MétaCan
Menu
Back to cohort
Record W2493935713 · doi:10.1093/ndt/gfw142.04

MO067LONG-TERM PULSE WAVE VELOCITY AND VO2PEAK OUTCOMES WITH 12 WEEKS OF AEROBIC OR RESISTANCE TRAINING IN KIDNEY TRANSPLANT RECIPIENTS: A FOLLOW-UP OF THE EXERT STUDY

2016· article· en· W2493935713 on OpenAlexaff
Ellen O’Connor, Herolin Lindup, Eilish Nugent, David Goldsmith, Iain C. Macdougall, Sharlene A. Greenwood

Bibliographic record

VenueNephrology Dialysis Transplantation · 2016
Typearticle
Languageen
FieldEngineering
TopicNon-Invasive Vital Sign Monitoring
Canadian institutionsSt. Thomas Hospital
Fundersnot available
KeywordsMedicineTerm (time)Kidney transplantResistance trainingAerobic exerciseInternal medicineKidneyKidney transplantationIntensive care medicine

Abstract

fetched live from OpenAlex

Introduction and Aims: Kidney transplantation improves survival, quality of life, and is more cost-effective than other treatments for end stage renal disease (ESRD). Despite this, the incidence for cardiovascular disease remains up to 3 to 5 times higher than the general population. Therefore cardiovascular risk, and the potential interventions to reduce this, are of upmost clinical importance in this patient population. Pulse wave velocity (PWV), the gold standard measure of arterial stiffness, is a known predictor of mortality in ESRD, and cardiovascular disease in kidney transplant recipients. Peak oxygen uptake (VO2peak), a measure of cardiorespiratory fitness, has been shown to predict survival in haemodialysis and kidney transplant patients. Whilst studies have shown improvement immediately following exercise interventions in both of these outcomes, the long-term effects remain unexplored. The aim of this study was therefore to investigate the long-term PWV and relative VO2 peak outcomes following completion of a 12-week aerobic (AT) or resistance training (RT) programme in new kidney transplant recipients.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.209
Threshold uncertainty score0.609

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.017
GPT teacher head0.226
Teacher spread0.208 · 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.

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

Citations1
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueNephrology Dialysis TransplantationSame topicNon-Invasive Vital Sign MonitoringFrench-language works237,207