Are hospital nurse staffing practices associated with postoperative cardiac events and death? A systematic review
Bibliographic record
Abstract
INTRODUCTION: Postoperative cardiac events are frequent complications of surgery, and their occurrence could be associated with suboptimal nurse staffing practices, but the existing evidence remains scattered. We systematically reviewed studies linking nurse staffing practices to postoperative cardiac events and two related outcomes, all-cause mortality and failure-to-rescue. METHODS: A systematic search of the English/French literature was undertaken in the CINAHL, PsychInfo, and Medline databases. Studies were included if they: a) were published between 1996 and 2018; b) used a quantitative design; c) examined the association between at least one of seven staffing practices of interest (i.e., staffing levels, skill mix, work environment characteristics, levels of education and experience of the registered nurses, and overtime or temporary staff use) and postoperative cardiac events, mortality or failure-to-rescue; and d) were conducted among surgical patients. Data extraction, analysis, and synthesis, along with study methodological quality appraisal, were performed by two authors. High methodological heterogeneity precluded a formal meta-analysis. RESULTS: Among 3,375 retrieved articles, 44 studies were included (39 cross-sectional, 3 longitudinal, 1 case-control, 1 interrupted time series). Existing evidence shows that higher nurse staffing levels, a higher proportion of registered nurses with an education at the baccalaureate degree level, and more supportive work environments are related to lower rates of both 30-day mortality and failure-to-rescue. Other staffing practices were less often studied and showed inconsistent associations with mortality or failure-to-rescue. Similarly, few studies (n = 10) examined the associations between nurse staffing practices and postoperative cardiac events and showed inconsistent results. CONCLUSION: Higher nurse staffing levels, higher registered nurse education (baccalaureate degree level) and more supportive work environments were cross-sectionally associated with lower 30-day mortality and failure-to-rescue rates among surgical patients, but longitudinal studies are required to corroborate these associations. The existing evidence regarding postoperative cardiac events is limited, which warrants further investigation.
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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 | 0.013 | 0.062 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.009 |
| Bibliometrics | 0.011 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".