Ralstonia mannitolilytica in cystic fibrosis: A new predictor of worse outcomes
Bibliographic record
Abstract
BACKGROUND: Patients with Cystic Fibrosis are subject to repeated respiratory tract infections, with recent increasing isolation of unusual pathogens. Ralstonia species have lately been isolated at our institution, an organism historically frequently misidentified as Burkholderia or Pseudomonas. The prevalence of Ralstonia spp. in cystic fibrosis populations has yet to be determined, along with its clinical implications. CASE PRESENTATIONS: Seven patients out of the 301 followed at our cystic fibrosis clinic have had Ralstonia strains identified in their respiratory tract. Most strains identified were multi-drug resistant. After aquisition of Ralstonia spp., the patients' clinical course was characterized by more frequent and more severe respiratory infections along with prolonged hospitalizations, greater decline of lung function, and greater mortality. The mortality rate in this group of patients was 86%. No other factor that could explain such a dramatic evolution was identified upon review of patient data. Some of the strains involved were recognized as clones on Pulse Field Electrophoresis Gel, raising the question of person-to-person transmission. CONCLUSION: New pathogens are identified with the evolution of the microbiota in cystic fibrosis respiratory tracts. In our cohort of patients, acquisition of Ralstonia spp. was associated with dramatic outcomes in terms of disease acceleration and raised mortality rates. It is of critical importance to continue to better define the prevalence and clinical impact of Ralstonia in cystic fibrosis populations.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".