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Record W1494075927 · doi:10.1159/000313722

Fluid Balance Issues in the Critically Ill Patient

2010· review· en· W1494075927 on OpenAlexaff
José e Bouchard, Ravindra L. Mehta

Bibliographic record

VenueContributions to nephrology · 2010
Typereview
Languageen
FieldMedicine
TopicHemodynamic Monitoring and Therapy
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsMedicineResuscitationCritically illIntensive care medicineSepsisSeptic shockRandomized controlled trialShock (circulatory)Balance (ability)PopulationEmergency medicineInternal medicinePhysical therapy

Abstract

fetched live from OpenAlex

In critically ill patients, fluid balance management is an integral part of the process of care. In patients in shock or severe sepsis, aggressive initial fluid resuscitation has been shown to improve overall prognosis. However, in critically ill patients, cumulative fluid accumulation is recognized as a potential contributing factor to increased morbidity and mortality. Randomized clinical trials are urgently required to assess the role of fluid overload in mortality and morbidity in this population. In the meantime, we should not only focus on acute fluid resuscitation but also on cumulative fluid balance as the amount and duration of fluid accumulation may influence outcomes.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0020.001

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 head0.017
GPT teacher head0.370
Teacher spread0.353 · 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 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

Citations50
Published2010
Admission routes1
Has abstractyes

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