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Record W1977982204 · doi:10.1002/ccd.24440

Accurate measurement of oxygen consumption in children undergoing cardiac catheterization

2012· review· en· W1977982204 on OpenAlexaff
Jia Li

Bibliographic record

VenueCatheterization and Cardiovascular Interventions · 2012
Typereview
Languageen
FieldMedicine
TopicHemodynamic Monitoring and Therapy
Canadian institutionsStollery Children's HospitalUniversity of Alberta
Fundersnot available
KeywordsMedicineCardiac catheterizationFick principleCardiac outputVentilation (architecture)HemodynamicsCardiologyMechanical engineering

Abstract

fetched live from OpenAlex

Oxygen consumption (VO(2) ) is an important part of hemodynamics using the direct Fick principle in children undergoing cardiac catheterization. Accurate measurement of VO(2) is vital. Obviously, any error in the measurement of VO(2) will translate directly into an equivalent percentage under- or overestimation of blood flows and vascular resistances. It remains common practice to estimate VO(2) values from published predictive equations. Among these, the LaFarge equation is the most commonly used equation and gives the closest estimation with the least bias and limits of agreement. However, considerable errors are introduced by the LaFarge equation, particularly in children younger than 3 years of age. Respiratory mass spectrometry remains the "state-of-the-art" method, allowing highly sensitive, rapid and simultaneous measurement of multiple gas fractions. The AMIS 2000 quadrupole respiratory mass spectrometer system has been adapted to measure VO(2) in children under mechanical ventilation with pediatric ventilators during cardiac catheterization. The small sampling rate, fast response time and long tubes make the equipment a unique and powerful tool for bedside continuous measurement of VO(2) in cardiac catheterization for both clinical and research purposes.

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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.104
GPT teacher head0.338
Teacher spread0.235 · 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

Citations34
Published2012
Admission routes1
Has abstractyes

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