Prevalence and Predictors of Bacterial Contamination in Excisional Lymph Node Biopsies
Bibliographic record
Abstract
Routine tissue handling exposes lymph node specimens to microbial contamination that can confound microbiological culture results and interfere with diagnosis. The scope and impact of this problem remain poorly understood. We combined over 13 years of lymph node pathology, culture data, and patient records to define the prevalence, predisposing factors, microbiology, and clinical management of false-positive lymph node cultures at a large academic medical center. Nearly one third (31.9%) of 216 cultured lymph nodes yielded bacterial growth. Approximately 90% of positive bacterial cultures grew 1 of 2 common skin-resident taxa-coagulase-negative Staphylococcus and Cutibacterium acnes-with well-documented predispositions for contamination in other clinical settings. Lymph nodes excised from axillary, cervical, and inguinal regions yielded higher positive culture rates than nodes excised from the mediastinum, suggesting proximity to the skin surface may increase contamination risk. Accordingly, cultures from thoracoscopic pulmonary resections displayed contamination rates over 5-fold lower than those from percutaneously accessed lymph nodes. Lymph nodal tissue allocated for culture in the operating room yielded unexpectedly high contamination rates, significantly higher than cultures sent from the frozen section processing area. A significant minority of contamination events were noted in the clinical record and prompted antibiotic therapy on multiple occasions. Collectively, our results illuminate the risk factors contributing to bacterial contamination and argue that routine lymph node bacterial cultures provide minimal clinical benefit for adult patients. This widespread bacterial contamination also warrants cautious implementation of increasingly sensitive molecular microbiology tools for excised tissues.
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How this classification was reachedexpand
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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".