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Record W4405375273 · doi:10.3390/jcdd11120402

Identification and Evaluation of Angiogenesis-Related Proteins That Predict Major Adverse Cardiovascular Events in Patients with Peripheral Artery Disease

2024· article· en· W4405375273 on OpenAlexafffund
Ben Li, Farah Shaikh, Houssam Younes, Batool Abuhalimeh, Jason Chin, Khurram Rasheed, Abdelrahman Zamzam, Rawand Abdin, Mohammad Qadura

Bibliographic record

VenueJournal of Cardiovascular Development and Disease · 2024
Typearticle
Languageen
FieldMedicine
TopicLipid metabolism and disorders
Canadian institutionsMcMaster UniversityUniversity of TorontoSt. Michael's Hospital
FundersUniversity of TorontoBlair Foundation
KeywordsMedicineMyocardial infarctionInternal medicineAngiogenesisCohortStroke (engine)BiomarkerCoronary artery diseaseProportional hazards modelCardiologyDiseaseCohort studyOncologyBiology

Abstract

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Background: The most common cause of death in patients with peripheral artery disease (PAD) are major adverse cardiovascular events (MACEs), including myocardial infarction (MI) and stroke. However, data on biomarkers that could be used to help predict MACEs in patients with PAD to guide clinical decision making is limited. Angiogenesis-related proteins have been demonstrated to play an important role in systemic atherosclerosis and may act as prognostic biomarkers for MACEs in patients with PAD. In this study, we evaluated a large panel of angiogenesis-related proteins and identified specific biomarkers associated with MACEs in patients with PAD. Methods: We conducted a prognostic study using a prospectively recruited cohort of 406 patients (254 with PAD and 152 without PAD). Plasma concentrations of 22 circulating angiogenesis-related proteins were measured at baseline, and the cohort was followed for 2 years. The primary outcome was 2-year MACEs (composite of MI, stroke, or death). Plasma protein concentrations were compared between PAD patients with and without 2-year MACEs using Mann–Whitney U tests. Differentially expressed proteins were further investigated in terms of their prognostic potential. Specifically, Cox proportional hazards analysis was performed to determine the independent association between differentially expressed proteins and 2-year MACEs, controlling for all baseline demographic and clinical characteristics, including existing coronary artery disease and cerebrovascular disease. Kaplan–Meier analysis was conducted to assess 2-year freedom from MACEs in patients with low vs. high levels of the differentially expressed proteins based on median plasma concentrations. Results: The mean age of the cohort was 68.8 (SD 11.1), and 134 (33%) patients were female. Two-year MACEs occurred in 63 (16%) individuals. The following proteins were significantly elevated in PAD patients with 2-year MACEs compared to those without 2-year MACEs: endostatin (69.15 [SD 58.15] vs. 51.34 [SD 29.07] pg/mL, p < 0.001), angiopoietin-like protein 4 (ANGPTL4) (0.20 [SD 0.09] vs. 0.12 [SD 0.04] pg/mL, p < 0.001), and ANGPTL3 (51.57 [SD 21.92] vs. 45.16 [SD 21.90] pg/mL, p = 0.001). Cox proportional hazards analysis demonstrated that these three proteins were independently associated with 2-year MACEs after adjusting for all baseline demographic and clinical characteristics: endostatin (HR 1.39 [95% CI 1.12–1.71] p < 0.001), ANGPTL4 (HR 1.35 [95% CI 1.08–1.68], p < 0.001), and ANGPTL3 (HR 1.35 [95% CI 1.12–1.63], p < 0.001). Over a 2-year follow-up period, patients with higher levels of endostatin, ANGPTL4, and ANGPTL3 had a lower freedom from MACEs. Supplementary analysis demonstrated that these three proteins were not significantly associated with 2-year MACEs in patients without PAD. Conclusions: Among a panel of 22 angiogenesis-related proteins, endostatin, ANGPTL4, and ANGPTL3 were identified to be independently and specifically associated with 2-year MACEs in patients with PAD. Measurement of plasma concentrations of these proteins can support MACE risk stratification in patients with PAD, thereby informing clinical decisions on multidisciplinary referrals to cardiologists, neurologists, and vascular medicine specialists and guiding aggressiveness of medical treatment, thereby improving cardiovascular outcomes in patients with PAD.

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)0.002
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 score0.099
Threshold uncertainty score0.587

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
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 head0.010
GPT teacher head0.215
Teacher spread0.206 · 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

Citations1
Published2024
Admission routes2
Has abstractyes

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