Longer-Duration Antimicrobial Therapy Does Not Prevent Treatment Failure in High-Risk Patients with Complicated Intra-Abdominal Infections
Bibliographic record
Abstract
Background: Recent studies have suggested the length of treatment of intra-abdominal infections (IAIs) can be shortened without detrimental effects on patient outcomes. However, data from high-risk patient populations are lacking. We hypothesized that patients at high risk for treatment failure will benefit from a longer course of antimicrobial therapy. Methods: Patients enrolled in the Study to Optimize Peritoneal Infection Therapy (STOP-IT) trial were evaluated retrospectively to identify risk factors associated with treatment failure, which was defined as the composite outcome of recurrent IAI, surgical site infection, or death. Variables were considered risk factors if there was a positive statistical association with treatment failure. Patients were then stratified according to the presence and number of these risk factors. Univariable analyses were performed using the Kruskal-Wallis, χ2, and Fisher exact tests. Logistic regression controlling for risk factors and original randomization group, either a fixed four-day antimicrobial regimen (experimental) or a longer course based on clinical response (control), also was performed. Results: We identified corticosteroid use, Acute Physiology and Chronic Health Evaluation II score ≥5, hospital-acquired infection, or a colonic source of IAI as risk factors associated with treatment failure. Of the 517 patients enrolled, 263 (50.9%) had one or two risk factors and 16 (3.1%) had three or four risk factors. The rate of treatment failure rose as the number of risk factors increased. When controlling for randomization group, the presence and number of risk factors were independently associated with treatment failure, but the duration of antimicrobial therapy was not. Conclusions: We were able to identify patients at high risk for treatment failure in the STOP-IT trial. Such patients did not benefit from a longer course of antibiotic administration. Further study is needed to determine the optimum duration of antimicrobial therapy in high-risk patients.
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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 | 0.001 | 0.006 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".