Development and interpretation of a machine learning predictive model for early cognitive impairment in hypertension associated with environmental factors
These videos have been matched automatically. Contact us if they are not relevant.
These videos have been matched automatically. Contact us if they are not relevant.
View abstract on PubMed
Summary
This summary is machine-generated.This study developed an XGBoost model using personal and environmental factors to predict early cognitive impairment in hypertensive patients. The model shows superior performance in identifying at-risk individuals, aiding in early intervention strategies.
Area Of Science
- Cardiovascular Health
- Neuroscience
- Environmental Health
Background
- Hypertensive cognitive impairment poses a significant health challenge.
- Existing risk models lack comprehensive integration of personal and natural environmental factors.
- Early identification is crucial for effective management of hypertension-related cognitive decline.
Purpose Of The Study
- To develop a machine learning (ML) model for assessing the risk of early cognitive impairment in hypertensive patients.
- To investigate the combined influence of personal and natural environmental factors on cognitive function in hypertension.
- To establish a predictive tool for early detection and intervention.
Main Methods
- Utilized data from 757 Chinese hypertensive patients.
- Employed 5-fold cross-validated LASSO regression to identify significant predictors.
- Developed and evaluated five ML classifiers, including XGBoost, using AUC, accuracy, sensitivity, specificity, and F1 scores.
- Assessed clinical utility with Decision Curve Analysis (DCA).
Main Results
- Identified age, waist circumference, urban green coverage, education, sunshine hours, and noise levels as key predictors.
- The XGBoost model demonstrated strong predictive performance (AUC=0.893, accuracy=0.837).
- The model showed significant clinical net benefit according to DCA.
Conclusions
- An XGBoost model integrating personal and natural environmental factors effectively predicts early cognitive impairment in hypertension.
- This model offers a promising tool for early identification and risk stratification.
- Further validation in larger cohorts is recommended to enhance predictive capabilities.
These videos have been matched automatically. Contact us if they are not relevant.
These videos have been matched automatically. Contact us if they are not relevant.
Related Concept Videos
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...
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,...
Hypertension, the most common cardiovascular disease, is diagnosed through repeated measurements of elevated blood pressure. Its risks, including damage to the kidney, heart, and brain, are directly proportional to blood pressure levels. Starting from 115/75 mm Hg, the risk of cardiovascular disease doubles with each increment of 20/10 mm Hg. The diagnosis relies on blood pressure measurements, not on patient symptoms, as hypertension is often asymptomatic until end-organ damage is imminent or...
Blood pressure monitoring is a crucial clinical procedure in diagnosing and managing various cardiovascular conditions. Despite its significance, the accuracy of blood pressure measurements can be compromised by multiple factors, potentially leading to either falsely high or low readings. These inaccuracies are critical as they can significantly impact patient care. So, it is vital to understand these challenges deeply and adopt strategic approaches to minimize errors.
Several factors...
The neural regulation of blood pressure involves intricate interactions between the autonomic nervous system (ANS) and cardiovascular system, ensuring adequate perfusion of tissues. This regulation primarily occurs through baroreceptor and chemoreceptor reflexes, involving both short-term and long-term mechanisms.
Baroreceptor Reflex
Baroreceptors, located in the carotid sinuses and aortic arch, detect changes in blood pressure. When blood pressure rises, these stretch-sensitive receptors...
Several physiological and lifestyle factors influence blood pressure (BP). Understanding these factors is crucial as they are significant in patient education and blood pressure management.
Physiological Factors:
• Age: As individuals age, their arteries become stiffer and lose elasticity. This reduction in elasticity hinders the arteries' ability to dilate and absorb pressure changes, often resulting in higher systolic pressures in older adults due to decreased elasticity.
...