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Record W2585215474 · doi:10.3747/pdi.2016.00079

Endotoxemia in Peritoneal Dialysis Patients: A Pilot Study to Examine the Role of Intestinal Perfusion and Congestion

2017· article· en· W2585215474 on OpenAlexaff
Claire Grant, L. Harrison, Caroline L. Hoad, Luca Marciani, Eleanor Cox, Charlotte Buchanan, Carolyn Costigan, Susan Francis, Ka‐Bik Lai, Cheuk‐Chun Szeto, Penny Gowland, Christopher W. McIntyre

Bibliographic record

VenuePeritoneal Dialysis International · 2017
Typearticle
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsWestern University
Fundersnot available
KeywordsMedicineSplanchnicPeritoneal dialysisPerfusionCirculatory systemHemodialysisSuperior mesenteric arteryCardiologyInternal medicineMagnetic resonance imagingSplanchnic CirculationDialysisIntravascular volume statusGastroenterologyHemodynamicsRadiology

Abstract

fetched live from OpenAlex

Endotoxemia is common in advanced chronic kidney disease and is particularly severe in those receiving dialysis. In hemodialysis patients, translocation from the bowel occurs as a consequence of recurrent circulatory stress leading to a reduction in circulating splanchnic volume and increased intestinal permeability. Peritoneal dialysis (PD) patients are often volume expanded and have continuous direct immersion of bowel in fluid; these may also be important factors in endotoxin translocation and would suggest different therapeutic strategies to improve it. The mechanisms leading to endotoxemia have never been specifically studied in PD. In this study, 17 subjects (8 PD patients, 9 healthy controls) underwent detailed gastrointestinal and cardiac magnetic resonance imaging during fasted and fed states. Gross splanchnic perfusion was assessed by quantification of superior mesenteric artery flow. Magnetic resonance imaging findings were correlated to endotoxemia, markers of hydration status and cardiac structure and function.

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)0.001
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 score0.053
Threshold uncertainty score0.660

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.016
GPT teacher head0.284
Teacher spread0.268 · 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

Citations6
Published2017
Admission routes1
Has abstractyes

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