Objective: This study tests the hypothesis that the use of semantic organizational strategy during the free-recall phase of a verbal memory task predicts remission of geriatric depression.
Methods: Sixty-five older patients with major depression participated in a 12-week escitalopram treatment trial. Neuropsychological performance was assessed at baseline after a 2-week drug washout period. The Hopkins Verbal Learning Test-Revised was used to assess verbal learning and memory. Remission was defined as a Hamilton Depression Rating Scale score of ≤ 7 for 2 consecutive weeks and no longer meeting the DSM-IV-TR criteria for major depression. The association between the number of clusters used at the final learning trial (trial 3) and remission was examined using Cox's proportional hazards survival analysis. The relationship between the number of clusters utilized in the final learning trial and the number of words recalled after a 25-min delay was examined in a regression with age and education as covariates.
Results: Higher number of clusters utilized predicted remission rates (hazard ratio, 1.26 (95% confidence interval, 1.04-1.54); χ(2) = 4.23, df = 3, p = 0.04). There was a positive relationship between the total number of clusters used by the end of the third learning trial and the total number of words recalled at the delayed recall trial (F(3,58) = 7.93; p < 0.001).
Conclusions: Effective semantic strategy use at baseline on a verbal list learning task by older depressed patients was associated with higher rates of remission with antidepressant treatment. This result provides support for previous findings indicating that measures of executive functioning at baseline are useful in predicting antidepressant response.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3188360 | PMC |
http://dx.doi.org/10.1002/gps.2743 | DOI Listing |
Sci Rep
December 2024
Clinical Trials and Evidence-Based Syntheses Research Unit (CTEBs RU), Department of Clinical Pharmacy, Faculty of Pharmacy, Mahasarakham University, Mahasarakham, 44150, Thailand.
Spontaneous adverse drug reactions (ADRs) reporting by health care professionals (HCPs) plays a vital role in pharmacovigilance (PV). However, under-reporting remain a major challenge worldwide, especially in low and middle-income countries, including Lao PDR. This cluster-randomized controlled trial evaluated the effectiveness of the modified TaWai mobile app for ADR reporting compared with the usual practice in hospitals.
View Article and Find Full Text PDFSci Rep
December 2024
Clinical Teaching Hospital of Medical School, Nanjing Children's Hospital, Nanjing University, Nanjing, 210008, China.
Gastric cancer (GC) is characterized by notable heterogeneity and the impact of molecular subtypes on treatment and prognosis. The role of programmed cell death (PCD) in cellular processes is critical, yet its specific function in GC is underexplored. This study applied multiomics approaches, integrating transcriptomic, epigenetic, and somatic mutation data, with consensus clustering algorithms to classify GC molecular subtypes and assess their biological and immunological features.
View Article and Find Full Text PDFSci Rep
December 2024
Department of Nephrology, General Hospital of Ningxia Medical University, Yinchuan, China.
Metabolic syndrome, a cluster of conditions including obesity, hyperglycemia, hypertension, and dyslipidemia, is increasingly recognized for its association with kidney disease. However, the impact of metabolic syndrome on the long-term prognosis of IgA nephropathy(IgAN) remains understudied. From August 2009 to December 2018, we conducted a retrospective cohort study at the Department of Nephrology, General Hospital of Ningxia Medical University, involving 698 patients with primary IgAN identified by the initial renal biopsy.
View Article and Find Full Text PDFSci Rep
December 2024
Department of Computer Engineering, Sharif University of Technology, Azadi Avenue, Tehran, Iran.
Numerous algorithms have been proposed to infer the underlying structure of the social networks via observed information propagation. The previously proposed algorithms concentrate on inferring accurate links and neglect preserving the essential topological properties of the underlying social networks. In this paper, we propose a novel method called DANI to infer the underlying network while preserving its structural properties.
View Article and Find Full Text PDFSci Rep
December 2024
State Key Laboratory of Media Convergence and Communication, Communication University of China, Beijing, 100024, China.
The proliferation of multi-platform network information has expanded communication channels for users, enabling the integration and dissemination of information across both Social Networking Services (SNS)-type app and Instant Message (IM)-type app. With the intensification of convergent communication, some users in the two types of apps show active alternation in spreading information to each other's platforms. The study of the evolution trend of information in different platforms is of great practical significance for the mastery of the communication law.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!