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Record W4283826069 · doi:10.1097/mcc.0000000000000957

Inotrope and vasopressor use in cardiogenic shock: what, when and why?

2022· review· en· W4283826069 on OpenAlexaff
Kira Hu, Rebecca Mathew

Bibliographic record

VenueCurrent Opinion in Critical Care · 2022
Typereview
Languageen
FieldEngineering
TopicMechanical Circulatory Support Devices
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsInotropeMedicineLevosimendanDobutamineCardiogenic shockMilrinonePlaceboIntensive care medicineNorepinephrineSeptic shockShock (circulatory)IntensivistAnesthesiaCardiologyIntensive care unitInternal medicineSepsisHemodynamicsMyocardial infarction

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Despite increasing interest in the management of cardiogenic shock (CS), mortality rates remain unacceptably high. The mainstay of supportive treatment includes vasopressors and inotropes. These medications are recommended in international guidelines and are widely used despite limited evidence supporting safety and efficacy in CS. RECENT FINDINGS: The OptimaCC trial further supports that norepinephrine should continue to be the first-line vasopressor of choice in CS. The CAPITAL DOREMI trial found that milrinone is not superior to dobutamine in reducing morbidity and mortality in CS. Two studies currently underway will offer the first evidence of the necessity of inotrope therapy in placebo-controlled trials: CAPITAL DOREMI2 will randomize CS patients to inotrope or placebo in the initial resuscitation of shock to evaluate the efficacy of inotrope therapy and LevoHeartShock will examine the efficacy of levosimendan against placebo in early CS requiring vasopressor therapy. SUMMARY: Review of the current literature fails to show significant mortality benefit with any specific vasopressor or inotropic in CS patients. The upcoming DOREMI 2 and levosimendan versus placebo trials will further tackle the question of inotrope necessity in CS. At this time, inotrope selection should be guided by physician experience, availability, cost, and most importantly, individual patients' response to therapy.

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 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 score0.986
Threshold uncertainty score1.000

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 communication0.0000.001
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 head0.250
GPT teacher head0.405
Teacher spread0.155 · 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

Citations18
Published2022
Admission routes1
Has abstractyes

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