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Record W2471486224 · doi:10.2196/resprot.5619

Vascular Health Assessment of The Hypertensive Patients (VASOTENS) Registry: Study Protocol of an International, Web-Based Telemonitoring Registry for Ambulatory Blood Pressure and Arterial Stiffness

2016· article· en· W2471486224 on OpenAlexvenueno aff
Stefano Omboni, I.N. Posokhov, Gianfranco Parati, Alberto Avolio, А. Н. Рогоза, Yu. V. Kotovskaya, María Lorenza Muiesan, Yа. A. Orlova, Е. А. Григоричева, E. Cardona Muñoz, Parounak Zelveian, Telmo Pereira, João Maldonado

Bibliographic record

VenueJMIR Research Protocols · 2016
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Health and Disease Prevention
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineArterial stiffnessPulse wave velocityBlood pressureAmbulatory blood pressureAmbulatoryPulse pressureCardiologyInternal medicineEmergency medicinePhysical therapy

Abstract

fetched live from OpenAlex

BACKGROUND: Hypertension guidelines recommend ambulatory blood pressure (ABP), central aortic pressure (CAP), and pulse wave velocity (PWV) as parameters for estimating blood pressure (BP) control and vascular impairment. Recent advances in technology have enabled devices to combine non-invasive estimation of these parameters over the 24-hour ABP monitoring. However, currently there is limited evidence on the usefulness of such an approach for routine hypertension management. OBJECTIVE: We recently launched an investigator-initiated, international, multicenter, observational, prospective study, the Vascular health Assessment Of The Hypertensive patients (VASOTENS) Registry, aimed at (1) evaluating non-invasive 24-hour ABP and arterial stiffness estimates (through 24-hour pulse wave analysis, PWA) in hypertensive subjects undergoing ambulatory blood pressure monitoring (ABPM) for clinical reasons; (2) assessing the changes in estimates following treatment; (3) weighing the impact of 24-hour PWA on target organ damage and cardiovascular prognosis; (4) assessing the relationship between arterial stiffness, BP absolute mean level and variability, and prognosis; and (5) validating the use of a 24-hour PWA electronic health (e-health) solution for hypertension screening. METHODS: Approximately 2000 subjects, referred to 20 hypertension clinics for routine diagnostic evaluation and follow-up of hypertension of any severity or stage, will be recruited. Data collection will include ABPM, performed with a device allowing simultaneous non-invasive assessment of 24-hour CAP and arterial stiffness (BPLab), and clinical data (including cardiovascular outcomes). As recommended by current guidelines, each patient will be followed-up with visits occurring at regular intervals (ideally every 6 months, and not less than once a year depending on disease severity). A Web-based telemedicine platform (THOLOMEUS) will be used for data collection. The use of the telemedicine system will allow standardized and centralized data collection, data validation by experts and counseling to remote centers, setup and maintenance of the Registry, and prompt data analysis. RESULTS: First follow-up results are expected to be available in the next 2 years. CONCLUSIONS: The results of the VASOTENS Registry will help define the normalcy thresholds for current and future indices derived from 24-hour PWA, according to outcome data, and will also provide supporting evidence for the inclusion of this type of evaluation in hypertension management. TRIAL REGISTRATION: Clinicaltrials.gov NCT02577835; https://clinicaltrials.gov/ct2/show/NCT02577835 (Archived by WebCite at http://www.Webcitation.org/6hzZBKY2Q).

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)0.024
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.024
Threshold uncertainty score0.125

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.017
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.004
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0030.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0110.005

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 head0.090
GPT teacher head0.499
Teacher spread0.409 · 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 designNot applicable
Domainnot available
GenreProtocol

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

Citations19
Published2016
Admission routes1
Has abstractyes

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