Death in two Canadian intensive care units: Institutional difference and changes over time
Bibliographic record
Abstract
OBJECTIVE: To study and compare the mode of death in two different institutions' intensive care units (ICUs) for the two time periods, 1988 and 1993. DESIGN: Retrospective chart review. SETTING: Medical/surgical/trauma ICUs in two tertiary care teaching hospitals. PATIENTS: Patients dying in the medical/surgical/trauma ICUs between January 1, 1988 and December 31, 1988; and January 1, 1993 and December 31, 1993. Data collection included demographics, origin of admission, date of ICU admission, date of death, Acute Physiology and Chronic Health Evaluation (APACHE) III diagnostic categories, APACHE II physiologic variables, organ system failures present at the time of admission and 24 hrs before death, and mode of dying. APACHE II scores and mortality risk were calculated. Data analysis included a multiple analysis of variance to assess overall effect, with subsequent analyses of variance to assess the effect of institution and year on each individual dependent variable. All results are reported as mean +/- SEM values. RESULTS: A total of 439 charts were reviewed. Gender, age, and origin of admission were not different between the 2 yrs or the two institutions. Mean APACHE II scores and organ system failures were lower at Hospital A in 1998 vs. Hospital B, as was predicted mortality. These factors increased at Hospital A in 1993 and were similar to those at Hospital B. Withdrawal of support was much more common in 1993 than 1988 at both institutions (43% at Hospital A and 46% at Hospital B in 1988 vs. 66% at A and 80% at B in 1993), increasing to a greater extent in 1993 at Hospital B (p<.05). Length of stay in the ICU was significantly longer at Hospital A than at Hospital B in 1988 (9.4+/-1.4 vs. 4.3+/-0.6 days; p<.05) and in 1993 (8.2+/-2.9 vs. 3.8+/-0.5 days; p < .05). CONCLUSIONS: There has been an increase in withdrawal of life support, in recent years, at both the institutions studied. Differences exist between institutions with respect to end-of-life decisions in the ICU. These differences are likely representative of widely prevalent regional differences and are the result of many factors.
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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 | 0.001 |
| 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) | 0.002 | 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".