PCI has been a standard approach to achieve revascularization of obstructive coronary CAD. The improvement of techniques and equipment dramatically decreases the incidence of severe complications after PCI, such as stent thrombosis, perforation, and death [
The most common mechanisms of PMI could be classified into two types: one is due to side branch occlusion proximal to the target lesion of PCI, and the other is due to microvascular dysfunction distal of the treated lesion [
Impaired endothelial function detected by PAT was associated with higher adverse cardiac event rate during follow-up [
This study was approved by the Ethical Committee of Zhongshan Hospital, Fudan University (Approval No: B2016-018, Date: 2016/02/29). All patients provided their written, informed consent. The study was carried out in accordance with the principles of the Declaration of Helsinki.
From May 2015 to November 2015, 268 patients suspected with stable CAD admitted for elective PCI were enrolled. Exclusion criteria were acute coronary syndrome, malignant hypertension, New York Heart Association (NYHA) class III to IV heart failure, cardiomyopathy, and cardiac valvular disease. Patients with active infection, carcinoma, immunological disorders, and liver or kidney dysfunction (eGFR < 60 mL/min/1.73 m2 or liver enzyme >3 × upper reference limit (URL)) were also excluded.
RHI was measured with Endo-PAT2000™ (Itamar Medical, Israel) before coronary angiography by cardiologists who were blinded to the results of clinical characteristics and laboratory testing. This measurement was arranged in a quiet test room at 8 am–10 am with temperature set to 24–28 centigrade. All vasoactive medications (such as calcium antagonists and nitrate) were discontinued at least 24 h prior to testing. According to previous studies and device protocols, a blood pressure cuff was placed on one upper arm, while the other arm served as a control. PAT probes were placed on each index finger for continuous recording of the pulse signal. After a 10 min equilibration period, the blood pressure cuff was inflated to suprasystolic pressure (200 mmHg or 60 mmHg plus systolic blood pressure) for 5 min. Then, the cuff was deflated to induce reactive hyperemia and PAT was recorded for a further 5 min. The pulse amplitude recordings were automatically analyzed and quantified as RHI.
CAD was diagnosed when at least one lesion led to a >50% reduction in lumen diameter in coronary angiography. Coronary angiography, syntax score evaluation, and intervention were performed by cardiologists blinded to laboratory testing and RHI. Venous serum samples were collected on admission and 16–20 hours after PCI for laboratory measurements.
PMI was defined as a cTnT value above the 99% URL after the procedure. Patients were followed up with a median 18-month interval through telephone consultation or outpatient clinic attendance. The primary outcomes were major adverse cardiovascular events (MACEs), including cardiac death, nonfatal myocardial infarction (MI), stroke, target vessel revascularization (TVR), and rehospitalization driven by heart failure.
All statistical analyses were performed with SPSS for Windows, release 25.0 (IBM SPSS, Inc., Chicago, IL, USA). Continuous variables are presented as mean ± standard deviation (SD) or median with the interquartile range (IQR). Categorical data are expressed as counts and percentages. Chi-square or Fisher's exact test was used to compare the frequency for categorical variables. Means for continuous variables were compared by Student’s t or Mann–Whitney U test. Logistic regression was performed to identify risk factors and the Spearman test for correlation analyses. Kaplan–Meier survival analysis was conducted to compare the difference in incidence of MACEs. The prognostic impact of RHI was assessed with a univariable and multivariable Cox proportional hazard model, adjusted to age, male, hypertension, diabetes, smoking, low-density lipoprotein cholesterol, and hemoglobin. All
268 patients suspected with stable CAD undergoing elective coronary angiography were recruited in this study. 189 patients (70.5%) were diagnosed with CAD by angiography, and 119 patients (44.4%) accepted DES implantation. When PMI was defined as a post-PCI cTnT value > 99% URL, 51 out of the 119 patients (42.9%) had PMI.
Compared with patients without CAD, CAD patients had a lower RHI (1.88 ± 0.55 vs. 2.02 ± 0.58,
Violin plot of RHI in different groups. Distribution of RHI in different patient groups was presented in a violin plot. The width of the box represents the density of values. Solid lines and dotted lines represent the median and interquartile range of RHI, respectively. Patients with CAD or PMI had lower RHI compared with patients without CAD or PMI, separately.
Demographics and clinical characteristics.
Total (268) | RHI > 1.81 (131) | RHI ≤ 1.81 (137) | ||
---|---|---|---|---|
Age | 62.9 ± 9.0 | 63.2 ± 8.8 | 62.6 ± 9.3 | 0.654 |
Male | 185 (69.0) | 87 (66.4) | 98 (71.5) | 0.365 |
Hypertension | 170 (63.4) | 80 (61.1) | 90 (65.7) | 0.432 |
Diabetes | 60 (22.3) | 28 (21.4) | 32 (23.4) | 0.697 |
Smoking history | 95 (35.4) | 42 (32.1) | 53 (38.7) | 0.257 |
BMI | 24.7 ± 3.0 | 24.5 ± 3.2 | 24.9 ± 2.8 | 0.228 |
CAD | 189 (70.5) | 87 (66.4) | 102 (74.5) | 0.149 |
Syntax score | 14.9 ± 8.0 | 12.0 ± 6.6 | 17.3 ± 8.3 | <0.001 |
Coronary slow flow | 11 (4.1) | 4 (3.1) | 7 (5.1) | 0.396 |
Systolic blood pressure (mmHg) | 132.4 ± 12.3 | 131.6 ± 12.2 | 133.2 ± 12.4 | 0.592 |
Diastolic blood pressure (mmHg) | 80.0 ± 8.2 | 79.0 ± 8.4 | 81.0 ± 8.0 | 0.100 |
NT-proBNP (pg/ml) | 214.2 ± 536.7 | 215.1 ± 523.9 | 213.0 ± 550.6 | 0.461 |
Creatinine (mg/dl) | 78.2 ± 16.9 | 76.8 ± 17.3 | 79.5 ± 16.6 | 0.187 |
CK (U/L) | 94.4 ± 47.6 | 94.0 ± 50.8 | 94.8 ± 44.4 | 0.317 |
CK-MB (U/L) | 12.9 ± 8.2 | 13.0 ± 10.2 | 12.7 ± 5.2 | 0.941 |
hs-CRP (mg/L) | 3.94 ± 7.27 | 3.55 ± 7.17 | 4.35 ± 7.40 | 0.096 |
Hemoglobin (g/L) | 134.4 ± 14.5 | 132.9 ± 13.9 | 135.9 ± 14.8 | 0.091 |
Platelet (×10^9/L) | 207.5 ± 64.2 | 205.9 ± 62.1 | 209.0 ± 66.4 | 0.827 |
Total cholesterol (mmol/L) | 3.82 ± 0.97 | 3.73 ± 0.86 | 3.91 ± 1.07 | 0.252 |
Low-density lipoprotein (mmol/L) | 1.97 ± 0.81 | 1.94 ± 0.74 | 1.99 ± 0.87 | 0.892 |
Triglyceride (mmol/L) | 1.77 ± 1.40 | 1.59 ± 0.96 | 1.94 ± 1.71 | 0.038 |
High-density lipoprotein (mmol/L) | 1.14 ± 0.46 | 1.15 ± 0.57 | 1.13 ± 0.33 | 0.938 |
Lp (a) (mmol/L) | 349.6 ± 485.8 | 351.8 ± 468.7 | 347.5 ± 503.5 | 0.370 |
HbA1c (%) | 6.2 ± 1.4 | 6.1 ± 1.2 | 6.3 ± 1.5 | 0.111 |
LA (mm) | 38.9 ± 4.3 | 38.1 ± 4.4 | 39.5 ± 0.4 | 0.010 |
LVEDD (mm) | 47.1 ± 4.5 | 46.5 ± 4.2 | 47.6 ± 4.8 | 0.050 |
LVESD (mm) | 30.3 ± 4.3 | 30.0 ± 3.7 | 30.8 ± 4.8 | 0.090 |
SPAP (mmHg) | 32.4 ± 6.3 | 32.7 ± 7.0 | 32.1 ± 5.7 | 0.784 |
EF (%) | 64.4 ± 7.0 | 64.3 ± 7.3 | 64.5 ± 6.6 | 0.906 |
Statin | 237 (88.4) | 113 (86.3) | 124 (90.5) | 0.277 |
Β-blockade | 175 (65.2) | 86 (65.6) | 89 (65.0) | 0.906 |
Nitrates | 132 (49.3) | 59 (45.0) | 73 (53.3) | 0.177 |
Calcium channel blockade | 68 (25.4) | 35 (26.7) | 33 (24.1) | 0.621 |
Data are shown as mean ± SD or
As shown in Table
Baseline and procedural characteristics of PMI.
Total (119) | Non-PMI (68) | PMI (51) | ||
---|---|---|---|---|
Age | 63.7 ± 9.5 | 64.0 ± 9.8 | 63.2 ± 9.3 | 0.476 |
Male | 91 (76.4) | 50 (73.5) | 41 (80.4) | 0.382 |
Hypertension | 81 (68.1) | 44 (64.7) | 37 (72.5) | 0.364 |
Diabetes | 25 (21.0) | 16 (23.5) | 9 (17.5) | 0.687 |
Smoking history | 49 (41.1) | 25 (36.8) | 24 (47.1) | 0.259 |
BMI | 24.8 ± 3.2 | 24.7 ± 3.2 | 24.9 ± 3.3 | 0.573 |
Syntax score | 15.2 ± 7.5 | 13.4 ± 6.3 | 17.4 ± 8.4 | 0.008 |
RHI | 1.86 ± 0.46 | 1.95 ± 0.50 | 1.75 ± 0.37 | 0.039 |
NT-proBNP (pg/ml) | 225.1 ± 582.9 | 229.7 ± 735.7 | 219.2 ± 298.2 | 0.006 |
Creatinine (mg/dl) | 78.3 ± 15.8 | 76.6 ± 15.0 | 80.6 ± 16.6 | 0.088 |
CK (U/L) | 94.6 ± 45.6 | 96.0 ± 50.8 | 92.9 ± 38.3 | 0.658 |
CK-MB (U/L) | 12.8 ± 3.8 | 12.8 ± 4.3 | 12.8 ± 3.1 | 0.596 |
hs-CRP (mg/L) | 5.07 ± 9.41 | 3.95 ± 6.08 | 6.46 ± 12.3 | 0.691 |
Hemoglobin (g/L) | 136.2 ± 14.1 | 135.4 ± 13.8 | 137.3 ± 14.7 | 0.512 |
Platelet (×10^9/L) | 208.3 ± 68.2 | 205.4 ± 76.4 | 212.3 ± 56.0 | 0.262 |
Total cholesterol (mmol/L) | 3.86 ± 1.02 | 3.70 ± 0.99 | 4.08 ± 1.03 | 0.032 |
Low-density lipoprotein (mmol/L) | 2.04 ± 0.83 | 1.88 ± 0.77 | 2.24 ± 0.86 | 0.024 |
Triglyceride (mmol/L) | 1.83 ± 1.70 | 1.97 ± 2.10 | 1.66 ± 0.92 | 0.912 |
High-density lipoprotein (mmol/L) | 1.08 ± 0.30 | 1.06 ± 0.34 | 1.12 ± 0.24 | 0.025 |
Lp (a) (mmol/L) | 339.2 ± 438.2 | 300.0 ± 298.6 | 391.8 ± 485.2 | 0.393 |
HbA1c (%) | 6.1 ± 1.2 | 6.1 ± 1.4 | 6.1 ± 0.9 | 0.400 |
LA (mm) | 39.2 ± 4.2 | 39.2 ± 4.5 | 39.4 ± 3.8 | 0.900 |
LVEDD (mm) | 46.7 ± 4.0 | 46.5 ± 4.5 | 47.2 ± 3.2 | 0.350 |
LVESD (mm) | 30.2 ± 3.4 | 30.1 ± 3.6 | 30.4 ± 3.1 | 0.644 |
SPAP (mmHg) | 32.9 ± 7.4 | 33.1 ± 8.2 | 32.6 ± 6.3 | 0.973 |
EF (%) | 64.7 ± 6.1 | 65.0 ± 6.2 | 64.5 ± 6.2 | 0.529 |
Aspirin | 115 (96.6) | 64 (94.1) | 51 (100) | 0.134 |
Statin | 118 (99.2) | 67 (98.5) | 51 (100) | 1.000 |
Β-blockade | 87 (73.1) | 54 (79.4) | 34 (66.7) | 0.117 |
Nitrates | 74 (62.2) | 39 (57.4) | 35 (68.6) | 0.060 |
Calcium channel blockade | 29 (24.3) | 16 (23.5) | 13 (25.5) | 0.805 |
Stent length (mm) | 44.4 ± 26.3 | 38.0 ± 21.5 | 52.8 ± 29.8 | 0.002 |
Use of GBI | 20 (16.8) | 11 (16.2) | 9 (17.6) | 0.832 |
Average stent diameter (mm) | 3.06 ± 0.44 | 3.11 ± 0.45 | 2.99 ± 0.41 | 0.149 |
1 | 96 (80.7) | 58 (85.3) | 38 (74.5) | 0.140 |
2 | 20 (16.8) | 9 (13.2) | 11 (21.6) | 0.229 |
3 | 3 (2.5) | 1 (1.5) | 2 (1.7) | 0.576 |
Data are shown as mean ± SD or
Binary logistic analysis was performed to evaluate the role of RHI on the occurrence of PMI. Our results demonstrated that RHI (odds ratio (OR) 0.35, 95% confidence interval (CI) 0.4–0.86,
Risk factors of PMI.
Odds ratio (95% CI) | ||
---|---|---|
Age ≥65 y | 0.67 (0.33–1.40) | 0.291 |
Male | 1.48 (0.61–3.55) | 0.384 |
Hypertension | 1.44 (0.65–3.18) | 0.365 |
Diabetes | 0.70 (0.28–1.73) | 0.437 |
Dyslipidemia | 1.47 (0.64–3.38) | 0.362 |
Smoking history | 1.53 (0.73–3.20) | 0.260 |
Body mass index | 1.02 (0.91–1.14) | 0.738 |
Stent length | 1.02 (1.01–1.04) | 0.004 |
Target vessel number | 1.82 (0.83–4.00) | 0.137 |
Average stent diameter | 0.52 (0.22–1.24) | 0.141 |
RHI | 0.35 (0.14–0.86) | 0.022 |
RHI, reactive hyperemia index.
Cumulative incidence of MACEs. Patients with RHI ≤ 1.81 had a higher risk of MACEs (
Patients were followed up for a mean period of 18 months, during which 20 patients had adverse events (Table
Long-term outcomes and RHI.
. | RHI ≤ 1.81 | RHI > 1.81 | HR | adHR | ||
---|---|---|---|---|---|---|
MACEs | 16 | 4 | 3.34 (1.10–10.16) | 0.033 | 3.31 (1.07–10.22) | 0.038 |
Nonfatal myocardial infarction | 1 | 0 | — | 0.784 | — | — |
Target vessel revascularization | 10 | 3 | — | 0.193 | — | — |
Cardiac death | 0 | 0 | — | 1 | — | — |
Rehospitalization driven by heart failure | 4 | 0 | — | 0.784 | — | — |
Ischemic stroke | 1 | 1 | — | 0.053 | — | — |
Values are given as
ROC curve for the prediction of PMI. The dotted diagonal line is the null hypothesis with AUC = 0.50. RHI < 1.83 had a sensitivity of 62.7% and specificity of 50.0% to predict PMI with AUC = 0.61 (95% CI 0.51–0.71). AUC, area under the curve; CI, confidence interval; PMI, periprocedural myocardial injury; RHI, reactive hyperemia index; ROC, receiver operating characteristic.
In the past decades, the development of both equipment and technique has made PCI a mainstay in the treatment of obstructive coronary disease. While severe complications of PCI keep declining over the years, there has not been an ideal way to predict PMI and cut down the incidence. Coronary microvascular dysfunction plays an essential role in PMI, which is not only the consequence of microcirculatory damage but also a crucial risk factor to exacerbate myocardial injury. Assessment of CMD relies on functional assessment of microcirculation, which can be performed invasively, such as index of microvascular resistance (IMR) [
In this cohort, the incidence of PMI was consistent with our previous study [
Moreover, RHI is reported to be closely related with risk factors and early stage of CAD as well as poor cardiovascular prognosis [
There are some limitations in our study. First, this is a single-centered study with a relatively small sample size. However, the present study has been a relatively large one to investigate the independent role of RHI on the long-term composite outcome after DES implantation. Second, this study was conducted on a rather homogenous population. Patients with comorbidities such as ACS and renal or liver dysfunction were excluded. As a result, additional research is needed to verify if these findings could be extended to other cohorts. Third, we could not acquire the details about RHI when MACEs happened, for RHI measured at follow-up may reflect the simultaneous state of endothelial function and more closely related with the type of MACEs. However, this will not affect the conclusion that baseline RHI was a predictor of PMI and correlated with high risk of MACEs. Fourth, multicentered research is pended to bring out a uniform cutoff value of RHI to predict, and the specificity and sensitivity of RHI need to be tested in larger populations.
RHI assessed by PAT could be a promising predictor of PMI before the procedure. Low RHI is correlated with high risk of long-term MACEs in CAD patients after DES implantation.
Readers can access the data supporting the conclusions of this study by contacting the correspondence author.
There are no conflicts of interest pertaining to this submission.
Zhangwei Chen, You Zhou, and Jiasheng Yin contributed equally to this article.
This study was supported by the National Program on Key Basic Research Project of China (Grant Nos. 2019YFC0840601 and 2014CBA02003), National Natural Science Foundation of China (Grant Nos. 81870267, 81970295, 81521001, 81670318, and 81570314), grant of Shanghai Shenkang on Key Clinical Research Project (Grant Nos. SHDC2020CR2015A and SHDC12019104), grant of Shanghai Science and Technology Committee (Grant Nos. 19MC1910300, 18411950200, and 20JC1410800), Key Medical and Health Projects of Xiamen Province (No. 3502Z20204004), grant of Shanghai Municipal Commission of Health and Family Planning (Grant No. 2017YQ057), grant of Zhongshan Hospital Affiliated to Fudan University (Grant No. 2018ZSLC01), VG Funding of Clinical Trials (2017-CCA-VG-036) and Merck Funding (Xinxin-merck-fund-051), and National Key Research and Development Program of China from the Ministry of Science and Technology of the People’s Republic of China (2016YFC1301203).