Neonatal epidermolysis bullosa: a clinical practice guideline
Bibliographic record
Abstract
DEBRA International is undertaking a long-term initiative to develop clinical practice guidelines (CPGs) for epidermolysis bullosa (EB), to -improve the clinical care of people living with EB. Current neonatal care is based on evidence, clinical expertise and trial and error, with collaboration between the EB specialist team, parent or carer and patient, and is dependent on the neonate's individual presentation and type of EB. Early intervention based on research and clinical practice is needed to establish a foundation of knowledge to guide international practitioners to create and improve standards of care and to be able to work effectively with those newly diagnosed with EB. This CPG was created by an international panel with expertise working with persons with EB. The CPG focuses on neonatal care using a systematic review methodology covering four key areas: (i) diagnosis and parental psychosocial support; (ii) hospital management: medical monitoring, wound care and pain; (iii) feeding and nutrition; and (iv) discharge planning and EB education. These four areas highlight the importance of a multidisciplinary team approach, to provide a patient-specific holistic care model that incorporates the needs and wishes of the parents and carers. The Hospital Implementation Tool included promotes transfer of theory to clinical practice.
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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 | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".