A Multicenter Study of the Point Prevalence of Drug-Induced Hypotension in the ICU
Bibliographic record
Abstract
OBJECTIVE: To determine the point prevalence of drug-induced hypotension episodes in critically ill patients, to assess the episodes resulting from error, and to describe how episodes are treated. DESIGN: Multicenter observational, 24-hour snapshot study. SETTING: Forty-seven ICUs in 27 institutions located in the United States, Canada, and Singapore. PATIENTS: A total of 688 ICU patients were evaluated. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Patients were included in the study if they had an episode of hypotension in the 24 hours prior to the clinical pharmacists' evaluation. The definition for a hypotensive episode is either a systolic blood pressure less than 90 mm Hg or a decrease in systolic blood pressure of 30 mm Hg over a 2-hour period. Each episode of unintentional hypotension was assessed for suspected drug-related causes. When a drug-related cause was suspected, an objective assessment tool, the modified Kramer, was used to determine causality. A score of at least "possible" was considered drug induced, referred to as a "drug-related hazardous condition." A drug-related hazardous condition is the temporal gap (intermediate stage) between the identification of an adverse drug reaction and the subsequent onset of drug-induced injury, known as an "adverse drug event." Drug-induced episodes were evaluated for medication errors and treatment. One hundred fifty-eight patients experienced 204 hypotensive episodes that were considered unintentional and drug related. Common drugs implicated included propofol, fentanyl, metoprolol, lorazepam, hydralazine, and furosemide. A total of 54 episodes (26.5%) resulted from medication errors. Common error types were improper dose/quantity (46%) and prescribing (25%). A total of 56.9% episodes were treated. CONCLUSIONS: Many hypotensive episodes in the ICU are drug related and require treatment. A substantial portion of these episodes result from errors and are therefore preventable. This presents opportunities to improve prescribing including optimizing drug dosing to avoid possible patient harm from drug-induced hypotension.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".