The Association of ICU Acuity and Organizational Factors With Outcomes of Low-Risk Patients
Bibliographic record
Abstract
OBJECTIVE: Outcomes of low-risk patients may be affected by the overall acuity of the ICU to which they were admitted. Studies addressing this topic are very scarce and the underlying mechanisms supporting this association remain incompletely understood. Here, we investigated the effects of ICU acuity (defined as the mean Simplified Acute Physiology Score 3 of all admitted patients in the bimester in which a given patient was admitted) and organizational factors on the outcomes of patients with a low risk of dying admitted to ICUs. DESIGN: Retrospective cohort study. SETTING: One hundred and thirty-four ICUs from Brazil and Uruguay. PATIENTS: All low-risk (defined as a Simplified Acute Physiology Score 3 probability of death < 3%) patients admitted between 2016 and 2018. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The primary outcome was hospital mortality; secondary outcomes were ICU mortality, and ICU and hospital lengths of stay (LOS). ICU acuity was evaluated as a continuous variable. Multilevel multivariable regression analyses were used to explore the association between ICU acuity, organizational characteristics, and outcomes. Of 285,553 patients, 69,675 (24.4%) were considered low risk. Elective surgeries (66.2%) were the main admission reason. In the models adjusted for patient- and ICU-level characteristics, ICU acuity was not associated with hospital mortality (odds ratio [OR] = 1.095 [0.942-1.274]) and all secondary outcomes. These results were consistent in sensitivity analyses. The presence of dedicated pharmacists in the ICU (OR = 0.531 [0.365-0.773]) and the number of implemented clinical protocols (OR = 0.817 [0.688-0.970]) were independently associated with lower hospital mortality. Clinical protocols were also associated with shorter ICU and hospital LOS. CONCLUSIONS: ICU acuity was not associated with outcomes in low-risk patients. Appropriate multidisciplinary staffing coupled with adherence to best clinical practices are essential to optimize efficiency and minimize variability of care for this population.
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 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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".