Profiles of Individuals With Long COVID Reporting Persistent Cognitive Complaints
Bibliographic record
Abstract
OBJECTIVE: A subset of COVID-19 patients continues to experience cognitive difficulties 24 months post-infection. The factors driving these symptoms are complex, and the underlying pathophysiology is unclear. This study aimed to characterize individuals with Long COVID reporting cognitive issues. METHOD: One hundred twenty-three patients underwent a comprehensive neuropsychological evaluation resulting from the baseline of an RCT study (COVCOG), along with questionnaires assessing cognitive complaints, fatigue, sleep difficulties, quality of life, psychological distress, and impact on daily activities. Latent Profile Analyses on cognitive scores were conducted to investigate the presence of different patient profiles. Robust analyses of variance and Pearson's chi-square examined the profiles' effects on demographic variables and questionnaire scores. RESULTS: Patients had had predominantly mild to moderate infections (87.8%) and were assessed an average of 20.9 (±8.6) months post-infection. Neuropsychological assessment showed cognitive impairment in at least one domain in 72% of the patients, mainly in attention and executive functions. Over 80% reported sleep problems and fatigue, 97% concentration problems, and some 80% memory and word-finding problems. The self-report questionnaires also revealed significant complaints. Three profiles emerged (all ps < .001). Profiles 1 and 2 both experienced widespread cognitive issues; Profile 1 patients expressed more complaints about cognitive functioning and daily fatigue (all ps < .045). Patients in Profile 3 were more frequently men (all ps < .049) with a specific impairment of verbal long-term memory and fewer complaints. CONCLUSIONS: The study identifies three different profiles of individuals with Long COVID, highlighting the need for comprehensive evaluations including neuropsychological, psychological, somatic, and functional aspects to implement effective, tailored interventions. Clinicaltrials.gov: NCT05167266.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".