Search

Background: Deprescribing is the planned/supervised method of dose reduction or cessation of medications that might be harmful, or no longer be beneficial. Though benefits of deprescribing are debatable in improving clinical outcomes, it has been associated with decreased number of potentially inappropriate medications, which may potentially reduce the risk of adverse events among hospitalized older adults. With unclear evidence for deprescribing in this population, this study aimed to examine time‐to‐first unplanned healthcare utilization, which included 90‐day emergency department (ED) visits or hospital readmission and associated predictors, during a deprescribing intervention. Methods: A secondary data analysis of a clinical trial (Shed‐MEDS NCT02979353) was performed. Cox regression was used to compare the time‐to‐first 90‐day ED visit/readmission/death from hospital discharge for the intervention and control groups. Additionally, we performed exploratory analysis of predictors (comorbidities, functional health status, drug burden index (DBI), hospital length of stay, health literacy, food insecurity, and financial burden) associated with the time‐to‐first 90‐day ED visit/readmission/death. Results: The hazard of first 90‐day ED visits/readmissions/death was 15% lower in the intervention versus the control group (95% CI: 0.61–1.19, p = 0.352, respectively); however, this difference was not statistically significant. For every additional number of comorbidities (Hazard ratio (HR): 1.12, 95% CI: 1.04–1.21) and each additional day of hospital length of stay (HR: 1.04, 95% CI: 1.01–1.07) were significantly associated with a higher hazard of 90‐day ED visit/readmission/death in the intervention group; whereas for each unit of increase in pre‐hospital DBI score (HR: 1.08 and HR 1.16, respectively) was significantly associated with a higher hazard of 90‐day ED visit/readmission/death in the control group. Conclusions: The intervention and control groups had comparable time‐to‐first 90‐day ED visit/readmission/death during a deprescribing intervention. This finding suggests that deprescribing did not result in a higher risk of ED visit/readmission/death during the 90‐day period following hospital discharge. [ABSTRACT FROM AUTHOR]

The article presents a study which aimed to understand from clinicians and older adults ways to optimize a proposed home-based deprescribing intervention that focuses on tailoring medications based on patient's daily and life goals. Topics include clinicians included in the study, daily activities/goals for older adults, and the need to identify older adults prototypes and design flexible deprescribing interventions that can target a broad range of older adults for maximum impact.

Background: Although the atherogenic index of plasma (AIP) based on a single measurement is a known risk factor for cardiovascular disease (CVD), little is known about whether changes in AIP over time are related to incident CVD. We aimed to determine whether AIP trajectory, which reflects homogenous AIP trends for a particular period, is associated with CVD risk. Methods: Data from 5,843 participants of the Korean Genome and Epidemiology Study (KoGES) were analyzed. The KoGES had been conducted biennially from the baseline survey (2001–2002) to the eighth follow-up survey (2017–2018). The research design specifies the exposure period from baseline to the third follow-up, designates the latent period at the fourth follow-up, and establishes the event accrual period from the fifth to the eighth follow-up. During the exposure period, we identified two trajectories: a decreasing (n = 3,036) and an increasing group (n = 2,807) using latent variable mixture modeling. Information on CVD was collected initially through the self-reporting, followed by in depth person-to-person interview conducted by a well-trained examiner. During the event accrual period, the cumulative incidence rates of CVD between the two AIP trajectory groups were estimated using Kaplan–Meier analysis with the log-rank test. Multiple Cox proportional hazard models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). Results: The increasing AIP trajectory group had a significantly higher cumulative incidence rate of CVD than the decreasing AIP trajectory group. Compared to the decreasing AIP trajectory group, the increasing AIP trajectory group had a higher risk of incident CVD (HR: 1.31, 95% CI: 1.02–1.69) after adjusting for confounders. Conclusions: The risk of incident CVD increased when the AIP level showed an increasing trend and remained high over a long period. This suggests that checking and managing the trajectory of the AIP can be a preventive strategy for incident CVD. [ABSTRACT FROM AUTHOR]

Background: Although lesion counting is an evaluation method that effectively analyzes facial acne severity, its usage is limited because of difficult implementation. Objectives: We aimed to develop and validate an automated algorithm that detects and counts acne lesions by type, and to evaluate its clinical applicability as an assistance tool through a reader test. Methods: A total of 20,699 lesions (closed and open comedones, papules, nodules/cysts, and pustules) were manually labeled on 1213 facial images of 398 facial acne photography sets (frontal and both lateral views) acquired from 258 patients and used for training and validating algorithms based on a convolutional neural network for classifying five classes of acne lesions or for binary classification into noninflammatory and inflammatory lesions. Results: In the validation dataset, the highest mean average precision was 28.48 for the binary classification algorithm. Pearson's correlation of lesion counts between algorithm and ground-truth was 0.72 (noninflammatory) and 0.90 (inflammatory), respectively. In the reader test, eight readers (100.0%) detected and counted lesions more accurately using the algorithm compared with the reader-alone evaluation. Conclusions: Overall, our algorithm demonstrated clinically applicable performance in detecting and counting facial acne lesions by type and its utility as an assistance tool for evaluating acne severity. [ABSTRACT FROM AUTHOR]

Dendropanax morbifera ( D. morbifera), a species endemic to Korea, is largely distributed throughout the southern part of the country. Its leaves, stems, roots, and seeds have been used as a form of alternative medicine for various diseases and neurological disorders including paralysis, stroke, and migraine. However, the molecular mechanisms that underlie the remedial effects of D. morbifera remain largely unknown. In this paper, extracts from D. morbifera leaves were prepared using ethyl acetate as a solvent (abbreviated as DMLE). The modulatory effects of DMLE on neuroinflammation were studied in a lipopolysaccharide (LPS)-stimulated BV2 murine microglial cell line. Production of pro-inflammatory cytokines, activation of mitogen-activated protein kinases (MAPKs) and nuclear factor-kappa B (NF-B), and different M1/M2 activation states of microglia were examined. DMLE treatment suppressed the production of pro-inflammatory cytokines including tumor necrosis factor- (TNF-), interleukin-6 (IL-6), and nitric oxide (NO) in LPS-stimulated BV2 cells. DMLE treatment also attenuated the activation of MAPKs and NF-B. In a novel discovery, we found that DMLE up-regulated the marker genes representing an alternative, anti-inflammatory M2 polarization, while suppressing the expression of the classical, pro-inflammatory M1 activation state genes. Here, we uncovered the cellular mechanisms underlying the beneficial effects of D. morbifera against neuroinflammation using BV2 microglia cells. These results strongly suggest that DMLE was able to counter the effects of LPS on BV2 cells via control of microglia polarization states. Additionally, study results indicated that DMLE may have therapeutic potential as a neuroinflammation-suppressing treatment for neurodegenerative diseases. [ABSTRACT FROM AUTHOR]