Citations

ImportanceRedirection of care refers to withdrawal, withholding, or limiting escalation of treatment. Whether maternal social determinants of health are associated with redirection of care discussions merits understanding.ObjectiveTo examine associations between maternal social determinants of health and redirection of care discussions for infants born extremely preterm.Design, Setting, and ParticipantsThis is a retrospective analysis of a prospective cohort of infants born at less than 29 weeks’ gestation between April 2011 and December 2020 at 19 National Institute of Child Health and Human Development Neonatal Research Network centers in the US. Follow-up occurred between January 2013 and October 2023. Included infants received active treatment at birth and had mothers who identified as Black or White. Race was limited to Black and White based on service disparities between these groups and limited sample size for other races. Maternal social determinant of health exposures were education level (high school nongraduate or graduate), insurance type (public/none or private), race (Black or White), and ethnicity (Hispanic or non-Hispanic).Main Outcomes and MeasuresThe primary outcome was documented discussion about redirection of infant care. Secondary outcomes included subsequent redirection of care occurrence and, for those born at less than 27 weeks’ gestation, death and neurodevelopmental impairment at 22 to 26 months’ corrected age.ResultsOf the 15 629 infants (mean [SD] gestational age, 26 [2] weeks; 7961 [51%] male) from 13 643 mothers, 2324 (15%) had documented redirection of care discussions. In unadjusted comparisons, there was no significant difference in the percentage of infants with redirection of care discussions by race (Black, 1004/6793 [15%]; White, 1320/8836 [15%]) or ethnicity (Hispanic, 291/2105 [14%]; non-Hispanic, 2020/13 408 [15%]). However, after controlling for maternal and neonatal factors, infants whose mothers identified as Black or as Hispanic were less likely to have documented redirection of care discussions than infants whose mothers identified as White (Black vs White adjusted odds ratio [aOR], 0.84; 95% CI, 0.75-0.96) or as non-Hispanic (Hispanic vs non-Hispanic aOR, 0.72; 95% CI, 0.60-0.87). Redirection of care discussion occurrence did not differ by maternal education level or insurance type.Conclusions and RelevanceFor infants born extremely preterm, redirection of care discussions occurred less often for Black and Hispanic infants than for White and non-Hispanic infants. It is important to explore the possible reasons underlying these differences.

Abstract Skin fibrosis is a clinical problem with devastating impacts but limited treatment options. In the setting of diabetes, insulin administration often causes local dermal fibrosis, leading to a range of clinical sequelae including impeded insulin absorption. Mechanical forces are important drivers of fibrosis and, clinically, physical tension offloading at the skin level using an elastomeric patch significantly reduces wound scarring. However, it is not known whether tension offloading could similarly prevent skin fibrosis in the setting of pro-fibrotic injections. Here, we develop a porcine model using repeated local injections of bleomycin to recapitulate key features of insulin-induced skin fibrosis. Using histologic, tissue ultrastructural, and biomechanical analyses, we show that application of a tension-offloading patch both prevents and rescues existing skin fibrosis from bleomycin injections. By applying single-cell transcriptomic analysis, we find that the fibrotic response to bleomycin involves shifts in myeloid cell dynamics from favoring putatively pro-regenerative to pro-fibrotic myeloid subtypes; in a mechanomodulatory in vitro platform, we show that these shifts are mechanically driven and reversed by exogenous IL4. Finally, using a human foreskin xenograft model, we show that IL4 treatment mitigates bleomycin-induced dermal fibrosis. Overall, this study highlights that skin tension offloading, using an FDA cleared, commercially available patch, could have significant potential clinical benefit for the millions of patients dependent on insulin.

AbstractBackgroundThe causes of rapidly progressive dementia are heterogeneous, including neurodegenerative, vascular, and autoimmune/inflammatory diseases. Overlap in presenting symptoms and signs, results of cognitive testing, and findings on brain imaging and other common diagnostic tests confounds the etiologic diagnosis, contributing to diagnostic delays, missed opportunities for treatment, and poorer outcomes in patients with RPD. New tools and approaches are needed to improve diagnostic accuracy, with particular emphasis on improving early recognition of patients with potentially treatable causes of RPD.MethodsEstablished and emerging biomarkers of Alzheimer disease neuropathology (Aβ42/40, p‐tau181, p‐tau231), neuroaxonal and neuronal injury (neurofilament light [NfL], VILIP‐1, total tau), neuroinflammation (YKL‐40, sTREM2, GFAP, MCP‐1), and synaptic dysfunction (SNAP‐25, neurogranin) were measured in cerebrospinal fluid obtained at presentation from 78 prospectively accrued patients with RPD due to neurodegenerative (n = 35), vascular (n = 9), and autoimmune/inflammatory (n = 34) diseases, and 72 age‐ and sex‐similar cognitively normal individuals (controls). Causes of RPD were further classified as potentially treatment‐responsive or nonresponsive, referencing the extant literature. Biomarker levels were compared across etiologic diagnoses and by treatment responsiveness, referencing control values. Analyses were adjusted for the effects of age (ANCOVA).ResultsAlzheimer disease biomarkers (low Aβ42/40 and elevated p‐tau181 and p‐tau231) were associated with neurodegenerative causes of RPD (ANCOVA, p = 0.02 p = 0.30, p = 0.15), while high NfL (p = 0.61), low VILIP‐1 (p = 0.009), and elevated markers of inflammation (sTREM2, p = 0.009; YKL‐40, p<0.001) identified patients with autoimmune/inflammatory diseases (Figure). MCP‐1 levels were highest in patients with vascular causes of RPD (p = 0.08). 44 patients (56.4%) had potentially treatment‐responsive causes of RPD. Treatment responsiveness was associated with higher levels of CSF Aβ42/40 (p = 0.003), NfL (p<0.001), sTREM2 (p<0.001) and YKL‐40 (p<0.001); and lower levels of p‐tau‐181 and p‐tau231 (p<0.001, p<0.001) and VILIP‐1 (p<0.001).ConclusionSelected biomarkers measured in CSF at presentation associate with etiologic diagnosis and treatment responsiveness in patients with neurodegenerative, vascular, and autoimmune/inflammatory causes of RPD. Biomarker panels may be adapted to improve recognition of patients with treatment‐responsive causes of RPD early in the symptomatic course when treatments may be most effective.

Objective Deep learning (DL) has shown promising results for improving mammographic breast cancer diagnosis. However, the impact of artificial intelligence (AI) on the breast cancer screening process has not yet been fully elucidated in terms of potential workload reduction. We aim to assess if AI-based triaging of breast cancer screening mammograms could reduce the radiologist's workload with non-inferior sensitivity. Methods PubMed, EMBASE, Cochrane Central, and Web of Science databases were systematically searched for studies that evaluated AI algorithms on computer-aided triage of breast cancer screening mammograms. We extracted data from homogenous studies and performed a proportion meta-analysis with a random-effects model to examine the radiologist's workload reduction (proportion of low-risk mammograms that could be theoretically ruled out from human's assessment) and the software's sensitivity to breast cancer detection. Results Thirteen studies were selected for full review, and three studies that used the same commercially available DL algorithm were included in the meta-analysis. In the 156,852 examinations included, the threshold of 7 was identified as optimal. With these parameters, radiologist workload decreased by 68.3% (95%CI 0.655–0.711, I² = 98.76%, p < 0.001), while achieving a sensitivity of 93.1% (95%CI 0.882–0.979, I² = 83.86%, p = 0.002) and a specificity of 68.7% (95% CI 0.684–0.723, I² = 97.5%, p < 0.01). Conclusions The deployment of DL computer-aided triage of breast cancer screening mammograms reduces the radiology workload while maintaining high sensitivity. Although the implementation of AI remains complex and heterogeneous, it is a promising tool to optimize healthcare resources.

Abstract Glioblastoma is the most common primary malignant brain tumor. Despite maximal safe resection, followed by chemoradiation, median survival is 15 months, and 5-year survival is 6.8%. Efficacy of immunotherapy is limited by glioblastoma-mediated immunosuppression. Extracellular vesicles (EVs) are a heterogeneous group of small membrane-bound particles that are released from all cell types. Glioblastoma-derived EVs regulate the tumor microenvironment and tumor progression in a paracrine manner. They also regulate glioblastoma-mediated systemic immunosuppression in an IL6- and PDL1-dependent manner by inducing myeloid-derived suppressor cells (MDSCs) ultimately resulting in T cell depletion. Primary cilia are ubiquitous microtubule-based organelles that project from the mother centriole and are present on glioblastoma cells. Inhibition of ciliogenesis–through knockdown of KIF3A, IFT88, or ARL13B (structural ciliary proteins required for ciliogenesis)–abolishes IL6 induction in response to chemoradiation and significantly reduces the induction of MDSCs in normal human donor monocytes exposed to glioblastoma-derived EVs. Inhibition of ciliogenesis does not affect the biophysical properties of EVs but our data instead suggest significant alterations in EV packaging and content in response to ciliary loss. These data suggest a novel role for primary cilia in packaging of EV contents and connects these organelles with tumor EV-mediated immunosuppression in glioblastomas. These findings have potential implications for improving the efficacy of immunotherapy in glioblastoma–a universally fatal disease.

ObjectiveThis study was undertaken to apply established and emerging cerebrospinal fluid (CSF) biomarkers to improve diagnostic accuracy in patients with rapidly progressive dementia (RPD). Overlap in clinical presentation and results of diagnostic tests confounds etiologic diagnosis in patients with RPD. Objective measures are needed to improve diagnostic accuracy and to recognize patients with potentially treatment‐responsive causes of RPD.MethodsBiomarkers of Alzheimer disease neuropathology (amyloid‐β 42/40 ratio, phosphorylated tau [p‐tau181, p‐tau231]), neuroaxonal/neuronal injury (neurofilament light chain [NfL], visinin‐like protein‐1 [VILIP‐1], total tau), neuroinflammation (chitinase‐3‐like protein [YKL‐40], soluble triggering receptor expressed on myeloid cells 2 [sTREM2], glial fibrillary acidic protein [GFAP], monocyte chemoattractant protein‐1 [MCP‐1]), and synaptic dysfunction (synaptosomal‐associated protein 25kDa, neurogranin) were measured in CSF obtained at presentation from 78 prospectively accrued patients with RPD due to neurodegenerative, vascular, and autoimmune/inflammatory diseases; 35 age‐ and sex‐matched patients with typically progressive neurodegenerative disease; and 72 cognitively normal controls. Biomarker levels were compared across etiologic diagnoses, by potential treatment responsiveness, and between patients with typical and rapidly progressive presentations of neurodegenerative disease.ResultsAlzheimer disease biomarkers were associated with neurodegenerative causes of RPD. High NfL, sTREM2, and YKL‐40 and low VILIP‐1 identified patients with autoimmune/inflammatory diseases. MCP‐1 levels were highest in patients with vascular causes of RPD. A multivariate model including GFAP, MCP‐1, p‐tau181, and sTREM2 identified the 44 patients with treatment‐responsive causes of RPD with 89% accuracy. Minimal differences were observed between typical and rapidly progressive presentations of neurodegenerative disease.InterpretationSelected CSF biomarkers at presentation were associated with etiologic diagnoses and treatment responsiveness in patients with heterogeneous causes of RPD. The ability of cross‐sectional biomarkers to inform upon mechanisms that drive rapidly progressive neurodegenerative disease is less clear. ANN NEUROL 2024;95:299–313