Traumatic brain injury (TBI) initiates a complex cascade of pathophysiological events that have far-reaching consequences beyond the initial injury. This review examines the current state of the literature on the mechanisms underlying neurotrauma and neuroinflammation, with particular emphasis on the molecular cross-talk between these disparate pathways that ultimately precipitates the development of chronic traumatic encephalopathy (CTE). We integrate this mechanistic knowledge with potential diagnostic biomarkers, such as glial fibrillary acidic protein (GFAP), neurofilament light chain (NfL), and ubiquitin carboxy-terminal hydrolase L1 (UCH-L1), and advances in neuroimaging and machine learning-based predictive tools. Finally, we discuss the current therapeutic approaches under investigation, and highlight which molecular targets have yet to be explored for potential therapeutic development.

Study Design: Retrospective Cohort Study. Objectives: To compare 1-year postoperative outcomes and complication rates between single-level lumbar laminectomy and hemilaminectomy using a large, multicenter, propensity-matched dataset. Methods: We queried the TriNetX global health research network (≥160 million patients) for adults undergoing single-level lumbar decompression between January 2005 and July 2025. Cohorts were defined by CPT codes: laminectomy and hemilaminectomy, with qualifying diagnoses of lumbar disc herniation, spinal stenosis, spondylolisthesis, or radiculopathy. Patients with fusion, prior lumbar surgery, or non-degenerative pathology were excluded. Outcomes included new postoperative events within 1 year: mortality, weakness, pain, sensory loss, cauda equina syndrome, radiculopathy, foot drop, CSF leak, and surgical-site infection. Propensity-score matching balanced demographics and comorbidities. Cox proportional hazards models, Kaplan–Meier curves, and relative risks were calculated. Results: Of 167,177 patients, 80,440 underwent laminectomy and 86,737 hemilaminectomy. After matching, 50,853 patients per cohort were analyzed. One-year mortality was similar (0.57% vs 0.49%, HR 1.20; 95% CI 1.01-1.42; P = 0.045). Laminectomy conferred significantly higher risks of CSF leak (1.41% vs 1.00%; RR 1.41), surgical-site infection (1.45% vs 1.00%; RR 1.45), cauda equina syndrome (0.36% vs 0.22%; RR 1.62), and persistent weakness (4.12% vs 3.67%; RR 1.12). Persistent radiculopathy was modestly less frequent after laminectomy (10.5% vs 12.0%; RR 0.87). Other outcomes, including pain and foot drop, were comparable. Conclusions: Hemilaminectomy was associated with lower perioperative complication rates compared to laminectomy, while laminectomy provided a modest reduction in persistent radiculopathy. These findings highlight a tradeoff between safety and decompressive efficacy, emphasizing the importance of patient-specific surgical selection.

Background: Traumatic brain injury (TBI) imposes a substantial public health burden through long-term physical, cognitive, and psychiatric effects. This includes substance use disorders (SUDs) for which TBI is a demonstrated risk factor; however, prior studies have not comprehensively compared relative incidences of SUD subtypes post-TBI or differences between intracranial hemorrhage (ICH) and non-ICH TBI in patients without prior SUD history. This global retrospective analysis using the TriNetX database aims to quantify new-onset SUD incidence post-TBI in the largest cohort of patients evaluated to date, with cohorts stratified by SUD subtype and ICH versus non-ICH TBI, to highlight opportunities for post-injury care models to mitigate SUD risk. Methods: De-identified data from the TriNetX Research Network were used to select patients with TBI (n = 1,889,112) and define distinct cohorts based upon the presence (n = 420,868) or absence (n = 1,471,592) of ICH. Patients with previously diagnosed SUD before the date of TBI were excluded. Patient demographics and medical comorbidities were calculated for each group. The incidence of new SUD diagnosis over the lifetime and at 1-, 3-, and 5-years post-TBI were calculated and compared. Subtypes of SUD were defined and calculated based on the specific substance used. Propensity scores were calculated to create balanced matched ICH and non-ICH cohorts (n = 331,812 each) were used for comparisons of 5-year SUD incidence. Results: In the full TBI cohort, 5-year new SUD incidence was 4.2% overall, with nicotine (2.4%) and alcohol (1.1%) predominating, followed by cannabis (0.9%) and opioids (0.4%). Rates of SUDs increased over time, but attenuated beyond 5 years, with approximately 50% of those who would ultimately be diagnosed with SUD manifesting (lifetime) by 3 years post-TBI. After propensity matching, non-ICH TBI showed higher 5-year risk for any SUD (4.2% vs. 3.6%; risk difference −0.65%, p < 0.0001) and all subtypes (p < 0.05) except inhalants (p = 0.53). Conclusions: This largest-to-date analysis of new-onset SUD post-TBI demonstrates significantly higher rates of SUD in TBI patients; rates of nicotine, alcohol, cannabis, and opioid use disorders were most common. Non-ICH TBI patients demonstrated greater rates of SUD after injury than patients with ICH-associated TBI. Of patients suffering from TBI without ICH who would eventually be diagnosed with SUD, approximately 50% had obtained that diagnosis within 3 years of the injury. Taken together, these findings demonstrate the clinical need for routine SUD screening in post-TBI care, especially for 3 years post-injury. Such an intervention has the potential to significantly alleviate the public health burden and associated cost of care for TBI-associated substance use disorder patients.

BACKGROUND AND OBJECTIVES: The optimal antithrombotic therapy after carotid artery stenting (CAS) in patients requiring oral anticoagulation is uncertain; in particular, the safety and effectiveness of combining direct oral anticoagulants (DOACs) with single antiplatelet therapy (SAPT) compared with DOACs combined with dual antiplatelet therapy (DAPT) are not well-established. METHODS: This retrospective cohort study used data from the TriNetX Research Network, which aggregates deidentified electronic health records from multiple healthcare organizations. Patients aged 35 to 90 years who underwent CAS between January 2010 and January 2025 were included. Patients receiving DOAC + SAPT were compared with those receiving DOAC + DAPT. Propensity score matching (1:1) was performed. The primary end point was intracranial hemorrhage, and secondary end points included gastrointestinal bleeding, all-cause mortality, venous thromboembolism, inpatient readmissions, new ischemic stroke, and head imaging utilization. RESULTS: Of 1973 patients identified, 304 received DOAC + SAPT and 1669 received DOAC + DAPT before matching. After matching, 293 patients remained in each cohort. No statistically significant difference was observed between the 2 groups in the rate of intracranial hemorrhage (3.8% vs 4.1%, respectively; risk ratio 0.917, 95% CI, 0.411-2.044; P = .832). Other secondary outcomes like head imaging ( P = .931), gastrointestinal bleeding ( P = .456), all-cause mortality ( P = .520), incidence of pulmonary embolism/deep venous thrombosis ( P = .261), inpatient readmissions ( P = .210), and new ischemic stroke ( P = .101) were comparable between cohorts. CONCLUSION: Among patients undergoing CAS who required anticoagulation, DOAC combined with SAPT was associated with similar clinical outcomes compared with DOAC combined with DAPT. Given the theoretical hemorrhagic risk associated with triple antithrombotic therapy, these findings cautiously support consideration of DOAC + SAPT as a clinically reasonable alternative—particularly in patients at elevated bleeding risk—while recognizing that individual risk-benefit assessment remains essential. These data inform the design of a dedicated randomized controlled trial comparing antithrombotic regimens after CAS in patients requiring long-term anticoagulation.

Web-based large language models (LLMs) are increasingly used by patients for medical self-assessment, but their efficacy in spine imaging diagnostics remains underexplored. This study systematically evaluated 5 leading multimodal LLMs-Grok 2, Grok 3, Grok 4, ChatGPT, and Gemini-for detecting scoliosis and lumbar spinal stenosis across radiographs and MRI modalities. We assessed 171 full-length anterior-posterior radiographs (100 with scoliosis, 71 normal) and 200 axial T2-weighted lumbar spine MRIs (100 with severe stenosis, 100 normal) from public databases. Models were prompted without examples to identify pathology and quantify certainty (0%-100%). Analyses included McNemar's test for accuracy and ANOVA for confidence levels. In scoliosis detection, Grok 4 exhibited superior accuracy (0.942), followed by Gemini (0.912), Grok 2 (0.890), ChatGPT (0.643), and Grok 3 (0.637). For stenosis, Gemini performed best (0.600), then Grok 4 (0.575), ChatGPT (0.545), Grok 2 (0.500), and Grok 3 (0.450). All models sustained >70% mean certainty (SD < 5.3%) across pathologies. ChatGPT and Grok 3 demonstrated reduced confidence in erroneous scoliosis responses (P < 0.0001), while only ChatGPT did so for stenosis. Gemini reported elevated confidence in incorrect stenosis responses (P < 0.0001). LLMs perform highly in scoliosis detection but struggle to identify lumbar stenosis. ChatGPT's superior confidence calibration suggests enhanced reliability. Performance inconsistencies across model iterations (e.g., Grok 3 underperforming Grok 2) underscore the necessity for specialized medical imaging training. Although promising for patient education in simple spine conditions, substantial advancements in accuracy and confidence metrics are essential prior to clinical adoption or broad patient utilization.