Rapid response teams and recommended ward-based management of acute deterioration: a single-centre retrospective cohort study in an inner-city London (UK) teaching hospital
Bibliographic record
Abstract
OBJECTIVES : To describe the associations between Rapid Response Team (RRT) patient review and other predefined clinical management actions, with risk of in-hospital cardiac arrest and in-hospital mortality in the first unplanned admission (UPA) to the adult intensive care unit (ICU) from the ward environment for each patient.To describe a novel RRT assessment tool for ward-based care for patients who were deteriorating. DESIGN: A retrospective cohort study. SETTING: A large multispecialty, tertiary referral and teaching hospital in England, UK. PARTICIPANTS: The study included 3175 consecutive adult ICU UPAs from hospital wards over a 6-year period (2014-2019). OUTCOME MEASURES: Ward-based management of deterioration prior to ICU admission was assessed by the RRT, using a scored checklist-the UPA score. Admissions were compared in two groups according to their exposure to an RRT review in the 72 hours before ICU admission. Associations with in-hospital cardiac arrest within 24 hours before ICU admission and all-cause in-hospital mortality were estimated, using unadjusted and adjusted odds ratios (aORs) with 95%CI. RESULTS: RRT review occurred in 1413 (44.5%) admissions and was associated with reduced odds of in-hospital cardiac arrest (aOR 0.51; 95% CI 0.36 to 0.78; p<0.001), but similar odds of in-hospital mortality (OR 0.97; 95% CI 0.83 to 1.12; p=0.65). The median (IQR) UPA score was 1 (0 to 2), and each point increase was associated with increased odds of in-hospital cardiac arrest (aOR 1.13; 95% CI 1.06 to 1.23; p<0.001) and in-hospital mortality (aOR 1.10; 95% CI 1.05 to 1.15; p<0.001). Among individual UPA score items, Nursing Escalation Failure, Blood Gas Omission and Laboratory Blood Omission were associated with increased odds of in-hospital cardiac arrest, whereas Delayed Vital Signs and Failure to Recognise Deterioration were associated with increased odds of in-hospital mortality. CONCLUSIONS AND RELEVANCE: An RRT review in the 72 hours prior to ICU admission was associated with reduced odds of in-hospital cardiac arrest but did not impact in-hospital mortality. Higher UPA scores were associated with increased incidence of both in-hospital cardiac arrest and in-hospital mortality. In addition, this study describes a novel and adaptable RRT scoring tool (the UPA score) for safety monitoring and 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".