Development of criteria for cognitive dysfunction in post-COVID syndrome: the IC-CoDi-COVID approach

被引:35
|
作者
Matias-Guiu, Jordi A. [1 ]
Herrera, Elena [2 ]
Gonzalez-Nosti, Maria [2 ]
Krishnan, Kamini [3 ]
Delgado-Alonso, Cristina [1 ]
Diez-Cirarda, Maria [1 ]
Yus, Miguel [4 ]
Martinez-Petit, Alvaro [5 ]
Pagan, Josue [5 ,6 ]
Matias-Guiu, Jorge [1 ]
Luis Ayala, Jose [6 ,7 ]
Busch, Robyn [3 ]
Hermann, Bruce P. [8 ]
机构
[1] Univ Complutense Madrid, Hlth Res Inst San Carlos IdISCC, Hosp Clin San Carlos, Dept Neurol, Madrid, Spain
[2] Univ Oviedo, Fac Psychol, Oviedo, Spain
[3] Cleveland Clin, Dept Neurol, Cleveland, OH 44106 USA
[4] Univ Complutense Madrid, Dept Radiol, Clin San Carlos, Hlth Res Inst San Carlos IdISCC, Madrid, Spain
[5] Univ Politecn Madrid, Dept Elect Engn, Madrid, Spain
[6] Univ Politecn Madrid, Ctr Computat Simulat, Campus Montegancedo, Madrid, Spain
[7] Univ Complutense, Dept Automat Architecture & Automat, Madrid, Spain
[8] Univ Wisconsin, Dept Neurol, Sch Med & Publ Hlth, Madison, WI 53706 USA
关键词
COVID-19; Cognitive; neuropsychological; Machine learning; Post-COVID syndrome; IC-CoDi-COVID; PROJECT METHODS; DISORDERS; ADULTS;
D O I
10.1016/j.psychres.2022.115006
中图分类号
R749 [精神病学];
学科分类号
100205 ;
摘要
Background: We aimed to develop objective criteria for cognitive dysfunction associated with the post-COVID syndrome.Methods: Four hundred and four patients with post-COVID syndrome from two centers were evaluated with comprehensive neuropsychological batteries. The International Classification for Cognitive Disorders in Epilepsy (IC-CoDE) framework was adapted and implemented. A healthy control group of 145 participants and a com-plementary data-driven approach based on unsupervised machine-learning clustering algorithms were also used to evaluate the optimal classification and cutoff points.Results: According to the developed criteria, 41.2% and 17.3% of the sample were classified as having at least one cognitive domain impaired using-1 and-1.5 standard deviations as cutoff points. Attention/processing speed was the most frequently impaired domain. There were no differences in base rates of cognitive impairment between the two centers. Clustering analysis revealed two clusters, although with an important overlap (silhouette index 0.18-0.19). Cognitive impairment was associated with younger age and lower education levels, but not hospitalization.Conclusions: We propose a harmonization of the criteria to define and classify cognitive impairment in the post-COVID syndrome. These criteria may be extrapolated to other neuropsychological batteries and settings, contributing to the diagnosis of cognitive deficits after COVID-19 and facilitating multicenter studies to guide biomarker investigation and therapies.
引用
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页数:10
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