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Record W2032618042 · doi:10.1097/mcc.0000000000000100

Current tools for assessing heart function and perfusion adequacy

2014· review· en· W2032618042 on OpenAlexaff
Sheldon Magder

Bibliographic record

VenueCurrent Opinion in Critical Care · 2014
Typereview
Languageen
FieldMedicine
TopicHemodynamic Monitoring and Therapy
Canadian institutionsRoyal Victoria HospitalMcGill University Health Centre
Fundersnot available
KeywordsMedicineCardiac outputCardiac function curveReliability (semiconductor)PerfusionCritically illIntensive care medicineVasoactiveRisk analysis (engineering)CardiologyInternal medicineHemodynamicsHeart failure

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Many devices are currently available for measuring cardiac output and function. Understanding the utility of these devices requires an understanding of the determinants of cardiac output and cardiac function, and the use of these parameters in the management of critically ill patients. This review stresses the meaning of the physiological measures that are obtained with these devices and how these values can be used. RECENT FINDINGS: Evaluation of devices for haemodynamic monitoring can include just measurement of cardiac output, the potential to track spontaneous changes in cardiac output or changes produced by volume infusions or vasoactive drugs, or the ability to assess cardiac function. Each of these puts different demands on the need for accuracy, precision, and reliability of the devices, and thus devices must be evaluated based on the clinical need. SUMMARY: Evaluation of cardiac function is useful when first dealing with an unstable patient, but for ongoing management measurement of cardiac output itself is key and even more so the trend in relationship to the patient's overall condition. This evaluation would be greatly benefited by the addition of objective measures of tissue perfusion.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.910
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.319
GPT teacher head0.541
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
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
Published2014
Admission routes1
Has abstractyes

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