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Intraoperative assessment of diastolic function: utility of echocardiography

2003· article· en· W2331909437 on OpenAlexaff
George Djaiani, Stanton K. Shernan

Bibliographic record

VenueCurrent Opinion in Anaesthesiology · 2003
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Function and Risk Factors
Canadian institutionsToronto General HospitalUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicinePerioperativeDiastoleDiastolic functionCardiologyModalitiesInternal medicineIntensive care medicineSurgeryBlood pressure

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: This review discusses the current and future applications of different echocardiographic modalities in evaluating diastolic function intraoperatively. RECENT FINDINGS: Normal diastolic function is required for optimal cardiac performance. There is sufficient evidence to support the significant prevalence of preoperative diastolic dysfunction and its incidence following cardiac surgery, however controversy still exists regarding the impact of diastolic dysfunction on adverse outcomes. Echocardiography provides a relatively safe, practical and noninvasive means to evaluate perioperative diastolic function, however conventional measures may be limited by the impact of changes in heart rate, rhythm and loading conditions. Newer echocardiographic modalities are reportedly less sensitive to acute changes in loading conditions, and may therefore complement the use of conventional echocardiographic techniques in the perioperative period. SUMMARY: The availability of effective technology for diagnosing the presence and progression of perioperative diastolic function should assist in the identification of high-risk cardiac surgical patients who may benefit from appropriate triaging and therapeutic intervention.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.434

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.046
GPT teacher head0.348
Teacher spread0.301 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations7
Published2003
Admission routes1
Has abstractyes

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