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Record W4211058426 · doi:10.1097/ccm.0000000000001847

Guidelines for the Appropriate Use of Bedside General and Cardiac Ultrasonography in the Evaluation of Critically Ill Patients—Part II: Cardiac Ultrasonography

2016· article· en· W4211058426 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCritical Care Medicine · 2016
Typearticle
Languageen
FieldMedicine
TopicUltrasound in Clinical Applications
Canadian institutionsMcMaster UniversityFoothills Medical CentreUniversity of Calgary
Fundersnot available
KeywordsMedicineIntensivistGrading (engineering)TerminologyAppropriate Use CriteriaIntensive care medicineIntensive careInternal medicine

Abstract

fetched live from OpenAlex

Objective: To establish evidence-based guidelines for the use of bedside cardiac ultrasound, echocardiography, in the ICU and equivalent care sites. Methods: Grading of Recommendations, Assessment, Development and Evaluation system was used to rank the “levels” of quality of evidence into high (A), moderate (B), or low (C) and to determine the “strength” of recommendations as either strong (strength class 1) or conditional/weak (strength class 2), thus generating six “grades” of recommendations (1A–1B–1C–2A–2B–2C). Grading of Recommendations, Assessment, Development and Evaluation was used for all questions with clinically relevant outcomes. RAND Appropriateness Method, incorporating the modified Delphi technique, was used in formulating recommendations related to terminology or definitions or in those based purely on expert consensus. The process was conducted by teleconference and electronic-based discussion, following clear rules for establishing consensus and agreement/disagreement. Individual panel members provided full disclosure and were judged to be free of any commercial bias. Results: Forty-five statements were considered. Among these statements, six did not achieve agreement based on RAND appropriateness method rules (majority of at least 70%). Fifteen statements were approved as conditional recommendations (strength class 2). The rest (24 statements) were approved as strong recommendations (strength class 1). Each recommendation was also linked to its level of quality of evidence and the required level of echo expertise of the intensivist. Key recommendations, listed by category, included the use of cardiac ultrasonography to assess preload responsiveness in mechanically ventilated (1B) patients, left ventricular (LV) systolic (1C) and diastolic (2C) function, acute cor pulmonale (ACP) (1C), pulmonary hypertension (1B), symptomatic pulmonary embolism (PE) (1C), right ventricular (RV) infarct (1C), the efficacy of fluid resuscitation (1C) and inotropic therapy (2C), presence of RV dysfunction (2C) in septic shock, the reason for cardiac arrest to assist in cardiopulmonary resuscitation (1B–2C depending on rhythm), status in acute coronary syndromes (ACS) (1C), the presence of pericardial effusion (1C), cardiac tamponade (1B), valvular dysfunction (1C), endocarditis in native (2C) or mechanical valves (1B), great vessel disease and injury (2C), penetrating chest trauma (1C) and for use of contrast (1B–2C depending on indication). Finally, several recommendations were made regarding the use of bedside cardiac ultrasound in pediatric patients ranging from 1B for preload responsiveness to no recommendation for RV dysfunction. Conclusions: There was strong agreement among a large cohort of international experts regarding several class 1 recommendations for the use of bedside cardiac ultrasound, echocardiography, in the ICU. Evidence-based recommendations regarding the appropriate use of this technology are a step toward improving patient outcomes in relevant patients and guiding appropriate integration of ultrasound into critical care practice.

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.

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)0.003
metaresearch head score (Gemma)0.071
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.165
Threshold uncertainty score0.937

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.071
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
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 head0.135
GPT teacher head0.418
Teacher spread0.283 · 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