Organisation of clinical research in intensive care units: A scoping review
Bibliographic record
Abstract
BACKGROUND: Clinical research is essential for the development and progress of therapies and procedures. Intensive care units (ICUs) manage the sickest patients. Numerous clinical trials are organised in ICUs to evaluate new treatments or support techniques. Concomitantly, new professions involved in clinical research set-ups are emerging. AIM: The aim of this scoping review was to identify the nature and extent of research evidence on the organisation of clinical research in ICUs. METHODS: This review focusses on observational and qualitative narrative studies dealing with clinical research organisation in ICUs, with a special interest in structures coordinating research, the roles of clinical research professionals, and the training required. Medline and Embase were analysed between January 2000 and June 2024. Assessment of the study quality was based on the Let Evidence Guide Every New Decision evaluation system and the Newcastle-Ottawa quality assessment scale. RESULTS: Of the 14 studies reviewed, four were narrative and 10 observational descriptive. All were based on cross-sectional surveys. Most studies were carried out in North America, the United Kingdom, and Australia/New Zealand. ICU clinical research professionals were mostly female nurses aged between 31 and 50 years who had a wide diversity of training profiles and performed greatly varied tasks from data collection to publication of the article. Reported job satisfaction depended on the degree of autonomy, the workload, the extent of professional recognition, and opportunities for professional promotion. CONCLUSIONS: The organisation of ICU clinical research reflects considerable diversity in training, tasks, job organisation, and responsibilities.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.299 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.005 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".