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Record W3033426817 · doi:10.1159/000508498

The Prospective Studies of Atherosclerosis (Proof-ATHERO) Consortium: Design and Rationale

2020· article· en· W3033426817 on OpenAlexaff
Lena Tschiderer, Lisa Seekircher, Gerhard Klingenschmid, Raffaele Izzo, Damiano Baldassarre, Bernhard Iglseder, Laura Calabresi, Jing Liu, Jackie F. Price, Jang‐Ho Bae, Frank P. Brouwers, Eric de Groot, Caroline Schmidt, Göran Bergström, Gülay Aşçı, Paolo Gresele, Shuhei Okazaki, Kostas Kapellas, Manuel F. Landecho, Naveed Sattar, Stefan Agewall, Christopher D. Byrne, Prabath W.B. Nanayakkara, Αikaterini Papagianni, Miles D. Witham, Enrique Bernal, Robert Ekart, Michiel A. van Agtmael, Mário Fritsch Neves, Eiichi Sato, М. В. Ежов, James Walters, Michael Hecht Olsen, Radojica Stolić, Dorota Zozulińska‐Ziółkiewicz, M Hanefeld, Daniel Staub, Michiaki Nagai, Pythia T. Nieuwkerk, Menno V. Huisman, Akihiko Kato, Hirokazu Honda, Grace Párraga, Dianna J. Magliano, Rafael Gabriel, Tatjana Rundek, Mark A. Espeland, Stefan Kiechl, Johann Willeit, Lars Lind, Jean‐Philippe Empana, Eva Lonn, Tomi-Pekka Tuomainen, Alberico L. Catapano, Kuo‐Liong Chien, Dirk Sander, Maryam Kavousi, Joline W. J. Beulens, Michiel L. Bots, Michael Sweeting, Matthias Lorenz, Peter Willeit

Bibliographic record

VenueGerontology · 2020
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Health and Disease Prevention
Canadian institutionsMcMaster UniversityPopulation Health Research InstituteHamilton General HospitalWestern University
FundersNational Institute of Neurological Disorders and StrokeNational Heart, Lung, and Blood InstituteErasmus Universitair Medisch Centrum RotterdamTechnische Universität MünchenCentre National de la Recherche ScientifiqueInstitut National de la Santé et de la Recherche MédicaleNational Taiwan UniversityItä-Suomen YliopistoChang Gung Medical FoundationChang Gung UniversityAustrian Science FundNational Taiwan University HospitalUniversità degli Studi di Milano
KeywordsMedicineProspective cohort studyGerontologyInternal medicinePsychology

Abstract

fetched live from OpenAlex

Atherosclerosis - the pathophysiological mechanism shared by most cardiovascular diseases - can be directly or indirectly assessed by a variety of clinical tests including measurement of carotid intima-media thickness, carotid plaque, -ankle-brachial index, pulse wave velocity, and coronary -artery calcium. The Prospective Studies of Atherosclerosis -(Proof-ATHERO) consortium (https://clinicalepi.i-med.ac.at/research/proof-athero/) collates de-identified individual-participant data of studies with information on atherosclerosis measures, risk factors for cardiovascular disease, and incidence of cardiovascular diseases. It currently comprises 74 studies that involve 106,846 participants from 25 countries and over 40 cities. In summary, 21 studies recruited participants from the general population (n = 67,784), 16 from high-risk populations (n = 22,677), and 37 as part of clinical trials (n = 16,385). Baseline years of contributing studies range from April 1980 to July 2014; the latest follow-up was until June 2019. Mean age at baseline was 59 years (standard deviation: 10) and 50% were female. Over a total of 830,619 person-years of follow-up, 17,270 incident cardiovascular events (including coronary heart disease and stroke) and 13,270 deaths were recorded, corresponding to cumulative incidences of 2.1% and 1.6% per annum, respectively. The consortium is coordinated by the Clinical Epidemiology Team at the Medical University of Innsbruck, Austria. Contributing studies undergo a detailed data cleaning and harmonisation procedure before being incorporated in the Proof-ATHERO central database. Statistical analyses are being conducted according to pre-defined analysis plans and use established methods for individual-participant data meta-analysis. Capitalising on its large sample size, the multi-institutional collaborative Proof-ATHERO consortium aims to better characterise, understand, and predict the development of atherosclerosis and its clinical consequences.

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 score0.542
Threshold uncertainty score0.181

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.112
GPT teacher head0.340
Teacher spread0.228 · 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

Citations4
Published2020
Admission routes1
Has abstractyes

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