Therapy of <i>Clostridium difficile</i> infection: perspectives on a changing paradigm
Bibliographic record
Abstract
INTRODUCTION: Clostridium difficile disease (CDI) have increased in frequency and severity over the past decade and are a leading cause of hospital acquired infections, contributing to increased hospital length of stay and costs, as well as associated increased mortality, especially amongst the elderly. Standard therapy has been associated with 20 - 30% relapse rates. Consequently, new CDI therapeutic approaches have emerged. AREAS COVERED: The role of metronidazole, vancomycin, fidaxomicin, rifaximin, nitizoxanide, tigecycline, fusidic acid, LFF-571, cardazolid, SMT 19969, CamSA and surotomycin were reviewed. EXPERT OPINION: New IDSA/SHEA guidelines are expected within the next year and may impact selection of primary therapy for CDI. Until then, metronidazole will likely remain as first line therapy because of low cost and despite its inferiority compared to vancomycin. Vancomycin will likely see increasing use, especially as generics become available. Fidaxomicin will emerge as an important therapy for relapse patients and perhaps as initial therapy for patients at greatest risk for relapse, with concomitant antibiotics, multiple comorbidities and renal insufficiency, advanced age and hypoalbuminemia. Biotherapeutics such as fecal microbiota transplantation and non-toxogenic C. difficile prevention will emerge as the preferred therapy in multiple relapse patients and the development of an oral formulation will occur within five years.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".