Michigan Ear Institute

Abstract Background Understanding differences in COVID-19 vaccine uptake is crucial for addressing public health inequities. Immigrants in the United States face unique structural and socioeconomic barriers that may influence vaccination rates, including access to healthcare, acculturation, and trust in medical institutions. This study examines differences in COVID-19 vaccine uptake among immigrant and non-immigrant populations, with attention to the role of socioeconomic and demographic factors. Methods This study utilizes data from the 2021-2022 Medical Expenditure Panel Survey (MEPS), a nationally representative survey of the U.S. non-institutionalized population. The analytic sample includes 39,767 adults aged 18 and older. Immigration status is categorized as U.S.-born, foreign-born residing in the U.S. for less than 15 years, and acculturated immigrants (residing in the U.S. for 15 years or more). Logistic regression models, adjusted for sociodemographic factors, estimate the association between immigration status and COVID-19 vaccine uptake. Results Preliminary unweighted analyses indicate higher COVID-19 vaccination rates among foreign-born individuals compared to U.S.-born populations. However, differences emerge when considering acculturation, with acculturated immigrants showing a distinct vaccination trajectory. Adjusted models will further explore the impact of socioeconomic factors, such as education and income, on vaccination likelihood. Conclusion Findings suggest that immigration status and acculturation play significant roles in shaping COVID-19 vaccine uptake. Future research should explore barriers to vaccination among acculturated immigrants and identify targeted interventions to improve vaccine accessibility and trust among immigrant communities.

DaxibotulinumtoxinA for injection (DAXI), the first long-acting botulinum toxin (BoNT) type A, is FDA approved for cervical dystonia (CD). DAXI's novel formulation, which includes a custom-engineered peptide, is designed to provide an extended duration of clinical benefit. To evaluate the pooled efficacy and safety of DAXI for CD across two phase 3, multicenter, randomized, double-blind, placebo-controlled trials: ASPEN-1, conducted in North America and Europe, and ASPEN-1-CN, a similarly designed, smaller pivotal clinical trial, conducted in China. Adults with moderate-to-severe CD were randomized (3:3:1) to receive DAXI 125U, DAXI 250U, or placebo. The primary endpoint was change from baseline in Toronto Western Spasmodic Torticollis Rating Scale (TWSTRS) total score averaged across weeks 4 and 6. A key secondary endpoint was duration, defined as time until loss of >80% of peak effect. In all, 357 subjects were randomized and received DAXI 125U (n=149), DAXI 250U (n=154), or placebo (n=54). DAXI 125U (-12.0) and DAXI 250U (-11.9) significantly improved the mean TWSTRS total score versus placebo (-4.6; P<0.0001). Median (95% CI) duration of effect was 24.1 (20.6-28.9) weeks for DAXI 125U and 22.0 (20.1-24.3) weeks for DAXI 250U. Rates of treatment-related dysphagia (125U: 4.7%, 250U: 4.5%) and muscle weakness (125U: 5.4%, 250U: 4.5%) were low for both active doses. This pooled analysis of two phase 3 trials demonstrates that DAXI is an effective, safe, and long-acting treatment for CD. Key adverse events occurred at rates lower than prior pivotal trials of BoNTs for CD.

SummaryBackgroundBrain metastases (BrM) are a frequent complication among patients with non-small cell lung cancer (NSCLC). While guidelines exist for baseline CNS screening in advanced NSCLC, surveillance strategies for early-stage disease remain limited. This study aimed to develop a time-dependent BrM risk prediction nomogram using readily available clinical information.MethodsWe analyzed a retrospective cohort of NSCLC patients at Penn State Health. Our objectives were to (1) systematically evaluate the performance of existing BrM risk prediction algorithms and (2) construct novel nomograms for BrM risk prediction in NSCLC. Using Cox-proportional hazard models with L1-regularization, we predicted BrM risk at 6-month, 1-year, and 2-year follow-up intervals.FindingsThe patient cohort included 1904 patients (median age 68 years, range 38–94 years, BrM incidence 22.8%). The cohort included 1059 males (55.6%) and 845 females (44.4%). Of the cohort, 92.8% of patients identified as White (n = 1766), 1.0% as Asian (n = 19), 4.0% as Black (n = 77), and 2.2% as another race (n = 42). The Zhang 2021 model demonstrated the highest performance in predicting BrM incidence in our cohort, achieving an AUROC of 0.91 (95% CI: 0.87, 0.95). Two novel models were developed: a baseline model incorporating clinical and imaging data at diagnosis (cTNM stage, age at diagnosis), and an extended model including additional clinical and treatment data (number of extracranial metastatic sites, prior radiotherapy, chemotherapy, surgery, and histology) (https://nmikolajewicz.shinyapps.io/nomogram_wilding2024/). While both models showed similar short-term performance, the extended model demonstrated superior predictive capacity (AUROC 0.91 at 3-years) for longer-term outcomes. Our nomograms rely exclusively on clinical features routinely documented in patient records, thereby requiring no additional investigations.InterpretationThese clinically accessible nomograms for BrM prediction will facilitate prognostic modeling, risk stratification, refinement of CNS screening guidelines, and patient counseling.FundingNone.

The internet has changed the way that medical information by journals is disseminated, with a shift toward online distribution. Given this, it is important to include alternative metrics that measure online attention when determining the influence of otolaryngology journals. To describe a ranking system for otolaryngology journals that reflects the amount of publicity received online and to determine factors associated with these rankings. In this cross-sectional study, online attention was measured using Altmetric Attention Scores obtained for all 26 112 articles published by the 43 journals classified under the Journal Citation Reports category of otorhinolaryngology from 2018 to 2022. Data were analyzed from January to June 2023. Altmetric journal rankings were created from the top 500 articles with the highest Altmetric Attention Scores, using a rank sum weight-based method to assign credit for an article's attention online to its respective journal. The association of article content, study design and type, and social media presence on X (formerly Twitter) with ranking was examined. Comparisons between Altmetric journal rankings and bibliometric rankings (5-year Impact Factor) were also performed. Of 43 otolaryngology journals, JAMA Otolaryngology-Head & Neck Surgery had the highest Altmetric journal ranking. Most articles in the Altmetric top 500 were nonoperative clinical studies (220 articles [43.5%]) or described the natural history of disease (176 articles [34.9%]) and involved otology/neurotology (158 articles [29.9%]) or rhinology/allergy (134 articles [25.4%]). The COVID-19 pandemic was a common topic (169 articles [33.5%]). The presence of an active X account for the entire 5-year period was associated with a higher Altmetric total rank sum score for journals (η2 = 0.07; 95% CI, 0.02-0.13 [moderate effect size]). There was a moderate statistically significant correlation between Altmetric journal rankings and 5-year Impact Factor rankings (r = 0.5; 95% CI, 0.2-0.7). This cross-sectional study demonstrates that metrics based on online attention provide an alternative way to assess the reach and influence of medical journals. Journals seeking to expand their influence online may benefit from a presence on social media.