Outcomes of Older Hospitalized Patients Requiring Rapid Response Team Activation for Acute Deterioration
Bibliographic record
Abstract
OBJECTIVES: Rapid response teams are groups of healthcare providers that have been implemented by many hospitals to respond to acutely deteriorating patients admitted to the hospital wards. Hospitalized older patients are at particular risk of deterioration. We sought to examine outcomes of older patients requiring rapid response team activation. DESIGN: Analysis of a prospectively collected registry. SETTING: Two hospitals within a single tertiary care level hospital system between 2012 and 2016. PATIENTS: Five-thousand nine-hundred ninety-five patients were analyzed. Comparisons were made between older patients (defined as ≥ 75 yr old) and younger patients. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: All patient information, outcomes, and rapid response team activation information were gathered at the time of rapid response team activation and assessment. The primary outcome was in-hospital mortality, analyzed using multivariate logistic regression. Two-thousand three-hundred nine were older patients (38.5%). Of these, 835 (36.2%) died in-hospital, compared with 998 younger patients (27.1%) (adjusted odds ratio, 1.83 [1.54-2.18]; p < 0.001). Among patients admitted from home, surviving older patients were more likely to be discharged to a long-term care facility (adjusted odds ratio, 2.38 [95% CI, 1.89-3.33]; p < 0.001). Older patients were more likely to have prolonged delay to rapid response team activation (adjusted odds ratio, 1.79 [1.59-2.94]; p < 0.001). Among patients with goals of care allowing for ICU admission, older patients were less likely to be admitted to the ICU (adjusted odds ratio, 0.66 [0.36-0.79]), and less likely to have rapid response team activation during daytime hours (adjusted odds ratio, 0.73 [0.62-0.98]; p < 0.001). CONCLUSIONS: Older patients with in-hospital deterioration requiring rapid response team activation had increased odds of death and long-term care disposition. Rapid response team activation for older patients was more likely to be delayed, and occur during nighttime hours. These findings highlight the worse outcomes seen among older patients with in-hospital deterioration, identifying areas for future quality improvement.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.000 | 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".