Comparison of Use of Fentanyl, Hydromorphone, and Morphine Infusions in Critically Ill Patients With Acute Respiratory Failure
Bibliographic record
Abstract
Limited evidence suggests that the choice of opioid may influence the intensity of opioid exposure for patients receiving invasive mechanical ventilation (IMV). Is the choice of opioid associated with overall opioid exposure or short-term outcomes? This was a retrospective cohort study of patients receiving IMV in 21 ICUs who received an initial opioid infusion (> 6 hours) of fentanyl, hydromorphone, or morphine. The primary outcome was mean hourly opioid dose (morphine milligram equivalents [MMEs]) of all opioids, including boluses, after the initiation of an opioid infusion until death, transition to comfort measures, or discharge from the ICU. Secondary outcomes included ICU and hospital mortality. All comparisons were with fentanyl using generalized estimating equation models to account for clustering of patients within ICUs. Among 8,262 patients receiving IMV, the mean (SD) age was 53.9 (17.0) years and 38.0% were female. Overall, 6,913 patients (83.7%) received fentanyl, 1,148 patients (13.9%) received hydromorphone, and 201 patients (2.4%) received morphine. Patients treated initially with hydromorphone were started on a higher dose (median, 10.0 MME [interquartile range (IQR), 5.0-10.0 MME] vs 3.3 MME [IQR, 1.7-6.7 MME] for fentanyl and 5.0 MME [IQR, 3.0-5.0 MME] for morphine). The median hourly MMEs of opioids during the ICU stay was highest for patients who received hydromorphone (median, 3.3 MME [IQR, 1.6-6.3 MME] vs 1.7 MME [IQR, 0.8-3.4 MME] for fentanyl and 3.0 MME [IQR, 1.4-4.8 MME] for morphine). These differences remained for hydromorphone vs fentanyl after adjustment for patient characteristics, but not after accounting for clustering within ICUs (adjusted rate ratio for hydromorphone vs fentanyl: 1.14 MME [IQR, 0.93-1.41 MME]; and for morphine vs fentanyl: 0.98 MME [IQR, 0.75-1.27 MME]). All other measures of opioid exposure were similarly highest for hydromorphone, but were not different after adjustment. No differences in short-term outcomes were noted. Among patients receiving IMV, use of hydromorphone infusions was associated with a greater overall opioid exposure, which was not accounted for by patient characteristics; accounting for clustering of patients within ICUs attenuated the differences.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".