Bibliographic record
Abstract
PURPOSE OF REVIEW: Intensivists have a professional and personal interest in trying to answer whether immediate review of patients by a consultant intensivist improves outcomes. Although some advocate in-hospital around-the-clock consultant intensivist presence, does the available evidence suggest all ICUs should be staffed in such a manner and is such a service sustainable given the shortage of intensivists, potential loss of staff from burnout and cost? RECENT FINDINGS: We present in narrative form the background and recent literature for a consultant resident service in terms of the ethical tenets of nonmaleficence, beneficence, autonomy and justice. Nonmaleficence - what is the evidence it is bad for patients not to provide a resident service? Beneficence - what is the evidence a resident intensivist service is good for patients? Autonomy - is it in intensivists' own interests to provide a 24-h service? And justice - is it a justifiable use of healthcare resources? SUMMARY: A unified staffing solution within a country's different ICUs, let alone between countries, is unlikely. The current evidence does not universally support or justify 24 h/7 days consultant intensivist presence. International differences in staffing models and ICU structures make direct comparisons difficult and in some circumstances the balance may favour 24 h/7 days consultant intensivists.
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".