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情感症状的亚型是否与认知随时间的变化有不同的关联:潜类分析。

Are subtypes of affective symptoms differentially associated with change in cognition over time: A latent class analysis.

机构信息

Adapt Lab, Research Department of Clinical, Educational and Health Psychology, University College London, London, UK.

Adapt Lab, Research Department of Clinical, Educational and Health Psychology, University College London, London, UK; Centre for Outcomes Research and Effectiveness, Research Department of Clinical, Educational and Health Psychology, University College London, London, UK.

出版信息

J Affect Disord. 2022 Jul 15;309:437-445. doi: 10.1016/j.jad.2022.04.139. Epub 2022 Apr 29.

Abstract

BACKGROUND

In the absence of disease-modifying treatments, identifying potential psychosocial risk factors for dementia is paramount. Depression and anxiety have been identified as potential risk factors. Studies however have yielded mixed findings, lending possibility to the fact that potential constellations of co-occurring depression and anxiety symptoms may better explain the link between affective symptoms and cognitive decline.

METHODS

Data from participants (aged 50 and above) of the PROTECT study was used. Latent Class Analysis (LCA) was conducted on 21,684 participants with baseline anxiety and depression measures. Multiple linear regressions models, using a subset of these participants (N = 6136) who had complete cognition data at baseline and at 2-year follow-up, were conducted to assess for associations between class membership and longitudinal changes in cognition.

RESULTS

The LCA identified a 5-class solution: "No Symptoms", "Sleep", "Sleep and Worry", "Sleep and Anhedonia", and "Co-morbid Depression and Anxiety". Class membership was significantly associated with longitudinal change in cognition. Furthermore, this association differed across different cognitive measures.

LIMITATIONS

Limitations included significant attrition and a generally healthy sample which may impact generalisability.

CONCLUSIONS

Substantial heterogeneity in affective symptoms could explain previous inconsistent findings concerning the association between affective symptoms and cognition. Clinicians should not focus solely on total symptom scores on a single affective domain, but instead on the presence and patterns of symptoms (even if sub-clinical) on measures across multiple affective domains. Identifying particular subgroups that are at greater risk of poor cognitive outcomes may support targeted prevention work.

摘要

背景

在缺乏疾病修正治疗的情况下,识别痴呆的潜在心理社会风险因素至关重要。抑郁和焦虑已被确定为潜在的风险因素。然而,这些研究的结果喜忧参半,这可能表明潜在的共病性抑郁和焦虑症状组合可能更好地解释情感症状与认知能力下降之间的联系。

方法

使用 PROTECT 研究参与者(年龄在 50 岁及以上)的数据。对 21684 名基线时存在焦虑和抑郁测量值的参与者进行潜在类别分析(LCA)。使用这些参与者的一个子集(N=6136)进行多项线性回归模型,这些参与者在基线和 2 年随访时具有完整的认知数据,以评估类别成员与认知的纵向变化之间的关联。

结果

LCA 确定了 5 个类别解决方案:“无症状”、“睡眠”、“睡眠和担忧”、“睡眠和快感缺失”和“共病性抑郁和焦虑”。类别成员与认知的纵向变化显著相关。此外,这种关联在不同的认知测量中存在差异。

局限性

局限性包括大量的流失和一般健康的样本,这可能会影响普遍性。

结论

情感症状的显著异质性可以解释先前关于情感症状与认知之间关联的不一致发现。临床医生不应该仅仅关注单一情感领域的总症状评分,而应该关注多个情感领域的测量中症状的存在和模式(即使是亚临床症状)。确定特定的亚组,这些亚组更容易出现认知结局不良的风险,可能有助于有针对性的预防工作。

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