Citations

Abstract Increased innate immune activity promotes neurodegeneration and contributes to progression in multiple sclerosis. This prospective case-control study aims to investigate thalamic microglia density on 18kDa translocator protein PET in patients with multiple sclerosis using a third-generation radioligand, 11C-ER176, and investigate the associations of 11C-ER176 PET uptake with imaging and clinical measures of progression in multiple sclerosis. Patients with multiple sclerosis (n = 50) and controls (n = 55) were prospectively enrolled and they underwent 11C-ER176 PET and MRI including diffusion MRI with neurite orientation dispersion and density imaging. Disease characteristics, expanded disability status scale and multiple sclerosis functional composite scores were obtained in patients with multiple sclerosis. Age at imaging (mean ± standard deviation: patients = 49.6 ± 12.9 years, controls = 48.2 ± 15.4 years, P = 0.63) and sex (female ratio; patients = 72%, controls = 65%, P = 0.47) were not different between the groups. Thalamus 11C-ER176 PET uptake was highest in patients with progressive multiple sclerosis (1.272 ± 0.072 standardized uptake value ratio), followed by patients with relapsing multiple sclerosis (1.209 ± 0.074 standardized uptake value ratio) and lowest in controls (1.162 ± 0.067 standardized uptake value ratio, P < 0.001). Patients with thalamic lesions had higher thalamus 11C-ER176 PET uptake than those without thalamic lesions in both relapsing multiple sclerosis and progressive multiple sclerosis (P < 0.001). In patients with multiple sclerosis, higher thalamus 11C-ER176 PET uptake correlated with lower thalamic volume (r = −0.45, P = 0.001), higher mean diffusivity (r = 0.56, P < 0.001), lower neurite density index (r = −0.43, P = 0.002), lower orientation dispersion index (r = −0.40, P = 0.005) and higher free water fraction (r = 0.42, P = 0.003) in the thalamus. In patients with multiple sclerosis, higher thalamus 11C-ER176 PET uptake also correlated with higher mean diffusivity (r = 0.47, P < 0.001) and lower neurite density index (r = −0.36, P = 0.012) in the corpus callosum. In patients with multiple sclerosis, higher thalamus 11C-ER176 PET uptake correlated with worse expanded disability status scale scores (r = 0.33, P = 0.02), paced auditory serial addition test scores (r = −0.43, P = 0.003) and multiple sclerosis functional composite z-scores (r = −0.46, P = 0.001). Microglia density in the thalamus is highest in patients with progressive multiple sclerosis and is associated with imaging biomarkers of neurodegeneration and clinical disease severity. As a signature imaging biomarker of progression in multiple sclerosis, effectively reflecting the global disease burden, 11C-ER176 PET may aid development and efficacy evaluation of therapeutics targeting microglia.

ABSTRACTThe optimal conditioning schedule and CD34+ cell dose for autologous stem cell transplantation (ASCT) for AL amyloidosis is unknown. Patients (n = 1704) who underwent ASCT for AL amyloidosis between 2003 and 2020 in 9 centers were included. Data on melphalan conditioning dose, number of conditioning days, whether a rest day between conditioning and stem cell infusion was given or not, and infused CD34+ cell dose were collected. Full‐dose melphalan (≥ 180 mg/m2) was administered in 63.7% of the patients, and 80.4% had melphalan split into 2‐day conditioning. A rest day (day −1) between the conditioning regimen and stem cell infusion was provided in 52.5% of patients. The median infused CD34+ cell count was 4.7 × 106/kg. An infused CD34+ cell count ≥ 4.5 × 106/kg was associated with a shorter time to neutrophil and platelet engraftment. In a nominal regression analysis, full‐dose melphalan, 1‐day melphalan conditioning, and omitting a rest day between conditioning and stem cell infusion were independent predictors of post‐ASCT higher deep hematological response. The median follow‐up was 8.6 years, and 38% of patients died. Independent predictors of superior overall survival in multivariate Cox regression analysis included full‐dose melphalan, having no rest day, and infused CD34+ cells ≥ 4.5 × 106/kg. Independent predictors of higher day‐100 transplant‐related mortality (TRM) in nominal logistic regression analysis included poorer performance status, NT‐proBNP/BNP ≥ 1800/400 pg/mL, serum albumin < 2.5 g/dL, CD34+ cells < 4.5 × 106/kg, and not having a rest day. In conclusion, 1 day of melphalan conditioning and administration of CD34+ cells ≥ 4.5 × 106/kg are recommended for ASCT in AL amyloidosis.

Summary Amyloid light‐chain (AL) amyloidosis is a systemic clonal plasma cell disorder characterized by the production and deposition of misfolded immunoglobulin light chains (LCs), resulting in multiorgan dysfunction. Due to its intricate molecular mechanisms and diverse organ involvement, the disease poses significant diagnostic and therapeutic challenges. This review explores the molecular landscape of AL amyloidosis, emphasizing genetic, transcriptomic and proteomic alterations. Key findings include chromosomal abnormalities, somatic mutations, aberrant gene expression, disrupted protein folding pathways and the role of cytokine and chemokine secretion. These factors collectively drive the overproduction and destabilization of amyloidogenic LCs, leading to organ‐specific amyloid deposition, clinical heterogeneity and variable patient outcomes. Despite therapeutic advancements, the disease's complexity challenges the development of effective biological models. Progressing towards personalized therapies requires the development of preclinical models and the identification of biomarkers and molecular data to design targeted interventions. This review highlights the importance of integrating DNA, RNA and protein‐level analyses to deepen the understanding of AL amyloidosis pathogenesis. Such insights are pivotal for improving diagnostics, prognostics and therapeutic strategies, ultimately advancing precision medicine for this challenging disease.

ABSTRACTBackgroundAs a component of goal‐oriented care, goal‐setting is an important strategy to improve self‐management and reduce the economic and personal burden of chronic illness. Primary care nurses, as integral members of the healthcare team, play a pivotal role in providing self‐management support to patients with multiple chronic illnesses. Yet, little is known about their perspectives on partnering with patients to set meaningful goals within self‐management support programmes.AimTo explore perspectives of primary care nurses about their practice of goal‐setting with patients to improve self‐management.MethodsFor this qualitative exploratory study, we conducted semi‐structured interviews with 28 primary care nurses who provided self‐management support to patients with multiple chronic illnesses. Data were analysed using inductive thematic analysis. This research was approved by the Mayo Clinic Institutional Review Board.ResultsKey themes from interviews focused on: (1) goal‐setting practices; (2) challenges encountered in goal‐setting; and (3) the perceived value‐add of using a patient‐centred goal‐setting approach. Nurses described practices that empower patients to take charge of goal‐setting, emphasising that the opportunity to create personal goals enhances motivation and enables the development of realistic action plans. Key challenges faced were patients' lack of familiarity with personal goal‐setting, competing life stressors and patients' reluctance to change.ConclusionOur findings contribute valuable insights about how primary care nurses approach goal‐setting within a self‐management support program. Notably, unlike previous studies where clinicians reported that time‐limited appointments and institutional expectations hindered patient‐centred goal‐setting, our participants practicing in an institutionally supported goal‐oriented patient‐centred model of care did not report time constraints or pressures to prioritise clinical goals over patient goals. Instead, they described patient‐centred goal‐setting practices that are associated with positive patient and clinical outcomes. To potentially corroborate and expand upon our findings and inform practice and training, future research should include qualitative and survey studies to explore primary care RNs perspectives about goal‐setting and observational research to evaluate nurse–patient goal‐setting interactions.

ABSTRACTObjectiveTo explore pre–hematopoietic stem cell transplant (HSCT) demographic, disease, and psychological factors predictive of future transplant regret and to determine post‐HSCT variables associated with regret.Patients and MethodsHSCT candidates participated in a prospective cohort study (June 2008–October 2013) examining health behaviors and HSCT outcomes, including completion of standardized surveys at pre‐HSCT (baseline) and 1‐year post‐HSCT. Cases were participants that endorsed regret at 1‐year post‐HSCT follow‐up, and controls were participants without regret at 1 year, matched on age, sex, and transplant type. For cases and controls, pre‐HSCT psychosocial evaluations were abstracted from the electronic health record and coded to determine the Psychosocial Assessment of Candidates for Transplantation score, psychosocial stressors, and mental health diagnoses. The association of selected factors with regret was estimated with odds ratios and 95% confidence intervals from conditional logistic regression models.ResultsAt post‐HSCT, 49 participants of 638 endorsed transplant regret (8%) and formed the case group; 98 controls were matched from remaining participants. Cases and controls were well matched on age (56.6 vs. 57.2 years), sex (both groups 34.7% female), and transplant type (both groups 81.6% autologous). After controlling for the number of hospitalizations and active treatment status, conditional logistic regression revealed that patients who endorsed regret were 3.7 times (95% CI = 1.37–9.69, p = 0.008) more likely to not be in remission compared to controls at 1‐year post‐HSCT.ConclusionMatched case–control analyses revealed that no pre‐HSCT variables collected during the pre‐HSCT evaluation period were predictive of transplant regret, while poorer outcomes at 1‐year after transplant were associated with regret.

Objectives/Goals: This study aims to evaluate the performance of a third-party artificial intelligence (AI) product in predicting diagnosis-related groups (DRGs) in a community healthcare system. We highlight a use case illustrating how clinical practice leverages AI-predicted information in unexpected yet advantageous ways and assess the AI predictions accuracy and practical application. Methods/Study Population: DRGs are crucial for hospital reimbursement under the prospective payment model. The Mayo Clinic Health System (MCHS), a network of clinics and hospitals serving a substantial rural population in Minnesota and Wisconsin, has recently adopted an AI algorithm developed by Xsolis (an AI-focused healthcare solution provider). This algorithm, a 1D convolutional neural network, predicts DRGs based on clinical documentation. To assess the accuracy of AI-generated DRG predictions for inpatient discharges, we analyzed data from 930 patients hospitalized at MCHS Mankato between March 2 and May 13, 2024. The Xsolis platform provided the top three DRG predictions for the first 48 hours of each inpatient stay. The accuracy of these predictions was then compared against the final billed DRG codes from the hospital’s records. Results/Anticipated Results: In our validation set, Xsolis achieved a top-3 DRG prediction accuracy of 71% at 24 hours and 81% at 48 hours, which is lower than the originally reported accuracy of 81.1% and 83.3%, respectively. Interestingly, discussions with clinical practice leaders revealed that the most valuable information derived from the AI predictions was the expected geometric mean length of stay (GMLOS), which Xsolis was perceived to predict accurately. In the Medicare system, each DRG is associated with an expected GMLOS, a critical factor for efficient hospital flow planning. A subsequent analysis comparing predicted GMLOS with the actual length of stay showed variances of -0.10 days on day 1 and 0.14 days on day 2, indicating a high degree of accuracy and aligning with clinical practice perceptions. Discussion/Significance of Impact: Our research underscores that clinical practice can leverage AI predictions in unexpected yet beneficial ways. While initially focused on DRG prediction, the associated GMLOS emerged as more significant. This suggests that AI algorithm validation should be tailored to specific clinical needs rather than relying solely on generalized benchmarks.

ABSTRACTObjectiveTo examine the outcomes of a clinical sample of young patients with restrictive eating disorders who received Family‐Based Treatment for Primary Care (FBT‐PC).MethodsParticipants were 134 youth (mean age = 15.7 years) and their caregiver(s). Participants and caregivers completed measures of eating disorder symptomatology, quality of life, and caregiver self‐efficacy.ResultsOf the 134 patients who received at least one session of FBT‐PC, 55.9% completed treatment, 20.1% were followed until they began a higher level of care, and 23.8% were non‐completers. Weekly measures for the full sample were evaluated using intention‐to‐treat analyses. Patient‐reported scores on the ED‐15 improved by −0.1 (SE = 0.02, F (1,133)= 26.4, p < 0.0001) per week, and caregivers' ratings of patient symptoms also improved by 0.85 (SE = 0.2, F (1,133)=13.1, p = 0.0003) per week. Patient's BMI percentile increased by 1.25 points per week (SE = 0.14, F (1,133) = 83.9, p < 0.0001). For patients who completed FBT‐PC, eating disorder symptoms, per patient‐ (M = −1.43, p < 0.0001) and caregiver‐report (M = −1.33 p < 0.0001) decreased significantly from baseline to end of treatment. Patient's quality of life increased significantly from baseline to end of treatment (M = 21.6, p < 0.0001) and caregivers showed significant increases in self‐efficacy (M = 3.41, p < 0.0001, d = 0.856). At the end of treatment, 62.5% of patients with complete data met criteria for full research remission, and 44.6% met criteria for full clinical remission.DiscussionFindings provide preliminary support for FBT‐PC as an effective treatment for youth with restrictive eating disorders. Additional research is needed to replicate these findings in other primary care settings and to understand the durability of treatment effects.