Recruitment feasibility to a cohort study of endocrine and metabolic health among survivors of childhood brain tumours: a report from the Canadian study of Determinants of Endometabolic Health in ChIlDrEn (CanDECIDE)
Bibliographic record
Abstract
OBJECTIVES: The aim of this study was to test the feasibility of recruitment and performance of study procedures of the Canadian Study of Determinants of Endometabolic Health in ChIlDrEn (CanDECIDE) study, which was designed to assess the determinants of endocrine and metabolic health in survivors of childhood brain tumours. SETTING: A single paediatric tertiary care centre in Hamilton, Ontario, Canada. PARTICIPANTS: We included boys and girls, aged 5 years and older, who were lean (body mass index (BMI) below 85th centile for age and gender) or overweight/obese (BMI 85th centile or above for age and gender). We excluded children on steroids or immunosuppressant therapy, smokers and those who had an active infection for the 2 weeks prior to participation. OUTCOMES: Feasibility targets included recruitment rate of at least 50%, the consenting of 80% of participants to provide biological samples, 90% questionnaire completion rate and the ability to process biological samples from at least 80% of participants. RESULTS: We approached 210 potential participants, and of the 112 (53%) who agreed to participate, 30 (26.8%) completed the study visit over 7 months. All participants agreed to fast, provide biological samples and complete the questionnaires. Sample collection was successful in 97% (29/30) of participants and laboratory procedures were feasible in 100% of collected samples. We also tested resources required for the conduct of the full study including personnel, space, laboratory equipment and procedures and determined that they are all feasible. CONCLUSIONS: Recruitment and consenting of patients for the CanDECIDE study may be feasible. However, we are considering prolonging recruitment duration and collaboration with other centres to meet recruitment targets due to lower than expected recruitment rate. Completion of questionnaires and implementation of sample processing protocols are feasible.
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 | 0.012 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".