Safety Outcomes of Direct Discharge Home From ICUs: An Updated Systematic Review and Meta-Analysis (Direct From ICU Sent Home Study)*
Bibliographic record
Abstract
OBJECTIVE: To evaluate the impact of direct discharge home (DDH) from ICUs compared with ward transfer on safety outcomes of readmissions, emergency department (ED) visits, and mortality. DATA SOURCES: We searched MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials, and Cumulative Index to Nursing and Allied Health Literature from inception until March 28, 2022. STUDY SELECTION: Randomized and nonrandomized studies of DDH patients compared with ward transfer were eligible. DATA EXTRACTION: We screened and extracted studies independently and in duplicate. We assessed risk of bias using the Newcastle-Ottawa Scale for observational studies. A random-effects meta-analysis model and heterogeneity assessment was performed using pooled data (inverse variance) for propensity-matched and unadjusted cohorts. We assessed the overall certainty of evidence for each outcome using the Grading Recommendations Assessment, Development and Evaluation approach. DATA SYNTHESIS: Of 10,228 citations identified, we included six studies. Of these, three high-quality studies, which enrolled 49,376 patients in propensity-matched cohorts, could be pooled using meta-analysis. For DDH from ICU, compared with ward transfers, there was no difference in the risk of ED visits at 30-day (22.4% vs 22.7%; relative risk [RR], 0.99; 95% CI, 0.95-1.02; p = 0.39; low certainty); hospital readmissions at 30-day (9.8% vs 9.6%; RR, 1.02; 95% CI, 0.91-1.15; p = 0.71; very low-to-low certainty); or 90-day mortality (2.8% vs 2.6%; RR, 1.06; 95% CI, 0.95-1.18; p = 0.29; very low-to-low certainty). There were no important differences in the unmatched cohorts or across subgroup analyses. CONCLUSIONS: Very low-to-low certainty evidence from observational studies suggests that DDH from ICU may have no difference in safety outcomes compared with ward transfer of selected ICU patients. In the future, this research question could be further examined by randomized control trials to provide higher certainty data.
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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 | 0.018 | 0.044 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.041 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".