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Screening for Mild Cognitive Impairment in the Preoperative Setting: A Narrative Review - PMC
Source: ncbi.nlm.nih.gov
Article summary:
1. Cognitive impairment can lead to delirium and postoperative cognitive dysfunction in older patients.
2. This review aimed to describe the available cognitive screeners suitable for preoperative screening and their psychometric properties for identifying mild cognitive impairment.
3. The MoCA screener was found to have the highest combination of sensitivity and specificity for detecting mild cognitive impairment in an older population.
Article analysis:
The article “Screening for Mild Cognitive Impairment in the Preoperative Setting: A Narrative Review” is a comprehensive review of existing literature on preoperative cognitive screening tools, with a focus on mild cognitive impairment (MCI). The authors conducted an extensive search of PubMed, PsycInfo, ClinicalKey, and ScienceDirect from 2015-2020 to identify relevant studies. They then provided an overview of the characteristics of each screener, such as interrater and test-retest reliability correlations, sensitivity and specificity for MCI and cognitive impairment, duration time, and cutoff points.
The article is generally reliable and trustworthy due to its comprehensive search strategy that included multiple databases as well as its detailed description of each screener’s characteristics. However, there are some potential biases that should be noted. For example, the authors did not include informant-based screeners in their review which may have resulted in an incomplete picture of available preoperative screening tools. Additionally, the authors did not explore any potential risks associated with using these screeners or discuss any possible counterarguments or alternative perspectives on their use in the preoperative setting.
In conclusion, this article provides a thorough overview of existing literature on preoperative cognitive screening tools with a focus on MCI; however it should be noted that there are some potential biases that could affect its trustworthiness and reliability.