| Literature DB >> 28266644 |
Wen-Hsien Lee1,2,3,4, Po-Chao Hsu2,4, Chun-Yuan Chu2,4, Szu-Chia Chen1,3,4, Hung-Hao Lee2, Meng-Kuang Lee2,3, Chee-Siong Lee2,4, Hsueh-Wei Yen2,4, Tsung-Hsien Lin2,4, Wen-Chol Voon2,4, Wen-Ter Lai2,4, Sheng-Hsiung Sheu2,4, Po-Lin Kuo1, Ho-Ming Su2,3,4.
Abstract
The aim of this study was to evaluate the use of renal systolic time intervals measured by electrocardiographic gated Doppler ultrasonography for predicting adverse cardiac events. This longitudinal observation study enrolled 205 patients. Renal systolic time intervals, including pre-ejection period (PEP) and ejection time (ET), and ratio of renal PEP to ET, were measured by electrocardiographic gated Doppler ultrasound. The 14 adverse cardiac events identified in this population included 9 cardiac deaths and 5 hospitalizations for heart failure during an average follow up of 30.9 months (25th-75th percentile: 30-33 months). Renal PEP (hazard ratio = 1.023, P = 0.001), renal ET (hazard ratio = 0.975, P = 0.001) and renal PEP/ET (per 0.01 unit increase, hazard ratio = 1.060, P < 0.001) were associated with poor cardiac outcomes. The addition of renal PEP/ET to a Cox model containing important clinical variables and renal resistive index further improved the value in predicting adverse cardiac events (Chi-square increase, 9.996; P = 0.002). This study showed that parameters of intra-renal hemodynamics were potential predictors of adverse cardiac outcomes. However, the generalizability of these indicators need to be investigated in future large-scale studies.Entities:
Mesh:
Year: 2017 PMID: 28266644 PMCID: PMC5339860 DOI: 10.1038/srep43825
Source DB: PubMed Journal: Sci Rep ISSN: 2045-2322 Impact factor: 4.379
Figure 1Flowchart of recruitment procedure.
Clinical and renal Doppler ultrasonographic characteristics of study patients.
| Characteristics | All patients (number = 205) |
|---|---|
| Age (years) | 64.4 ± 12.3 |
| Male gender (%) | 59.5 |
| Smoking (%) | 20.0 |
| Diabetes mellitus (%) | 30.2 |
| Hypertension (%) | 73.2 |
| CAD (%) | 16.6 |
| Stroke (%) | 10.2 |
| Heart failure (%) | 17.6 |
| Systolic BP (mmHg) | 133.3 ± 17.8 |
| Diastolic BP (mmHg) | 75.4 ± 11.1 |
| Pulse pressure (mmHg) | 57.9 ± 12.6 |
| Heart rate (min−1) | 68.6 ± 11.7 |
| Body mass index (kg/m2) | 26.3 ± 3.8 |
| Total cholesterol (mg/dL) | 191.3 ± 41.0 |
| eGFR (mL/min/1.73 m2) | 60.9 ± 20.8 |
| Glucose (mg/dl) | 120.5 ± 43.5 |
| Hemoglobin (g/dL) | 13.4 ± 1.9 |
| ACEI (%) | 18.0 |
| ARB (%) | 44.4 |
| β-blocker (%) | 44.9 |
| CCB (%) | 47.3 |
| Diuretics (%) | 35.1 |
| Renal RI | 0.69 ± 0.084 |
| Renal PEP (ms) | 123.3 ± 23.7 |
| Renal ET (ms) | 304.8 ± 36.7 |
| Renal PEP/ET | 0.41 ± 0.11 |
Abbreviations.ACEI: angiotensin converting enzyme inhibitor; ARB: angiotensin II receptor blocker; BP: blood pressure; CAD: coronary artery disease; CCB: calcium channel blocker; eGFR: estimated glomerular filtration rate; ET: ejection time; ms, millisecond; pre-ejection period; RI: resistive index.
Predictors of cardiac events (cardiac death and hospitalization for heart failure) using Cox proportional hazards model.
| Parameter | HR (95% CI) | |
|---|---|---|
| Age (year) | 1.001 (0.959, 1.045) | 0.949 |
| Male gender (%) | 1.264 (0.423, 3.771) | 0.675 |
| Smoking (%) | 1.079 (0.301, 3.868) | 0.907 |
| Diabetes mellitus (%) | 6.367 (1.996, 20.318) | 0.002 |
| Hypertension (%) | 2.231 (0.499, 9.971) | 0.293 |
| CAD (%) | 1.479 (0.412, 5.303) | 0.548 |
| Stroke (%) | 0.693 (0.091, 5.297) | 0.724 |
| Heart failure (%) | 38.017 (8.424, 171.565) | <0.001 |
| Systolic BP (mmHg) | 0.999 (0.969, 1.029) | 0.928 |
| Diastolic BP (mmHg) | 1.025 (0.985, 1.067) | 0.221 |
| Pulse pressure (mmHg) | 0.972 (0.927, 1.018) | 0.228 |
| Heart rate (min−1) | 1.050 (1.010, 1.092) | 0.013 |
| Body mass index (kg/m2) | 0.952 (0.820, 1.107) | 0.525 |
| Total cholesterol (mg/dL) | 0.989 (0.972, 1.006) | 0.203 |
| eGFR (mL/min/1.73 m2) | 0.941 (0.916, 0.966) | <0.001 |
| Glucose (mg/dl) | 1.010 (1.002, 1.018) | 0.011 |
| Hemoglobin | 0.612 (0.457, 0.819) | 0.001 |
| ACEI use (%) | 0.336 (0.044, 2.566) | 0.293 |
| ARB use (%) | 2.384 (0.799, 7.113) | 0.119 |
| β-blocker use (%) | 4.822 (1.345, 17.293) | 0.016 |
| CCB use (%) | 0.423 (0.133, 1.348) | 0.146 |
| Diuretics use (%) | 4.965 (1.557, 15.837) | 0.007 |
| Renal RI (per 0.01) | 1.093 (1.017, 1.173) | 0.015 |
| Renal PEP (ms) | 1.023 (1.010, 1.037) | 0.001 |
| Renal ET (ms) | 0.975 (0.961, 0.989) | 0.001 |
| Renal PEP/ET (per 0.01) | 1.060 (1.034, 1.088) | <0.001 |
HR: hazard ratio; CI: confidence interval; other abbreviations as in Table 1.
Figure 2Results of Kaplan-Meier analysis of cardiac event-free survival in study patients.
Figure 3Addition of the ratio of renal pre-ejection period (PEP) to ejection time (ET) significantly improved prediction of adverse cardiac events in the basic clinical model (diabetes mellitus, chronic heart failure, serum glucose, estimated glomerular filtration rate, hemoglobin, and diuretic and β blocker use) and in the basic clinical model with the addition of renal resistive index (RI) (both P = 0.002).