Background: Shared decision-making is a joint process where patients, or their surrogates, and clinicians make health choices based on evidence and preferences. We aimed to determine the extent and predictors of shared decision-making for goals-of-care discussions for critically ill neurological patients, which is crucial for patient-goal-concordant care but currently unknown. Methods: We analyzed 72 audio-recorded routine clinician-family meetings during which goals-of-care were discussed from seven US hospitals. These occurred for 67 patients with 72 surrogates and 29 clinicians; one hospital provided 49/72 (68%) of the recordings. Using a previously validated 10-element shared decision-making instrument, we quantified the extent of shared decision-making in each meeting. We measured clinicians' and surrogates' characteristics and prognostic estimates for the patient's hospital survival and 6-month independent function using post-meeting questionnaires. We calculated clinician-family prognostic discordance, defined as ≥ 20% absolute difference between the clinician's and surrogate's estimates. We applied mixed-effects regression to identify independent associations with greater shared decision-making. Results: The median shared decision-making score was 7 (IQR 5-8). Only 6% of meetings contained all 10 shared decision-making elements. The most common elements were "discussing uncertainty"(89%) and "assessing family understanding"(86%); least frequent elements were "assessing the need for input from others"(36%) and "eliciting the context of the decision"(33%). Clinician-family prognostic discordance was present in 60% for hospital survival and 45% for 6-month independent function. Univariate analyses indicated associations between greater shared decision-making and younger clinician age, fewer years in practice, specialty (medical-surgical critical care > internal medicine > neurocritical care > other > trauma surgery), and higher clinician-family prognostic discordance for hospital survival. After adjustment, only higher clinician-family prognostic discordance for hospital survival remained independently associated with greater shared decision-making (p = 0.029). Conclusion: Fewer than 1 in 10 goals-of-care clinician-family meetings for critically ill neurological patients contained all shared decision-making elements. Our findings highlight gaps in shared decision-making. Interventions promoting shared decision-making for high-stakes decisions in these patients may increase patient-value congruent care; future studies should also examine whether they will affect decision quality and surrogates' health outcomes.

Objective: This study reports the vaccine effectiveness (VE) of COVID-19 vaccine regimens in the United States, based on the National COVID Cohort Collaborative (N3C) database. Methods: Data from 10.4 million adults, enrolled in the N3C from 11 December 2020 to 30 June 2022, were analyzed. VE against infection and death outcomes were evaluated across 13 vaccine regimens in recipient cohorts during the Pre-Delta, Delta, and Omicron periods. VE was estimated as (1-odds ratio) × 100% by multivariate logistic regression, using the unvaccinated cohort as reference. Results: Natural immunity showed a highly protective effect (70.33%) against re-infection, but the mortality risk among the unvaccinated population was increased after re-infection; vaccination following infection reduced the risk of re-infection and death. mRNA-1273 full vaccination plus mRNA-1273 booster showed the highest anti-infection effectiveness (47.59%) (95% CI, 46.72-48.45) in the overall cohort. In the type 2 diabetes cohort, VE against infection was highest with BNT162b2 full vaccination plus mRNA-1273 booster (61.19%) (95% CI, 53.73-67.75). VE against death was also highest with BNT162b2 full vaccination plus mRNA-1273 booster (89.56%) (95% CI, 85.75-92.61). During the Pre-Delta period, all vaccination regimens showed an anti-infection effect; during the Delta period, only boosters, mixed vaccines, and Ad26.COV2.S vaccination exhibited an anti-infection effect; during the Omicron period, none of the vaccine regimens demonstrated an anti-infection effect. Irrespective of the variant period, even a single dose of mRNA vaccine offered protection against death, thus demonstrating survival benefit, even in the presence of infection or re-infection. Similar patterns were observed in patients with type 2 diabetes. Conclusions: Although the anti-infection effect declined as SARS-CoV-2 variants evolved, all COVID-19 mRNA vaccines had sustained effectiveness against death. Vaccination was crucial for preventing re-infection and reducing the risk of death following SARS-CoV-2 infection.

Objectives: To define pregnancy episodes and estimate gestational age within electronic health record (EHR) data from the National COVID Cohort Collaborative (N3C). Materials and methods: We developed a comprehensive approach, named Hierarchy and rule-based pregnancy episode Inference integrated with Pregnancy Progression Signatures (HIPPS), and applied it to EHR data in the N3C (January 1, 2018-April 7, 2022). HIPPS combines: (1) an extension of a previously published pregnancy episode algorithm, (2) a novel algorithm to detect gestational age-specific signatures of a progressing pregnancy for further episode support, and (3) pregnancy start date inference. Clinicians performed validation of HIPPS on a subset of episodes. We then generated pregnancy cohorts based on gestational age precision and pregnancy outcomes for assessment of accuracy and comparison of COVID-19 and other characteristics. Results: We identified 628 165 pregnant persons with 816 471 pregnancy episodes, of which 52.3% were live births, 24.4% were other outcomes (stillbirth, ectopic pregnancy, abortions), and 23.3% had unknown outcomes. Clinician validation agreed 98.8% with HIPPS-identified episodes. We were able to estimate start dates within 1 week of precision for 475 433 (58.2%) episodes. 62 540 (7.7%) episodes had incident COVID-19 during pregnancy. Discussion: HIPPS provides measures of support for pregnancy-related variables such as gestational age and pregnancy outcomes based on N3C data. Gestational age precision allows researchers to find time to events with reasonable confidence. Conclusion: We have developed a novel and robust approach for inferring pregnancy episodes and gestational age that addresses data inconsistency and missingness in EHR data.

Seasonal "common-cold" human coronaviruses are widely spread throughout the world and are mainly associated with mild upper respiratory tract infections. The emergence of highly pathogenic coronaviruses MERS-CoV, SARS-CoV, and most recently SARS-CoV-2 has prompted increased attention to coronavirus biology and immunopathology, but the T-cell response to seasonal coronaviruses remains largely uncharacterized. Here we report the repertoire of viral peptides that are naturally processed and presented upon infection of a model cell line with seasonal coronavirus OC43. We identified MHC-bound peptides derived from each of the viral structural proteins (spike, nucleoprotein, hemagglutinin-esterase, membrane, and envelope) as well as non-structural proteins nsp3, nsp5, nsp6, and nsp12. Eighty MHC-II bound peptides corresponding to 14 distinct OC43-derived epitopes were identified, including many at very high abundance within the overall MHC-II peptidome. Fewer and less abundant MHC-I bound OC43-derived peptides were observed, possibly due to MHC-I downregulation induced by OC43 infection. The MHC-II peptides elicited low-abundance recall T-cell responses in most donors tested. In vitro assays confirmed that the peptides were recognized by CD4+ T cells and identified the presenting HLA alleles. T-cell responses cross-reactive between OC43, SARS-CoV-2, and the other seasonal coronaviruses were confirmed in samples of peripheral blood and peptide-expanded T-cell lines. Among the validated epitopes, spike protein S903-917 presented by DPA1*01:03/DPB1*04:01 and S1085-1099 presented by DRB1*15:01 shared substantial homology to other human coronaviruses, including SARS-CoV-2, and were targeted by cross-reactive CD4 T cells. Nucleoprotein N54-68 and hemagglutinin-esterase HE128-142 presented by DRB1*15:01 and HE259-273 presented by DPA1*01:03/DPB1*04:01 are immunodominant epitopes with low coronavirus homology that are not cross-reactive with SARS-CoV-2. Overall, the set of naturally processed and presented OC43 epitopes comprise both OC43-specific and human coronavirus cross-reactive epitopes, which can be used to follow CD4 T-cell cross-reactivity after infection or vaccination, and to guide selection of epitopes for inclusion in pan-coronavirus vaccines.

Chimeric antigen receptor-T (CAR-T) therapies represent a major breakthrough in cancer medicine, given the ex vivo-based technology that harnesses the power of one's own immune system. These therapeutics have demonstrated remarkable success for relapsed/refractory B-cell lymphomas. Although more than a decade has passed since the initial introduction of CAR-T therapeutics for patients with leukaemia and lymphoma, there is still significant debate as to where CAR-T therapeutics fit into the management paradigm, as consensus guidelines are limited. Competing interventions deployed in subsequent lines of therapy for aggressive lymphoma include novel targeted agents, bispecific antibodies, and time-honoured stem cell transplant. In this focused review, we discuss the major obstacles to advancing the therapeutic reach for CAR-T products in early lines of therapy. Such barriers include antigen escape, "cold" tumour microenvironments, host inflammation and CAR-T cell exhaustion. We highlight solutions including point-of-care CAR-T manufacturing and early T lymphopheresis. We review the evidence basis for early CAR-T deployment for B-cell lymphomas in light of the recent Food and Drug Administration (FDA) approval of three first-in-class anti-CD3/CD20 bispecific antibodies-mosunetuzumab, epcoritamab and glofitamab. We propose practical recommendations for 2024.

Aberrant alternative splicing of mRNAs results in dysregulated gene expression in multiple neurological disorders. Here, we show that hundreds of mRNAs are incorrectly expressed and spliced in white blood cells and brain tissues of individuals with fragile X syndrome (FXS). Surprisingly, the FMR1 (Fragile X Messenger Ribonucleoprotein 1) gene is transcribed in >70% of the FXS tissues. In all FMR1-expressing FXS tissues, FMR1 RNA itself is mis-spliced in a CGG expansion-dependent manner to generate the little-known FMR1-217 RNA isoform, which is comprised of FMR1 exon 1 and a pseudo-exon in intron 1. FMR1-217 is also expressed in FXS premutation carrier-derived skin fibroblasts and brain tissues. We show that in cells aberrantly expressing mis-spliced FMR1, antisense oligonucleotide (ASO) treatment reduces FMR1-217, rescues full-length FMR1 RNA, and restores FMRP (Fragile X Messenger RibonucleoProtein) to normal levels. Notably, FMR1 gene reactivation in transcriptionally silent FXS cells using 5-aza-2'-deoxycytidine (5-AzadC), which prevents DNA methylation, increases FMR1-217 RNA levels but not FMRP. ASO treatment of cells prior to 5-AzadC application rescues full-length FMR1 expression and restores FMRP. These findings indicate that misregulated RNA-processing events in blood could serve as potent biomarkers for FXS and that in those individuals expressing FMR1-217, ASO treatment may offer a therapeutic approach to mitigate the disorder.

Background and objectives: There are no evidence-based guidelines for discussing prognosis in critical neurologic illness, but in general, experts recommend that clinicians communicate prognosis using estimates, such as numerical or qualitative expressions of risk. Little is known about how real-world clinicians communicate prognosis in critical neurologic illness. Our primary objective was to characterize prognostic language clinicians used in critical neurologic illness. We additionally explored whether prognostic language differed between prognostic domains (e.g., survival, cognition). Methods: We conducted a multicenter cross-sectional mixed-methods study analyzing deidentified transcripts of audio-recorded clinician-family meetings for patients with neurologic illness requiring intensive care (e.g., intracerebral hemorrhage, traumatic brain injury, severe stroke) from 7 US centers. Two coders assigned codes for prognostic language type and domain of prognosis to each clinician prognostic statement. Prognostic language was coded as probabilistic (estimating the likelihood of an outcome occurring, e.g., "80% survival"; "She'll probably survive") or nonprobabilistic (characterizing outcomes without offering likelihood; e.g., "She may not survive"). We applied univariate and multivariate binomial logistic regression to examine independent associations between prognostic language and domain of prognosis. Results: We analyzed 43 clinician-family meetings for 39 patients with 78 surrogates and 27 clinicians. Clinicians made 512 statements about survival (median 0/meeting [interquartile range (IQR) 0-2]), physical function (median 2 [IQR 0-7]), cognition (median 2 [IQR 0-6]), and overall recovery (median 2 [IQR 1-4]). Most statements were nonprobabilistic (316/512 [62%]); 10 of 512 prognostic statements (2%) offered numeric estimates; and 21% (9/43) of family meetings only contained nonprobabilistic language. Compared with statements about cognition, statements about survival (odds ratio [OR] 2.50, 95% CI 1.01-6.18, p = 0.048) and physical function (OR 3.22, 95% 1.77-5.86, p < 0.001) were more frequently probabilistic. Statements about physical function were less likely to be uncertainty-based than statements about cognition (OR 0.34, 95% CI 0.17-0.66, p = 0.002). Discussion: Clinicians preferred not to use estimates (either numeric or qualitative) when discussing critical neurologic illness prognosis, especially when they discussed cognitive outcomes. These findings may inform interventions to improve prognostic communication in critical neurologic illness.

Background: Identifying individuals with a higher risk of developing severe coronavirus disease 2019 (COVID-19) outcomes will inform targeted and more intensive clinical monitoring and management. To date, there is mixed evidence regarding the impact of preexisting autoimmune disease (AID) diagnosis and/or immunosuppressant (IS) exposure on developing severe COVID-19 outcomes. Methods: A retrospective cohort of adults diagnosed with COVID-19 was created in the National COVID Cohort Collaborative enclave. Two outcomes, life-threatening disease and hospitalization, were evaluated by using logistic regression models with and without adjustment for demographics and comorbidities. Results: Of the 2 453 799 adults diagnosed with COVID-19, 191 520 (7.81%) had a preexisting AID diagnosis and 278 095 (11.33%) had a preexisting IS exposure. Logistic regression models adjusted for demographics and comorbidities demonstrated that individuals with a preexisting AID (odds ratio [OR], 1.13; 95% confidence interval [CI]: 1.09-1.17; P < .001), IS exposure (OR, 1.27; 95% CI: 1.24-1.30; P < .001), or both (OR, 1.35; 95% CI: 1.29-1.40; P < .001) were more likely to have a life-threatening disease. These results were consistent when hospitalization was evaluated. A sensitivity analysis evaluating specific IS revealed that tumor necrosis factor inhibitors were protective against life-threatening disease (OR, 0.80; 95% CI: .66-.96; P = .017) and hospitalization (OR, 0.80; 95% CI: .73-.89; P < .001). Conclusions: Patients with preexisting AID, IS exposure, or both are more likely to have a life-threatening disease or hospitalization. These patients may thus require tailored monitoring and preventative measures to minimize negative consequences of COVID-19.

Background: Rapid antigen detection tests (Ag-RDT) for SARS-CoV-2 with emergency use authorization generally include a condition of authorization to evaluate the test's performance in asymptomatic individuals when used serially. We aim to describe a novel study design that was used to generate regulatory-quality data to evaluate the serial use of Ag-RDT in detecting SARS-CoV-2 virus among asymptomatic individuals. Methods: This prospective cohort study used a siteless, digital approach to assess longitudinal performance of Ag-RDT. Individuals over 2 years old from across the USA with no reported COVID-19 symptoms in the 14 days prior to study enrollment were eligible to enroll in this study. Participants throughout the mainland USA were enrolled through a digital platform between October 18, 2021 and February 15, 2022. Participants were asked to test using Ag-RDT and molecular comparators every 48 hours for 15 days. Enrollment demographics, geographic distribution, and SARS-CoV-2 infection rates are reported. Key results: A total of 7361 participants enrolled in the study, and 492 participants tested positive for SARS-CoV-2, including 154 who were asymptomatic and tested negative to start the study. This exceeded the initial enrollment goals of 60 positive participants. We enrolled participants from 44 US states, and geographic distribution of participants shifted in accordance with the changing COVID-19 prevalence nationwide. Conclusions: The digital site-less approach employed in the "Test Us At Home" study enabled rapid, efficient, and rigorous evaluation of rapid diagnostics for COVID-19 and can be adapted across research disciplines to optimize study enrollment and accessibility.

Purpose: We conducted a scoping review of studies to examine the implementation of interventions to promote adolescent cancer prevention in rural, primary care settings and identify barriers and facilitators. Methods: We followed the JBI scoping review protocol and used a systematic extraction and coding process. Our search of MEDLINE, PsycInfo, Cochrane, CINAHL, and Scopus identified articles related to implementation of interventions in the following areas: obesity, human papillomavirus (HPV) vaccination, tobacco use, and sun exposure. We used the Consolidated Framework for Implementation Research (CFIR), an implementation framework consisting of 5 domains (outer setting, inner setting, intervention characteristics, individual characteristics, process), each with a sub-set of constructs, to classify barriers and facilitators reported. Results: We identified 3046 references, excluded 2969 during initial screening, assessed 74 for full-text eligibility, and abstracted 24. Of these, 17 addressed obesity, 6 addressed HPV vaccination, 1 addressed skin cancer, and 1 addressed multiple behaviors. 10 studies were either non-randomized experimental designs (n=8) or randomized controlled trials (n=2). The remaining were observational or descriptive research. Barriers in the outer setting (e.g., lack of external funding sources, patients' beliefs) and inner setting (e.g., time available for implementation efforts and clinic infrastructure) were most common, compared to the other CFIR domains. Similarly, facilitators in the outer setting (e.g., partnerships with other organizations and parents' trust in health care providers) and inner setting (e.g., efficiency in practice protocols) were commonly reported. Conclusions: Adolescence is a critical growth window to establish healthy behaviors to prevent future cancers. Rural areas have higher rates of cancer morbidity and mortality than urban ones, putting rural adolescents at heightened risk for cancers. Yet, we found a dearth of studies addressing the implementation of adolescent cancer prevention in rural primary care settings. Further research is needed to understand the implementation challenges and potential strategies to improve implementation efforts to promote cancer prevention among rural adolescents.