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Record W2186753845 · doi:10.21693/1933-088x-13.4.179

Pathophysiologic Principles in the Management of Severe PAH

2015· article· en· W2186753845 on OpenAlexaff
John Granton

Bibliographic record

VenueAdvances in Pulmonary Hypertension · 2015
Typearticle
Languageen
FieldMedicine
TopicPulmonary Hypertension Research and Treatments
Canadian institutionsToronto General HospitalUniversity of TorontoUniversity Health NetworkMount Sinai Hospital
Fundersnot available
KeywordsAfterloadMedicineCardiologyInternal medicinePulmonary hypertensionVolume overloadHeart failureVentricleDecompensationPulmonary embolismContext (archaeology)Intensive care medicine

Abstract

fetched live from OpenAlex

In the face of tremendous advances in our understanding of the pathophysiology and new treatment options, for many patients, pulmonary arterial hypertension (PAH) remains a progressive condition. The often-relentless reduction in the cross-sectional area of the pulmonary vasculature leads to progressive increase in right ventricular (RV) afterload. Although the right ventricle can adapt to an increase in afterload, progression of the pulmonary vasculopathy in PAH causes many patients to develop progressive RV failure.1 Alternately, for those with other forms of pulmonary hypertension, worsening lung disease or cardiac disease may destabilize the RV function. Acute RV decompensation may be triggered by disorders that lead to either an acute increase in cardiac demand (such as sepsis, surgery, or pregnancy), or an increase in ventricular afterload (such as an interruption in medical therapy or pulmonary embolism), or destabilization of a compensated RV (such as arrhythmia or volume overload). The poor reserve of the RV, RV ischemia, and adverse RV influence on left ventricular filling may lead to a global reduction in oxygen delivery and multi-organ failure.2 The goals of this article are to provide an approach to right heart failure in the context of an increase in its afterload. This article will focus on pathophysiologic principles on which to build an approach to medical therapies. Mechanical and surgical strategies will be the focus in the accompanying article by Dr de Perrot.

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 score0.420
Threshold uncertainty score0.424

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.059
GPT teacher head0.312
Teacher spread0.253 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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