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Record W3110514806 · doi:10.1093/ehjci/ehaa946.0963

Role of angiotensin peptides in risk stratification and prognostication for heart failure: focus on plasma Ang 1–7/Ang II ratio

2020· article· en· W3110514806 on OpenAlexaffabout
K Wang, R Basu, Marko Poglitsch, Jeffrey A. Bakal, G. Oudit

Bibliographic record

VenueEuropean Heart Journal · 2020
Typearticle
Languageen
FieldMedicine
TopicHeart Failure Treatment and Management
Canadian institutionsUniversity of AlbertaCanadian VIGOUR Centre
Fundersnot available
KeywordsMedicineInternal medicineHeart failureRenin–angiotensin systemAngiotensin IIAldosteroneProspective cohort studyCohortCardiologyPlasma renin activityEndocrinologyBlood pressure

Abstract

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Abstract Background ACE2 and Ang 1–7 are endogenous negative regulators of the renin-angiotensin system (RAS) exerting cardioprotective effects in models of heart failure (HF). Recombinant ACE2 markedly increased plasma Ang 1–7 and lowered Ang II levels in clinical trials. Elevated plasma ACE2 activity is associated with adverse outcomes in HF patients. However, the direct effects of systemic and tissue ACE2 activation on angiotensin peptides in relation to long-term HF outcomes has yet to be examined. Purpose To generate insights into the ACE2 mediated cardioprotective arm through the relative levels of its substrates and products using the plasma Ang 1–7/Ang II ratio, and assess its prognostic utility in HF patients. Methods 110 HF patients were prospectively enrolled from outpatient clinics and the emergency department. Comprehensive circulating and equilibrium levels of plasma angiotensin peptides were assessed using novel liquid chromatography-mass spectrometry/mass spectroscopy techniques. Plasma aldosterone, BNP, active renin activity and clinical profiles were captured at baseline. Patients were stratified into above and below median cohorts based on equilibrium and circulating levels of Ang 1–7/Ang II ratio, as a surrogate for ACE2 functionality. During a median follow-up of 5.1±0.8 years, composite clinical outcomes were assessed through all-cause in-patient hospitalizations and mortality. Results Circulating and equilibrium angiotensin peptide levels strongly correlated in our patient cohort. All-cause mortality for HF patients with equilibrium Ang 1–7/Ang II ratios above the median showed higher survival rates compared to below median patients (76.4% vs. 50.9%; p=0.004); similar results were observed for circulating Ang 1–7/Ang II ratios (72.7% vs. 54.5%; p=0.041). Adjusting for covariates, elevated equilibrium (HR: 0.24; 95% CI: 0.09 to 0.69; p=0.008) and circulating (HR: 0.35; 95% CI: 0.13 to 0.94; p=0.036) Ang 1–7/Ang II ratios was associated with improved survival. Lower hospitalization duration was also associated with elevated equilibrium (p<0.001) and circulating (p=0.023) Ang 1–7/Ang II ratios. In nested models, net reclassification analysis showed considerable improvement in risk prediction for all-cause mortality at 5 years provided by both the equilibrium (+45.0% [95% CI: 7.3% to 82.7%]) and circulating Ang 1–7/Ang II ratios (+24.3% [95% CI: 0.4% to 59.6%]) respectively. Conclusions We extensively profiled plasma angiotensin peptides in HF patients and identified elevated ACE2 signature, reflected through the Ang 1–7/Ang II ratio, as an independent and incremental predictor of beneficial outcomes, higher survival rate, and decreased hospitalization duration. These findings provide important clinical evidence supporting strategies aiming to promote the beneficial ACE2/Ang 1–7/Mas receptor axis concurrent with RAS blockade therapies inhibiting the detrimental ACE/Ang II/AT1 receptor axis. Funding Acknowledgement Type of funding source: Public grant(s) – National budget only. Main funding source(s): Alberta Innovates, Canadian Institute of Health Research

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.030
GPT teacher head0.269
Teacher spread0.239 · 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 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
Published2020
Admission routes2
Has abstractyes

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