A randomized controlled trial protocol for the introduction of a multidisciplinary individualized nutritional intervention in children with cerebral palsy
Bibliographic record
Abstract
Introduction: Children with Cerebral Palsy (CP) encounter substantial nutritional challenges that impair their health and quality of life. Despite the importance of nutrition in managing CP and the recognition of physiological, behavioral, and social causes of malnutrition, research on the effectiveness of individualized nutritional interventions developed and supported by multidisciplinary teams is scarce. Aim: The study will evaluate the impact of an individualized nutritional intervention developed and supported by a multidisciplinary team on the anthropometric outcomes and overall health of children with CP. Methods: A single-center, randomized controlled trial, conducted at the Medical University of Varna, Bulgaria, will enroll 100 children aged 2-12 years and diagnosed with CP. Participants will be randomly assigned to either an intervention group, receiving comprehensive structured dietary assessment and individualized nutrition plan developed by a multidisciplinary team of experts, or to a standard care group. Outcomes assessed will focus on anthropometric measures of nutritional status, but also include health outcomes, child development and clinical assessments, and quality of life indicators. Ethics: Ethical approval for this study has been obtained from the Medical Ethics Committee at the Medical University of Varna (Protocol No. 134 dated 20.07.2023). Conclusion: This study will assess the benefits of a multidisciplinary, individualized nutritional intervention for children with CP. The findings will have implications for clinical guidelines and interventions aiming to improve their care and quality of life.
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 | 0.022 | 0.027 |
| Meta-epidemiology (narrow) | 0.006 | 0.002 |
| Meta-epidemiology (broad) | 0.012 | 0.004 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.009 | 0.008 |
| Insufficient payload (model declined to judge) | 0.075 | 0.007 |
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".