The role of leech water sampling in choice of prophylactic antibiotics in medical leech therapy
Bibliographic record
Abstract
Medical leech therapy (MLT) with Hirudo medicinalis is well established as a treatment for venous congestion of tissue flaps, grafts, and replants. Unfortunately, this treatment is associated with surgical site infections with bacterial species, most commonly Aeromonas hydrophila, which is an obligate symbiot of H. medicinalis. For this reason, prophylactic antibiotics are recommended in the setting of MLT. After culturing Aeromonashydrophila resistant to ciprofloxacin from a tissue specimen from a patient with a failed replant of three digits post-MLT, we performed environmental surveillance cultures and antibiotic susceptibility testing on water collected from leech tanks. This surveillance was performed twice weekly for 2.5 months. Fourteen surveillance cultures demonstrated 21 isolates of Aeromonas species, 71.4% of which were ciprofloxacin susceptible. All isolates were sulfamethoxazole-trimethoprim (SXT) susceptible. The prophylactic antibiotic regimen of choice for leech therapy at our institution is SXT, with culture of tank water to refine antimicrobial choice if necessary. This study demonstrates the importance of regular surveillance to detect resistant Aeromonas species in medical leeches; however optimal practice has not been established.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".