Participation of ICUs in Critical Care Pandemic Research
Bibliographic record
Abstract
OBJECTIVE: Little information exists to identify barriers to participation in pandemic research involving critically ill patients. We sought to characterize clinical research activity during the recent influenza A pandemic and to understand the experiences, beliefs, and practices of key stakeholders involved in pandemic research implementation. DESIGN: Cross-sectional, provincial postal questionnaire. SETTING: Level III ICUs. PARTICIPANTS: ICU administrators and research coordinators. MEASUREMENTS: We used rigorous survey methodology to identify potential respondents and to develop, test, and administer two-related questionnaires. MAIN RESULTS: We analyzed responses from 39 research coordinators and 139 administrators (response rates: 70.9% and 73.2%, respectively). Compared with non-influenza A studies, influenza A studies were less likely to be randomized trials and most often investigator-initiated and peer-review funded. Whereas both respondent groups felt that pandemic research would be helpful in providing care during future pandemics, research coordinators placed significantly greater importance on their ICU's participation in pandemic research. Both respondent groups expressed a need for rapid approval processes, designated funding for research personnel, adequate funding for start-up and patient screening, preapproved template protocols and consent forms, and clearer guidance regarding co-enrollment. Research coordinators acknowledged a need for alternative consent models to increase their capacity to participate in future pandemic research. More administrators expressed willingness to participate in the next pandemic if the required research resources were made available to them. CONCLUSIONS: Whereas research personnel and administrators support participation in pandemic ICU research, several modifiable barriers to participation exist. Pandemic research preparedness planning with regulatory bodies and dedicated funding to support research infrastructure, especially in community settings, are required to optimize future pandemic research participation.
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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 | 0.057 | 0.161 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".