2435. The Impact of Treatment Strategy and Toxin Status on Outcomes of Patients with Clostridioides difficile Infections
Bibliographic record
Abstract
Abstract Background Clostridioides difficile infection (CDI) is an important cause of morbidity and mortality and management continues to evolve. For laboratories that diagnose by detection of toxin gene, it is unclear whether reporting toxin production is additive to patient care. Furthermore, is there still a role for metronidazole (MNZ) given treatment guidelines now recommend vancomycin (VAN) as first-line therapy for non-severe cases? We analyzed cases of CDI in our hospital to assess outcomes of patients on MNZ vs. VAN and with or without toxin production. Methods A retrospective chart review of inpatients with CDI (based on detection of C. difficile toxin gene by PCR) was conducted between November 2017 and August 2018. Comparison of demographics and outcomes was performed in a) cases that were toxin-positive by enzyme immunoassay vs. negative and b) non-severe cases initially managed with MNZ vs. VAN. Results 76 patients were included (46 toxin-positive, 30 toxin-negative). Toxin-positive patients were older (mean age 77 vs. 62, p = 0.002) but had similar disease severity and initial treatment. A CDI recurrence occurred in 22% vs 0% in the toxin-positive cases (p = 0.006). Any CDI-related complication occurred in 23% of toxin-negative and 35% of toxin-positive cases (ns). After adjusting for toxin-status, age, and severity, the odds ratio of the composite outcome of any complication with toxin-positive CDI was not significant (OR 1.45 95% CI 0.45 -4.6, p = 0.52). There were 37 (49%) patients with non-severe CDI (27 MNZ, 10 VAN). Patients treated with VAN had higher stooling/day (6.3 vs 4.4, p = 0.04) and heart rate (p = 0.02). Initial MNZ use was associated with treatment escalation in 48% of cases compared with 10% in those treated with VAN alone (p = 0.03). CDI-associated mortality was higher in the VAN group (2/10 vs 0/27, p = 0.017). The rate of other complications was not significantly different. Conclusion Although no difference in the composite outcome of any CDI-related complication was detected between toxin positive vs negative patients, toxin-positivity may predict patients at risk for subsequent recurrence. Patients with non-severe CDI did not have increased risk of complications when managed with MNZ; however, they were more likely to require treatment escalation. Disclosures All authors: No reported disclosures.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".