Effects of a Protocol for the Preparation of Oxygen-Moisturizing Chambers on the Count of Its Bacteria Colony
Bibliographic record
Abstract
This study aims to evaluate the effect of the protocol for the preparation of oxygen-moisturizing chamber on the count of its bacteria. This study is a double- group clinical trial before and after intervention, which was carried out in the neurology ward of an educational hospital in Esfahan from July to December 2015. In this study, 64 oxygen humidifying chambers were studied in terms of number and type of microorganisms in two groups of 32 during three phases, before, immediately after, and 6 hours after its intervention. In order to identify the microorganisms, the samples were cultured on the blood agar and EMB (Eosin Methylene Blue). Then, the routine laboratory methods were used to identify the types of microorganisms. Data were analyzed using SPSS 18, Wilcoxon, Mann-Whitney, chi-square and Friedman statistical tests. The results showed that before intervention, 71.9% (46/64) of oxygen-moisturizing chambers were contaminated with microorganisms. The extent of microbial contamination was from 0 to 105 CFU. Most of the contamination was with microorganisms such as Lactobacillus spp 23.4% (15/64), Bacillus sp17.2% (11/64), Pseudomonas aeruginosa 10.9% (7/64), Coagulase-negative staphylococci 7.8% (5/64), Acinetobacter baumannii 3.1% (2/64), Sphingomonas spp 3.1%(2/64), Escherichia coli 1.6% (1/64), Streptococcus spp 3.1% (2/64), Fungus spp 3.1% (2/64). However, immediately after the intervention and 6 hours after connecting oxygen-moisturizing chamber to the patient, the infection rate was substantially reduced and reached zero (p<0/001). With regard to the fact that the contamination of oxygen-moisturizing chamber was significantly reduced after the implementation of care protocol, the implementation of this Protocol can be one of the effective measures in reducing the transmission of nosocomial infections.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".