A rare case of catatonia associated with COVID-19 infection
Bibliographic record
Abstract
COVID-19, caused by the SARS-CoV-2 virus, has well-documented common symptoms such as cough and fever. There is also extensive documentation on the more severe outcomes, such as sepsis and death. However, there is minimal literature regarding the neuropsychiatric effects of COVID-19. This case report outlines a patient who presented with apparent psychosis shortly after COVID-19 infection. Shortly after hospitalization, she began to develop symptoms of catatonia. Her catatonia subsequently was recognized and resolved with appropriate treatment with lorazepam. There have been a handful of similar reports regarding patients with COVID-19 developing catatonia and responding well to lorazepam. Therefore, catatonia may be associated with COVID-19. Clinicians should consider catatonia diagnosis in patients with COVID-19 who have changes in behaviour, mental status, or motor function, to prevent deterioration secondary to untreated catatonia. Furthermore, COVID-19 testing should be considered in patients with acute psychiatric presentations.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".