Effects of Pain Relief on Arterial Blood O2 Saturation
Bibliographic record
Abstract
BACKGROUND: Pain management with the use of sedatives and analgesics has several advantages and few complications or side effects. OBJECTIVES: In this study, we planned to evaluate the effects of pain control on oxygen saturation independent of other factors, such previous cardio-pulmonary conditions or respiratory rate. PATIENTS AND METHODS: Sixty-seven adult patients with direct trauma to extremities, who were referred to Imam Hossein Educational Hospital emergency room were enrolled in this study. Exclusion criteria were trauma to parts of the body other than extremities, and comorbidity with cardiovascular, pulmonary, or other disorders. Pain was evaluated using a numerical rating scale and scored between 0-10. Patients' respiratory rates (RR) were recorded by a physician and blood oxygen saturations were measured using a pulse oximeter. Then, fentanyl 1 μg/kg was administered under direct supervision of a physician. After five minutes, pain score, oxygen saturation, and RR were measured in the above-mentioned order. RESULTS: The data from 67 patients with a average age of 30 years were collected: 77% were male and 23% were female. The average pain score of these patients was 7.3 at the time of admission, which significantly decreased to 3.8 after fentanyl administration (P < 0.001). Upon arrival in emergency department the mean oxygen saturation and RR were 97.1% and 21.5/minute, respectively. After pain control, mean oxygen saturation and RR were 94.9% and 19.2 /minute, respectively, showing a significant decrease only for RR in comparison with that at the time of admission (P < 0.001). Regression analysis of pain score and O2 saturation differentiation showed no significant relation between these variables. There were no side effects or complications of fentanyl observed in these patients. CONCLUSIONS: The results of our study revealed no independent causative relationship between pain control and oxygen saturation.
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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 | 0.000 | 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) | 0.003 | 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".