Epidemiological and clinical perspectives of long COVID syndrome
Bibliographic record
Abstract
Long COVID, or post-acute COVID-19 syndrome, is characterized by multi-organ symptoms lasting 2+ months after initial COVID-19 virus infection. This review presents the current state of evidence for long COVID syndrome, including the global public health context, incidence, prevalence, cardiopulmonary sequelae, physical and mental symptoms, recovery time, prognosis, risk factors, rehospitalization rates, and the impact of vaccination on long COVID outcomes. Results are presented by clinically relevant subgroups. Overall, 10-35% of COVID survivors develop long COVID, with common symptoms including fatigue, dyspnea, chest pain, cough, depression, anxiety, post-traumatic stress disorder, memory loss, and difficulty concentrating. Delineating these issues will be crucial to inform appropriate post-pandemic health policy and protect the health of COVID-19 survivors, including potentially vulnerable or underrepresented groups. Directed to policymakers, health practitioners, and the general public, we provide recommendations and suggest avenues for future research with the larger goal of reducing harms associated with long COVID syndrome.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".