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1.
medrxiv; 2023.
Preprint en Inglés | medRxiv | ID: ppzbmed-10.1101.2023.12.14.23299928

RESUMEN

We investigated performance validity tests (PVTs) in patients presenting with new onset cognitive complaints associated with post-acute sequelae of COVID-19 infection (PASC). Retrospective data were obtained from IRB-approved registries. All patients completed the Victoria Symptom Validity Test (VSVT) in conjunction with a neuropsychological evaluation. A sub-analysis included 7 other PVT measures. The PASC sample was compared to an analogous multiple sclerosis (MS) sample with known PVT failure rates. The PASC sample consisted of 177 patients (49.4 ± 11.2 years), educated (14.7 ± 2.3 years), predominantly female (81.4%), and white, non-Hispanic (85.3%) patients. Seven percent of the PASC sample scored below the established VSVT hard item cut-off, and of those with invalid VSVT over 50% failed 3 or more additional PVTs. In comparison to a MS sample, the PASC sample reported comparable psychological symptoms, but were significantly less likely to produce invalid VSVT scores and seek disability benefits. This study provides a profile of PVTs in patients presenting with PASC. The general infrequence of invalid responding in this PASC sample (7%) is noteworthy compared to an MS sample and highlights the role of additional factors in non-credible response such as elevated psychological symptoms or pursuit of disability.


Asunto(s)
Neoplasias Testiculares , Insuficiencia Cardíaca , Esclerosis Múltiple , COVID-19 , Disfunciones Sexuales Psicológicas
2.
medrxiv; 2022.
Preprint en Inglés | medRxiv | ID: ppzbmed-10.1101.2022.10.21.22281239

RESUMEN

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 complementary data-driven approach based on unsupervised machine-learning clustering algorithms was 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 according to the severity of cognitive impairment, but there was no difference in cognitive profiles. 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.


Asunto(s)
COVID-19 , Trastornos del Conocimiento
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