New‑onset neuropsychiatric sequelae and ‘long‑COVID’ syndrome (Review)
Bibliographic record
Abstract
The ongoing coronavirus disease 2019 (COVID-19) pandemic has had a widespread impact on individuals' mental health through indirect psychological and social mechanisms, related to factors such as fear of infection or death, social isolation, lack of social support and financial instability. The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has also been associated with the development or recurrence of neuropsychiatric symptoms, both during the acute phase, as well as during the post-acute 'long-COVID' phase. In addition to the COVID-19 survivors with a mental health history that are at a high risk of experiencing a range of neuropsychiatric symptoms following resolution of acute COVID-19, there is accumulating evidence that a diagnosis of COVID-19 may also be associated with new-onset neuropsychiatric morbidity among survivors without pre-existing mental health disorders. In particular, studies investigating the incidence of post-acute neuropsychiatric sequelae, based mostly on retrospective cohort study designs and data from national health registries, have reported the development of new-onset manifestations, including depression, anxiety, psychotic symptoms, sleep disturbances and fatigue. Nevertheless, when COVID-19 survivors were compared with SARS-CoV-2-negative controls and especially survivors of other disorders (such as influenza), the findings regarding the risk of incident neuropsychiatric manifestations varied among studies. While there is evidence of an association between SARS-CoV-2 infection and the subsequent occurrence of new-onset neuropsychiatric symptoms, especially among patients with increased disease severity, further research using methodological approaches less susceptible to confounding bias is required to establish causal relationships.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".