Recommendation

Is memory affected in the long run following SARS-CoV-2 infection?

ORCID_LOGO based on reviews by Phivos Phylactou, Dipanjan Ray and Mitul Mehta
A recommendation of:

Changes in memory function in adults following SARS-CoV-2 infection: findings from the Covid and Cognition online study

Abstract

EN
AR
ES
FR
HI
JA
PT
RU
ZH-CN
Submission: posted 14 August 2023
Recommendation: posted 28 February 2024, validated 28 February 2024
Cite this recommendation as:
Sreekumar, V. (2024) Is memory affected in the long run following SARS-CoV-2 infection?. Peer Community in Registered Reports, . https://rr.peercommunityin.org/PCIRegisteredReports/articles/rec?id=547

Recommendation

COVID-19 has been suspected to have long-lasting effects on cognitive function. The SARS-CoV-2 virus may enter the central nervous system (Frontera et al., 2020; Miners, Kehoe, & Love, 2020), explaining the observed detrimental effects of COVID-19 on verbal planning and reasoning (Hampshire et al., 2021; Wild et al., 2021), executive function (Hadad et al., 2022), and long-term memory (Guo et al., 2022). In particular, Guo et al. (2022) used verbal item recognition and non-verbal associative memory tasks. Weinerova et al. (2024), in the current study, propose to conduct a replication of Guo et al. (2022), but specifically, to disentangle the effect of COVID-19 infection status on both memory type (item vs. associative) and stimulus modality (verbal vs. non-verbal). Furthermore, Weinerova et al. (2024) propose to analyze cognitive function based on vaccination status before infection to provide a critical test of the potential protective effects of vaccination on cognitive function.

Data collection has been completed with 325 participants after exclusion criteria were applied (COVID group N = 232, No COVID group N = 93). Simulations assuming an effect size observed in Guo et al. (2022), a Bayesian t-test comparing the groups, and a Bayes Factor of 6 indicated that N = 320 is sufficient to detect an effect on 79% of simulations. The main analyses will be conducted using a Bayesian ANCOVA that allows for the inclusion of control variables such as age, sex, country, and education level. Both accuracy and reaction times from the item and associative recognition tasks will be analyzed as the dependent variables. In one analysis, vaccination status will be included as a between-subjects factor, to understand whether vaccination status at the time of infection influences subsequent cognitive function. 

It is important to note that participants were recruited through long-COVID Facebook groups and clinics. Therefore, the results must be interpreted carefully to avoid generalizing to all COVID-19 infections. The data are part of a larger longitudinal study, and the current pre-registration applies only to the baseline timepoint for a cross-sectional analysis. The remaining longitudinal data collection is ongoing and is not part of the current pre-registration.  

The study plan was refined after one round of review, with input from three external reviewers who all agreed that the proposed study was well-designed and scientifically valid. The recommender then reviewed the revised manuscript and judged that the study met the Stage 1 criteria for in-principle acceptance (IPA).
 
URL to the preregistered Stage 1 protocol: https://osf.io/tjs5u (under temporary private embargo)
 
Level of bias control achieved: Level 3. At least some data/evidence that will be used to the answer the research question has been previously accessed by the authors (e.g. downloaded or otherwise received), but the authors certify that they have not yet observed ANY part of the data/evidence.
 
List of eligible PCI RR-friendly journals:
 
 
References
 
1. Frontera, J., Mainali, S., Fink, E.L. et al. Global Consortium Study of Neurological Dysfunction in COVID-19 (GCS-NeuroCOVID): Study Design and Rationale. Neurocrit Care 33, 25–34 (2020). https://doi.org/10.1007/s12028-020-00995-3

2. Guo, P., Benito Ballesteros, A., Yeung, S. P., Liu, R., Saha, A., Curtis, L., Kaser, M., Haggard, M. P. & Cheke, L. G. (2022). COVCOG 2: Cognitive and Memory Deficits in Long COVID: A Second Publication From the COVID and Cognition Study. Frontiers in Aging Neuroscience. https://doi.org/10.3389/fnagi.2022.804937  

3. Hadad, R., Khoury, J., Stanger, C., Fisher, T., Schneer, S., Ben-Hayun, R., Possin, K., Valcour, V., Aharon-Peretz, J. & Adir, Y. (2022). Cognitive dysfunction following COVID-19 infection. Journal of NeuroVirology, 28(3), 430–437. https://doi.org/10.1007/s13365-022-01079-y  

4. Hampshire, A., Trender, W., Chamberlain, S. R., Jolly, A. E., Grant, J. E., Patrick, F., Mazibuko, N., Williams, S. C., Barnby, J. M., Hellyer, P. & Mehta, M. A. (2021). Cognitive deficits in people who have recovered from COVID-19. EClinicalMedicine, 39, 101044. https://doi.org/10.1016/j.eclinm.2021.101044

5. Miners, S., Kehoe, P. G., & Love, S. (2020). Cognitive impact of COVID-19: looking beyond the short term. Alzheimer's research & therapy, 12, 1-16. https://doi.org/10.1186/s13195-020-00744-w 
 
6. Weinerova, J., Yeung, S., Guo, P., Yau, A., Horne, C., Ghinn, M., Curtis, L., Adlard, F., Bhagat, V., Zhang, S., Kaser, M., Bozic, M., Schluppeck, D., Reid, A., Tibon, R. & Cheke, L. G. (2024). Changes in memory function in adults following SARS-CoV-2 infection: findings from the Covid and Cognition online study. In principle acceptance of Version 2 by Peer Community in Registered Reports. https://osf.io/tjs5u

7. Wild, C. J., Norton, L., Menon, D. K., Ripsman, D. A., Swartz, R. H. & Owen, A. M. (2022). Disentangling the cognitive, physical, and mental health sequelae of COVID-19. Cell Reports Medicine, 3, 100750. https://doi.org/10.1016/j.xcrm.2022.100750 
Conflict of interest:
The recommender in charge of the evaluation of the article and the reviewers declared that they have no conflict of interest (as defined in the code of conduct of PCI) with the authors or with the content of the article.

Evaluation round #1

DOI or URL of the report: https://osf.io/vz68b?view_only=228165eb161d490b945ca019143ba98c

Version of the report: 1

Author's Reply, 12 Feb 2024

Decision by ORCID_LOGO, posted 08 Dec 2023, validated 08 Dec 2023

We now have detailed reviews from 3 reviewers, who all agree that the work is timely and well designed. They have made some suggestions to improve the study and analysis plans. So I invite you to address the reviewers' comments and submit your revised manuscript, which may or may not be sent back out for review.

One reviewer advocates using only one statistical framework (i.e., either frequentist or Bayesian, but not both). I agree with the reviewer that it creates room for analytic flexibility. On the other hand, it is also encouraging when both frameworks agree on the robustness of a result. So I would recommend that you specify all the priors assumed in your Bayesian tests as the reviewer recommends, but continue to use both frameworks to report the statistical results. The other two reviews also provide some useful conceptual and design suggestions.

 

Reviewed by ORCID_LOGO, 13 Oct 2023

Reviewed by , 29 Nov 2023

Reviewed by ORCID_LOGO, 07 Dec 2023

The aims are to understand covid related cognitive impairment with the first hypothesis asking if there is a relationship between covid status and item and associative memory. The study is embedded/part of a longitudinal cohort. I think it is important to know more about this cohort and wider aims (see below on 'who' this study is about) and also consider alternative interpretations of the tasks.

The main aim of the work is good as there is a known vulnerability of associative memory to impairment relative to item memory across multiple conditions. While it is reasonable to ask if the same is the case for covid-related cognitive deficits, no reason is given as to why it is expected to be so after COVID, except that this is a common pattern of deficits. What would be the reasoning for COVID to produce cognitive deficit patterns similar to other conditions? Is there evidence of damage, or dysfunction in the relevant brain networks for example? Some more information would be very useful here.

This is an observational study of the deficits experienced by patients. In addition, the impact of vaccination status will be assessed. The authors do mention long-covid regularly and the recruitment method includes long-covid groups. There is no formal, internationally recognised definition of long-covid as far as I know, and no criteria are given in the manuscript, making recruitment based on long-covid more difficult. Clear recruitment criteria around the long-term symptoms are required. There is a risk of self-selection among those who are informed of the study towards those participants with cognitive difficulties. The current recruitment routes and methods therefore allows for different inferences compared to simply recruiting on the basis of previous infection and vaccination without selecting. I urge the authors to reflect on precisely who their research questions are about and about what they would like to make inferences (e.g. long-covid, SaRS-CoV2 infection).

Please also consider including questionnaires on other potential important factors such as depression symptoms and trait anxiety levels and consider inclusion of these as covariates for the group comparisons or correlates within the covid group. Also, in our previous study we found a big difference in cognitive impairment between those with confirmed and suspected COVID. Given other infections do exist i would urge the authors to focus their primary comparisons on the confirmed group.

I suggest for page 4 of the document our own paper is included as a reference if the authors want to cite findings from covid infection in general (Hampshire et al 2021 – already cited elsewhere). Of course, do check if relevant as I do not insist our paper is further cited, but as our largest effect size was in word finding this aligns very well with your point, but outside of a long-covid group.

For the tasks I have two queries/concerns and suggest further consideration or justification is given.

First for the verbal memory task on page 7/8, how can the researchers be sure verbal mediation strategies are not used, making the non-verbal task more like a verbal task? Also, is there a concern that those who take longer will be tested (on average) at a later time compared to those who respond faster? Could this have knock-on effects for the associative recognition task.

Second, the WCST is a very old task and problems with this have been expressed in the literature for a number of decades. Some of the problems with scoring are highlighted here: https://doi.org/10.3758/s13428-021-01551-3. 

 

Other issues are conceptual and exemplified in the Id/ed literature (e.g. Downes et al (1989). Impaired extra-dimensional shift performance in medicated and unmedicated Parkinson's disease: Evidence for a specific attentional dysfunction. Neuropsychologia,27,1329±1344.)

 

The analyses seem appropriate for the data.

User comments

No user comments yet