Symptoms, physical measures and cognitive tests after SARS-CoV-2 infection in a large population-based case-control study
Bibliographic record
Abstract
Abstract Persistent symptoms are common after SARS-CoV-2 infection but the correlation with objective measures is unclear. We utilized the deCODE Health Study to compare multiple symptoms and physical measures between 1,721 Icelanders with prior SARS-CoV-2 infection (cases) and 546 contemporary and 13,842 historical controls. Cases participated in the study five to 17 months after the acute infection. One percent reported still suffering severe symptoms more than a year after the infection. 46 of the 88 symptoms explored associated with prior infection, most significantly disturbed smell and taste, memory disturbance, and dyspnea. On the contrary, only a handful of objective measures associated with prior infection. Cases were more likely to have measured impairment in smell and taste, lower grip strength, and poorer immediate and delayed memory recall than controls. No other objective measure associated with prior infection including heart rate, blood pressure, postural orthostatic tachycardia, oxygen saturation, exercise tolerance, hearing, and traditional inflammatory, cardiac, liver and kidney blood biomarkers. There was no evidence of more anxiety or depression among cases. We estimated the prevalence of long Covid to be 7–8%. Thus, in our large case-control study of mostly non-hospitalized Icelanders, diverse symptoms were common after SARS-CoV-2 infection while objective differences between cases and controls were few and, except for smell and taste, small. Discrepancies between symptoms and objective measures suggest a more complicated biological or biopsychosocial contribution to symptoms related to prior infection than is captured by conventional tests. Traditional clinical assessment would thus not be expected to be particularly informative in relating symptoms to a past SARS-CoV-2 infection.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".