A multicenter trial of the efficacy and safety of tigecycline versus imipenem/cilastatin in patients with complicated intra-abdominal infections [Study ID Numbers: 3074A1-301-WW; ClinicalTrials.gov Identifier: NCT00081744]
Bibliographic record
Abstract
BACKGROUND: Complicated intra-abdominal infections (cIAI) remain challenging to treat because of their polymicrobial etiology including multi-drug resistant bacteria. The efficacy and safety of tigecycline, an expanded broad-spectrum glycylcycline antibiotic, was compared with imipenem/cilastatin (IMI/CIS) in patients with cIAI. METHODS: A prospective, double-blind, multinational trial was conducted in which patients with cIAI randomly received intravenous (IV) tigecycline (100 mg initial dose, then 50 mg every 12 hours [q12h]) or IV IMI/CIS (500/500 mg q6h or adjusted for renal dysfunction) for 5 to14 days. Clinical response at the test-of-cure (TOC) visit (14-35 days after therapy) for microbiologically evaluable (ME) and microbiological modified intent-to-treat (m-mITT) populations were the co-primary efficacy endpoint populations. RESULTS: A total of 825 patients received >or= 1 dose of study drug. The primary diagnoses for the ME group were complicated appendicitis (59%), and intestinal (8.8%) and gastric/duodenal perforations (4.6%). For the ME group, clinical cure rates at TOC were 80.6% (199/247) for tigecycline versus 82.4% (210/255) for IMI/CIS (95% CI -8.4, 5.1 for non-inferiority tigecycline versus IMI/CIS). Corresponding clinical cure rates within the m-mITT population were 73.5% (227/309) for tigecycline versus 78.2% (244/312) for IMI/CIS (95% CI -11.0, 2.5). Nausea (31.0% tigecycline, 24.8% IMI/CIS [P = 0.052]), vomiting (25.7% tigecycline, 19.4% IMI/CIS [P = 0.037]), and diarrhea (21.3% tigecycline, 18.9% IMI/CIS [P = 0.435]) were the most frequently reported adverse events. CONCLUSION: This study demonstrates that tigecycline is as efficacious as imipenem/cilastatin in the treatment of patients with cIAI.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".