining 57% were assigned to the recovery group. The best results were achieved for the axial plane with an average accuracy of 0.59 and an average area under the curve (AUC) of 0.56. Across the model's 8 folds. The highest performance across folds reached an AUC of 0.78, accuracy of 0.69, and recall of 0.83. Saliency maps highlighted the right insula, bilateral ventromedial prefrontal cortex, and periaqueductal gray matter as key regions. Our study provides insights at the intersection of neurology, neuroimaging, and predictive modeling, demonstrating that early T1-weighted MRI scans may offer useful information for predicting chronic head and neck pain. Saliency maps may help identify brain regions linked to chronic pain, representing an initial step toward targeted rehabilitation and early intervention for patients with mTBI to enhance clinical outcomes.

BACKGROUND: While clinical practice guidelines advocate for multidisciplinary heart team (MDHT) discussions in coronary revascularization, variability in implementation across health care settings remains a challenge. This variability could potentially be addressed by language learning models like ChatGPT, offering decision-making support in diverse health care environments. Our study aims to critically evaluate the concordance between recommendations made by MDHT and those generated by language learning models in coronary revascularization decision-making. METHODS: From March 2023 to July 2023, consecutive coronary angiography cases (n=86) that were referred for revascularization (either percutaneous or surgical) were analyzed using both ChatGPT-3.5 and ChatGPT-4. Case presentation formats included demographics, medical background, detailed description of angiographic findings, and SYNTAX score (Synergy Between Percutaneous Coronary Intervention With Taxus and Cardiac Surgery; I and II), which were presented in 3 different formats. The recommendations of the models were compared with those of an MDHT. RESULTS: ChatGPT-4 showed high concordance with decisions made by the MDHT (accuracy 0.82, sensitivity 0.8, specificity 0.83, and kappa 0.59), while ChatGPT-3.5 (0.67, 0.27, 0.84, and 0.12, respectively) showed lower concordance. Entropy and Fleiss kappa of ChatGPT-4 were 0.09 and 0.9, respectively, indicating high reliability and repeatability. The best correlation between ChatGPT-4 and MDHT was achieved when clinical cases were presented in a detailed context. Specific subgroups of patients yielded high accuracy (>0.9) of ChatGPT-4, including those with left main disease, 3 vessel disease, and diabetic patients. CONCLUSIONS: The present study demonstrates that advanced language learning models like ChatGPT-4 may be able to predict clinical recommendations for coronary artery disease revascularization with reasonable accuracy, especially in specific patient groups, underscoring their potential role as a supportive tool in clinical decision-making.

Abstract Traumatic brain injury (TBI) annually impacts 69 million individuals worldwide. Mild TBI constitutes approximately 90% of all TBIs. Chronic pain post-mTBI occurs in 29% to 58% of patients. This study aims to introduce a predictive model for chronic pain development in individuals diagnosed with mild traumatic brain injury (mTBI) immediately postinjury. We included individuals who had sustained mTBI in motor vehicle accident (MVA). All patients had initial assessments within the first 72 hours (representing the subacute period) after the injury and performed follow-ups for 1 year. Machine learning model was applied to the integrated measures of clinical pain, pain-related psychological parameters, mTBI clinical signs, and sociodemographic information. This study included 203 patients experiencing acute head or neck pain attributable to mTBI post-MVA. We categorized these patients into 2 groups: patients who progressed to develop chronic head or neck pain (n = 89, 43.8%) and patients who recovered (low/mild pain) (n = 114, 56.2%). Severity of the subacute neck pain, number of painful body areas, and education years were identified as the most significant factors predicting chronic pain. The optimized predictive model demonstrated high efficacy, with an accuracy of 83%, a sensitivity of 92%, and an area under the receiver operating characteristic curve of 0.8. Our findings indicate feasibility in predicting chronic post-MVA pain within the critical 72-hour window postinjury using simple bedside metrics. This approach offers a promising avenue for the early detection of individuals at increased risk for chronic pain, enabling the implementation of targeted early interventions.

Background: The normal limits of nerve conduction studies are commonly determined by testing healthy subjects. However, in comprehensive real-life nerve conduction electrodiagnostic (EDX) evaluations, multiple nerves are tested, including normal nerves, for purposes of comparison with abnormal ones. Objective: This study aims to evaluate the average values of normal nerve conduction studies in a large population and examined the influence of age and sex. Methods: EDX parameters were extracted from an electronic database of studies performed from May 2016 to February 2022. Established normal values were used to determine the classification of a nerve study as normal. Results: We identified 10,648 EDX reports with 5077 normally interpreted nerve conduction studies (47.6%) of which 57% ( n = 2890) were for females. The median age of studies with no abnormalities was 45.1 years (range < 1 to 92) overall and 42.5 years (range: 0.16 –89.5 years) for males and 47.5 years (range:<1 –91.7) for females. Correlations between age and amplitude, latency, and velocity ( p < 0.001) were observed in most nerves. Amplitude correlated negatively with age in adults in all nerves with a mean of –0.44 (range: –0.24 to –0.62). However, in the pediatric population (age < 18 years), amplitude as well as velocity increased significantly with age. In the adult cohort, sex differences were noted, where females had higher mean sensory nerve action potentials in ulnar, median, and radial evaluations ( p < 0.001). In older patients (aged > 70 years) with normally interpreted EDX studies (845 records of 528 patients), sural responses were present in 97%. Conclusions: This real-life study confirms that advanced aging is associated with decreased nerve conduction amplitudes, increased latency, and the slowing of conduction velocity. The findings also indicate higher sensory amplitudes and conduction velocities in females. Sural nerve responses were identified in most adults over age 70.