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Record W2994251502 · doi:10.1038/s41598-019-54851-2

Associations between echocardiographic findings and prospective changes in residual renal function in patients new to peritoneal dialysis

2019· article· en· W2994251502 on OpenAlexaff
S. Sara Mahdavi, Kibar Yared, George Wu, Billy Omar, Dinesh Savundra, Gordon Nagai, Edgar Hockmann, Anton Svendrovski, Antonio Bellasi, Paul Tam, Tabo Sikaneta

Bibliographic record

VenueScientific Reports · 2019
Typearticle
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsThe Scarborough HospitalTrillium Health CentreUniversity of Toronto
Fundersnot available
KeywordsMedicinePeritoneal dialysisCardiologyInternal medicineLeft ventricular hypertrophyEjection fractionRenal functionDialysisProspective cohort studyCalcificationBlood pressureHeart failure

Abstract

fetched live from OpenAlex

Although echocardiograms are often performed when peritoneal dialysis is started, associations between commonly reported findings and prospective changes in renal function remain understudied. Ninety-nine of 101 patients in the Trio Trial had transthoracic echocardiograms within 6 months of dialysis initiation, and measurements of residual renal function every six weeks for up to two years. Generalized mixed modelling linear regression in STATA was used to examine associations between left atrial size, left ventricular hypertrophy, left ventricular ejection fraction, right ventricular systolic pressure, and left valvular calcification with subsequent slopes in renal function. After echocardiography (performed a median of 16 days following peritoneal dialysis initiation) right ventricular systolic pressure was associated with faster, while declining left ventricular ejection fraction and valvular calcification were associated with slower declines in residual renal function. Future studies could be conducted to confirm these findings, and identify pathophysiological mechanisms.

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)0.009
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.010
GPT teacher head0.238
Teacher spread0.229 · 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 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
Published2019
Admission routes1
Has abstractyes

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