Efficacy, safety, and population pharmacokinetics of a single 1500mg dose of dalbavancin for short-term therapy in patients with chronic prosthetic joint infections
Bibliographic record
Abstract
ABSTRACT The efficacy, safety, and population pharmacokinetics of a single 1,500 mg dose of dalbavancin as a sequencing treatment for Gram-positive chronic prosthetic joint infections (CPJIs) have not been described. We present an observational, retrospective study conducted in two Spanish hospitals including patients with CPJI caused by Gram-positive bacteria susceptible to dalbavancin managed with two-stage exchange, antibiotic-loaded spacers, and a single 1,500 mg dose of dalbavancin. Follow-up visits included measurement of dalbavancin plasma concentrations. Negative intraoperative cultures at second-stage surgery defined microbiological cure. Population pharmacokinetics and Monte Carlo dosing simulations were used to evaluate whether this dose provided a therapeutic antibiotic exposure defined as the ratio between the area under the unbound concentration curve and the bacteria minimum inhibitory concentration (ƒAUC 0-24h /MIC) ≥ 50 for the entire treatment period. Twenty patients were included, with CPJI mostly caused by coagulase-negative staphylococci (71%). After 11.5 days of intravenous antibiotic therapy (vancomycin, 75%), patients received 1,500 mg of dalbavancin without adverse events. Microbiological cure was 94.7% (median follow-up, 693 days). Dosing simulations suggest that a single 1,500 mg dose of dalbavancin is sufficient for maintaining ƒAUC 0-24h /MIC ≥ 50 for MIC ≤ 0.25 mg/L for 3–4 weeks after administration. A single 1,500 mg dose of dalbavancin combined with antibiotic-loaded spacers may be an effective and safe sequencing treatment for CPJI and provide 3–4 weeks of therapeutic exposure for susceptible microorganisms. Considering dalbavancin’s unique pharmacokinetics, this approach may be considered in the clinical management of CPJI.
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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 | 0.003 |
| 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 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".