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Establishment and Evaluation of a Risk Prediction Model for Abnormal Circadian Rhythm of Blood Pressure in Young
Qinhao Chen1, Lei Shi2, Xiang Li1
1Department of Electrocardiogram, 901st Hospital of the Chinese People's Liberation Army Joint Logistics Support Force, Hefei, Anhui Province, People's Republic of China.
Insights
A new nomogram accurately predicts abnormal circadian blood pressure rhythms in young hypertension patients. Key predictors include lymphocyte-to-monocyte ratio, systemic inflammatory response index, triglycerides, and uric acid.
Area of Science:
- Cardiology
- Hypertension Research
- Biomarkers
Background:
- Circadian blood pressure rhythm abnormalities are prevalent in young hypertensive patients.
- Early detection and intervention are crucial for managing hypertension and preventing complications.
- Existing predictive models may lack clinical applicability or accuracy.
Purpose of the Study:
- To develop and validate a simple, clinically applicable nomogram for predicting abnormal circadian blood pressure rhythm in young hypertensive patients.
- To identify independent risk factors associated with abnormal circadian blood pressure rhythms.
- To enable early detection and timely intervention for at-risk individuals.
Main Methods:
- A cohort of 211 young hypertensive patients was studied, with external validation using 203 additional patients.
- Patients were classified into dipper and non-dipper groups based on 24-hour ambulatory blood pressure monitoring.
- Multivariate logistic regression identified independent risk factors, which were used to construct and validate a nomogram.
Main Results:
- Univariate analysis showed significant differences in lymphocyte-to-monocyte ratio (LMR), systemic inflammatory response index (SIRI), triglycerides (TG), and uric acid (UA) between groups.
- Multivariate analysis identified decreased LMR, increased SIRI, elevated TG, and elevated UA as independent predictors.
- The nomogram demonstrated strong predictive performance with an area under the curve (AUC) of 0.883 (internal) and 0.844 (external).
Conclusions:
- LMR, SIRI, TG, and UA are significant independent predictors of abnormal circadian blood pressure rhythms in young hypertensive patients.
- The developed nomogram is a rapid, accurate, and clinically valuable tool for risk stratification.
- This nomogram facilitates early detection and intervention, potentially improving patient outcomes.
Objective:
This study aimed to develop and validate a simple and clinically applicable nomogram to predict abnormal circadian blood pressure rhythm in young hypertensive patients, enabling early detection and intervention.
Methods:
A total of 211 young hypertensive patients were enrolled between January 2023 and June 2024, with an additional 203 patients from other hospitals included for external validation. Patients were categorized into dipper and non-dipper groups based on 24-hour ambulatory blood pressure monitoring. Independent risk factors for abnormal circadian blood pressure rhythms were identified using multivariate logistic regression analysis, which was subsequently used to construct and externally validate a nomogram model.
Results:
Univariate analysis revealed significant differences (P<0.05) in the lymphocyte-to-monocyte ratio (LMR), systemic inflammatory response index (SIRI), systemic immune-inflammatory index (SII), triglycerides (TG), high-density lipoprotein (HDL), low-density lipoprotein (LDL), and uric acid (UA) between the dipper and non-dipper groups. Multivariate analysis identified decreased LMR, increased SIRI, elevated TG, and elevated UA as independent risk factors for abnormal circadian blood pressure rhythms in young hypertensive patients. The risk nomogram model was established based on the variables filtered by the multi-factor Logistic regression model. The evaluation results showed that the area under the curve (AUC) was 0.883. External validation showed an AUC of 0.844, with calibration confirming excellent predictive performance.
Conclusion:
LMR, SIRI, TG, and UA are independent predictors of abnormal circadian blood pressure rhythms in young hypertensive patients. The developed nomogram model is straightforward, rapid, and exhibits clinically relevant accuracy, providing valuable insights for clinical application.
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