ABSTRACT
Objective
To investigate the characteristics of blood pressure (BP) circadian rhythm disruption and its relationship with prognosis in patients with acute anterior ST‐elevation myocardial infarction (STEMI) after emergency percutaneous coronary intervention (PCI).
Methods
A total of 330 patients with anterior STEMI who underwent emergency PCI were enrolled in this study (MI group). Additionally, 131 physical examination patients were selected as the control group. Based on 24‐h ambulatory blood pressure monitoring (ABPM) results, BP rhythm in both groups was classified into Extreme dipper, Dipper, Non‐dipper, and Reverse dipper. The characteristics of BP rhythm were compared between the two groups. Patients with anterior MI were followed up for 1 year postoperatively. The occurrence of major adverse cardiovascular events (MACE) was compared among subgroups with different BP rhythms.
Results
The proportion of dipper BP in the study group (11.21%) was significantly lower than that of the control group (63.36%) (p = 0.001). The proportions of non‐dipper (43.03%) and reverse dipper (40%) BP in the MI group were higher than the control group (22.90% and 7.63%, respectively; all p < 0.001). Multivariate Cox regression analysis, using dipper BP as the reference, showed that reverse dipper BP was independently associated with MACE (HR = 6.417, p = 0.002). The cumulative risk of the primary endpoint event (Log Rank p = 0.021) was significantly higher in the reverse dipper group compared to the dipper group.
Conclusion
Patients with anterior STEMI are still under the burden of disrupted BP circadian rhythm and reduced dipper BP rhythm. The reverse dipper BP rhythm may serve as an independent factor of MACE.
Keywords: anterior STEMI, blood pressure, circadian rhythm, MACE, PCI
This study retrospectively analyzed the characteristics of blood pressure rhythm after emergency PCI for patients with anterior STEMI, discovering the burden of disrupted BP circadian rhythm. The reverse dipper BP rhythm may serve as an independent factor of MACE. This provides new insights into the intervention of blood pressure rhythm after myocardial infarction.
1. Introduction
Human blood pressure (BP) exhibits diurnal fluctuations over a 24‐h cycle, known as the BP circadian rhythm, characterized by a morning rise and a nocturnal fall [1]. In normal individuals, BP rhythm follows a “two‐peak, one‐valley” dipper pattern, peaking during waking daytime hours and falling during nocturnal sleep. A physiological nocturnal BP dip of approximately 10%–20% is termed “Dipper”. A dip less than 10% is termed “Non‐Dipper”, a dip exceeding 20% is termed “Extreme Dipper”, and a rise in nocturnal BP is termed “Reverse Dipper” [2, 3]. The Dipper pattern is generally considered the normal BP circadian rhythm, while Extreme Dipper, Non‐Dipper, and Reverse Dipper patterns represent pathological disruptions of the BP circadian rhythm. Disruption of the BP circadian rhythm is closely associated with the occurrence and development of cardiovascular and cerebrovascular diseases [4, 5, 6].
Acute ST‐elevation myocardial infarction (STEMI) is a critical condition with poor prognosis, and its incidence continues to rise, posing a severe threat to human life and health [7]. Although survival rates for STEMI patients have improved over the past two decades through percutaneous coronary intervention (PCI) and dual antiplatelet therapy (DAPT), post‐infarction complications remain a significant cause of high mortality and disability rates [8]. Acute anterior myocardial infarction, caused by severe lesions in the left anterior descending artery, involves larger areas of myocardial necrosis compared to infarctions in other locations, leading to more severe impacts on cardiac function and systemic hemodynamics, higher acute and long‐term mortality, and poorer prognosis [9]. Disruption of BP circadian rhythm is closely linked to cardiovascular disease. Previous studies have shown that BP circadian rhythm disruption has predictive value for the occurrence and prognosis of myocardial infarction [1, 4]. However, there is a lack of literature reporting on the characteristics of BP rhythm after myocardial infarction and its association with prognosis.
This study primarily explores the characteristics of BP circadian rhythm after emergency PCI for acute anterior myocardial infarction and its relationship with major adverse cardiovascular events (MACE), aiming to provide a reference for BP intervention and prognosis improvement in post‐MI PCI patients.
2. Method
2.1. Study Population
This was a retrospective study. We retrospectively enrolled 330 consecutive patients with acute anterior STEMI admitted to Wuxi People's Hospital, affiliated to Nanjing Medical University, between December 2018 and December 2023 as the study group. Concurrently, 131 patients who underwent physical examination and completed 24‐h ABPM at the Physical Examination Center of the same hospital were selected as the control group. Included patients met the following criteria: (1) First diagnosis of acute anterior STEMI; (2) Underwent emergency PCI within 12 h of symptom onset or beyond 12 h due to clinical and/or electrocardiographic evidence of ongoing myocardial ischemia; (3) In case of multivessel disease on coronary angiography, only the culprit left anterior descending artery vessel was treated; (4) The patient survived beyond the initial circadian cycle following PCI; (5) Drugs affecting blood pressure are taken in the morning (6:00–10:00 am), including calcium antagonists, beta‐blockers, RAAS blockers, and mineralocorticoid receptor antagonists. Exclusion criteria: (1) History of myocardial infarction, chronic heart failure, congenital heart disease, cardiomyopathy, or severe valvular heart disease; (2) Incomplete clinical data; (3) Failure to complete follow‐up successfully.
Acute anterior STEMI was defined as: (1) Meeting the diagnostic criteria for acute STEMI, including ischemic chest pain, new or presumed new significant ECG changes (ST‐segment elevation and T‐wave changes) in two or more contiguous leads, and abnormal cardiac biomarkers (elevation and/or fall of cardiac troponin values, with at least one value above the 99th percentile upper reference limit) [10, 11, 12]; (2) ECG showing ST‐segment elevation in leads V1–V4; coronary angiography confirming left anterior descending artery lesion; transthoracic echocardiography showing segmental wall motion abnormality in the anterior wall.
2.2. Clinical Data Acquisition
The following clinical parameters were collected via the electronic medical record system and imaging system after enrollment: (1) Basic information: gender, age, body mass index (BMI), diabetes, hypertension, dyslipidemia, smoking history, and family history of cardiovascular disease. (2) Results of initial blood laboratory tests, including: white blood cell count (WBC), neutrophil percentage (N%), C‐reactive protein (CRP), total cholesterol (TC), triglycerides (TG), low‐density lipoprotein cholesterol (LDL‐C), high‐density lipoprotein cholesterol (HDL‐C), estimated glomerular filtration rate (eGFR), cardiac troponin I (cTnI), and N‐terminal pro‐B‐type natriuretic peptide (NT‐proBNP). Peak biomarker values (including creatine kinase [CK] and CK‐MB) were obtained from repeated blood tests during hospitalization. (3) Initial transthoracic echocardiography data, including left ventricular ejection fraction (LVEF), left ventricular end‐diastolic diameter (LVEDD), left atrial diameter (LAD), etc. (4) Coronary angiography parameters: number of diseased vessels, Gensini score, TIMI risk score for STEMI [12], number of stents implanted, post‐PCI TIMI flow, and symptom‐to‐reperfusion time. Coronary angiography was analyzed by two independent interventional cardiologists. (5) BP rhythm classification: For the control group, classification was based on the 24‐h ABPM results.
For MI patients, classification was based on the first 24‐h ABPM measurement after admission (first daytime period 06:00–22:00 to next morning 06:00). Daytime was defined as 06:00–22:00, and nighttime as 22:00–06:00. BP rhythm types were defined based on the nocturnal SBP dipping percentage: Dipper (> 10% to 20%), Extreme dipper (> 20%), Non‐dipper (0% to 10%), Reverse dipper (< 0%) [13]. (6) Follow‐up endpoint and definition: All patients were followed up from the end of the procedure until 12 months post‐PCI via medical record review or telephone consultation to monitor MACE occurrence at 1, 3, 6, 9, and 12 months. MACE was defined as a composite of all‐cause death, recurrent myocardial infarction, unplanned repeat revascularization, and hospitalization for heart failure [14]. If a subject experienced multiple MACE events, only the first event was recorded.
2.3. Statistical Analysis
Statistical analysis was performed using SPSS software version 26.0. Normally distributed continuous data were expressed as mean ± standard deviation (mean ± SD) and compared between two groups using the independent samples t‐test. Comparisons among multiple groups were performed using analysis of variance (ANOVA). Non‐normally distributed data were expressed as median and interquartile range (IQR) and compared between two groups using the Mann‐Whitney U test. Comparisons among multiple groups were performed using the Kruskal‐Wallis test. Categorical data were described as frequency and percentage, and compared using the χ 2 test. Univariate Cox proportional hazards regression analysis was used to screen potential risk factors for endpoint events. Multivariate Cox regression analysis was used to investigate the relationship between BP circadian rhythm and endpoint events. Kaplan‐Meier curves were used to display the cumulative incidence of endpoint events for different BP circadian rhythms. A p value < 0.05 was considered statistically significant.
3. Results
3.1. Baseline Characteristics of the Study Patients
A total of 461 patients were included: 131 in the control group and 330 in the MI group. Compared to controls, the MI group had a significantly higher proportion of males and smokers, higher BMI, and higher prevalence of hypertension, diabetes, and dyslipidemia (all p < 0.01). There was no significant difference in the family history of cardiovascular disease between groups. Regarding blood tests and CRP, the MI group had significantly higher WBC count, neutrophil percentage, and CRP values than controls (all p < 0.01). Regarding lipids, TC and LDL‐C were significantly higher in the MI group (p < 0.01), while TG and HDL‐C showed no significant difference (p > 0.05). eGFR showed no significant difference. Echocardiography showed significantly larger LAD and LVEDD and significantly lower LVEF in the MI group compared to controls (all p < 0.01). as revealed in Table 1.
Table 1.
Baseline clinical characteristics.
| Variables | Control group (n = 131) | MI group (n = 330) | t/χ 2 /Z Value | p‐Value |
|---|---|---|---|---|
| Age (years) | 58.73 ± 7.52 | 57.95 ± 13.18 | 0.797 | 0.426 |
| Male sex | 66 (50.38%) | 289 (87.56%) | 73.266 | < 0.001* |
| BMI (kg/m2) | 24.05 ± 2.95 | 25.19 ± 3.35 | −3.597 | < 0.001* |
| Cardiovascular risk factors | ||||
| Current smoking | 33 (25.19%) | 190 (57.58%) | 39.381 | < 0.001* |
| Family history of IHD | 4 (3.05%) | 18 (5.45%) | 1.190 | 0.275 |
| Hypertension | 30 (22.90%) | 181 (54.85%) | 38.561 | < 0.001* |
| Diabetes | 15 (11.45%) | 84(25.45%) | 10.906 | 0.001* |
| Dyslipidemia | 38 (29.01%) | 119(36.06%) | 2.077 | 0.015* |
| Laboratory data | ||||
| WBCs (× 109/L) | 7.25 ± 2.73 | 11.38 ± 3.59 | −13.333 | < 0.001* |
| N% | 68.32 ± 6.24 | 77.21 ± 8.33 | −12.479 | < 0.001* |
| CRP (mg/L) | 1.8 (0.6,5.6) | 4.8 (1.2,12.1) | −4.018 | < 0.001* |
| TC (mmol/L) | 4.56 ± 1.17 | 4.97 ± 1.53 | −3.095 | 0002* |
| TG (mmol/L) | 1.43 (0.72,1.83) | 1.50 (1.08,2.10) | −0.685 | 0.494 |
| LDL‐C (mmol/L) | 2.48 ± 0.72 | 3.08 ± 1.02 | −7.116 | < 0.001* |
| HDL‐C (mmol/L) | 1.12 ± 0.26 | 1.08 ± 0.31 | 1.408 | 0.160 |
| eGFE (mL/(min.1.73 m2)) | 96.52 ± 16.52 | 91.45 ± 21.78 | 2.702 | 0.170 |
| Echocardiographic data | ||||
| LAD(mm) | 33.21 ± 4.22 | 36.01 ± 4.57 | −6.273 | < 0.001* |
| LVEDD(mm) | 41.52 ± 4.61 | 47.91 ± 4.84 | −13.232 | < 0.001* |
| LVEF(%) | 55.22 ± 5.46 | 49.82 ± 7.28 | 8.667 | < 0.001* |
| 24 h ABPM averages | ||||
| SBP (mmHg) | 127.68 ± 7.66 | 115.99 ± 19.65 | 9.190 | < 0.001* |
| DBP (mmHg) | 78.01 ± 6.42 | 73.91 ± 11.65 | 4.812 | < 0.001* |
| Blood pressure rhythm types | ||||
| Dipper | 83 (63.36%) | 37(11.21%) | 132.435 | < 0.001* |
| Extreme dipper | 8 (6.11%) | 19(5.76%) | 0.021 | 0.885 |
| Non‐dipper | 30 (22.90%) | 142(43.03%) | 16.245 | < 0.001* |
| Reverse Dipper | 10 (7.63%) | 132(40%) | 46.089 | < 0.001* |
Abbreviations: ABPM, Ambulatory blood pressure; BMI, Body mass index; DBP, Diastolic blood pressure; eGFR, Estimated glomerular filtration rate; HDL‐C, high‐density lipoprotein cholesterol; IHD, ischemic heart disease; LAD, Left atrial diameter; LDL‐C, low‐density lipoprotein cholesterol; LVEDD, left ventricular end‐diastolic diameter; LVEF, left ventricular ejection fraction; N%, Neutrophil percentage; SBP, systolic blood pressure; TC, Total cholesterol; TG, Triglycerides; WBC, White blood cell count.
p < 0.05.
3.2. Characteristics of BP Circadian Rhythm After MI
The control group had significantly higher SBP than the MI group (both p < 0.01). The Dipper pattern predominated in controls (63.36%), while Non‐Dipper (43.03%) and Reverse Dipper (40%) patterns predominated in the MI group. The proportion of Dipper pattern was significantly lower in the MI group (11.21%) than in controls (63.36%) (p < 0.01), while the proportions of Non‐Dipper (43.03% vs 22.90%) and Reverse Dipper (40.00% vs 7.63%) patterns were significantly higher in the MI group (both p < 0.01). There was no significant difference in the Extreme Dipper proportion (p > 0.05). as revealed in Table 1.
3.3. Characteristics Across BP Rhythm Groups Within the MI Group
As shown in Table 2, there were no significant differences in age, gender distribution, or BMI among the Dipper, Extreme Dipper, Non‐Dipper, and Reverse Dipper subgroups within the MI group (all p > 0.05). Among cardiovascular risk factors, the proportions of hypertension, dyslipidemia, family history of IHD, and smoking showed no significant differences between groups (all p > 0.05), but the proportion of diabetes differed (p < 0.05), being highest in the Non‐Dipper group (32.39%). Regarding laboratory indices, only CRP differed significantly between groups (p < 0.01); WBC count, neutrophil percentage, lipids, eGFR, peak CK, peak CK‐MB, and NT‐proBNP showed no significant differences (all p > 0.05). Echocardiographic indices (LAD, LVEDD, LVEF) also showed no significant differences. Regarding MI treatment, there were no significant differences in symptom‐to‐reperfusion time, number of diseased vessels, Gensini score, TIMI risk score, number of stents implanted, or proportion achieving post‐PCI TIMI 3 flow (all p > 0.05). The proportion using RAAS blockers differed significantly (p < 0.01), being highest in the Extreme Dipper group (89.47%). Proportions using β‐blockers or MRAs showed no differences. MACE incidence differed significantly (p < 0.01), being lowest in the Dipper group (13.51%) and highest in the Reverse Dipper group (39.39%).
Table 2.
Characteristics of different BP rhythms after MI.
| Variables | Dipper (n = 37) | Extreme dipper (n = 19) | Non‐dipper (n = 142) | Reverse dipper (n = 132) | H/F/χ 2 | p‐value |
|---|---|---|---|---|---|---|
| Age (years) | 60.38 ± 13.13 | 54.84 ± 13.20 | 56.50 ± 13.54 | 59.30 ± 12.71 | 1.83 | 0.14 |
| Male sex | 29 (78.38%) | 16 (84.21%) | 124 (87.32%) | 120 (90.91%) | 1.90 | 0.54 |
| BMI (kg/m2) | 24.91 ± 3.25 | 24.87 ± 3.29 | 25.19 ± 3.13 | 25.31 ± 3.43 | 0.20 | 0.90 |
| Cardiovascular risk factors | ||||||
| Current smoking | 19 (51.35%) | 12 (63.16%) | 83 (58.45%) | 76 (57.58%) | 0.87 | 0.83 |
| Family history of IHD | 2 (5.41%) | 0 (0%) | 9 (6.34%) | 7 (5.30%) | 1.32 | 0.73 |
| Hypertension | 20 (54.05%) | 12 (63.16%) | 69 (48.59%) | 80 (60.61%) | 3.64 | 0.30 |
| Diabetes | 4 (10.81%) | 3 (15.79%) | 46 (32.39%) | 31 (23.48%) | 8.99 | 0.03* |
| Dyslipidemia | 9 (24.32%) | 4 (21.05%) | 58 (40.85) | 48 (36.36%) | 5.48 | 0.14 |
| Laboratory data | ||||||
| WBCs (× 109/L) | 11.41 ± 3.01 | 10.24 ± 3.42 | 11.87 ± 4.03 | 11.02 ± 3.09 | 2.12 | 0.10 |
| N% | 72.80 (70.35, 81.40) | 77.10 (66.40, 83.30) | 79.20 (72.08, 83.13) | 79.3 (72.08, 83.78) | 5.57 | 0.14 |
| CRP (mg/L) | 8.40 (2.20, 19.55) | 6.8 (0.90, 13.20) | 5.0 (1.40, 13.90) | 3.15 (1.50, 8.38) | 11.05 | 0.01* |
| TC (mmol/L) | 4.88 ± 1.62 | 4.85 ± 1.24 | 4.49 ± 1.68 | 5.12 ± 1.20 | 0.31 | 0.96 |
| TG (mmol/L) | 1.19 (0.94, 1.77) | 1.34 (1.20, 1.96) | 1.50 (1.11, 2.07) | 1.55 (1.12, 2.25) | 1.02 | 0.80 |
| LDL‐C (mmol/L) | 3.09 ± 1.14 | 2.96 ± 1.07 | 3.07 ± 0.99 | 3.11 ± 1.01 | 0.14 | 0.94 |
| HDL‐C (mmol/L) | 0.99 ± 0.20 | 1.04 ± 0.16 | 1.08 ± 0.28 | 1.10 ± 0.31 | 5.31 | 0.15 |
| eGFE (ml/ (min.1.73 m2)) | 96.60 (84.65, 106.00) | 99.70 (80.10, 107.40) | 96.0 (81.20, 107.15) | 93.9 (83.85, 104.4) | 3.42 | 0.33 |
| Peak CK (ng/mL) | 3119 (1402, 5815) | 4613 (1472, 5607) | 3234 (1472, 5292) | 3470.5 (1201, 5119) | 0.31 | 0.96 |
| Peak CK‐MB (ng/mL) | 253 (166, 549) | 275 (168, 446) | 253.6 (151, 406) | 270 (117, 428) | 0.64 | 0.87 |
| NT‐proBNP (ng/L) | 2090 (654.5, 6800) | 1230 (689, 3470) | 1520 (493, 5300) | 1200 (360, 4440) | 4.42 | 0.22 |
| LAD (mm) | 35.89 ± 4.71 | 35.21 ± 2.99 | 35.79 ± 4.82 | 36.39 ± 4.45 | 0.60 | 0.62 |
| LVEDD (mm) | 47.86 ± 4.28 | 46.58 ± 3.42 | 47.64 ± 4.81 | 48.41 ± 5.86 | 1.07 | 0.36 |
| LVEF (%) | 49.73 ± 7.80 | 48.21 ± 6.92 | 49.91 ± 7.01 | 49.98 ± 7.51 | 0.34 | 0.80 |
| 24 h ABPM averages | ||||||
| SBP (mmHg) | 109.05 ± 15.43 | 95.96 ± 16.65 | 112.01 ± 17.88 | 125.04 ± 18.79 | 23.27 | < 0.01* |
| DBP (mmHg) | 69.97 ± 7.81 | 63.67 ± 10.94 | 72.20 ± 11.31 | 78.29 ± 11.35 | 15.22 | < 0.01* |
| Recanalization time (h) | 5 (2.75, 8.00) | 4.5 (3.00, 8.00) | 4 (2.00, 6.25) | 3.5 (2.00, 6.00) | 5.08 | 0.17 |
| Number of diseased vessels | 1.843 ± 0.87 | 1.533 ± 0.60 | 1.553 ± 0.69 | 1.583 ± 0.69 | 2.28 | 0.52 |
| Number of Stents Implanted | 1.16 ± 0.37 | 1.05 ± 0.40 | 1.16 ± 0.48 | 1.22 ± 0.53 | 2.49 | 0.48 |
| Post‐PCI TIMI 3 flow | 33 (89.19%) | 17 (89.47%) | 131 (92.25%) | 120 (90.91%) | 3.57 | 0.73 |
| Gensini score | 80 (48.00, 90.00) | 80 (48.00, 90.00) | 80 (58.00, 84.00) | 80 (52, 84.75) | 0.95 | 0.82 |
| TIMI risk score | 4.0 (2, 5) | 4.5 (3, 8) | 3.5 (2, 5) | 3 (2, 5) | 0.51 | 0.92 |
| β‐blocker | 25 (67.57%) | 15 (78.95%) | 111 (78.17%) | 105 (79.55%) | 2.47 | 0.48 |
| RAAS ‐blocker | 21 (56.76%) | 17 (89.47%) | 55 (38.73%) | 77 (58.33%) | 9.27 | 0.05* |
| MRA | 3 (8.11%) | 1 (5.26%) | 17 (11.97%) | 13 (9.85%) | 1.54 | 0.67 |
| MACE | 5 (13.51%) | 3 (15.79%) | 39 (27.46%) | 52 (39.39%) | 12.60 | < 0.01* |
Abbreviations: ABPM, Ambulatory blood pressure; BMI, Body mass index; CK, Creatine kinase; CK‐MB, creatine kinase‐myocardial band; DBP, Diastolic blood pressure; eGFR, Estimated glomerular filtration rate; HDL‐C, high density lipoprotein cholesterol; IHD, ischemic heart disease; LAD, Left atrial diameter; LDL‐C, low density lipoprotein cholesterol; LVEDD, left ventricular end‐diastolic diameter; LVEF, left ventricular ejection fraction; MRA, Mineralocorticoid antagonist; NT‐proBNP, N‐terminal pro‐B‐type natriuretic peptide; N%, Neutrophil percentage; RAAS blocker, renin‐angiotensin‐aldosterone system; SBP, systolic blood pressure; TC, Total cholesterol; TG, Triglycerides; WBC, White blood cell count.
p < 0.05.
3.4. Relationship Between Clinical Prognosis and Risk Factors
Table 3 shows the results of univariate Cox regression analysis for MACE. Per unit increase: WBC count (HR 1.091, p = 0.009), Neutrophil percentage (HR 1.065, p < 0.01), Peak CK (HR 1.0, p < 0.01), LAD (HR 1.108, p < 0.01), LVEDD (HR 1.105, p < 0.01), Number of diseased vessels (HR 1.593, p < 0.01), Gensini score (HR 1.025, p < 0.01), TIMI risk score (HR 1.137, p < 0.05). Per unit decrease: LVEF (HR 0.888, p < 0.01). MRA use (HR 0.465, p = 0.035) and Reverse Dipper rhythm (HR 4.160, p < 0.01) were identified as potential risk factors for endpoint events. Potential risk factors from univariate analysis plus clinically recognized high‐risk factors (age, sex, hypertension, diabetes, dyslipidemia, smoking, BMI, family history of CVD) [15] were included in multivariate Cox regression analysis. Results (Figure 1) showed that increased LVEF (HR 0.905, p < 0.01 per 1% increase), increased Gensini score (HR 1.017, p = 0.043 per 1 score increase), and Reverse Dipper rhythm (using Dipper as reference, HR 6.417, p = 0.002) were independent risk factors for MACE.
Table 3.
Univariate COX regression analysis of MACE.
| Variables | B | SE | Wald | p‐value | HR | 95% CI |
|---|---|---|---|---|---|---|
| Age (years) | 0.009 | 0.009 | 0.918 | 0.338 | 1.009 | 0.991–1.027 |
| Male sex | 0.081 | 0.342 | 0.056 | 0.813 | 1.084 | 0.555–2.119 |
| BMI (kg/m2) | −0.031 | 0.037 | 0.737 | 0.391 | 0.969 | 0.902–1.041 |
| Cardiovascular risk factors | ||||||
| Current smoking | 0.059 | 0.243 | 0.059 | 0.808 | 1.061 | 0.659–1.707 |
| Family history of IHD | 0.427 | 0.580 | 0.541 | 0.462 | 1.532 | 0.491–4.777 |
| Hypertension | 0.017 | 0.241 | 0.005 | 0.942 | 1.018 | 0.634–1.633 |
| Diabetes | 0.015 | 0.276 | 0.003 | 0.956 | 1.015 | 0.591–1.745 |
| Dyslipidemia | 0.235 | 0.254 | 0.855 | 0.355 | 1.265 | 0.769–2.082 |
| Laboratory data | ||||||
| WBCs (×109/L) | 0.087 | 0.033 | 6.835 | 0.009* | 1.091 | 1.022–1.164 |
| N% | 0.063 | 0.017 | 14.196 | < 0.01* | 1.065 | 1.031–1.100 |
| CRP (mg/L) | 0.001 | 0.006 | 0.013 | 0.908 | 1.001 | 0.989–1.012 |
| TC (mmol/L) | −0.007 | 0.016 | 0.176 | 0.675 | 0.993 | 0.963–1.025 |
| TG (mmol/L) | 0.042 | 1.00 | 0.179 | 0.672 | 1.043 | 0.858–1.269 |
| LDL‐C (mmol/L) | 0.025 | 0.118 | 0.045 | 0.833 | 1.025 | 0.814–1.292 |
| HDL‐C (mmol/L) | −0.004 | 0.305 | 0.000 | 0.990 | 0.996 | 0.548–1.812 |
| eGFE (ml/min*1.73 m2) | −0.008 | 0.005 | 2.306 | 0.129 | 0.992 | 0.981–1.002 |
| Peak CK (ng/mL) | 0.000 | 0.000 | 6.422 | 0.011* | 1.00 | 1.000–1.000 |
| Peak CK‐MB (ng/mL) | 0.001 | 0.000 | 3.815 | 0.051 | 1.001 | 1.00–1.001 |
| NT‐proBNP (ng/L) | 0.000 | 0.000 | 1.141 | 0.285 | 1.00 | 1.00–1.000 |
| LAD (mm) | 0.103 | 0.027 | 14.087 | < 0.01* | 1.108 | 1.050–1.170 |
| LVEDD (mm) | 0.10 | 0.026 | 14.154 | < 0.01* | 1.105 | 1.049–1.164 |
| LVEF (%) | −0.119 | 0.020 | 36.077 | < 0.01* | 0.888 | 0.854–0.923 |
| Recanalization time (h) | −0.033 | 0.028 | 1.334 | 0.248 | 0.968 | 0.915–1.023 |
| Number of diseased vessels | 0.465 | 0.167 | 7.771 | 0.005* | 1.593 | 1.148–2.209 |
| Number of Stents Implanted | 0.078 | 0.245 | 0.103 | 0.749 | 1.081 | 0.670–1.747 |
| Post‐PCI TIMI 3 flow | −0.285 | 0.414 | 0.473 | 0.492 | 0.752 | 0.334–1.693 |
| Gensini score | 0.024 | 0.006 | 18.109 | < 0.01* | 1.025 | 1.013–1.036 |
| TIMI risk score | 0.128 | 0.056 | 5.218 | 0.022* | 1.137 | 1.018–1.269 |
| β‐blocker | −0.227 | 0.282 | 0.649 | 0.421 | 0.797 | 0.459–1.384 |
| RAAS ‐blocker | −0.294 | 0.242 | 1.473 | 0.225 | 0.746 | 0.464–1.198 |
| MRA | −0.766 | 0.363 | 4.447 | 0.035* | 0.465 | 0.228–0.947 |
| 24 h ABPM averages | ||||||
| SBP (mmHg) | −0.001 | 0.004 | 0.110 | 0.740 | 0.999 | 0.990–1.007 |
| DBP (mmHg) | 0.001 | 0.008 | 0.012 | 0.911 | 1.001 | 0.985–1.017 |
| Blood pressure rhythm types | ||||||
| Dipper (reference) | ||||||
| Non‐dipper | 0.885 | 0.516 | 2.939 | 0.086 | 2.423 | 0.881–6.667 |
| Reverse Dipper | 1.426 | 0.513 | 7.727 | 0.005* | 4.160 | 1.523–11.366 |
| Extreme dipper | 0.182 | 0.792 | 0.053 | 0.818 | 1.200 | 0.254–5.665 |
Abbreviations: ABPM, Ambulatory blood pressure; BMI, Body mass index; CK, Creatine kinase; CK‐MB, creatine kinase‐myocardial band; DBP, Diastolic blood pressure; eGFR, Estimated glomerular filtration rate; HDL‐C, high density lipoprotein cholesterol; IHD, ischemic heart disease; LAD, Left atrial diameter; LDL‐C, low density lipoprotein cholesterol; LVEDD, left ventricular end‐diastolic diameter; LVEF, left ventricular ejection fraction; MRA, Mineralocorticoid antagonist; NT‐proBNP, N‐terminal pro‐B‐type natriuretic peptide; N%, Neutrophil percentage; RAAS blocker, renin‐angiotensin‐aldosterone system; SBP, systolic blood pressure; TC, Total cholesterol; TG, Triglycerides; WBC, White blood cell count.
p < 0.05.
Figure 1.
Multivariate COX regression analysis of the MACE.
3.5. Relationship Between BP Rhythm and Endpoint Events
After 12 months of follow‐up, 99 MACE events occurred cumulatively: 8 all‐cause deaths, 2 recurrent MIs, 56 unplanned repeat revascularizations, and 27 hospitalizations for heart failure. MACE incidence rates were: Dipper 13.51%, Extreme Dipper 15.79%, Non‐Dipper 27.46%, Reverse Dipper 39.39%. Compared to the Dipper group (13.51%), MACE incidence in the Extreme Dipper (15.79%) and Non‐Dipper (27.46%) groups showed no significant difference (p > 0.05), but was significantly higher in the Reverse Dipper group (39.39%, p < 0.01). Figure 2 shows the Kaplan‐Meier cumulative risk curves for different BP rhythms. The cumulative risk of MACE differed significantly across BP rhythm groups (Log Rank p = 0.048). The Dipper group had the lowest cumulative risk, the Reverse Dipper group the highest, and the cumulative risk in the Reverse Dipper group was significantly higher than in the Dipper group (Log Rank p = 0.021).
Figure 2.
KM curve of Blood pressure rhythm types and cumulative incidence of MACE events.
4. Discussion
In healthy individuals, blood pressure is regulated by clock genes such as Bmal1, Per1/2, Clock, and Cry, exhibiting a distinct circadian rhythm with peaks during the awake daytime and troughs during nighttime sleep [16]. Based on the nocturnal SBP dipping percentage, BP circadian rhythm is classified into four types: Dipper, Extreme dipper, Non‐dipper, and Reverse dipper. According to literature, slightly more than half of hypertensive patients are dippers at baseline, about one‐quarter to one‐third are non‐dippers, and less than 10% are reverse dippers [17, 18], consistent with our findings in the control group. Factors such as age, shift work, circadian misalignment, social jet lag, genetic variants/mutations, and cardiovascular/cerebrovascular diseases can influence BP rhythm [2, 19].
Acute Anterior STEMI causes extensive myocardial necrosis, leading to overactivation of the neuroendocrine system, predisposing patients to cardiac dysfunction and systemic hemodynamic disturbances [20]. Our study on BP rhythm characteristics after emergency PCI for acute anterior MI revealed that BP rhythm disruption occurs as early as the first day post‐PCI. While dipper BP was predominant in controls, non‐dipper and reverse dipper patterns predominated in the MI group. Compared to controls, the MI group had a significantly lower proportion of dippers and significantly higher proportions of non‐dippers and reverse dippers. No significant difference was found in the proportion of extreme dippers.
There are clear differences between the control group and the myocardial infarction group in terms of sex distribution, body mass index, and cardiovascular risk factors. These differences are not the main factors influencing blood pressure rhythms, and these comparisons are descriptive rather than intended to show a causal relationship. Numerous studies have confirmed that the blood pressure rhythm is mainly the combined result of both endogenous circadian mechanisms, as well as 24‐h environmental and behavioral variations, such as the sleep/wake, rest/activity, fasting/eating, dark/light, and postural, mental stress, and environmental cycles [21]. For patients with acute myocardial infarction, according to the Guideline‐directed medical therapy, they usually need to take drugs such as beta‐blockers, RAAS blockers, and mineralocorticoid receptor antagonists to improve prognosis. The effects of these drugs and their dosing times on nocturnal blood pressure and blood pressure rhythm are still controversial. Ye discovered that olmesartan and amlodipine administered before bedtime can better control nocturnal blood pressure and improve the circadian rhythm [22]. However, currently, most experts do not recommend taking antihypertensive drugs before bedtime, mainly because most outcome trials use morning administration, and there is no clear and strong evidence indicating that bedtime administration has additional outcome benefits. This study uses morning administration, and the drugs taken are all long‐acting preparations. In most individuals, they are likely to remain above the treatment threshold within 24 h. Therefore, theoretically, the type and time of administration should not have any impact on the efficacy. The anterior STEMI BP rhythm disruption likely results from multiple interacting factors. Firstly, anterior STEMI causes large‐scale ischemic necrosis of the left ventricular anterior wall, damaging mechanoreceptors and leading to decreased baroreflex sensitivity. This subsequently triggers sympathetic overactivation and inhibition of vagal tone [20]. This autonomic imbalance causes abnormal nocturnal norepinephrine release, phase shifts in cortisol secretion, and loss of diurnal differences in nitric oxide bioavailability [23, 24]. Secondly, inflammatory mediators released during MI inhibit the expression of the CLOCK/BMAL1 complex in cardiomyocytes via the IL‐6/STAT3 signaling pathway, leading to the loss of circadian secretion rhythm of angiotensinogen (AGT) [25, 26, 27, 28]. Additionally, MI disrupts sleep patterns [29] and “inhibits” the rhythm‐regulating function of the suprachiasmatic nucleus (SCN) [26, 30], causing dysfunction of clock gene BMAL1 [25]and vascular smooth muscle cell PRDM16 [31, 32]. These multifactorial mechanisms collectively contribute to BP rhythm disruption post‐MI.
In this study, we further analyzed the characteristics of patients with different BP rhythms post‐MI. Apart from differences in diabetes prevalence, no statistically significant differences were found among the BP rhythm groups regarding age, gender, BMI, or common cardiovascular risk factors. This might be because diabetes itself, through a series of pathophysiological processes including inflammation, oxidative stress, and insulin resistance, can exacerbate BP rhythm disruption [33, 34]. As far as the laboratory indicators are concerned, CRP, reflecting inflammation, showed a difference between groups, with dipper patients seemingly having higher levels, which contradicts previous findings [35], which suggests that post‐MI BP rhythm is complex, influenced by numerous factors beyond inflammation alone.
Regarding MI severity assessment, PCI procedure, and medication regimens, there were no significant differences among the BP rhythm groups. However, outcome data clearly showed the lowest MACE incidence in the dipper group and the highest in the reverse dipper group, indicating that BP rhythm disruption likely impacts MACE occurrence in MI patients. Univariate Cox regression analysis identified WBC count, neutrophil percentage, peak CK, LAD, LVEDD, LVEF, number of diseased vessels, Gensini score, TIMI risk score, MRA use, and reverse dipper rhythm as potential risk factors for MACE post‐MI. Incorporating these potential risk factors along with demographic characteristics and common risk factors into a multivariate Cox regression analysis revealed that LVEF, Gensini score, and reverse dipper BP rhythm were independently associated with MACE.
The association of LVEF and Gensini score with post‐MI MACE is well‐established by previous studies [9, 36, 37]. The JAMP study [38] showed that disrupted BP circadian rhythm (reverse dipping) was significantly associated with higher overall cardiovascular risk, compared to normal circadian rhythm (dipping). This aligns with our findings. Our study demonstrated that reverse dipper BP increased the risk of MACE by 6.42‐fold compared to dipper BP (HR = 6.42, 95%CI 1.94–21.20). The Kaplan‐Meier cumulative risk curve also showed higher cumulative risk for endpoint events in the reverse dipper group. We therefore conclude that in acute anterior MI, the reverse dipper BP rhythm is independently associated with the occurrence of MACE events. Other types of disrupted BP rhythm (non‐dipper, extreme dipper) did not show independent association with MACE events, possibly because reverse dipping represents a more severe form of circadian disruption with greater detrimental cardiovascular impact.
Numerous studies indicate that reverse dipper hypertension is an independent risk factor for cardiovascular death. Potential mechanisms for poor prognosis in reverse dipper patients post‐MI are as follows: Firstly, elevated nocturnal BP keeps the cardiovascular system under constant high load, exacerbating endothelial damage and arterial stiffness [39]. Secondly, reverse dipping is associated with nocturnal autonomic dysfunction, characterized by sympathetic overactivation, impaired baroreflex sensitivity, sodium and water retention, and nocturnal volume overload [40, 41, 42]. Furthermore, nocturnal BP elevation can lead to excessive activation of inflammatory responses and disruption of clock gene expression, all of which can increase MACE incidence [26, 29], increasing MACE risk. Recent research by Ruan et al [43]demonstrated that ischemia‐reperfusion injury following acute anterior STEMI follows a circadian pattern. Administering treatments timed according to this rhythm (“chronotherapy”) can significantly improve patient outcomes. The circadian pattern of post‐MI ischemia‐reperfusion injury resembles the BP rhythm patterns we studied, and both are regulated by the clock gene BMAL1. Whether correcting disrupted BP circadian rhythm in post‐MI patients using antihypertensive or vasoactive drugs timed to the rhythm can improve prognosis warrants further exploration.
However, this study also has some limitations. As a single‐center retrospective study with a relatively small sample size, potential biases exist, necessitating confirmation by large‐scale randomized controlled trials (RCTs). Secondly, defining daytime and nighttime using fixed time intervals, although endorsed by relevant guidelines and validated by some researchers [44], may not reflect the true circadian patterns of individual patients, potentially introducing misclassification of BP rhythm types. Thirdly, Blood pressure circadian rhythm was assessed only during the first 24 h after myocardial infarction. This period is often affected by pain, stress, inflammation, and early post‐PCI instability. Therefore, the measured blood pressure pattern may reflect an acute response rather than the patient's usual circadian rhythm. Last but not least, the 24‐h blood pressure rhythm after PCI of acute myocardial infarction was identified as a research topic in this study, with the limitation of difficulties for repeated measurement.
5. Conclusion
According to this study, in spite of aggressive PCI therapies in time, patients with acute anterior wall myocardial infarction are still under the burden of disrupted BP circadian rhythm and reduced dipper BP rhythm. Furthermore, the reverse dipper BP rhythm may serve as an independent factor of MACE. This study could provide guidance for blood pressure management and prognosis improvement in patients with anterior wall myocardial infarction.
Author Contributions
Yangge Shao wrote the main manuscript text; Yangge Shao, Yajuan Yang, and Chao Wang collected and analyzed the data; Zhiming Yu and Ruxing Wang put forward revision comments on the shortcomings of the article. All authors read and approved the final manuscript.
Ethics Statement
The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.
Conflicts of Interest
The authors declare no conflicts of interest.
Acknowledgments
This work was supported by the National Natural Science Foundation of China (No. 82200357 to Y.Y.)
Shao Y., Yang Y., Wang C., Yu Z., and Wang R., “Association Between Disruption of Blood Pressure Circadian Rhythm and Prognosis After Acute Anterior Myocardial Infarction,” Clinical Cardiology 49 (2026): e70377, 10.1002/clc.70377.
Yangge Shao, Yajuan Yang, and Chao Wang contributed equally to this work.
Contributor Information
Zhiming Yu, Email: yuzhimi8660@sina.com.
Ruxing Wang, Email: ruxingw@aliyun.com.
Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.
The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.
References
- 1. Yano Y. and Kario K., “Nocturnal Blood Pressure and Cardiovascular Disease: A Review of Recent Advances,” Hypertension Research 35, no. 7 (2012): 695–701. [DOI] [PubMed] [Google Scholar]
- 2. Faraci F. M. and Scheer F. A. J. L., “Hypertension: Causes and Consequences of Circadian Rhythms in Blood Pressure,” Circulation Research 134, no. 6 (2024): 810–832. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3. Cuspidi C., Sala C., Tadic M., et al., “Clinical and Prognostic Significance of a Reverse Dipping Pattern on Ambulatory Monitoring: An Updated Review,” Journal of Clinical Hypertension 19, no. 7 (2017): 713–721. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4. Wang W., Chen M., Guo J., et al., “Construction and Validation of Nomogram Model for Predicting the Risk of Ventricular Arrhythmia After Emergency PCI in Patients With Acute Myocardial Infarction,” Aging (Albany, NY) 16, no. 9 (2024): 8246–8259. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5. Tang T., Zhang G., Chen Z., Thomas A. M., Zhou J., and Li S., “Association of Reverse Dipping Blood Pressure With Mortality Among Critically Ill Patients With Ischemic Stroke,” Internal and Emergency Medicine 20, no. 3 (2025): 701–708. [DOI] [PubMed] [Google Scholar]
- 6. Kocak A., Senol C., Yildirim O., et al., “Correlations of the Circadian Rhythmicity of Blood Pressure With Erectile Dysfunction,” Journal of Clinical Hypertension (Greenwich) 27, no. 1 (2025): e14935. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7. Barnett R., “Acute Myocardial Infarction,” Lancet 393, no. 10191 (2019): 2580. [DOI] [PubMed] [Google Scholar]
- 8. Damluji A. A., van Diepen S., Katz J. N., et al., “Mechanical Complications of Acute Myocardial Infarction: A Scientific Statement From the American Heart Association,” Circulation 144, no. 2 (2021): e16–e35. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9. Liang J. and Zhang Z., “Predictors of In‐Hospital Heart Failure in Patients With Acute Anterior Wall ST‐Segment Elevation Myocardial Infarction,” International Journal of Cardiology 375 (2023): 104–109. [DOI] [PubMed] [Google Scholar]
- 10. Thygesen K., Alpert J. S., Jaffe A. S., et al., “Fourth Universal Definition of Myocardial Infarction (2018),” European Heart Journal 40, no. 3 (2019): 237–269. [DOI] [PubMed] [Google Scholar]
- 11. Ibanez B., James S., Agewall S., et al., “2017 ESC Guidelines for the Management of Acute Myocardial Infarction in Patients Presenting With ST‐Segment Elevation: The Task Force for the Management of Acute Myocardial Infarction in Patients Presenting With St‐Segment Elevation of the European Society of Cardiology (ESC),” European Heart Journal 39, no. 2 (2018): 119–177. [DOI] [PubMed] [Google Scholar]
- 12. Rao S. V., O'Donoghue M. L., Ruel M., et al., “2025 ACC/AHA/ACEP/NAEMSP/SCAI Guideline for the Management of Patients With Acute Coronary Syndromes: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines,” Circulation 151, no. 13 (2025): e771–e862. [DOI] [PubMed] [Google Scholar]
- 13. Tang A., Yang E., and Ebinger J. E., “Non‐Dipping Blood Pressure or Nocturnal Hypertension: Does One Matter More?,” Current Hypertension Reports 26, no. 1 (2024): 21–30. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14. Kim C. H., Lee S. H., Kim H. K., et al., “Prognostic Implications of N‐Terminal Pro‐B‐Type Natriuretic Peptide in Patients With Non‐ST‐Elevation Myocardial Infarction,” Circulation Journal 88, no. 8 (2024): 1237–1245. [DOI] [PubMed] [Google Scholar]
- 15. Martin S. S., Aday A. W., Allen N. B., et al., “2025 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association,” Circulation 151, no. 8 (2025): e41–e660. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16. Zhang J., Sun R., Jiang T., Yang G., and Chen L., “Circadian Blood Pressure Rhythm in Cardiovascular and Renal Health and Disease,” Biomolecules 11, no. 6 (2021): 868. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17. Mancia G., Facchetti R., Bombelli M., Quarti‐Trevano F., Cuspidi C., and Grassi G., “Short‐ and Long‐Term Reproducibility of Nighttime Blood Pressure Phenotypes and Nocturnal Blood Pressure Reduction,” Hypertension 77, no. 5 (2021): 1745–1755. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18. Palatini P., Verdecchia P., Beilin L. J., et al., “Association of Extreme Nocturnal Dipping With Cardiovascular Events Strongly Depends on Age,” Hypertension 75, no. 2 (2020): 324–330. [DOI] [PubMed] [Google Scholar]
- 19. Lal H., Verma S. K., Wang Y., Xie M., and Young M. E., “Circadian Rhythms in Cardiovascular Metabolism,” Circulation Research 134, no. 6 (2024): 635–658. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20. Hansen T. W., Li Y., Boggia J., Thijs L., Richart T., and Staessen J. A., “Predictive Role of the Nighttime Blood Pressure,” Hypertension 57, no. 1 (2011): 3–10. [DOI] [PubMed] [Google Scholar]
- 21. Gumz M. L., Shimbo D., Abdalla M., et al., “Toward Precision Medicine: Circadian Rhythm of Blood Pressure and Chronotherapy for Hypertension ‐ 2021 NHLBI Workshop Report,” Hypertension (Dallas, Tex.: 1979) 80, no. 3 (2023): 503–522. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22. Ye R., Yang X., Zhang X., et al., “Morning vs Bedtime Dosing and Nocturnal Blood Pressure Reduction in Patients With Hypertension: The OMAN Randomized Clinical Trial,” JAMA Network Open 8, no. 7 (2025): e2519354. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23. van Dalfsen J. H. and Markus C. R., “The Influence of Sleep on Human Hypothalamic‐Pituitary‐Adrenal (HPA) Axis Reactivity: A Systematic Review,” Sleep Medicine Reviews 39 (2018): 187–194. [DOI] [PubMed] [Google Scholar]
- 24. Quarti‐Trevano F., Seravalle G., and Grassi G., “Clinical Relevance of the Sympathetic‐Vascular Interactions in Health and Disease,” Biomedicines 9, no. 8 (2021): 1007. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25. Filipovska E., Skalova K., Spisska V., et al., “Stat3 Silencing Affects Circadian Clock Gene Expression and Lipopolysaccharide Response in the Suprachiasmatic Nucleus, Cortex, and Glioblastoma Cell Cultures,” FASEB Journal 39, no. 10 (2025): e70577. [DOI] [PubMed] [Google Scholar]
- 26. Ziegler K. A., Engelhardt S., Carnevale D., et al., “Neural Mechanisms in Cardiovascular Health and Disease,” Circulation Research 136, no. 11 (2025): 1233–1261. [DOI] [PubMed] [Google Scholar]
- 27. Gibbs J. E., Blaikley J., Beesley S., et al., “The Nuclear Receptor REV‐ERBα Mediates Circadian Regulation of Innate Immunity Through Selective Regulation of Inflammatory Cytokines,” Proceedings of the National Academy of Sciences 109, no. 2 (2012): 582–587. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28. Yang L. N., Xu S., Tang M., et al., “The Circadian Rhythm Gene Bmal1 Ameliorates Acute Deoxynivalenol‐Induced Liver Damage,” Archives of Toxicology 97, no. 3 (2023): 787–804. [DOI] [PubMed] [Google Scholar]
- 29. Huynh P., Hoffmann J. D., Gerhardt T., et al., “Myocardial Infarction Augments Sleep to Limit Cardiac Inflammation and Damage,” Nature 635, no. 8037 (2024): 168–177. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30. Lecarpentier Y., Schussler O., Hébert J. L., and Vallée A., “Molecular Mechanisms Underlying the Circadian Rhythm of Blood Pressure in Normotensive Subjects,” Current Hypertension Reports 22, no. 7 (2020): 50. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31. Wang Z., Mu W., Zhong J., et al., “Vascular Smooth Muscle Cell PRDM16 Regulates Circadian Variation in Blood Pressure,” Journal of Clinical Investigation 135, no. 3 (2024): e183409. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32. Hao K., Zhai Q., Gu Y., et al., “Disturbance of Suprachiasmatic Nucleus Function Improves Cardiac Repair After Myocardial Infarction by IGF2‐mediated Macrophage Transition,” Acta Pharmacologica Sinica 44, no. 8 (2023): 1612–1624. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33. Higashikuni Y., Liu W., and Sata M., “Nocturnal Blood Pressure and Left Ventricular Hypertrophy in Patients With Diabetes Mellitus,” Hypertension Research 47, no. 3 (2024): 819–822. [DOI] [PubMed] [Google Scholar]
- 34. Mohan M., Dihoum A., Mordi I. R., Choy A. M., Rena G., and Lang C. C., “Left Ventricular Hypertrophy in Diabetic Cardiomyopathy: A Target for Intervention,” Frontiers in Cardiovascular Medicine 8 (2021): 746382. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35. Tsioufis C., Syrseloudis D., Dimitriadis K., et al., “Disturbed Circadian Blood Pressure Rhythm and C‐Reactive Protein in Essential Hypertension,” Journal of Human Hypertension 22, no. 7 (2008): 501–508. [DOI] [PubMed] [Google Scholar]
- 36. Ye J., Xu D., Yuan R., et al., “Significance of Multiple Lymphocyte‐To‐C‐Reactive Protein Ratios in Predicting Long‐Term Major Cardiovascular Adverse Events in Emergency Percutaneous Coronary Intervention Patients With St‐Segment Elevation Myocardial Infarction,” Journal of Inflammation Research 17 (2024): 3407–3418. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37. Gabaldon‐Perez A., Marcos‐Garces V., Gavara J., et al., “Prognostic Value of Cardiac Magnetic Resonance Early After ST‐Segment Elevation Myocardial Infarction in Older Patients,” Age and Ageing 51, no. 11 (2022): afac248. [DOI] [PubMed] [Google Scholar]
- 38. Kario K., Hoshide S., Mizuno H., et al., “Nighttime Blood Pressure Phenotype and Cardiovascular Prognosis: Practitioner‐Based Nationwide JAMP Study,” Circulation 142, no. 19 (2020): 1810–1820. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39. Sun Y., Zhang Y., Liu F., et al., “The Relationship Between Circadian Rhythm of Blood Pressure and Vascular Dysfunction in Essential Hypertension,” Clinical and Experimental Hypertension 45, no. 1 (2023): 2229535. [DOI] [PubMed] [Google Scholar]
- 40. Wang J., Xu J., Yang L., et al., “Heart Rate Deceleration and Acceleration Capacities Associated With Circadian Rhythm of Blood Pressure in Essential Hypertension,” BMC Cardiovascular Disorders 24, no. 1 (2024): 257. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41. Grassi G., Seravalle G., Quarti‐Trevano F., et al., “Adrenergic, Metabolic, and Reflex Abnormalities in Reverse and Extreme Dipper Hypertensives,” Hypertension 52, no. 5 (2008): 925–931. [DOI] [PubMed] [Google Scholar]
- 42. Redon J. and Lurbe E., “Nocturnal Blood Pressure Versus Nondipping Pattern: What Do They Mean?,” Hypertension 51, no. 1 (2008): 41–42. [DOI] [PubMed] [Google Scholar]
- 43. Ruan W., Li T., Bang I. H., et al., “BMAL1‐HIF2A Heterodimer Modulates Circadian Variations of Myocardial Injury,” Nature 641 (2025): 1017–1028. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44. Slusniene A., Navickas P., Stankus A., Lauceviciene I., Ryliskyte L., and Laucevicius A., “Defining the Nocturnal Period in 24‐h Ambulatory Blood Pressure Monitoring: A Comparison of Three Methods,” Blood Pressure Monitoring 26, no. 3 (2021): 207–214. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.
The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.