The Effect of Rubber Dam Placement on the Arterial Oxygen Saturation in Dental Patients
Bibliographic record
Abstract
This study assessed the effect of rubber dam placement on arterial blood oxygen saturation in dental patients; it also determined whether the effects are technique sensitive. The study group consisted of 28 ASA Class I patients who were randomly allocated to one of two groups: Group A--rubber dam isolation of the maxilla (from tooth #14 to #6) and Group B-rubber dam isolation of the mandible (from tooth #19 to #27). A pulse oximeter was used to detect arterial blood oxygen saturation in both groups. Each patient's oxygen saturation (Sp02) was recorded every 30 seconds for two minutes to establish a baseline. Group A subjects received local infiltration in the vestibule above tooth #14, while Group B subjects received an inferior alveolar nerve block using 1.8 ml of 2% Lidocaine with 1:100,000 epiphrine, respectively. During the subsequent five minutes, the patient's Sp02 was recorded every 30 seconds. A rubber dam was then placed, which extended to the anterior septal angle (which completely covers the nose). This rubber dam remained in place for 20 minutes, with the patient's Sp02 being recorded every 30 seconds. The rubber dam was then altered (cut) to expose the nasal passages, creating what is known as proper rubber dam isolation, and the Sp02 was recorded every 30 seconds for 20 minutes. In both groups, there was no significant change in arterial oxygen saturation before or after rubber dam isolation was performed. Also, there was no significant difference in Sp02 when comparing the rubber dam isolation technique. Although rubber dam placement has no effect on blood oxygen levels in healthy patients, its effects on unhealthy patients are unknown.
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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 | 0.001 | 0.003 |
| 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) | 0.001 | 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".