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Record W2605597776 · doi:10.1002/pbc.26567

Exercise interventions for patients with pediatric cancer during inpatient acute care: A systematic review of literature

2017· review· en· W2605597776 on OpenAlexaff
Vanessa Rustler, Meaghan Hagerty, Julia Daeggelmann, Stacey Marjerrison, Wilhelm Bloch, Freerk T. Baumann

Bibliographic record

VenuePediatric Blood & Cancer · 2017
Typereview
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsMcMaster Children's HospitalMcMaster UniversityHamilton Health Sciences
Fundersnot available
KeywordsMedicinePsychological interventionPediatric oncologyPediatric cancerIntervention (counseling)Physical therapyAdverse effectSystematic reviewMEDLINEIntensive care medicineCancerInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

Physical inactivity has been shown to exacerbate negative side effects experienced by pediatric patients undergoing cancer therapy. Exercise interventions are being created in response. This review summarizes current exercise intervention data in the inpatient pediatric oncology setting. Two independent reviewers collected literature from three databases, and analyzed data following the PRISMA statement for systematic reviews and meta-analyses. Ten studies were included, representing 204 patients. Good adherence, positive trends in health status, and no adverse events were noted. Common strategies included individual, supervised, combination training with adaptability to meet fluctuating patient abilities. We recommend that general physical activity programming be offered to pediatric oncology inpatients.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.007
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.015
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.006
Bibliometrics0.0040.005
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.036
GPT teacher head0.380
Teacher spread0.344 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations68
Published2017
Admission routes1
Has abstractyes

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