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Routine Unloading in Patients Treated With Extracorporeal Membrane Oxygenation for Cardiogenic Shock

2020· letter· en· W3110136997 on OpenAlexaff
Sean van Diepen

Bibliographic record

VenueCirculation · 2020
Typeletter
Languageen
FieldEngineering
TopicMechanical Circulatory Support Devices
Canadian institutionsCanadian VIGOUR Centre
Fundersnot available
KeywordsCardiogenic shockExtracorporeal membrane oxygenationMedicineMyocardial infarctionCardiologyInternal medicineLife supportIntensive care medicine

Abstract

fetched live from OpenAlex

Cardiogenic ShockMixed Outcomes Set the Stage for Future Trials Article, see p 2095 C ardiogenic shock (CS) is most commonly caused by acute myocardial infarction, accounting for 80% of cases. 1 Despite improvements in revascularization and systems of care, mortality rates are still more than 30% in contemporary studies.[2][3][4] Hence, for critically ill patients with CS who do not respond to (or who deteriorate with) initial medical therapy and supportive measures, temporary mechanical circulatory support has emerged as a promising measure to interrupt the downward spiral of hypotension and end-organ hypoperfusion that may portend cardiac death.5,6 Among the temporary mechanical circulatory support options available, venoarterial extracorporeal membrane oxygenation (VA-ECMO) provides robust biventricular and respiratory support and may be the preferred option in patients requiring cardiopulmonary resuscitation, those with poor oxygenation that is not expected to improve with other devices, and those requiring biventricular support.6 One of the recognized complications of peripheral femoral VA-ECMO cannulation is the retrograde aortic perfusion of the heart.In some patients, the resultant increase in left ventricular (LV) afterload may impair LV ejection, raise the LV end-diastolic pressure, and potentially lead to North-South (or Harlequin) syndrome wherein pulmonary edema impairs gas exchange and deoxygenated blood enters the aorta leading to further coronary or cerebral ischemia.7,8 To minimize this complication, physicians caring for patients on VA-ECMO often aim to prevent a significant rise in LV end-diastolic pressure and to maintain aortic ejection by unloading the LV, either noninvasively with inotropes or with additional mechanical circulatory support.7 Whether these strategies should be used immediately at the time of cannulation, or provisionally in patients with either rising LV end-diastolic pressures measured with pulmonary arterial catheters, or clinical evidence of pulmonary edema or impaired gas exchange remains unclear.Thus far, high-quality evidence is lacking and evidence is limited to nonrandomized studies.In a seminal 2019 meta-analysis of 17 observational VA-ECMO studies Russo et al 9 reported that LV unloading with intra-aortic balloon pump, Impella with ECMO (ie, ECMELLA), or additional transeptal left atrial drainage catheters was associated with a lower risk of all-cause mortality at the expense of higher hemolysis rates.The retrospective nature of these data, however, precluded causal inferences and could not exclude treatment and selection biases or identify provisional versus immediate unloading strategies.In addition, the sum of the ECMELLA experience was limited to only 453 patients.In this study, Schrage and colleagues performed a retrospective analysis of a 16-center international cohort of patients with cardiogenic shock (77% male, 63% acute myocardial infarction, 67% precannulation cardiac arrest, 33% cannulation during extracorporeal cardiopulmonary resuscitation) treated with ECMO. 10

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)0.006
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: Editorial · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0120.007
Insufficient payload (model declined to judge)0.0030.001

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 head0.201
Teacher spread0.184 · 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
GenreEditorial

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".

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Citations5
Published2020
Admission routes1
Has abstractno

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