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Record W2021752889 · doi:10.1097/hco.0b013e3283358a2b

Ultrafiltration in the management of acute decompensated heart failure

2010· review· en· W2021752889 on OpenAlexafffund
Lisa Mielniczuk, Haissam Haddad, Ross A. Davies

Bibliographic record

VenueCurrent Opinion in Cardiology · 2010
Typereview
Languageen
FieldMedicine
TopicAcute Kidney Injury Research
Canadian institutionsUniversity of Ottawa
FundersUniversity of Ottawa
KeywordsMedicineUltrafiltration (renal)Acute decompensated heart failureIntensive care medicineHeart failureVolume overloadDiureticInternal medicine

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Admissions to hospital for acute decompensated heart failure continue to increase and represent a significant burden on both patients' and healthcare resources. The majority of these admissions are for the control of volume overload; however, standard treatment with intravenous diuretics is not always effective and can lead to increased renal morbidity. One alternative to standard therapy is mechanical fluid removal with ultrafiltration, this review will highlight the current evidence and efficacy regarding ultrafiltration use in acute heart failure. RECENT FINDINGS: Multiple recent clinical trials have demonstrated the safety and feasibility of ultrafiltration in the management of acute heart failure. Ultrafiltration may be more effective at removing fluid than standard diuretic therapy and has been associated with beneficial long-term results. However, it remains to be determined whether ultrafiltration is truly nephroprotective and when and how this therapy is best utilized. SUMMARY: Ultrafiltration is an attractive alternative to standard diuretic therapy in the management of volume overload from acute heart failure. Further research is needed to confirm the cost-effectiveness and to determine long-term impacts on morbidity and mortality.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.868
Threshold uncertainty score0.868

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
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 head0.121
GPT teacher head0.468
Teacher spread0.347 · 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 designNot applicable
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

Citations9
Published2010
Admission routes2
Has abstractyes

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