2022 Vol. 19, No. 6
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2022, 19(6): 409-417.
doi: 10.11909/j.issn.1671-5411.2022.06.002
Abstract:
BACKGROUND Cerebral microbleeds (CMBs) may increase the risk of future intracerebral hemorrhage and ischemic stroke. However, It is unclear whether antiplatelet medication is associated with CMBs. This study aimed to investigate the association between antiplatelet medication and CMBs in a community-based stroke-free population. METHODS In this cross-sectional study, stroke-free participants aged 18–85 years were recruited from a community in Beijing, China. Demographic, clinical, and antiplatelet medication data were collected through a questionnaire, and all participants underwent blood tests and brain magnetic resonance imaging at 3.0T. The presence, count, and location of CMBs were evaluated using susceptibility-weighted imaging. The association between antiplatelet medication and the presence of CMBs was analyzed using multivariable logistic regression. The associations between antiplatelet medication and CMBs by location (lobar, deep brain or infratentorial, and mixed regions) were also analyzed using multinomial logistic regression. A linear regression analysis was conducted to determine the association between antiplatelet medication and the log-transformed number of CMBs. RESULTS Of the 544 participants (mean age: 58.65 ± 13.66 years, 217 males), 119 participants (21.88%) had CMBs, and 64 participants (11.76%) used antiplatelet medication. Antiplatelet medication was found to be associated with CMBs at any location [odds ratio (OR) = 2.39, 95% CI: 1.24–4.58] and lobar region (OR = 2.83, 95% CI: 1.36–5.86), but not with the number of CMBs (β = 0.14, 95% CI: -0.21–0.48). Among antiplatelet medications, aspirin use was found to be associated with any CMB (OR = 3.17, 95% CI: 1.49–6.72) and lobar CMBs (OR = 3.61, 95% CI: 1.57–8.26). CONCLUSIONS Antiplatelet medication was associated with CMBs in stroke-free participants, particularly lobar CMBs. Among antiplatelet medications, aspirin use was associated with any CMB and lobar CMBs. Our findings suggest that it might be essential to optimize the management of antiplatelet medication in the stroke-free population with a higher burden of vascular risk factors to reduce the potential risk of CMBs.
2022, 19(6): 418-427.
doi: 10.11909/j.issn.1671-5411.2022.06.010
Abstract:
BACKGROUND Epidemiologic studies have explored the association between a single cardiovascular risk factor (CVRF) and resting heart rate (RHR), but the research on the relation of multiple risk factors with RHR remains scarce. This study aimed to explore the associations between CVRFs clustering and the risk of elevated RHR. METHODS In this cross-sectional study, adults aged 35–75 years from 31 provinces were recruited by the China PEACE Million Persons Projects from September 2015 to August 2020. We focused on seven risk factors: hypertension, diabetes mellitus, dyslipidemia, obesity, smoking, alcohol use, and low physical activity. Multivariate logistic regression was used to calculate odds ratios (OR) for elevated RHR (> 80 beats/min). RESULTS Among 1,045,405 participants, the mean age was 55.67 ± 9.86 years, and 60.4% of participants were women. The OR (95% CI) for elevated RHR for the groups with 1, 2, 3, 4 and ≥ 5 risk factor were 1.11 (1.08–1.13), 1.36 (1.33–1.39), 1.68 (1.64–1.72), 2.01 (1.96–2.07) and 2.58 (2.50–2.67), respectively (Ptrend < 0.001). The association between the CVRFs clustering number and elevated RHR was much more pronounced in young males than in other age-sex subgroups. Clusters comprising more metabolic risk factors were associated with a higher risk of elevated RHR than those comprising more behavioral risk factors. CONCLUSIONS There was a significant positive association between the CVRFs clustering number and the risk of elevated RHR, particularly in young males. Compared clusters comprising more behavioral risk factors, clusters comprising more metabolic risk factors were associated with a higher risk of elevated RHR. RHR may serve as an indicator of the cumulative effect of multiple risk factors.
2022, 19(6): 428-434.
doi: 10.11909/j.issn.1671-5411.2022.06.005
Abstract:
BACKGROUND Chronic obstructive pulmonary disease (COPD) and cardiovascular diseases are often comorbid conditions, their co-occurrence yields worse outcomes than either condition alone. This study aimed to investigate COPD impacts on the five-year prognosis of patients with coronary heart disease (CHD) after percutaneous coronary intervention (PCI). METHODS Patients with CHD who underwent PCI in 2013 were recruited, and divided into COPD group and non-COPD group. Adverse events occurring among those groups were recorded during the five-year follow-up period after PCI, including all-cause death and cardiogenic death, myocardial infarction, repeated revascularization, as well as stroke and bleeding events. Major adverse cardiac and cerebral events were a composite of all-cause death, myocardial infarction, repeated revascularization and stroke. RESULTS A total of 9843 patients were consecutively enrolled, of which 229 patients (2.3%) had COPD. Compared to non-COPD patients, COPD patients were older, along with poorer estimated glomerular filtration rate and lower left ventricular ejection fraction. Five-year follow-up results showed that incidences of all-cause death and cardiogenic death, as well as major adverse cardiac and cerebral events, for the COPD group were significantly higher than for non-COPD group (10.5% vs. 3.9%, 7.4% vs. 2.3%, and 30.1% vs. 22.6%, respectively). COPD was found under multivariate Cox regression analysis, adjusted for confounding factors, to be an independent predictor of all-cause death [odds ratio (OR) = 1.76, 95% CI: 1.15–2.70, P = 0.009] and cardiogenic death (OR = 2.02, 95% CI: 1.21–3.39, P = 0.007). CONCLUSIONS COPD is an independent predictive factor for clinical mortality, in which CHD patients with COPD are associated with worse prognosis than CHD patients with non-COPD.
2022, 19(6): 435-444.
doi: 10.11909/j.issn.1671-5411.2022.06.003
Abstract:
BACKGROUND Remote ischemic conditioning (RIC) is used to protect against myocardial injury. However, there is no adequate evidence for comprehensive RIC in elderly patients with ST-segment elevation myocardial infarction (STEMI). This study aimed to test whether comprehensive RIC, started pre-primary percutaneous coronary intervention (PPCI) and repeated daily on 1–30 days post-PPCI, can improve myocardial salvage index (SI), left ventricular ejection fraction (LVEF), Kansas City Cardiomyopathy Questionnaire Clinical Summary Score (KCCQ-CSS) and 6-min walk test distance (6MWD) in elderly patients with acute STEMI during 12 months follow-up. METHODS 328 consenting elderly patients were randomized to receive standard PPCI plus comprehensive RIC (the treatment group) or standard PPCI (the control group). SI at 5–7 days after PPCI, LVEF, left ventricular end-diastolic volume index (LVEDVI), left ventricular end-systolic volume index (LVESVI), KCCQ-CSS, 6MWD and adverse events rates were measured and assessed. RESULTS SI was significantly higher in the treatment group [interquartile range (IQR): 0.38–0.66, P = 0.037]. There were no significant differences in major adverse events at 12 months. Although the differences of LVEDVI, LVESVI and LVEF between the treatment group and the control group did not reach statistical significance at 6 months and 12 months, LVEF tended to be higher, LVEDVI tended to be lower in the treatment group. The KCCQ-CSS was significantly higher in the treatment group at 1 month (IQR: 46.5–87, P = 0.001) and 12 months (IQR: 55–93, P = 0.008). There was significant difference in 6MWD between the treatment group and the control group (IQR: 258–360 vs. IQR: 250–345, P = 0.002) at 1 month and (IQR: 360–445 vs. IQR: 345–432, P = 0.035) at 12 months. A modest correlation was found between SI and LVEF (r = 0.452, P < 0.01), KCCQ-CSS (r = 0.440, P < 0.01) and 6MWD (r = 0.384, P < 0.01) respectively at 12 months. CONCLUSIONS The comprehensive RIC can improve SI, KCCQ-CSS and 6MWD. It may be an adjunctive therapy to PPCI in elderly patients with STEMI.
2022, 19(6): 445-455.
doi: 10.11909/j.issn.1671-5411.2022.06.006
Abstract:
OBJECTIVE To establish a prediction model of coronary heart disease (CHD) in elderly patients with diabetes mellitus (DM) based on machine learning (ML) algorithms. METHODS Based on the Medical Big Data Research Centre of Chinese PLA General Hospital in Beijing, China, we identified a cohort of elderly inpatients (≥ 60 years), including 10,533 patients with DM complicated with CHD and 12,634 patients with DM without CHD, from January 2008 to December 2017. We collected demographic characteristics and clinical data. After selecting the important features, we established five ML models, including extreme gradient boosting (XGBoost), random forest (RF), decision tree (DT), adaptive boosting (Adaboost) and logistic regression (LR). We compared the receiver operating characteristic curves, area under the curve (AUC) and other relevant parameters of different models and determined the optimal classification model. The model was then applied to 7447 elderly patients with DM admitted from January 2018 to December 2019 to further validate the performance of the model. RESULTS Fifteen features were selected and included in the ML model. The classification precision in the test set of the XGBoost, RF, DT, Adaboost and LR models was 0.778, 0.789, 0.753, 0.750 and 0.689, respectively; and the AUCs of the subjects were 0.851, 0.845, 0.823, 0.833 and 0.731, respectively. Applying the XGBoost model with optimal performance to a newly recruited dataset for validation, the diagnostic sensitivity, specificity, precision, and AUC were 0.792, 0.808, 0.748 and 0.880, respectively. CONCLUSIONS The XGBoost model established in the present study had certain predictive value for elderly patients with DM complicated with CHD.
2022, 19(6): 456-468.
doi: 10.11909/j.issn.1671-5411.2022.06.001
Abstract:
BACKGROUND Triglyceride (TG) and its related metabolic indices, all recognized as surrogates of insulin resistance, have been demonstrated to be relevant to clinical prognosis. However, the relative value of these TG-related indices for predicting cardiovascular events among patients with acute coronary syndrome (ACS) has not been examined. METHODS The TG, the triglyceride-glucose (TyG) index, the atherogenic index of plasma, TG to high-density lipoprotein cholesterol ratio, and the lipoprotein combine index were assessed in 1694 ACS patients undergoing percutaneous coronary intervention. The primary endpoint was major adverse cardiovascular event (MACE), which was the composite of all-cause mortality, stroke, myocardial infarction, or unplanned repeat revascularization. RESULTS During a median follow-up of 31 months, 345 patients (20.4%) had MACE. The risk of the MACE was increased with higher TG and the four TG-derived metabolic indices [TG-adjusted hazard ratio (HR) = 1.002, 95% CI: 1.001–1.003; TyG index-adjusted HR = 1.736, 95% CI: 1.398–2.156; atherogenic index of plasma-adjusted HR = 2.513, 95% CI: 1.562–4.043; TG to high-density lipoprotein cholesterol ratio-adjusted HR = 1.148, 95% CI: 1.048–1.258; and lipoprotein combine index-adjusted HR = 1.009, 95% CI: 1.004–1.014; P < 0.001 for all indices]. TG and all the four indices significantly improved the predictive ability for MACE in addition to the baseline model. Among them, TyG index showed the best ability for predicting MACE compared with the other three indices from all the three measurements (P < 0.05 for all comparison). CONCLUSIONS TG and TG-derived metabolic indices were all strongly associated with MACE among ACS patients undergoing percutaneous coronary intervention. Among all the indices, TyG index showed the best ability to predict the risk of MACE.
