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Record W2513034959 · doi:10.1111/sdi.12532

An Update on Intradialytic Cardiac Dysfunction

2016· review· en· W2513034959 on OpenAlexaff
Aghogho Odudu, Christopher W. McIntyre

Bibliographic record

VenueSeminars in Dialysis · 2016
Typereview
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsWestern University
Fundersnot available
KeywordsMedicineHeart failureCardiologyCardiomyopathyDialysisIntensive care medicineAdverse effectInternal medicineCardiac function curveHemodialysis

Abstract

fetched live from OpenAlex

Cardiac dysfunction is a key factor in the high morbidity and mortality rates seen in hemodialysis (HD) patients. Much of the dysfunction is manifest as adverse changes in cardiac and vascular structure prior to commencing dialysis. This adverse vascular remodeling arises as a dysregulation between pro- and antiproliferative signaling pathways in response to hemodynamic and nonhemodynamic factors. The HD procedure itself further promotes cardiomyopathy by inducing hypotension and episodic regional cardiac ischemia that precedes global dysfunction, fibrosis, worsening symptoms, and increased mortality. Drug-based therapies have been largely ineffective in reversing HD-associated cardiomyopathy, in part due to targeting single pathways of low yield. Few studies have sought to establish natural history and there is no framework of priorities for future clinical trials. Targeting intradialytic cardiac dysfunction by altering dialysate temperature, composition, or ultrafiltration rate might prevent the development of global cardiomyopathy, heart failure, and mortality through multiple pathways. Novel imaging techniques show promise in characterizing the physiological response to HD that is a unique model of repetitive ischemia-reperfusion injury. Reducing HD-associated cardiomyopathy may need a paradigm shift from empirical delivery of solute clearance to a personalized therapy balancing solute and fluid removal with microvascular protection. This review describes the evidence for intradialytic cardiac dysfunction outlining cardioprotective strategies that extend to multiple organs with potential impacts on exercise tolerance, sleep, cognitive function, and quality of life.

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), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.989
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.018
GPT teacher head0.314
Teacher spread0.295 · 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 designOther design
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

Citations43
Published2016
Admission routes1
Has abstractyes

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