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Psychotic disorders as a framework for precision psychiatry. Nat Rev Neurol 2023; 19:221-234. [PMID: 36879033 DOI: 10.1038/s41582-023-00779-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/24/2023] [Indexed: 03/08/2023]
Abstract
People with psychotic disorders can show marked interindividual variations in the onset of illness, responses to treatment and relapse, but they receive broadly similar clinical care. Precision psychiatry is an approach that aims to stratify people with a given disorder according to different clinical outcomes and tailor treatment to their individual needs. At present, interindividual differences in outcomes of psychotic disorders are difficult to predict on the basis of clinical assessment alone. Therefore, current research in psychosis seeks to build models that predict outcomes by integrating clinical information with a range of biological measures. Here, we review recent progress in the application of precision psychiatry to psychotic disorders and consider the challenges associated with implementing this approach in clinical practice.
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Yang M, Sun D, Wang Y, Yan M, Zheng J, Ren J. Cognitive Impairment in Heart Failure: Landscape, Challenges, and Future Directions. Front Cardiovasc Med 2022; 8:831734. [PMID: 35198608 PMCID: PMC8858826 DOI: 10.3389/fcvm.2021.831734] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Accepted: 12/30/2021] [Indexed: 12/20/2022] Open
Abstract
Heart failure (HF) is a major global healthcare problem accounting for substantial deterioration of prognosis. As a complex clinical syndrome, HF often coexists with multi-comorbidities of which cognitive impairment (CI) is particularly important. CI is increasing in prevalence among patients with HF and is present in around 40%, even up to 60%, of elderly patients with HF. As a potent and independent prognostic factor, CI significantly increases the hospitalization and mortality and decreases quality of life in patients with HF. There has been a growing awareness of the complex bidirectional interaction between HF and CI as it shares a number of common pathophysiological pathways including reduced cerebral blood flow, inflammation, and neurohumoral activations. Research that focus on the precise mechanism for CI in HF is still ever insufficient. As the tremendous adverse consequences of CI in HF, effective early diagnosis of CI in HF and interventions for these patients may halt disease progression and improve prognosis. The current clinical guidelines in HF have begun to emphasize the importance of CI. However, nearly half of CI in HF is underdiagnosed, and few recommendations are available to guide clinicians about how to approach CI in patients with HF. This review aims to synthesize knowledge about the link between HF and cognitive dysfunction, issues pertaining to screening, diagnosis and management of CI in patients with HF, and emerging therapies for prevention. Based on data from current studies, critical gaps in knowledge of CI in HF are identified, and future research directions to guide the field forward are proposed.
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Affiliation(s)
- Mengxi Yang
- Heart Failure Center, China-Japan Friendship Hospital, Beijing, China
- Department of Cardiology, China-Japan Friendship Hospital, Beijing, China
| | - Di Sun
- Heart Failure Center, China-Japan Friendship Hospital, Beijing, China
- Department of Cardiology, China-Japan Friendship Hospital, Beijing, China
| | - Yu Wang
- Department of Neurology, China-Japan Friendship Hospital, Beijing, China
| | - Mengwen Yan
- Heart Failure Center, China-Japan Friendship Hospital, Beijing, China
- Department of Cardiology, China-Japan Friendship Hospital, Beijing, China
| | - Jingang Zheng
- Heart Failure Center, China-Japan Friendship Hospital, Beijing, China
- Department of Cardiology, China-Japan Friendship Hospital, Beijing, China
| | - Jingyi Ren
- Heart Failure Center, China-Japan Friendship Hospital, Beijing, China
- Department of Cardiology, China-Japan Friendship Hospital, Beijing, China
- Vascular Health Research Center of Peking University Health Science Center, Beijing, China
- *Correspondence: Jingyi Ren
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Evaluation of Available Cognitive Tools Used to Measure Mild Cognitive Decline: A Scoping Review. Nutrients 2021; 13:nu13113974. [PMID: 34836228 PMCID: PMC8623828 DOI: 10.3390/nu13113974] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2021] [Revised: 10/28/2021] [Accepted: 10/29/2021] [Indexed: 11/17/2022] Open
Abstract
Cognitive decline is a broad syndrome ranging from non-pathological/age-associated cognitive decline to pathological dementia. Mild cognitive impairment MCI) is defined as the stage of cognition that falls between normal ageing and dementia. Studies have found that early lifestyle interventions for MCI may delay its pathological progression. Hence, this review aims to determine the most efficient cognitive tools to discriminate mild cognitive decline in its early stages. After a systematic search of five online databases, a total of 52 different cognitive tools were identified. The performance of each tool was assessed by its psychometric properties, administration time and delivery method. The Montreal Cognitive Assessment (MoCA, n = 15), the Mini-Mental State Examination (MMSE, n = 14) and the Clock Drawing Test (CDT, n = 4) were most frequently cited in the literature. The preferable tools with all-round performance are the Six-item Cognitive Impairment Test (6CIT), MoCA (with the cut-offs of ≤24/22/19/15.5), MMSE (with the cut-off of ≤26) and the Hong Kong Brief Cognitive Test (HKBC). In addition, SAGE is recommended for a self-completed survey setting whilst a 4-point CDT is quick and easy to be added into other cognitive assessments. However, most tools were affected by age and education levels. Furthermore, optimal cut-off points need to be cautiously chosen while screening for MCI among different populations.
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