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Current Targets and Future Directions of Positive Inotropes for Heart Failure

2023· review· en· W4388130558 on OpenAlexaff
Shadreen Fairuz, Ang Chee Wei, Fatima Mraiche, Joo Kheng Goh

Bibliographic record

VenueCurrent Medicinal Chemistry · 2023
Typereview
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMilrinoneLevosimendanInotropeDobutamineHeart failureMedicineDigoxinIntensive care medicineAdverse effectCardiologyHeart diseaseInternal medicineEjection fractionHemodynamics

Abstract

fetched live from OpenAlex

While a congestive heart failure patient will ultimately need an assist device or even a replacement heart as the disease progresses, not every patient is qualified for such advanced therapy. Such patients awaiting better circulatory support benefit from positive inotropes in the meantime as palliative care. These agents are often prescribed in patients with acute decompensated heart failure, with reduced left ventricular ejection fraction and symptoms of organ dysfunction. Although positive inotropes, for example, digoxin, dobutamine, milrinone, levosimendan, etc., are successfully marketed and in use, a lot of their adverse effects, like arrhythmias, hypotension, and even sudden cardiac death, are rather encouraging further research on the development of novel positive inotropes. This review has investigated the molecular mechanisms of some of these adverse effects in terms of the proteins they target, followed by research on newer targets. Studies from 2013-2023 that have reported new small molecules with positive inotropic effects have been revisited in order to determine the progress made so far in drug discovery.

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)0.001
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: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.002

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 head0.021
GPT teacher head0.300
Teacher spread0.279 · 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
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

Citations3
Published2023
Admission routes1
Has abstractyes

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