Early administration of remdesivir to COVID-19 patients associates with higher recovery rate and lower need for ICU admission: A retrospective cohort study
Bibliographic record
Abstract
OBJECTIVES: Remdesivir is one of the most widely recommended and used medications for COVID-19 treatment. However, different outcomes have been reported for hospitalized patients with COVID-19 treated with remdesivir. Specifically, the effect of the timing of remdesivir initiation (from patient's symptom onset) on clinical outcomes in COVID-19 patients has not been investigated. METHODS: This is a retrospective cohort study of patients hospitalized with COVID-19 and treated with or without remdisivir. The primary outcome was patient's recovery rate, defined as clinical improvement and patient's discharge by day 14 of symptom onset. The secondary outcome was the need for intensive care unit (ICU) admission, mechanical ventilation, and mortality within 28 days of patient's symptom onset. RESULTS: Out of 323 hospitalized adults with COVID-19, 107 (33.1%) received no remdesivir during their hospital stay, 107 (33.1%) received remdesivir early within 7 days of the symptom onset, and 109 (33.7%) received it at 8 days or later of symptom onset. At day 14 following symptom onset, higher proportion of patients recovered in the early remdesivir compared to the late remdesivir cohort, or patients who did not receive remdesivir (adjusted odds ratio, aOR, 2.65; 95% confidence interval [CI], 1.31 to 5.35). Moreover, early administration of remdesivir was associated with lower admission to intensive care unit (adjusted hazard ratio [aHR], 0.31; 95% CI, 0.15 to 0.64), less need for mechanical ventilation (aHR, 0.22; 95% CI, 0.10 to 0.51), and lower mortality at 28 days (aHR, 0.15; 95% CI, 0.04 to 0.53), as compared to the late remdesivir cohort or patients who did not receive remdesivir. CONCLUSION: Early administration of remdesivir within 7 days of symptom onset is associated with less need for mechanical ventilation and lower 28-days mortality.
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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 | 0.001 | 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".