The Impact of Hospital and ICU Organizational Factors on Outcome in Critically Ill Patients
Bibliographic record
Abstract
OBJECTIVE: To investigate the impact of various facets of ICU organization on outcome in a large cohort of ICU patients from different geographic regions. DESIGN: International, multicenter, observational study. SETTING: All 1,265 ICUs in 75 countries that contributed to the 1-day point prevalence Extended Prevalence of Infection in Intensive Care study. PATIENTS: All adult patients present on a participating ICU on the study day. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The Extended Prevalence of Infection in Intensive Care study included data on 13,796 adult patients. Organizational characteristics of the participating hospitals and units varied across geographic areas. Participating North American hospitals had greater availability of microbiologic examination and more 24-hour emergency departments than did the participating European and Latin American units. Of the participating ICUs, 82.9% were closed format, with the lowest prevalence among North American units (62.7%) and the highest in ICUs in Oceania (92.6%). The proportion of participating ICUs with 24-hour intensivist coverage was lower in North America than in Latin America (86.8% vs 98.1%, p = 0.002). ICU volume was significantly lower in participating ICUs from Western Europe, Latin America, and Asia compared with North America. In multivariable logistic regression analysis, medical and mixed ICUs were independently associated with a greater risk of in-hospital death. A nurse:patient ratio of more than 1:1.5 on the study day was independently associated with a lower risk of in-hospital death. CONCLUSIONS: In this international large cohort of ICU patients, hospital and ICU characteristics varied worldwide. A high nurse:patient ratio was independently associated with a lower risk of in-hospital death. These exploratory data need to be confirmed in large prospective studies that consider additional country-specific ICU practice variations.
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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".