ReviewComputational and mathematical methods in medicine2013
Investigation on cardiovascular risk prediction using physiological parameters.
Review in Computational and mathematical methods in medicine, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed.
- Atherosclerosis diagnosis from magnetic resonance images: an empirical approach to automate carotid vessel wall segmentation and feature-based prediction.Physical and engineering sciences in medicine · 2026Article
- A correlation study of beat-to-beat R-R intervals and pulse arrival time under natural state and cold stimulation.Scientific reports · 2021Article
- Trends and Challenges of Wearable Multimodal Technologies for Stroke Risk Prediction.Sensors (Basel, Switzerland) · 2021Review
- Blood pressure waveform contour analysis for assessing peripheral resistance changes in sepsis.Biomedical engineering online · 2018Article
- Peripheral vascular disease assessment in the lower limb: a review of current and emerging non-invasive diagnostic methods.Biomedical engineering online · 2018Review
- Hemodynamic effects of perfusion level of peripheral ECMO on cardiovascular system.Biomedical engineering online · 2018Article
- A Combined Linkage and Exome Sequencing Analysis for Electrocardiogram Parameters in the Erasmus Rucphen Family Study.Frontiers in genetics · 2016Article
- Study to Predict Vascular Dysfunctions in High Risk Young Adults- An Immediate Non-Invasive Investigation to Prevent Early Vascular Ageing.Journal of clinical and diagnostic research : JCDR · 2015Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cardiovascular disease (CVD) is the leading cause of death worldwide. Early prediction of CVD is urgently important for timely prevention and treatment. Incorporation or modification of new risk factors that have an additional independent prognostic value of existing prediction models is widely used for improving the performance of the prediction models. This paper is to investigate the physiological parameters that are used as risk factors for the prediction of cardiovascular events, as well as summarizing the current status on the medical devices for physiological tests and discuss the potential implications for promoting CVD prevention and treatment in the future. The results show that measures extracted from blood pressure, electrocardiogram, arterial stiffness, ankle-brachial blood pressure index (ABI), and blood glucose carry valuable information for the prediction of both long-term and near-term cardiovascular risk. However, the predictive values should be further validated by more comprehensive measures. Meanwhile, advancing unobtrusive technologies and wireless communication technologies allow on-site detection of the physiological information remotely in an out-of-hospital setting in real-time. In addition with computer modeling technologies and information fusion. It may allow for personalized, quantitative, and real-time assessment of sudden CVD events.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.