Outcomes and Costs of Patients Admitted to the Intensive Care Unit Due to Accidental or Intentional Poisoning
Bibliographic record
Abstract
Introduction: Acute poisoning represents a major cause of morbidity and mortality, and many of these patients are admitted to the intensive care unit (ICU). However, little is known regarding ICU costs of acute poisoning. Methods: This was a retrospective matched database analysis of patients admitted to the ICU with acute poisoning from 2011 to 2014. It was performed in 2 ICUs within a single tertiary care hospital system. All patient information, outcomes, and costs were stored in the hospital data warehouse. Control patients were defined as randomly selected age-, sex-, severity index-, and comorbidity index-matched nonpoisoned ICU patients (1:4 matching ratio). Results: A total of 8452 critically ill patients were admitted during the study period, of whom 277 had a diagnosis of acute poisoning. The mean age was 44.5 years, and the most common xenobiotics implicated were sedative hypnotics (20.2%), antidepressants (15.2%), and opioids (10.5%). Of these, 73.6% of poisonings were deemed intentional. In-hospital mortality of poisoned patients was 5.1%, compared to 11.1% for control patients ( P < .01). The median ICU length of stay (LOS) for poisoned patients was 3.0 days, compared with 4.0 days for control patients ( P < .01). The mean total cost for poisoned patients was CAD$18 958. Control patients had a significantly higher mean total cost of CAD$60 628 ( P < .01). The xenobiotics associated with the highest costs were acetaminophen (CAD$18 585), toxic alcohols (CAD$16 771), and opioids (CAD$12 967). Conclusions: In our cohort, we confirmed the long-held belief that patients admitted to the ICU with a primary diagnosis of poisoning have a lower mortality rate, ICU LOS, and overall cost per ICU admission than nonpoisoned patients. However, poisoned patients still accrue significant daily costs, with the highest costs attributed to xenobiotics with known antidotes, such as acetaminophen, toxic alcohols, and opioids.
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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 | 0.018 |
| 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 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".