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October 17, 2025Medicine0 citationsOpen Access

Development and validation of a risk predictive model in young patients with hypertension

XZXueqiang ZhaoXYXiaohua YuLCLin Cheng

Key Result

A risk predictive model incorporating γ-glutamyl transpeptidase, urea, and superoxide dismutase accurately identified hypertension in young adults, achieving an area under the curve of 0.88.

Study Design

Type

Observational (n=1,778)

Multicenter

No

Structured PICO

P
Population
1,778 young adults aged 18 to 40, including 1,242 with essential hypertension and 536 healthy volunteers, were evaluated to develop and validate a risk predictive model for hypertension.
O
Outcome
Predictors of hypertension formation and predictive model performance (AUC, sensitivity, specificity)surrogate

A simplified scoring system incorporating γ-glutamyl transpeptidase, urea, and superoxide dismutase can accurately predict the risk of essential hypertension in young adults.

Main Result

Effect estimate: AUC 0.88 (95% CI 0.86-0.90)

Limitations

  • Retrospective cross-sectional design only identifies associations, failing to confirm temporal sequence or causality
  • No longitudinal follow-up exists to validate if biomarkers predict hypertension onset over time
  • Single-center, presumably Han Chinese population limits generalizability across ethnicities
  • Adolescent hypertension predictive value is unassessed

Abstract

Hypertension is increasingly prevalent in young people and is associated with poor long-term outcomes and an elevated risk of cardiovascular events. Therefore, it is important to identify reliable early predictors of hypertension formation in this population. Between January 2016 and December 2024, we collected data from 1242 young adults (33.86 ± 0.16) with essential hypertension and 536 healthy volunteers (33.90 ± 0.26). We split the hypertensive patients and healthy population in a 7:3 ratio between the training and validation sets. Logistic regression analysis was used to develop predictive models, and the receiver operating characteristic (ROC) curve was used to evaluate the model's effectiveness. The study included 1778 participants. Logistic regression analysis identified γ-glutamyl transpeptidase and urea as independent risk factors for hypertension, while superoxide dismutase was an independent protective factor. The ROC curve showed a sensitivity of 80.2% and specificity of 82.6%. We developed a simplified scoring system for each index, and the resulting ROC curve had an area under the curve of 0.87. The calibration analysis curve showed a mean absolute error of 0.01, and the clinical decision analysis curve indicated a positive benefit when the threshold probability was between 0.04 and 1.00. In conclusion, γ-glutamyl transpeptidase, superoxide dismutase, and urea are important predictors of hypertension in young people, and our findings suggest potential new diagnostic and treatment directions for hypertension prevention and treatment in this population.

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Cite This Study

Zhao et al. (2025) conducted an observational in Essential hypertension (n=1,778). Risk predictive model (GGT, urea, and SOD) vs. Healthy volunteers was evaluated on Predictive model discrimination (AUC) for hypertension (AUC 0.88, 95% CI 0.86-0.90). A risk predictive model incorporating γ-glutamyl transpeptidase, urea, and superoxide dismutase accurately identified hypertension in young adults, achieving an area under the curve of 0.88.

synapsesocial.com/papers/6a9b2cd2dfe9afe39865bf40https://doi.org/10.1097/md.0000000000045132
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