The Efficacy and Safety of Tigecycline for the Treatment of Complicated Intra‐Abdominal Infections: Analysis of Pooled Clinical Trial Data
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This pooled analysis includes 2 phase 3, double-blind trials designed to evaluate the safety and efficacy of tigecycline, versus that of imipenem-cilastatin, in 1642 adults with complicated intra-abdominal infections. Patients were randomized to receive either tigecycline (initial dose of 100 mg, followed by 50 mg intravenously every 12 h) or imipenem-cilastatin (500/500 mg intravenously every 6 h) for 5-14 days. The primary end point was the clinical response at the test-of-cure visit (12-42 days after therapy) in the co-primary end point microbiologically evaluable and microbiological modified intent-to-treat populations. For the microbiologically evaluable group, clinical cure rates were 86.1% (441/512) for tigecycline, versus 86.2% (442/513) for imipenem-cilastatin (95% confidence interval for the difference, -4.5% to 4.4%; P < .0001 for noninferiority). Clinical cure rates in the microbiological modified intent-to-treat population were 80.2% (506/631) for tigecycline, versus 81.5% (514/631) for imipenem-cilastatin (95% confidence interval for the difference, -5.8% to 3.2%; P < .0001 for noninferiority). Nausea (24.4% tigecycline, 19.0% imipenem-cilastatin [P = .01]), vomiting (19.2% tigecycline, 14.3% imipenem-cilastatin [P = .008]), and diarrhea (13.8% tigecycline, 13.2% imipenem-cilastatin [P = .719]) were the most frequently reported adverse events. This pooled analysis demonstrates that tigecycline was efficacious and well tolerated in the treatment of patients with complicated intra-abdominal infections.
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.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 it