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Record W2943584917 · doi:10.1681/asn.2018121194

Renal Perfusion during Hemodialysis: Intradialytic Blood Flow Decline and Effects of Dialysate Cooling

2019· article· en· W2943584917 on OpenAlexafffund
Raanan Marants, Elena Qirjazi, Claire Grant, Ting‐Yim Lee, Christopher W. McIntyre

Bibliographic record

VenueJournal of the American Society of Nephrology · 2019
Typearticle
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsLondon Health Sciences CentreLawson Health Research InstituteWestern University
FundersKidney Foundation of Canada
KeywordsHemodialysisMedicineDialysisPerfusionCardiologyInternal medicineMyocardial stunningCirculatory systemIschemia

Abstract

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Significance Statement Residual renal function (RRF) characteristically declines after patients with ESRD initiate dialysis. Although RRF preservation correlates with improved outcomes, poor understanding of the pathophysiology underlying RRF decline limits protection strategies. Previous research found that dialysate cooling reduces hemodialysis-induced circulatory stress and protects the brain and heart from ischemic injury. To examine renal perfusion decline during hemodialysis and the effects of cooling, the authors used computed tomography perfusion imaging to scan patients undergoing continuous dialysis with or without dialysate cooling. They found an acute decrease in renal perfusion during hemodialysis, a first step toward characterizing hemodialysis-mediated RRF loss. Dialysate cooling ameliorated this decline but this effect did not reach statistical significance. Further study is needed to explore the potential of dialysis-based interventions to slow RRF decline. Background Residual renal function (RRF) confers survival in patients with ESRD but declines after initiating hemodialysis. Previous research shows that dialysate cooling reduces hemodialysis-induced circulatory stress and protects the brain and heart from ischemic injury. Whether hemodialysis-induced circulatory stress affects renal perfusion, and if it can be ameliorated with dialysate cooling to potentially reduce RRF loss, is unknown. Methods We used renal computed tomography perfusion imaging to scan 29 patients undergoing continuous dialysis under standard (36.5°C dialysate temperature) conditions; we also scanned another 15 patients under both standard and cooled (35.0°C) conditions. Imaging was performed immediately before, 3 hours into, and 15 minutes after hemodialysis sessions. We used perfusion maps to quantify renal perfusion. To provide a reference to another organ vulnerable to hemodialysis-induced ischemic injury, we also used echocardiography to assess intradialytic myocardial stunning. Results During standard hemodialysis, renal perfusion decreased 18.4% ( P <0.005) and correlated with myocardial injury ( r =−0.33; P <0.05). During sessions with dialysis cooling, patients experienced a 10.6% decrease in perfusion (not significantly different from the decline with standard hemodialysis), and ten of the 15 patients showed improved or no effect on myocardial stunning. Conclusions This study shows an acute decrease in renal perfusion during hemodialysis, a first step toward pathophysiologic characterization of hemodialysis-mediated RRF decline. Dialysate cooling ameliorated this decline but this effect did not reach statistical significance. Further study is needed to explore the potential of dialysate cooling as a therapeutic approach to slow RRF decline.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0000.000
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 head0.005
GPT teacher head0.228
Teacher spread0.223 · 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

Citations74
Published2019
Admission routes2
Has abstractyes

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