Epidemiological and Clinical Characterization of Superinfections in Critically Ill Coronavirus Disease 2019 Patients
Bibliographic record
Abstract
OBJECTIVES: To describe the epidemiology of superinfections (occurring > 48 hr after hospital admission) and their impact on the ICU and 28-day mortality in patients with coronavirus disease 2019 with acute respiratory distress syndrome, requiring mechanical ventilation. DESIGN: Retrospective analysis of prospectively collected observational data. SETTING: University-affiliated adult ICU. PATIENTS: Ninety-two coronavirus disease 2019 patients admitted to the ICU from February 21, 2020, to May 6, 2020. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The prevalence of superinfection at ICU admission was 21.7%, and 53 patients (57.6%) had at least one superinfection during ICU stay, with a total of 75 (82%) ventilator-associated pneumonia and 57 (62%) systemic infections. The most common pathogens responsible for ventilator-associated pneumonia were Pseudomonas aeruginosa (n = 26, 34.7%) and Stenotrophomonas maltophilia (n = 14, 18.7%). Bloodstream infection occurred in 16 cases, including methicillin-resistant Staphylococcus epidermidis (n = 8, 14.0%), Enterococcus species (n = 6, 10.5%), and Streptococcus species (n = 2, 3.5%). Fungal infections occurred in 41 cases, including 36 probable (30 by Candida albicans, six by C. nonalbicans) and five proven invasive candidiasis (three C. albicans, two C. nonalbicans). Presence of bacterial infections (odds ratio, 10.53; 95% CI, 2.31–63.42; p = 0.005), age (odds ratio, 1.17; 95% CI, 1.07–1.31; p = 0.001), and the highest Sequential Organ Failure Assessment score (odds ratio, 1.27; 95% CI, 1.06–1.63; p = 0.032) were independently associated with ICU or 28-day mortality. CONCLUSIONS: Prevalence of superinfections in coronavirus disease 2019 patients requiring mechanical ventilation was high in this series, and bacterial superinfections were independently associated with ICU or 28-day mortality (whichever comes first).
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".