Bacterial isolate and resistance patterns of deep neck infections: The Manitoba experience
Bibliographic record
Abstract
Objective: The purpose of the study is to identify bacteria isolate patterns in deep neck infections managed by Oral & Maxillofacial Surgeons at a tertiary care centre in Manitoba, and analyze resistance profiles of the bacteria to specific antibiotics. Patients and Methods: A 2-year retrospective chart review on a population treated at a tertiary academic centre with deep neck infections surgically managed by the Oral & Maxillofacial Surgery service. 53 patients underwent surgical incision and drainage, received intravenous antibiotics, and had microbiological testing completed. Results: There were 25 male (47%) and 28 female (53%) patients treated by incision and drainage in an operating room setting and who had microbiological swabs obtained at the time of surgery. The submandibular space was most commonly involved (64%), followed by buccal space (34%) and lateral pharyngeal space (17%). Twenty five patients had involvement of multiple spaces. The total number of spaces involved was 90. Of the 53 patients treated, 46 grew bacterial cultures. The most commonly isolated bacteria were Streptococcus viridans, Anaerobic non-spore-forming gram positive bacilli, and Prevotella oralis. On microbiological analysis, anaerobic gram-negative rods grew in 38 cases (72%) and aerobic gram-positive cocci in 33 cases (62%). Resistance to penicillin G was highest (70%). Conclusions: Patients undergoing surgical incision and drainage by the Oral & Maxillofacial Surgery service tended towards multiple space involvement with submandibular, buccal, and lateral pharyngeal being most common. Cultures more often revealed growth of anaerobes than aerobes. Gram-negative rods and gram-positive cocci were most prevalent. Resistance was highest to the penicillin family of antibiotics, followed by clindamycin.
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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 | 0.000 | 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".