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Record W2589063450 · doi:10.1177/2045893216681025

Resistance over compliance describes right ventricular afterload better than resistance‐compliance time: a friendly amendment

2016· article· en· W2589063450 on OpenAlexaff
Thenappan Thenappan, Stephen L. Archer, Ε. Kenneth Weir

Bibliographic record

VenuePulmonary Circulation · 2016
Typearticle
Languageen
FieldMedicine
TopicPulmonary Hypertension Research and Treatments
Canadian institutionsQueen's University
FundersNational Heart, Lung, and Blood Institute
KeywordsMedicinePulmonary hypertensionAfterloadVascular resistanceCompliance (psychology)VentricleCardiologyInternal medicinePulsatile flowHemodynamics

Abstract

fetched live from OpenAlex

In their paper on combined pre- and post-capillary pulmonary hypertension, Assad et al. say that “the resistance-compliance (RC) time has emerged as a measure of pulmonary vascular physiology that integrates the mean and pulsatile afterload of the right ventricle.”1 They discuss reports in the literature of changes in RC time in a variety of conditions. The findings in their study show that “the RC times in combined post-capillary and pre-capillary pulmonary hypertension and in pulmonary arterial hypertension were nearly the same, and both were almost twice as high as that in isolated post-capillary pulmonary hypertension.”1 However, the nearly 2000 patients without pulmonary hypertension demonstrated that a “normal” RC time lies somewhere in-between. We consider that this shows that the RC time does not integrate the mean and pulsatile afterloads of the right ventricle. Indeed, as pulmonary hypertension worsens, the components of RC time go in opposite directions: pulmonary vascular resistance (PVR) increases, while pulmonary vascular compliance (PVC) decreases. Consequently, one offsets the other in the term, RC time. For the clinician trying to describe the severity of the afterload to right ventricular ejection, would it not make more sense to calculate the PVR times the reciprocal of the compliance (1/PVC). This (resistance over compliance; ROC) would increase steadily as the pulmonary hypertension worsens and would be more intuitive. To illustrate this, we calculated the RC time and ROC for the four groups of patients described by Assad et al.: controls, isolated post-capillary pulmonary hypertension, combined post-capillary and pre-capillary pulmonary hypertension, and pulmonary arterial hypertension.1 We used the mean PVR and PVC of the groups to compute the RC time and ROC as we did not have the individual patient level data. The ROC increased linearly as the severity of pulmonary hypertension increased from the control group to patients with isolated post-capillary pulmonary hypertension, combined post-capillary and pre-capillary pulmonary hypertension, and pulmonary arterial hypertension (Fig. 1). Comparison of RC vs. ROC in different forms and severities of pulmonary hypertension. These are patients who underwent right heart catheterization from 1998 to 2014 at Vanderbilt University and were in Vanderbilt’s Synthetic Derivative database.1 Controls are patients with no pulmonary hypertension. CpcPH, combined post-capillary and pre-capillary pulmonary hypertension; IpcPH, isolated post-capillary pulmonary hypertension; PAH, pulmonary arterial hypertension; RC, resistance-compliance time; ROC, resistance over compliance.

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)0.016
metaresearch head score (Gemma)0.068
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.026
Threshold uncertainty score0.088

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.068
Meta-epidemiology (narrow)0.0040.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0040.004
Science and technology studies0.0010.005
Scholarly communication0.0060.006
Open science0.0030.004
Research integrity0.0030.008
Insufficient payload (model declined to judge)0.0260.011

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 head0.031
GPT teacher head0.281
Teacher spread0.249 · 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 designTheoretical or conceptual
Domainnot available
GenreCommentary

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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Citations0
Published2016
Admission routes1
Has abstractyes

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