Identification of bacterial contaminants in sinus irrigation bottles from chronic rhinosinusitis patients.
Bibliographic record
Abstract
OBJECTIVE: To determine if sinus irrigation bottles from patients with chronic rhinosinusitis (CRS) harbour bacterial contaminants. DESIGN: Patients with symptoms of CRS who showed no mucopurulent infection and had no history of surgery were enrolled in the study. Patients were instructed on the proper use and cleaning of sinus irrigation bottles and were asked to return their rinse bottle during follow-up visits. METHODS: Bacterial contaminants were cultured from the inner surface of the sinus irrigation bottles obtained from patients. Genomic deoxyribonucleic acid (DNA) was isolated from purified colonies and used to polymerase chain reaction (PCR) amplify the 16S ribosomal ribonucleic acid (rRNA) genes. PCR products were sequenced and analyzed in the Human Oral Microbiome Database (HOMD) for genus and species identification based on 16S ribosomal DNA (rDNA) sequence comparisons. MAIN OUTCOME MEASURES: The outcomes included the recovery of bacterial contaminants and their subsequent identification. RESULTS: In total, 142 bacterial isolates were cultured and identified. The organisms included known oral flora bacteria, as well as pathogens of the upper respiratory tract and sinuses. Thirty-two different bacterial species were identified from 11 patients. There was no correlation between the length of bottle use and the degree of contamination. CONCLUSION: This study highlights the risk of bacterial contamination of sinus irrigation bottles and the potential for patient reinoculation.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".