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Central, Peripheral, and Other Blood Volume Changes During Hemodialysis

2002· article· en· W1984662924 on OpenAlexaff
Suma Prakash, Donal Reddan, A.Paul Heidenheim, C Kianfar, Robert M. Lindsay

Bibliographic record

VenueASAIO Journal · 2002
Typearticle
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsLondon Health Sciences CentreWestern University
Fundersnot available
KeywordsHematocritBlood volumeHemodialysisExtracellular fluidMedicineBody waterBlood pressureIntravascular volume statusCardiologyHypervolemiaBioelectrical impedance analysisCompliance (psychology)Internal medicineHemodynamicsCardiac outputVolume overloadBody fluidUltrafiltration (renal)PopulationArterial lineBody weightHeart failureChemistryExtracellularBody mass index

Abstract

fetched live from OpenAlex

Volume overload is a factor in development of hypertension in hemodialysis patients. Fluid removal by hemodialysis (HD), however, may cause intradialytic hypotension and associated symptoms. A better understanding of the relationships between blood pressure volume status and the pathophysiology of fluid removal during HD are, therefore, necessary to control blood pressure and to eliminate intradialytic hypotension. The objectives of the study were to determine the amount and direction of change of body fluid compartments after ultrafiltration (UF) and to determine whether any correlations exist between mean arterial pressure (MAP), change in circulating blood volume (deltaBV), total body water (TBW), central blood volume (which constitutes the volume of blood in the lungs, heart, and great vessels [CBV]), and intracellular and extracellular fluid volumes (ICF, ECF). The study population included 20 patients on regular HD. Each individual had their CBV, cardiac output, and peripheral vascular resistance (PVR) measured by means of saline dilution technique and deltaBV monitored by an online hematocrit sensor (Crit Line). MAP was calculated from measured blood pressure and ICF and ECF were measured using bioelectric impedance analysis techniques. Measurements were obtained before and after maximum UF measured by deltaBV (reduction of 6-10% by Crit Line). Ten healthy controls also had ECF and ICF values measured by bioelectric impedance analysis. Before HD, MAP correlated with TBW (r = 0.473, p = 0.035) and CBV (r = 0.419, p = 0.066), suggesting that hypertension here may be due to volume overload. Patients were ECF expanded before HD with an ECF:ICF ratio of 0.96, which was significantly higher than the control ratio of 0.74 (p < 0.0001). During UF, fluid was removed from both ECF and ICF, but more from the ECF volume ratio 0.92 post UF, a significant reduction (p < 0.0001). After UF, MAP no longer correlated with TBW or CBV but correlated with peripheral vascular resistance (r = 0.4575, p = 0.043). After UF, deltaBV correlated inversely with PVR (r = -0.50, p = 0.024). Despite the fall in deltaBV (7.11+/-2.49%) with UF, CBV was maintained. CBV were 0.899 L and 0.967 L pre and post UF, respectively. These data suggest that in hemodialysis patients, predialysis volume status influences predialysis blood pressure. UF causes BV to fall, but CBV is preferentially conserved by increasing PVR, which also maintains blood pressure. Failure of a PVR response likely leads to intradialytic hypotension.

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)0.002
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 score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.015
GPT teacher head0.222
Teacher spread0.207 · 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

Citations40
Published2002
Admission routes1
Has abstractyes

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