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Record W1980828265 · doi:10.1093/eurjhf/hfp188

Haemodialysis, not Ultrafiltration, can Correct Hyponatraemia in Heart Failure

2009· letter· en· W1980828265 on OpenAlexaboutno aff
Amir Kazory

Bibliographic record

VenueEuropean Journal of Heart Failure · 2009
Typeletter
Languageen
FieldMedicine
TopicElectrolyte and hormonal disorders
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineUltrafiltration (renal)Heart failureIntravascular volume statusHyponatremiaInternal medicineExtracorporealIntensive care medicinePopulationCardiologyTolvaptanBlood pressureChromatography

Abstract

fetched live from OpenAlex

Hyponatraemia is present in a significant subset of patients with heart failure (HF), and its association with adverse outcomes is well established in this population. It is still not clear whether hyponatraemia is merely a marker for severity of HF, or if it has a causal impact on the progression of the disease. The therapeutic strategies for hyponatraemia in this setting remain extremely limited and challenging. Current guidelines on management of HF from the American Heart Association/American College of Cardiology or Canadian Cardiovascular Society do not address this complication. In the most recent guidelines of the European Society of Cardiology on management of HF published in 2008, ultrafiltration has repeatedly been presented as a treatment option for hyponatraemia in HF.1 Ultrafiltration is an extracorporeal therapy that does not use any exchange or substitution solution; it extracts isotonic fluid from blood via convective forces, hence reducing intravascular volume. Consistent with its mechanism of action, studies have confirmed that the fluid extracted from blood (i.e. ultrafiltrate) has a sodium concentration similar to serum.2 Numerous trials have so far demonstrated that ultrafiltration does not affect concentration of serum electrolytes, and this has actually been considered a notable advantage over the use of diuretics in this setting.3,4 Moreover, since diuretics produce hypotonic urine (urinary sodium of ∼60 mEq/L), it has been suggested that for similar volumes of fluid removed, ultrafiltration extracts more sodium, and is therefore more efficient in reducing the total body sodium content.3 In contrast, in diffusion-based extracorporeal therapies such as haemodialysis, there is a significant exchange of electrolytes and solutes between dialysate solution and blood across a semi-permeable membrane (i.e. dialyzer). This transfer is indeed the major mechanism of clearance provided by haemodialysis therapy; combination of dialysis and ultrafiltration often used in patients with renal failure provides volume control, correction of electrolytes, and clearance.5 With the advent of newer portable ultrafiltration devices that have led to an increased interest in this modality for management of HF, the physicians' recognition of the above-mentioned distinction is crucial. In contrast to conventional haemodialysis machines that are capable of providing dialysis, ultrafiltration, or a combination of the two techniques, these devices exclusively provide ultrafiltration and, therefore, have no role in the correction of hyponatraemia (or other electrolyte abnormalities). This point merits being taken into consideration for the forthcoming updated version of the guidelines.

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), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.182
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.006
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 head0.012
GPT teacher head0.233
Teacher spread0.222 · 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 designNot applicable
Domainnot available
GenreCommentary

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
Published2009
Admission routes1
Has abstractyes

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