Boston University School of Medicine

Advances in understanding the molecular landscape of gastroesophageal junction (GEJ) adenocarcinoma underscore the need for biomarker-driven treatment approaches. The Society of Surgical Oncology (SSO) Gastrointestinal (GI) Disease Site Working Group has developed practice guidelines for the biomarker-based management of nonmetastatic GEJ adenocarcinoma, with specific integration of microsatellite instability (MSI) status. Although multimodal therapy has improved outcomes, treatment strategies for GEJ adenocarcinoma remain largely stage-based rather than biomarker-directed. With emerging evidence supporting the prognostic and predictive roles of MSI-high (MSI-H), human epidermal growth factor receptor 2 (HER2), and other novel targets, there is an urgent need for clear guidance on how to incorporate biomarkers into the management of resectable disease. These guidelines provide evidence-based recommendations to support precision oncology in GEJ cancer care.

BACKGROUND:Endovascular thrombectomy for acute ischemic stroke due to medium-vessel occlusion has had varying results across trials. Whether thrombectomy improves functional outcomes in patients with medium-vessel occlusion and moderate-to-severe deficits is unclear. METHODS:We conducted an open-label, randomized trial with blinded outcome assessment at 48 centers in China. Eligible patients were adults who presented within 24 hours after the onset of a moderate-to-severe stroke (National Institutes of Health Stroke Scale [NIHSS] score, ≥6; scale, 0 to 42, with higher scores indicating greater neurologic deficits) due to occlusion of a medium vessel. Patients were assigned in a 1:1 ratio to thrombectomy plus medical management (thrombectomy group) or medical management alone (control group). The primary outcome was functional disability as measured by the shift in the modified Rankin scale score (scale, 0 [no disability] to 6 [death]) at 90 days. Violation of the proportional-odds assumption precluded the use of shift in the modified Rankin scale score, so as prespecified, functional independence (modified Rankin scale score of 0, 1, or 2) at 90 days was used as the primary outcome. Safety outcomes were symptomatic intracranial hemorrhage and 90-day mortality. RESULTS:Among 280 patients in the thrombectomy group and 283 in the control group, the median age was 71 years, the median NIHSS score was 10 (range, 3 to 36), and 42.8% were women; 36.6% received intravenous thrombolysis. Functional independence at 90 days was seen in 58.6% of the patients in the thrombectomy group and in 46.6% of those in the control group (adjusted rate ratio, 1.24; 95% confidence interval, 1.07 to 1.44; P = 0.004). The incidence of symptomatic intracranial hemorrhage was 4.7% in the thrombectomy group and 2.2% in the control group; 90-day mortality was 11.1% and 10.2%, respectively. CONCLUSIONS:Among patients with acute ischemic stroke due to medium-vessel occlusion and moderate-to-severe deficits, thrombectomy led to a greater likelihood of functional independence than medical management alone but also to a higher risk of symptomatic intracranial hemorrhage. (Funded by the National Natural Science Foundation of China and the Noncommunicable Chronic Diseases-National Science and Technology Major Project; ORIENTAL-MeVO ClinicalTrials.gov number, NCT06146790.).

INTRODUCTION:Adequate sleep is vital for maintaining mental and physical health. In the United States, a substantial proportion of adults report sleep durations that fall outside the recommended range. Prior research has associated insufficient or excessive sleep with adverse health outcomes; however, few studies have systematically quantified these associations across multiple health indicators using nationally representative data. OBJECTIVE:This study aims to evaluate the impact of short sleep duration on four key health outcomes: depression diagnosis, number of self-reported poor mental health days, number of physically unhealthy days, and self-rated general health status, using nationally representative U.S. data. METHODOLOGY: METHODS:We analyzed nationally representative data from the Behavioral Risk Factor Surveillance System (BRFSS) collected between 2016 and 2023. Sleep duration was self-reported and categorized into three groups: short sleep (≤5 hours), recommended sleep (6-8 hours), and long sleep (≥9 hours), with short sleep serving as the reference category. The primary health outcomes included: (1) self-reported diagnosis of depression, (2) number of poor mental health days, (3) number of poor physical health days, and (4) self-rated general health, measured on a 5-point Likert scale from excellent to poor. To estimate the effect of sleep duration on these outcomes, we applied Inverse Probability Weighting (IPW) to derive the Average Treatment Effect (ATE), adjusting for key demographic and socioeconomic covariates. All analyses incorporated BRFSS complex survey weights to ensure national representativeness. RESULTS:The study included 318,000 adults (63.3% female; 74.5% White) with a mean age of 51.3 ± 18.4 years. Among individuals with recommended sleep duration (6-8 hours), the baseline prevalence of depression was 39.5% (95% CI: 39.4%-39.7%). Compared to this group, short sleep duration (≤5 hours) was associated with a 14.1 percentage point increase in depression incidence (95% CI: 13.8%-14.4%), while long sleep duration (≥9 hours) was linked to a 12.9 percentage point increase (95% CI: 12.5%-13.3%). Those with short sleep reported an average of 5.3 poor mental health days (95% CI: 5.3-5.4), 4.4 poor physical health days (95% CI: 4.3-4.4), and a higher prevalence of poor general health, 10.0% (0.1, 95% CI: 9.7%-10.2%), compared to individuals with recommended sleep. Similarly, individuals with long sleep duration (≥9 hours) also reported more poor mental (4.6 days, 95% CI: 4.5-4.7) and physical health days (3.2 days, 95% CI: 3.1-3.3), along with a higher prevalence of poor general health, 20.3% (20.3%%, 95% CI 19.4%-21.3%) compared to those with recommended sleep. CONCLUSION:Both short (≤5 hours) and long (≥9 hours) sleep durations are significantly associated with increased risk of depression, more days of poor mental and physical health, and worse self-rated general health compared to recommended sleep (6-8 hours). Promoting optimal sleep duration through targeted public health interventions, education, and screening may improve population well-being and reduce sleep-related health disparities.

BACKGROUND:Sleep underpins cognition, disease prevention, and overall brain health, yet objective, integrative biomarkers of brain health remain lacking. We hypothesized that overnight sleep electroencephalography (EEG) could provide a substrate for such a biomarker. We asked whether a newly developed, end-to-end, data-driven deep learning framework for sleep EEG can learn a latent representation of brain health and distill it into a single score relevant to cognition, disease status, and mortality. METHODS:We analyzed 36,000 polysomnography recordings from 27,000 subjects from six cohorts. EEG data were represented as one-dimensional time series or a two-dimensional time-frequency spectrogram. A multitask deep neural network, trained end-to-end without expert-defined features, learned a 1024-dimensional brain health latent space and jointly predicted cognitive performance, disease status, and sleep metrics. The latent representation was additionally distilled into a single brain health score. We compared performance with demographic baselines, conventional EEG metrics (e.g., rapid eye movement fraction, spindle density), and classic multivariate machine learning approaches. RESULTS:The deep learning-derived brain health scores consistently surpassed demographic and expert-defined EEG feature models. For cognitive outcomes, correlations (r) rose from small (demographic-only) to moderate (up to r=0.40), while disease classification areas under the receiver operator curve improved from 0.50-0.55 at baseline to 0.65-0.75. In age-adjusted Cox models, a one-standard-deviation increase in the brain health score was associated with a 31%-35% reduced risk of mortality (hazard ratio 0.65 to 0.69; P<0.0001), topping conventional EEG metrics. Gains over classic machine learning, plus latent space visualization, indicated that both established physiological markers and novel EEG features drove enhanced performance. CONCLUSIONS:A multitask, end-to-end deep learning approach generated an interpretable, sleep-derived brain health biomarker. By modeling cognition, disease, and mortality, this framework provides a robust index of brain health and may be extended to additional modalities, further enhancing its clinical utility. (Funded by the National Institutes of Health and others.).

BackgroundFunctional outcomes in patients with acute ischemic stroke (AIS) with large vessel occlusion (LVO) undergoing endovascular treatment (EVT) with successful reperfusion (expanded Thrombolysis In Cerebral Infarction (eTICI) 2b-3) complicated by symptomatic intracranial hemorrhage (sICH) were compared with patients with unsuccessful reperfusion (eTICI 0–2a) without sICH.MethodsPatients enrolled in this post hoc analysis were from two Chinese multicenter, randomized controlled trials: the DEVT and the RESCUE BT registries. Patients with AIS who underwent EVT were categorized into two groups according to the state of reperfusion: eTICI 2b-3 with sICH and eTICI 0–2a without sICH. The primary outcome was the modified Rankin Scale (mRS) scores at 90 days. The safety outcomes included early neurological deterioration and 90-day mortality.Results161 patients were included in this cohort analysis, among whom 71 experienced eTICI 2b-3 with sICH, and 90 had eTICI 0–2a without sICH. After adjusting for potential confounding factors, patients in the eTICI 2b-3 with sICH group had worse mRS at 90 days compared with those in the eTICI 0–2a without sICH group in the adjusted analysis (median 6 (IQR 4–6) vs median 4 (IQR 3–6); adjusted common OR 0.39, 95% CI 0.17 to 0.66). There were also higher rates of very poor outcome (mRS 5–6, 70.4% vs 42.2%; OR 2.90, 95% CI 1.38 to 6.11), mortality (66.2% vs 32.2%; OR 0.48, 95% CI 0.30 to 0.79), and early neurological deterioration (81.7% vs 40.0%; OR 0.16, 95% CI 0.07 to 0.35) in the eTICI 2b-3 with sICH group versus the eTICI 0–2a without sICH group.ConclusionsSuccessful reperfusion complicated by sICH after EVT was associated with worse outcomes and higher mortality than unsuccessful reperfusion without sICH. These findings emphasize the need for additional efforts in assessing and managing post-EVT-associated sICH to optimize treatment strategies and improve outcomes.Trial registration numberDirect Endovascular Treatment for Large Vessel Occlusion Stroke;https://www.chictr.org.cn; ChiCTR-IOR-17013568.Intravenous Tirofiban Before Endovascular Thrombectomy for Acute Ischemic Stroke;https://www.chictr.org.cn; ChiCTR-INR-17014167.