Association Between Intensive Care Unit Occupancy at Discharge, Afterhours Discharges, & Clinical Outcomes: An Historical Cohort Study
Bibliographic record
Abstract
Abstract Background: There is a paucity of contemporary, patient-level data evaluating the association between discharge occupancy in the intensive care unit (ICU) and clinical outcomes such as readmission and mortality. Additionally, it is unknown whether increased occupancy at discharge may modify the timing of discharge (i.e. increased afterhours discharge) and further provoke negative clinical consequences. The objective of this single-center historical cohort study was to explore the association between ICU occupancy on the day of discharge and afterhours discharges, 72-hour readmission and 30-day mortality. Methods: This was a historical cohort study of a single large quaternary ICU in Canada. Discharge occupancy was defined as the number of hours of patient care delivered on the day of discharge divided by the total amount of hours of care available for that day (number of funded beds x 24 hours). Afterhours discharge was defined as a discharge between 22:00 and 6:59. Logistic regression models controlling for important covariates were constructed. Adjusted restricted cubic spline models were also created to control for non-linear relationships. Results: A total of 8,862 ICU discharges, representing 7,288 individual patients, between April 1, 2010 and August 10, 2017 were included in this analysis. A total of 1180 (13.3%) afterhours discharges, 408 (4.6%) 72-hour readmissions, and 574 (6.5%) 30-day post discharge deaths occurred. In the adjusted analysis, greater discharge occupancy was associated with afterhours discharges (per 10% increase; adjusted odds ratio (aOR) 1.12, 95% 1.03-120, p = 0.005). Discharge occupancy was not associated with 72-hour readmission (per 10% increase; aOR 0.97, 95% CI 0.87-1.09, p= 0.624) or 30-day mortality (per 10% increase; aOR 1.05, 95% CI 0.95-1.16, p= 0.323). Afterhours discharge was not associated with neither 72-hour readmission (aOR 1.15, 95% CI 0.86-1.54, p= 0.341) nor 30-day mortality (aOR 1.05, 95% CI 0.82-1.36, p= 0.691). Conclusions: Greater ICU occupancy on the day of discharge was associated with a significant increase in afterhours discharges. However, neither discharge occupancy nor afterhours discharge were associated with 72-hr readmission or 30-day mortality. Keywords: Intensive care unit; occupancy; capacity strain; process-of-care; afterhours discharge; readmission; mortality
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".