MétaCan
Menu
Back to cohort
Record W2051352464 · doi:10.1159/000185188

Changes in Body Composition in Children following Kidney Transplantation

2008· article· en· W2051352464 on OpenAlexaff
Nachum Vaisman, Paul B. Pencharz, Denis F. Geary, Joan E. Harrison

Bibliographic record

Venue˜The œNephron journals/Nephron journals · 2008
Typearticle
Languageen
FieldMedicine
TopicRenal Transplantation Outcomes and Treatments
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsMedicineTransplantationBody waterLean body massWeight gainExtracellular fluidKidney transplantationBody mass indexInternal medicineAdipose tissueKidneyBody weightComposition (language)Animal scienceEndocrinologyExtracellularBiologyBiochemistry

Abstract

fetched live from OpenAlex

Rapid weight gain has been observed following kidney transplantation. To determine the accompanying changes in body composition, we studied 8 patients (7 females, 1 male) aged 3-17.5 years who underwent renal transplantation. Body composition measurements included weight, height, triceps skinfold thickness, total body potassium, total body water, and extracellular water. Excessive weight gain was observed in most of the patients. Weight as a percentage of ideal weight for height increased from 96.0 +/- 13.8 to 116.3 +/- 13.0% (p less than 0.01). This was accompanied by a gain in fat mass in the first 3 months and a subsequent increase in lean body mass in the next 3 months. Extracellular water was increased before transplantation (32.9 +/- 6.5% of body weight) and returned to normal (27.3 +/- 8.6%) 3 months after transplantation (p less than 0.01). The weight gain following kidney transplantation in children resulted mainly from increases in adipose tissue and lean body mass, and was not related to water retention.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.026
GPT teacher head0.305
Teacher spread0.279 · 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 teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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

Citations14
Published2008
Admission routes1
Has abstractyes

Explore more

Same venue˜The œNephron journals/Nephron journalsSame topicRenal Transplantation Outcomes and TreatmentsFrench-language works237,207