Post-acute sequelae of COVID-19: Evidence of mood & cognitive impairment
Bibliographic record
Abstract
Acute health consequences associated with coronavirus disease 2019 (COVID-19) infection have been thoroughly characterized; however, long-term impacts are not yet understood. Post-acute sequelae of COVID-19 (PASC), also known as Long COVID syndrome, is the persistence of COVID-19 symptoms long after viral infection. In addition to physical symptoms, those with PASC experience changes in mental health, but few studies have empirically examined these effects. The current study investigated mood and cognitive functioning in individuals who have recovered from COVID-19 infection. We recruited 100 male and female adults (M = 30 years old) with no history of mood or cognitive impairment prior to the COVID-19 pandemic (Jan. 2020). Half of the subjects were healthy controls (i.e., no prior COVID-19 infection) and half had received a past COVID-19 diagnosis (ascertained by PCR or antibody test) but were no longer infectious. Participants completed self-reported measures of stress, depression, and anhedonia, as well as the Attention Network Test (ANT), a behavioural measure of attentional alerting, orienting and executive functioning. Relative to controls, depression and anhedonia were significantly higher in the past-COVID group. Selective impairment in attention was observed in the past-COVID group, marked by deficits in executive functioning while alerting and orienting abilities remained intact. Effects were most pronounced among individuals diagnosed 1-4 months prior to assessment. There were no group differences in pandemic-related experiences with respect to social interaction, social distancing, or isolation. The past-COVID group scored significantly higher on perceived stress; however, this did not moderate any effects observed on mood or cognition. These findings implicate a protracted reaction to the virus, possibly via prolonged inflammation, contributing to sustained mood dysregulation and cognitive impairment. Future research should examine the neural and physiological underpinnings of PASC, particularly mechanisms that promote psychiatric sequelae 1-4 months following diagnosis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".