Pediatric Chronic Critical Illness: A Protocol for a Scoping Review
Bibliographic record
Abstract
Due to improvements in the delivery of intensive care, survival of even the most critically ill of children has increased, leading to a growing proportion of children with chronic and/or complex medical conditions in the pediatric intensive care unit (PICU). Some of these children are at significant risk of recurrent critical illness and persistent long-term morbidity, and become ‘superusers’ of PICU resources. These children are increasingly recognized as a unique high-risk population in the PICU referred to as children with chronic critical illness (CCI). To date, this population has been understudied, in part due to pediatric CCI being a novel concept without an accepted definition to consistently identify these children. This scoping review is the first step in the development of a consensus case definition for pediatric CCI. This comprehensive literature review will seek to first evaluate existing or suggested definitions of pediatric CCI, and in their absence, identify key terms and constructs to inform the development of a working definition of pediatric CCI for future research.
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 | 0.044 | 0.063 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.009 | 0.011 |
| Bibliometrics | 0.018 | 0.019 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.074 | 0.011 |
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".