Effectiveness of rapid response teams in reducing intrahospital cardiac arrests and deaths: a systematic review and meta-analysis
Bibliographic record
Abstract
OBJECTIVE: To evaluate the effectiveness of rapid response teams using early identification of clinical deterioration in reducing the occurrence of in-hospital mortality and cardiorespiratory arrest. DATA SOURCES: The MEDLINE, LILACS, Cochrane Library, Center for Reviews and Dissemination databases were searched. STUDY SELECTION: We included studies that evaluated the effectiveness of rapid response teams in adult hospital units, published in English, Portuguese, or Spanish, from 2000 to 2016; systematic reviews, clinical trials, cohort studies, and prepost ecological studies were eligible for inclusion. The quality of studies was independently assessed by two researchers using the Newcastle-Ottawa, modified Jadad, and Assessment of Multiple Systematic Reviews scales. DATA EXTRACTIONS: The results were synthesized and tabulated. When risk measures were reported by the authors of the included studies, we estimated effectiveness as 1-RR or 1-OR. In pre-post studies, we estimated effectiveness as the percent decrease in rates following the intervention. RESULTS: Overall, 278 studies were identified, 256 of which were excluded after abstract evaluation, and two of which were excluded after full text evaluation. In the meta-analysis of the studies reporting mortality data, we calculated a risk ratio of 0.85 (95%CI 0.76 - 0.94); and for studies reporting cardiac arrest data the estimated risk ratio was 0.65 (95%CI 0.49 - 0.87). Evidence was assessed as low quality due to the high heterogeneity and risk of bias in primary studies. CONCLUSION: We conclude that rapid response teams may reduce in-hospital mortality and cardiac arrests, although the quality of evidence for both outcomes is low.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.004 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".