The effect of patient‐controlled analgesia on coadministered red blood cells
Bibliographic record
Abstract
BACKGROUND: Patient-controlled analgesia (PCA) provides effective pain control. The possibility of administrating opioids in the same line as red blood cells (RBCs) for patients with poor venous access has been entertained. The literature on this approach is not extensive, but generally cautionary. STUDY DESIGN AND METHODS: Standard concentrations of morphine, hydromorphone (Dilaudid), and meperidine (Demerol) were used to determine the effect on RBCs. Three in vitro approaches were used: 1) continuous low-dose opioid infusion with a single bolus, 2) continuous infusion with multiple boluses, and 3) assessment of RBCs with different concentrations of opioids in test tubes. Samples were assayed for hemoglobin (Hb), mean corpuscular volume (MCV), plasma Hb, potassium, and lactate dehydrogenase, and a peripheral blood smear was made. RESULTS: Addition of each drug as a single or multiple bolus(-es) with continuous infusion showed the same effects as normal saline. In vitro exposure of Demerol at a 1:2 ratio (drug:blood) increased the MCV (110 fL), at 1:1 the MCV was 120 fL, and there was 4.5 percent hemolysis. At 2:1, hemolysis increased to 9.2 percent. Both morphine and Dilaudid had similar effects as normal saline. CONCLUSION: Morphine, Dilaudid, and Demerol, given as a bolus in the intravenous line, have the same effects as those seen with saline. When mixed directly with the blood for more than 1 hour, however, Demerol caused increasing RBC swelling and at high, nontherapeutic concentrations, caused hemolysis. Our study suggests that analgesia delivered via PCA may be safely coadministered with RBCs. Further clinical study is warranted.
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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 | 0.001 |
| 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".