Health System, Community-Based, or Usual Dementia Care for Persons With Dementia and Caregivers

ImportanceThe effectiveness of different approaches to dementia care is unknown.ObjectiveTo determine the effectiveness of health system-based, community-based dementia care, and usual care for persons with dementia and for caregiver outcomes.Design, setting, and participantsRandomized clinical trial of community-dwelling persons living with dementia and their caregivers conducted at 4 sites in the US (enrollment June 2019-January 2023; final follow-up, August 2023).InterventionsParticipants were randomized 7:7:1 to health system-based care provided by an advanced practice dementia care specialist (n = 1016); community-based care provided by a social worker, nurse, or licensed therapist care consultant (n = 1016); or usual care (n = 144).Main outcomes and measuresPrimary outcomes were caregiver-reported Neuropsychiatric Inventory Questionnaire (NPI-Q) severity score for persons living with dementia (range, 0-36; higher scores, greater behavioral symptoms severity; minimal clinically important difference [MCID], 2.8-3.2) and Modified Caregiver Strain Index for caregivers (range, 0-26; higher scores, greater strain; MCID, 1.5-2.3). Three secondary outcomes included caregiver self-efficacy (range, 4-20; higher scores, more self-efficacy).ResultsAmong 2176 dyads (individuals with dementia, mean age, 80.6 years; 58.4%, female; and 20.6%, Black or Hispanic; caregivers, mean age, 65.2 years; 75.8%, female; and 20.8% Black or Hispanic), primary outcomes were assessed for more than 99% of participants, and 1343 participants (62% of those enrolled and 91% still alive and had not withdrawn) completed the study through 18 months. No significant differences existed between the 2 treatments or between treatments vs usual care for the primary outcomes. Overall, the least squares means (LSMs) for NPI-Q scores were 9.8 for health system, 9.5 for community-based, and 10.1 for usual care. The difference between health system vs community-based care was 0.30 (97.5% CI, -0.18 to 0.78); health system vs usual care, -0.33 (97.5% CI, -1.32 to 0.67); and community-based vs usual care, -0.62 (97.5% CI, -1.61 to 0.37). The LSMs for the Modified Caregiver Strain Index were 10.7 for health system, 10.5 for community-based, and 10.6 for usual care. The difference between health system vs community-based care was 0.25 (97.5% CI, -0.16 to 0.66); health system vs usual care, 0.14 (97.5% CI, -0.70 to 0.99); and community-based vs usual care, -0.10 (97.5% CI, -0.94 to 0.74). Only the secondary outcome of caregiver self-efficacy was significantly higher for both treatments vs usual care but not between treatments: LSMs were 15.1 for health system, 15.2 for community-based, and 14.4 for usual care. The difference between health system vs community-based care was -0.16 (95% CI, -0.37 to 0.06); health system vs usual care, 0.70 (95% CI, 0.26-1.14); and community-based vs usual care, 0.85 (95% CI, 0.42 to 1.29).Conclusions and relevanceIn this randomized trial of dementia care programs, no significant differences existed between health system-based and community-based care interventions nor between either active intervention or usual care regarding patient behavioral symptoms and caregiver strain.Trial registrationClinicalTrials.gov Identifier: NCT03786471

A scoping review of cognitive behavioral therapy for gambling disorder and co-occurring psychiatric conditions

A scoping review of studies that have examined cognitive behavioral interventions (e.g., CBT) for gambling disorder and co-occurring psychiatric conditions

The Common Pathways of Epileptogenesis in Patients With Epilepsy Post-Brain Injury: Findings From a Systematic Review and Meta-analysis.

BACKGROUND AND OBJECTIVE: Epilepsy may result from various brain injuries, including stroke (ischemic and hemorrhagic), traumatic brain injury, and infections. Identifying shared common biological pathways and biomarkers of the epileptogenic process initiated by the different injuries may lead to novel targets for preventing the development of epilepsy. We systematically reviewed biofluid biomarkers to test their association with the risk of post-brain injury epilepsy. METHODS: We searched articles until January 25, 2022, in MEDLINE, Embase, PsycINFO, Web of Science, and Cochrane. The primary outcome was the difference in mean biomarker levels in patients with and without post-brain injury epilepsy. We used the modified quality score on prognostic studies for risk of bias assessment. We calculated each biomarker\u27s pooled standardized mean difference (SMD) and 95% confidence intervals (CI). Molecular interaction network and enrichment analyses were conducted in Cytoscape. (PROSPERO CRD42021297110) RESULTS: We included 22 studies with 1499 cases with post-brain injury epilepsy and 7929 controls without post-brain injury epilepsy. Forty-five biomarkers in blood or cerebrospinal fluid (CSF) were investigated with samples collected at disparate time points. Of 22 studies, 21 had a moderate-to-high risk of bias. Most biomarkers (28/45) were investigated in single studies; only nine provided validation data, and studies used variable definitions for early and late-onset seizures. A meta-analysis was possible for 19 biomarkers. Blood glucose levels in four studies were significantly higher in patients with post-stroke epilepsy (PSE) than without PSE (SMD 0.44; CI 0.19 to 0.69). From individual studies, 15 biomarkers in blood and seven in CSF were significantly associated with post-brain injury epilepsy. Enrichment analysis identified that the significant biomarkers (IL6, IL1β) were predominantly inflammation related. DISCUSSION: We cannot yet recommend using the reported biomarkers for designing anti-epileptogenesis trials or use in the clinical setting because of methodological heterogeneity, bias in the included studies, and insufficient validation studies. Even though our analyses indicate the plausible role of inflammation in epileptogenesis, this is likely not the only mechanism. For example, an individual\u27s genetic susceptibilities might contribute to his risk of epileptogenesis after brain injury. Rigorously designed biomarker studies with methods acceptable to the regulatory bodies should be conducted

High-Throughput Characterization of Blood Serum Proteomics of IBD Patients with Respect to Aging and Genetic Factors

To date, no large scale, systematic description of the blood serum proteome has been performed in inflammatory bowel disease (IBD) patients. By using microarray technology, a more complete description of the blood proteome of IBD patients is feasible. It may help to achieve a better understanding of the disease. We analyzed blood serum profiles of 1128 proteins in IBD patients of European descent (84 Crohn's Disease (CD) subjects and 88 Ulcerative Colitis (UC) subjects) as well as 15 healthy control subjects, and linked protein variability to patient age (all cohorts) and genetic components (genotype data generated from CD patients). We discovered new, previously unreported aging-associated proteomic traits (such as serum Albumin level), confirmed previously reported results from different tissues (i.e., upregulation of APOE with aging), and found loss of regulation of MMP7 in CD patients. In carrying out a genome wide genotype-protein association study (proteomic Quantitative Trait Loci, pQTL) within the CD patients, we identified 41 distinct proteomic traits influenced by cis pQTLs (underlying SNPs are referred to as pSNPs). Significant overlaps between pQTLs and cis eQTLs corresponding to the same gene were observed and in some cases the QTL were related to inflammatory disease susceptibility. Importantly, we discovered that serum protein levels of MST1 (Macrophage Stimulating 1) were regulated by SNP rs3197999 (p = 5.96E-10, FDR<5%), an accepted GWAS locus for IBD. Filling the knowledge gap of molecular mechanisms between GWAS hits and disease susceptibility requires systematically dissecting the impact of the locus at the cell, mRNA expression, and protein levels. The technology and analysis tools that are now available for large-scale molecular studies can elucidate how alterations in the proteome driven by genetic polymorphisms cause or provide protection against disease. Herein, we demonstrated this directly by integrating proteomic and pQTLs with existing GWAS, mRNA expression, and eQTL datasets to provide insights into the biological processes underlying IBD and pinpoint causal genetic variants along with their downstream molecular consequences