Background: This study aimed to investigate the relationships of AHA/ACC blood pressure stages and circadian blood pressure patterns with clinical, metabolic, inflammatory, and structural echocardiographic parameters in newly diagnosed hypertensive (HT) patients, and to identify independent predictors of high-risk circadian disruptions. Methods: A total of 539 patients undergoing 24 h Ambulatory Blood Pressure Monitoring (ABPM) between 2022 and 2024 were retrospectively analyzed. Patients were grouped by nocturnal blood pressure dipping percentages and HT stages; laboratory markers (TyG index (Triglyceride-Glucose İndex), AIP (Atherogenic İndex of Plasma), SII (Systemic Immune-Inflammation Index), AISI (Aggregate Index of Systemic Inflammation), NLR (Neutrophil-to-Lymphocyte Ratio)) and echocardiographic data were evaluated via multivariable logistic regression. Results: The mean cohort age was 46.49 ± 13.98 years. Progressing HT stages were associated with significant increases in metabolic risk indicators: TyG index (p = 0.002) and AIP (p = 0.004). The prevalence of left ventricular hypertrophy (LVH) increased significantly from 7.3% in the normal group to 34.5% in Stage 2 HT (p < 0.001). The highest-risk "reverse-dipper" group had a significantly higher mean age (50.32 ± 14.55 years) than other groups (p < 0.001). In multivariable logistic regression, left atrial diameter (LAd) was the only common independent structural predictor of circadian disruption across all models (Extreme-Dipper OR: 1.19, p = 0.003; Non-Dipper OR: 1.11, p = 0.001). In the Reverse-Dipper model score analysis, both LAd (p < 0.001) and LVH (p = 0.001) demonstrated strong independent predictive potential. Inflammatory indices (SII, AISI, NLR) showed no independent predictive value (p > 0.05). Conclusions: Advanced HT stages and disrupted circadian rhythms are strongly associated with metabolic impairment, left atrial dilatation, and LVH. In older hypertensive patients presenting with left atrial enlargement and LVH, echocardiographic screening and close ABPM are crucial for early "reverse-dipper" pattern detection.
