Clinical Outcomes Associated With Escherichia coli Infections in Adults With Cystic Fibrosis: A Cohort Study
Bibliographic record
Abstract
Abstract Background Analysis of “emerging” pathogens in cystic fibrosis (CF) lung disease has focused on unique pathogens that are rare in other human diseases or are drug resistant. Escherichia coli is recovered in the sputum of up to 25% of patients with CF, yet little is known about the epidemiology or clinical impact of infection. Methods We studied patients attending a Canadian adult CF clinic who had positive sputum cultures for E coli from 1978 to 2016. Infection was categorized as transient or persistent (≥3 positive sputum cultures, spanning >6 months). Those with persistent infection were matched 2:1 with age, sex, and time-period controls without history of E coli infection, and mixed-effects models were used to assess pulmonary exacerbation (PEx) frequency, lung function decline, hospitalization, and intravenous antibiotic days. Results Forty-five patients (12.3%) had E coli recovered from sputum samples between 1978 and 2016, and 18 patients (40%) developed persistent infection. Nine patients (24%) had PEx at incident infection, and increased bioburden was predictive of exacerbation (P = .03). Risk factors for persistent infection included lower nutritional status (P < .001) and lower lung function (P = .009), but chronic infection with Pseudomonas aeruginosa was protective. There was no difference in annual lung function decline, need for hospitalization or intravenous antibiotics, or risk of PEx in patients with persistent infection. Conclusions Persistent E coli infection was frequent and was more common in CF patients with low nutritional status and lung function. However, this does not predict clinical decline. Multicenter studies would allow better characterization of the epidemiology and clinical impact of E coli infection.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".