Faculty Bibliography

INTRODUCTION/BACKGROUND:Cenegermin is approved for treatment of neurotrophic keratopathy (NK) and has been studied in patients with stage 2 or 3 NK. This study evaluated the efficacy and safety of cenegermin in adults with stage 1 NK. METHODS:This was a phase IV, multicenter, prospective, open-label, uncontrolled trial. Adults with stage 1 NK (Mackie criteria) and decreased corneal sensitivity (≤ 4 cm) received 1 drop of cenegermin 20 mcg/ml in the affected eye(s) 6 times/day for 8 weeks with a 24-week follow-up. RESULTS:Of 37 patients, corneal epithelial healing was observed in 84.8% (95% confidence interval [CI] 68.1-94.9%; P < 0.001) at week 8; 95.2% (95% CI 76.2-99.9%; P < 0.001) of those patients remained healed at the end of the 24-week follow-up (week 32). At week 8, 91.2% (95% CI 76.3-98.1%; P < 0.001) of patients experienced improved corneal sensitivity; this improvement was observed in 82.1% (95% CI 63.1-93.9%; P < 0.001) of patients at week 32. Mean best-corrected distance visual acuity change from baseline at week 8 was - 0.10 logMAR (standard deviation [SD], 0.15; 95% CI - 0.16 to - 0.05; P < 0.001) and at week 32 was - 0.05 logMAR (SD, 0.16; 95% CI - 0.11 to 0.01; P = 0.122). At weeks 8 and 32, 15.2% (95% CI 5.1-31.9%; P < 0.001) and 10.7% (95% CI 2.3-28.2%; P < 0.001) of patients, respectively, had a 15-letter gain from baseline. At least one adverse event (AE) was reported by 73.0% and 45.7% of patients during the treatment and follow-up periods, respectively. The most common treatment-related, treatment-emergent AEs were eye pain (37.8%), blurred vision (10.8%), and eyelid pain (8.1%); these were mostly mild or moderate and were only reported during the treatment period. CONCLUSIONS:These results support the potential use of cenegermin for treating patients with stage 1 NK, and future confirmatory studies would be beneficial to elaborate on these findings. TRIAL REGISTRATION/BACKGROUND:DEFENDO; NCT04485546.

BACKGROUND:Websites serve as recruitment and educational tools for many fellowship programs, including neuroanesthesiology. Since the COVID-19 pandemic, when interviews, conferences, and institutional visits were moved online, websites have become more important for applicants when deciding on their preferred fellowship program. This study evaluated the content of the websites of neuroanesthesiology fellowship programs. METHODS:Neuroanesthesiology fellowship program websites were identified from the websites of the International Council on Perioperative Neuroscience Training and the Society for Neuroscience in Anesthesiology and Critical Care. The content was assessed against 24 predefined criteria. RESULTS:Fifty-three fellowship programs were identified, of which 42 websites were accessible through a Google search and available for evaluation. The mean number of criteria met by the 42 fellowship websites was 12/24 (50%), with a range of 6 to 18 criteria. None of the evaluated fellowship websites met all 24 predefined criteria; 20 included more than 50% of the criteria, whereas 7 included fewer than 30% of the criteria. Having a functional website, accessibility through a single click from Google, and a detailed description of the fellowship program were the features of most websites. Information about salary and life in the area, concise program summaries, and biographical information of past and current fellows were missing from a majority of websites. CONCLUSION/CONCLUSIONS:Important information was missing from most of the 42 evaluated neuroanesthesiology fellowship program websites, potentially hindering applicants from making informed choices about their career plans.

There are numerous internal fixation (IF) options available for distal radius fractures (DRFs). The choice of fixation method depends on factors such as fracture morphology, soft tissue integrity, the patient's clinical status, and the surgeon's training. While volar plate fixation has become the primary approach for addressing these fractures, alternative IF methods like K-wire fixation, fragment-specific fixation, and dorsal bridge plating continue to be effective. Despite the versatility of IF, there are certain clinical situations where prompt and conclusive management through open reduction and internal fixation (ORIF) is not suitable. These instances include the treatment of polytraumatized patients, individuals with compromised soft tissues, or those medically unstable to tolerate lengthy anesthesia. In such cases, proficiency in closed reduction and external fixation (EF) proves invaluable. Being able to identify these clinical scenarios and comprehend the efficacy and safety of EF in addressing DRFs is valuable for any surgeon handling such injuries.

Interactions within the tumor microenvironment (TME) significantly influence tumor progression and treatment responses. While single-cell RNA sequencing (scRNA-seq) and spatial genomics facilitate TME exploration, many clinical cohorts are assessed at the bulk tissue level. Integrating scRNA-seq and bulk tissue RNA-seq data through computational deconvolution is essential for obtaining clinically relevant insights. Our method, ProM, enables the examination of major and minor cell types. Through evaluation against existing methods using paired single-cell and bulk RNA sequencing of human urothelial cancer (UC) samples, ProM demonstrates superiority. Application to UC cohorts treated with immune checkpoint inhibitors reveals pre-treatment cellular features associated with poor outcomes, such as elevated SPP1 expression in macrophage/monocytes (MM). Our deconvolution method and paired single-cell and bulk tissue RNA-seq dataset contribute novel insights into TME heterogeneity and resistance to immune checkpoint blockade.

Background Commonly used pediatric lower extremity growth standards are based on small, dated data sets. Artificial intelligence (AI) enables creation of updated growth standards. Purpose To train an AI model using standing slot-scanning radiographs in a racially diverse data set of pediatric patients to measure lower extremity length and to compare expected growth curves derived using AI measurements to those of the conventional Anderson-Green method. Materials and Methods This retrospective study included pediatric patients aged 0-21 years who underwent at least two slot-scanning radiographs in routine clinical care between August 2015 and February 2022. A Mask Region-based Convolutional Neural Network was trained to segment the femur and tibia on radiographs and measure total leg, femoral, and tibial length; accuracy was assessed with mean absolute error. AI measurements were used to create quantile polynomial regression femoral and tibial growth curves, which were compared with the growth curves of the Anderson-Green method for coverage based on the central 90% of the estimated growth distribution. Results In total, 1874 examinations in 523 patients (mean age, 12.7 years ± 2.8 [SD]; 349 female patients) were included; 40% of patients self-identified as White and not Hispanic or Latino, and the remaining 60% self-identified as belonging to a different racial or ethnic group. The AI measurement training, validation, and internal test sets included 114, 25, and 64 examinations, respectively. The mean absolute errors of AI measurements of the femur, tibia, and lower extremity in the test data set were 0.25, 0.27, and 0.33 cm, respectively. All 1874 examinations were used to generate growth curves. AI growth curves more accurately represented lower extremity growth in an external test set (n = 154 examinations) than the Anderson-Green method (90% coverage probability: 86.7% [95% CI: 82.9, 90.5] for AI model vs 73.4% [95% CI: 68.4, 78.3] for Anderson-Green method; χ² test, P < .001). Conclusion Lower extremity growth curves derived from AI measurements on standing slot-scanning radiographs from a diverse pediatric data set enabled more accurate prediction of pediatric growth. © RSNA, 2024 Supplemental material is available for this article.

Discerning functional brain network variations related to neuropathological aggregates in Alzheimer's disease (AD), including amyloid-beta (Abeta) and phosphorylated tau (p-tau), is crucial for understanding their link to cognitive decline and underlying molecular mechanisms. However, these variations are often confounded by normal aging-related changes, complicating interpretation. To address this challenge, we first defined Alzheimer's continuum cases (Abeta positive (A+), n = 129) and normal elderly (Abeta negative (A-), n = 160) using cerebral spinal fluid amyloid levels, and then applied a novel deep learning approach to resting-state connectivity using functional magnetic resonance imaging (fMRI) of the 289 subjects to disentangle A+-specific dimensions in brain network alterations from those shared with A- individuals. The identified A+-specific dimensions were further refined to predict individual Abeta and p-tau levels separately. We observed that resulting brain signatures, defined from A+-specific dimensions for predicting these two CSF biomarkers, were both attributed to the right superior temporal and anterior cingulate cortices and associated with attention and memory domains. When linking the brain signatures to gene expression data from a public transcriptomic atlas, we found that the brain signatures were associated with molecular pathways involving synaptic dysfunction and disruptions in pathways containing activity of excitatory neurons, astrocytes, and microglia. For A--shared dimensions, the Aβ-linked brain signature involved the left fusiform and right middle cingulate cortices, correlating with the language cognitive measurement and language-related molecular pathways. The p-tau-linked signature predominantly involved the right insula and inferior temporal cortices, correlating with the aging-related molecular pathways. Collectively, our findings provided new insights in understanding of Alzheimer's continuum pathological biomarkers.

IMPORTANCE:SARS-CoV-2 viral load (VL) in the nasopharynx is difficult to quantify and standardize across settings, but it may inform transmission potential and disease severity. OBJECTIVE:To characterize VL at COVID-19 diagnosis among previously uninfected and unvaccinated individuals by evaluating the association of demographic and clinical characteristics, viral variant, and trial with VL, as well as the ability of VL to predict severe disease. DESIGN, SETTING, AND PARTICIPANTS:This secondary cross-protocol analysis used individual-level data from placebo recipients from 4 harmonized, phase 3 COVID-19 vaccine efficacy trials sponsored by Moderna, AstraZeneca, Janssen, and Novavax. Participants were SARS-CoV-2 negative at baseline and acquired COVID-19 during the blinded phase of the trials. The setting included the US, Brazil, South Africa, Colombia, Argentina, Peru, Chile, and Mexico; start dates were July 27, 2020, to December 27, 2020; data cutoff dates were March 26, 2021, to July 30, 2021. Statistical analysis was performed from November 2022 to June 2023. MAIN OUTCOMES AND MEASURES:Linear regression was used to assess the association of demographic and clinical characteristics, viral variant, and trial with polymerase chain reaction-measured log10 VL in nasal and/or nasopharyngeal swabs taken at the time of COVID-19 diagnosis. RESULTS:Among 1667 participants studied (886 [53.1%] male; 995 [59.7%] enrolled in the US; mean [SD] age, 46.7 [14.7] years; 204 [12.2%] aged 65 years or older; 196 [11.8%] American Indian or Alaska Native, 150 [9%] Black or African American, 1112 [66.7%] White; 762 [45.7%] Hispanic or Latino), median (IQR) log10 VL at diagnosis was 6.18 (4.66-7.12) log10 copies/mL. Participant characteristics and viral variant explained only 5.9% of the variability in VL. The independent factor with the highest observed differences was trial: Janssen participants had 0.54 log10 copies/mL lower mean VL vs Moderna participants (95% CI, 0.20 to 0.87 log10 copies/mL lower). In the Janssen study, which captured the largest number of COVID-19 events and variants and used the most intensive post-COVID surveillance, neither VL at diagnosis nor averaged over days 1 to 28 post diagnosis was associated with COVID-19 severity. CONCLUSIONS AND RELEVANCE:In this study of placebo recipients from 4 randomized phase 3 trials, high variability was observed in SARS-CoV-2 VL at the time of COVID-19 diagnosis, and only a fraction was explained by individual participant characteristics or viral variant. These results suggest challenges for future studies of interventions seeking to influence VL and elevates the importance of standardized methods for specimen collection and viral load quantitation.