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Hypertension is asymptomatic and also referred to as the "silent killer" until it progresses to a severe stage or causes target organ disease. Patients may experience symptoms stemming from the strain on blood vessels and tissues in various organs or the heart's increased workload.Physical exams might show no abnormalities other than high blood pressure. Signs of vascular damage, when present, correspond to the organs supplied by the affected vessels, leading to target organ damage. For...
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Hypertension is a chronic condition in which the blood's force against artery walls is excessively high, posing risks such as heart disease. The condition's underlying mechanisms involve complex interactions among the cardiovascular, kidney, and autonomic nervous systems.Renin-Angiotensin-Aldosterone System (RAAS): This system significantly influences blood pressure regulation. When blood pressure decreases, the kidneys secrete renin. This enzyme transforms angiotensinogen, a plasma protein,...
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Coronary Artery Disease (CAD): An Overview with Scientific InsightsCoronary Artery Disease (CAD), often referred to as C-A-D, is a prevalent blood vessel disorder classified under the broader category of atherosclerosis. Atherosclerosis is a pathological process characterized by the hardening and narrowing of arteries due to the accumulation of atherosclerotic plaques. These plaques are composed of cholesterol, fatty substances, inflammatory cells, calcium, and fibrin, reducing blood flow to...
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Prognostic Model of Prehypertension Risk Based on Molecular Markers.

V V Sherstnev1, M A Gruden2, A V Kuznetsova3

  • 1P. K. Anokhin Research Institute of Normal Physiology, Moscow, Russia. sherstnev.vv@yandex.ru.

Bulletin of Experimental Biology and Medicine
|March 31, 2021
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Summary

Computer models predict prehypertension risk using blood molecular markers and risk factors. The best model, using gradient boosting, shows high accuracy in identifying individuals at risk within 1-2 years.

Keywords:
molecular markersprehypertensionprognostic modelsrecognition technologies

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Area of Science:

  • Cardiovascular Health
  • Biomarker Discovery
  • Predictive Analytics

Background:

  • Prehypertension is a significant risk factor for future cardiovascular disease.
  • Early identification of individuals at risk is crucial for timely intervention.
  • Existing prognostic models may not fully leverage molecular data.

Purpose of the Study:

  • To develop and compare prognostic models for prehypertension risk.
  • To utilize computer recognition technology and molecular markers for prediction.
  • To assess model performance in diverse patient groups.

Main Methods:

  • Development of six prognostic models using computer recognition technology.
  • Inclusion of blood serum molecular markers and established risk factors.
  • Evaluation of models in individuals with optimal blood pressure and newly diagnosed prehypertension.
  • Comparison of model predictive power using metrics like ROC AUC, specificity, and accuracy.

Main Results:

  • The gradient boosting model, based on molecular markers, demonstrated superior predictive power (ROC AUC=0.76).
  • This model achieved high specificity (96.4%) and overall accuracy (86.6%).
  • A significant correlation (p=0.001) was observed between model prognosis and actual prehypertension symptoms.

Conclusions:

  • Molecular marker-based prognostic models, particularly using gradient boosting, are effective for predicting prehypertension.
  • These models offer a valuable tool for early risk assessment in adults aged 30-60.
  • The findings support the integration of advanced computational methods and biomarker analysis in cardiovascular risk prediction.