A systematic review of the evidence on the associations and safety of COVID-19 vaccination and post COVID-19 condition
Bibliographic record
Abstract
Post COVID-19 condition (PCC) refers to persistent or recurring symptoms (>8 weeks) occurring ≤12 weeks following acute COVID-19. The objective of this systematic review was to assess the evidence on the risk of PCC with vaccination before or after COVID-19 or after developing PCC, and the safety of vaccination among those already experiencing PCC. A search was conducted up to 13 December 2022 and standard systematic review methodology was followed. Thirty-one observational studies were included. There is moderate confidence that two doses of vaccine given pre-infection reduced the odds of PCC (pooled OR (pOR) 0.67, 95% CI 0.60-0.74, I2 = 59.9%), but low confidence that one dose may not reduce the odds (pOR 0.64, 95% CI 0.31#x2013;1.31, I2 = 99.2%), and the evidence is very uncertain about the effect of three doses (pOR 0.45, 95% CI 0.10#x2013;1.99, I2 = 30.9%). One of three studies suggested vaccination shortly after COVID-19 may offer additional protection from developing PCC compared to unvaccinated individuals, but this evidence was very uncertain. For those with PCC, vaccination was not associated with worsening PCC symptoms (10 studies) and appears safe (3 studies), but it is unclear if vaccination may change established PCC symptoms.
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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 | 0.012 | 0.061 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.012 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".