Detection and identification of oral anaerobes in intraoperative bronchial fluids of patients with pulmonary carcinoma
Bibliographic record
Abstract
Postoperative pneumonia may occur when upper respiratory tract protective reflexes such as cough and/or swallowing reflexes are impaired; thus, silent aspiration of oral bacteria may be a causative factor in postoperative pneumonia. This study aimed to quantify and identify bacteria in intraoperative bronchial fluids and to evaluate the relationship between impairment of cough/swallowing reflexes and silent aspiration of oral bacteria in elderly patients. After obtaining informed consent, cough and swallowing reflexes were assessed using an ultrasonic nebulizer and a nasal catheter, respectively. Using a micro-sampling probe, intraoperative bronchial fluids were collected from nine subjects with pulmonary carcinoma and cultured anaerobically on blood agar plates. After 7 days, CFUs were counted and isolated bacteria were identified by 16S rRNA gene sequencing. Four subjects (aged 71.0 ± 8.4 years) had impaired swallowing reflexes with normal cough reflexes, whereas five subjects (73.6 ± 6.5 years) had normal cough and swallowing reflexes. The bacterial counts (mean CFU ± SD) tended to be higher in intraoperative bronchial fluids of subjects with impaired swallowing reflexes ([5.1 ± 7.7] × 10(5)) than in those of subjects with normal reflexes ([1.2 ± 1.9] × 10(5)); however, this difference was not statistically significant. Predominant isolates from intraoperative bronchial fluids were Streptococcus (41.8%), Veillonella (11.4%), Gemella (8.9%), Porphyromonas (7.6%), Olsenella (6.3%) and Eikenella (6.3%). These findings indicate that intraoperative bronchial fluids contain bacteria, probably derived from the oral microbiota, and suggest that silent aspiration of oral bacteria occurs in elderly patients irrespective of impairment of swallowing reflex.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".