Use of fibrin sealants for the localized, controlled release of cefazolin.
Bibliographic record
Abstract
BACKGROUND: Fibrin sealants are used increasingly in surgery to reduce bleeding and improve wound healing. They have great potential as biocompatible, biodegradable drug delivery systems, because the sealant may adhere to the target tissue and allow controlled release of the drug over an extended period. We investigated the encapsulation, stability and controlled release of erythromycin and cefazolin from Beriplast fibrin sealants (Aventis Behring Canada). METHODS: Drug-loaded clots were cast in glass vials and allowed to set. We observed the clots for drug precipitation and aggregation, and we assessed the effect of drug encapsulation on clot strength. Drug stability and release from the clots in phosphate buffered saline (PBS) was quantified by ultraviolet and visible violet absorbance spectroscopy and high-performance liquid chromatography. RESULTS: Erythromycin was found to release slowly from the fibrin clots over the first 2 hours but then degrade rapidly. Cefazolin was found to be very stable in clots in PBS (97% stable at 2 d and 93% stable at 5 d). The drug released in a controlled manner over 2 days, with most being released during the first day. The dose of drug released could be varied by changing the amount placed in the thrombin solution. Clot thickness had no effect on the rate of cefazolin release. CONCLUSION: Overall, the 2-day release profile and the excellent stability of the drug suggest that cefazolin-loaded fibrin sealants may offer an effective route of postoperative antibiotic delivery.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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) | 0.001 | 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".