Antibiotic Treatment for 7 versus 14 Days in Patients with Bloodstream Infections
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Bloodstream infections are associated with substantial morbidity and mortality. Early, appropriate antibiotic therapy is important, but the duration of treatment is uncertain. METHODS: . The primary outcome was death from any cause by 90 days after diagnosis of the bloodstream infection, with a noninferiority margin of 4 percentage points. RESULTS: Across 74 hospitals in seven countries, 3608 patients underwent randomization and were included in the intention-to-treat analysis; 1814 patients were assigned to 7 days of antibiotic treatment, and 1794 to 14 days. At enrollment, 55.0% of patients were in the ICU and 45.0% were on hospital wards. Infections were acquired in the community (75.4%), hospital wards (13.4%) and ICUs (11.2%). Bacteremia most commonly originated from the urinary tract (42.2%), abdomen (18.8%), lung (13.0%), vascular catheters (6.3%), and skin or soft tissue (5.2%). By 90 days, 261 patients (14.5%) receiving antibiotics for 7 days had died and 286 patients (16.1%) receiving antibiotics for 14 days had died (difference, -1.6 percentage points [95.7% confidence interval {CI}, -4.0 to 0.8]), which showed the noninferiority of the shorter treatment duration. Patients were treated for longer than the assigned duration in 23.1% of the patients in the 7-day group and in 10.7% of the patients in the 14-day group. A per-protocol analysis also showed noninferiority (difference, -2.0 percentage points [95% CI, -4.5 to 0.6]). These findings were generally consistent across secondary clinical outcomes and across prespecified subgroups defined according to patient, pathogen, and syndrome characteristics. CONCLUSIONS: Among hospitalized patients with bloodstream infection, antibiotic treatment for 7 days was noninferior to treatment for 14 days. (Funded by the Canadian Institutes of Health Research and others; BALANCE ClinicalTrials.gov number, NCT03005145.).
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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) | 0.000 | 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 it