Caring for Critically Ill Patients in Humanitarian Settings
Bibliographic record
Abstract
Critical care medicine is far from the first medical field to come to mind when humanitarian action is mentioned, yet both critical care and humanitarian action share a fundamental purpose to save the lives and ease the suffering of people caught in acute crises. Critically ill children and adults will be present regardless of resource limitations and irrespective of geography, regional or cultural contexts, insecurity, or socioeconomic status, and they may be even more prevalent in a humanitarian crisis. Critical care is not limited to the walls of a hospital, and all hospitals will have critically ill patients regardless of designating a specific ward an ICU. Regular and consistent consideration of critical care principles in humanitarian settings provides crucial guidance to intensivists and nonintensivists alike. A multidisciplinary, systematic approach to patient care that encourages critical thinking, checklists that encourage communication among team members, and context-specific critical care rapid response teams are examples of critical care constructs that can provide high-quality critical care in all environments. Promoting critical care principles conveys the message that critical care is an integral part of health care and should be accessible to all, no matter the setting. These principles can be effectively adopted in humanitarian settings by normalizing them to everyday clinical practice. Equally, core humanitarian principles-dignity, accountability, impartiality, neutrality-can be applied to critical care. Applying principles of critical care in a context-specific manner and applying humanitarian principles to critical care can improve the quality of patient care and transcend barriers to resource limitations.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.016 | 0.003 |
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".