Opioid-associated iatrogenic withdrawal in critically ill adult patients: a multicenter prospective observational study
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Opioids and benzodiazepines are frequently used in the intensive care unit (ICU). Regular use and prolonged exposure to opioids in ICU patients followed by abrupt tapering or cessation may lead to iatrogenic withdrawal syndrome (IWS). IWS is well described in pediatrics, but no prospective study has evaluated this syndrome in adult ICU patients. The objective of this study was to determine the incidence of IWS caused by opioids in a critically ill adult population. This multicenter prospective cohort study was conducted at two level-1 trauma ICUs between February 2015 and September 2015 and included 54 critically ill patients. Participants were eligible if they were 18 years and older, mechanically ventilated and had received more than 72 h of regular intermittent or continuous intravenous infusion of opioids. For each enrolled patient and per each opioid weaning episode, presence of IWS was assessed by a qualified ICU physician or senior resident according to the 5th edition of Diagnostic and Statistical Manual of Mental Disorders criteria for opioid withdrawal. RESULTS: The population consisted mostly of males (74.1%) with a median age of 50 years (25th-75th percentile 38.2-64.5). The median ICU admission APACHE II score was 22 (25th-75th percentile 12.0-28.2). The overall incidence of IWS was 16.7% (95% CI 6-27). The median cumulative opioid dose prior to weaning was higher in patients with IWS (245.7 vs. 169.4 mcg/kg, fentanyl equivalent). Patients with IWS were also exposed to opioids for a longer period of time as compared to patients without IWS (median 151 vs. 125 h). However, these results were not statistically significant. CONCLUSIONS: IWS was occasionally observed in this very specific population of mechanically ventilated, critically ill ICU patients. Further studies are needed to confirm these preliminary results and identify risk factors.
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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 | 0.337 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it