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Record W2441166305 · doi:10.1186/s13643-016-0274-9

The effectiveness of interventions to treat obesity in survivors of childhood brain tumors: a systematic review protocol

2016· review· en· W2441166305 on OpenAlexaff
Kuan-Wen Wang, Marlie Valencia, Laura Banfield, Ruth Chau, Adam Fleming, Sheila K. Singh, Sarah Burrow, Russell J. de Souza, Lehana Thabane, M. Constantine Samaan

Bibliographic record

VenueSystematic Reviews · 2016
Typereview
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsMcMaster University Medical CentreMcMaster UniversitySt. Joseph’s Healthcare HamiltonMcMaster Children's Hospital
Fundersnot available
KeywordsMedicinePsychological interventionCINAHLSystematic reviewPsycINFOMEDLINEPopulationCochrane LibraryRandomized controlled trialIntensive care medicinePhysical therapyPsychiatryInternal medicineEnvironmental health

Abstract

fetched live from OpenAlex

BACKGROUND: Pediatric brain tumors are the most common solid tumors in children. Advances in understanding the hallmarks of cancer biology and novel therapies have led to an increasing number of survivors of childhood brain tumors (SCBT). However, these survivors are at an increased risk of obesity and cardiometabolic disorders that affect their quality of life and lifespan. It is important to define effective strategies to treat and prevent obesity in this population. This systematic review aims to investigate the effectiveness of lifestyle interventions, pharmacotherapy, and bariatric surgery on treating obesity in SCBT. METHODS: Searches will be conducted in PubMed, MEDLINE, EMBASE, PsycINFO, SPORTDiscus, CINAHL, Cochrane Database of Systematic Review, Cochrane Central Register of Controlled Trials (CENTRAL), and Database of Abstracts of Reviews of Effect (DARE). In addition, ClinicalTrials.gov and ProQuest Dissertations and Theses A&I will be searched to identify relevant gray literature. The reference lists of eligible articles will be searched for additional studies. All screening, quality assessment, and data abstraction will be done independently by two reviewers. We will perform meta-analysis if there are sufficient studies. DISCUSSION: This review will summarize evidence for the effectiveness of interventions used to reduce obesity risk in SCBT. This has significant implications for SCBT, as it can identify gaps in knowledge and provide insights into the development of new interventions to manage obesity in survivors, which may improve their outcomes. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42015025909.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.065
metaresearch head score (Gemma)0.049
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Meta-epidemiology (broad)
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.034
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0650.049
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0300.006
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.062
GPT teacher head0.425
Teacher spread0.363 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations4
Published2016
Admission routes1
Has abstractyes

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