Persistence of live virus in critically ill patients infected with SARS-COV-2: a prospective observational study
Bibliographic record
Abstract
BACKGROUND: Research on the duration of infectivity of ICU patients with COVID-19 has been sparse. Tests based on Reverse Transcriptase polymerase chain reaction (RT-PCR) detect both live virus and non-infectious viral RNA. We aimed to determine the duration of infectiousness based on viral culture of nasopharyngeal samples of patients with COVID-19. METHODS: Prospective observational study in adult intensive care units with a diagnosis of COVID-19 Pneumonia. Patients had repeated nasopharyngeal sampling performed after day 10 of ICU admission. Culture positive rate (based on viral culture on Vero cells in a level 4 lab) and Cycle threshold from RT-PCR were measured. RESULTS: Nine patients of the 108 samples (8.3%, 95% CI 3.9-15.2%) grew live virus at a median of 13 days (interquartile range 11-19) after their initial positive test. 74.1% of patients were RT-PCR positive but culture negative, and the remaining (17.6%) were RT-PCR and culture negative. Cycle threshold showed excellent ability to predict the presence of live virus, with a Ct < 25 with an AUC of 0.90 (95% CI 0.83-0.97, p < 0.001). The specificity of a Ct > 25 to predict negative viral culture was 100% (95% CI 70-100%). CONCLUSION: 8.3% of our ICU patients with COVID-19 grew live virus at a median of 13 days post-initial positive RT-PCR test. Severity of illness, use of mechanical ventilation, and time between tests did not predict the presence of live virus. Cycle threshold of > 25 had the best ability to determine the lack of live virus in these patents.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".