Cost Averted With Timely Fecal Microbiota Transplantation in the Management of Recurrent Clostridium difficile Infection in Alberta, Canada
Bibliographic record
Abstract
BACKGROUND: Fecal microbiota transplantation (FMT) is highly effective in treating recurrent Clostridium difficile infection (RCDI). However, the ideal timing for offering FMT remains to be determined. Furthermore, the direct medical costs averted with timely FMT have not been examined. METHODS: A retrospective review of the Edmonton FMT program database included patients who received FMT for RCDI (October 2012 to September 2014). They were divided into 2 groups: those who received FMT after 2 recurrences (the timely FMT group) and those who received FMT after at least 3 recurrences (the delayed FMT group). The primary outcome was the difference in direct medical costs related to hospital admissions and emergency room visits due to CDI between the 2 groups. The secondary outcomes were RCDI cure rate and duration of RCDI in each group. RESULTS: A total of 75 patients were included: 30 received timely FMT, whereas 45 received delayed FMT. The mean difference in hospital length of stay and emergency room visits related to CDI were 13.8 days shorter and 1.3 visits fewer with timely FMT, associated with a mean cost saving of $29,842 per patient. Sensitivity analysis was performed to examine the effect of outliers and comorbities on the differential costs, and it was found that the differences in average cost per patient were more pronounced in those with Charlson comorbidity index ≥3 compared with those with scores of 0 to 2. The cure rate was 94% (timely FMT group) and 93% (delayed FMT group). The mean duration of RCDI was 109 days (timely FMT group) and 281 days (delayed FMT group). CONCLUSIONS: Timely FMT can provide significant cost savings to health-care systems, especially for patients with multiple comorbidities.
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 | 0.001 | 0.003 |
| 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 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".