Quantification Analysis of the Intraoperative Bacterial Contamination Rate and Level in Osteochondral Autografts
Bibliographic record
Abstract
BACKGROUND: Inadvertent contamination of osteochondral (OC) autografts during harvesting and preparation can lead to significant complications and can cause the operating team to weigh the infection risk after reimplantation against discarding the OC fragment. The most commonly reported contamination mechanism is the accidental dropping of an OC fragment; however, associated contamination levels remain unclear. The rate and level of contamination during standard harvesting and preparation are also unknown. PURPOSE: To quantitatively evaluate the rate and level of bacterial contamination of OC autografts during harvesting and preparation compared with those of accidently dropped autografts. STUDY DESIGN: Controlled laboratory study. METHODS: Under sterile conditions, 138 fresh OC specimens were harvested and retrieved from 23 primary total knee arthroplasties (TKAs). Six OC fragments were retrieved from each TKA: 3 were used as controls, and 3 were dropped onto the operating room floor. Each specimen was incubated to allow for aerobic and anaerobic growth, and the number of colony-forming units (CFUs) per gram was calculated. RESULTS: Contamination rates (positive cultures) for the control and dropped groups were 29% (n = 20/69) and 42% (n = 29/69), respectively. The difference in the contamination rate between groups was not statistically significant (P = .109). The most common organisms identified were Staphylococcus aureus (40%) in the control group and Staphylococcus epidermidis (24.1%) and Bacillus species (20.7%) in the dropped group. The contamination level (CFUs/g) for both groups was low. The median (range) CFUs/g among the contaminated specimens in the dropped and control groups were 27 (1-120) and 3 (1-15), respectively (P < .0001). CONCLUSION: A relatively high rate of OC autograft contamination can be expected during harvesting and preparation (29%) or after accidentally dropping a specimen (42%). Although the types of organisms isolated differed between specimens contaminated during harvesting and preparation and dropped specimens, the quantification of the autograft contamination level revealed a very low CFUs/g in both cases. CLINICAL RELEVANCE: The intraoperative autograft contamination level is very low. Hence, in cases of grafts with a known contamination incident, saving and reimplanting them after proper decontamination is recommended over discarding them or using an allograft.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".