Hospital-acquired antibiotic-resistant organisms among patients with COVID-19
Bibliographic record
Abstract
Background: We sought to use existing in-patient surveillance data to investigate the risk of hospital-acquired antimicrobial-resistant organisms (ARO) among patients with COVID-19 infection. Methods: Prospective case capture was done for patients admitted with COVID-19, as well as those admitted with ARO and Clostridioides difficile infections (CDI). Odds ratios (OR) were used to measure the strength of association between COVID-19 infection and the risk of acquiring hospital-acquired ARO and CDI. Results: The odds of acquiring ARO/CDI were statistically higher among patients with hospital-acquired and community-acquired COVID-19 infections (OR=2.68 and 1.79 respectively) compared to persons without COVID-19 (OR=0.53). Conclusions: Our results show an association between COVID-19 infection and the acquisition of ARO/CDI in the in-patient setting. This finding suggests that prolonged hospitalization may expose patients to hospital-acquired infections, and this may have relevance in the management of patients requiring hospitalization for extended periods of time.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".