Exploring the factors influencing individuals seeking coronavirus disease 2019 (COVID-19) consultation to choose internet hospitals for follow-up care after their initial in-person visit is crucial for optimizing medical resource allocation and enhancing future infectious disease control. This study, anchored in the core constructs of the Health Belief Model, aims to systematically examine the key determinants influencing patients’ decision to pursue a second COVID-19 consultation via an Internet hospital following an initial face-to-face visit. This study included 1,055 individuals seeking advice about COVID-19 who consulted an internet hospital during the early outbreak. Model training and evaluation were conducted using stratified five-fold cross‐validation; in each fold, 844 subjects were allocated to the training set and 211 to the test set. We employed a full-feature baseline alongside four feature selection methods—analysis of variance (ANOVA), Boruta, least absolute shrinkage and selection operator (Lasso), and all subsets regression (ASR), and three resampling techniques: Oversampling, Oversampling Undersampling, and Artificial Synthesis Dataset. Eight machine learning models—logistic regression (LR), support vector machine (SVM), k-nearest neighbors (KNN), random forest (RF), fully connected neural network (FCNN), and extreme gradient boosting (XGBoost), light gradient boosting machine (LightGBM), and categorical boosting (CatBoost)—were constructed to compare performance metrics and rank variable importance in the best-performing model. The impact of different feature selection methods and resampling techniques on model performance varied. Statistically significant differences were observed in the performance of each model in terms of the area under the receiver operating characteristic curve (AUROC) and the area under the precision-recall curve (AUPRC) (AUROC: P < 0.001, AUPRC: P < 0.001). Following Boruta, the RF model using the Artificial Synthesis Dataset demonstrated the highest AUROC at 0.946 ± 0.027, whereas the LightGBM model trained on the original imbalanced dataset achieved the highest AUPRC at 0.864 ± 0.070. The key factors influencing the decision to use internet hospitals for follow-up consultations included taking medication on their own or as prescribed by offline doctors before the second visit, chronic respiratory diseases history, contact, consultation purposes, fatigue, cough, and sore throat. Machine learning may help identify factors influencing the choice of internet hospitals for follow-up consultations. Integrating the Health Belief Model enables a more nuanced understanding of individuals’ online consultation behaviors. Optimizing triage services could enhance the quality and accessibility of internet hospitals, offering valuable insights for future public health events.

To investigate the early diagnostic value of circulating microRNA-1 for unstable angina (UA) in type 2 diabetes patients presenting with chest pain as the main symptom and without ST-T changes on electrocardiograms and to assess the predictive value of microRNA-1 for the need for a second coronary angiography (CAG) in these UA patients. All hospitalized patients with chest pain undergoing first-time CAG demonstrated no ST-T changes on initial and pre-CAG electrocardiograms and normal initial high-sensitivity cardiac troponin I levels. Plasma microRNA-1 levels were measured via quantitative reverse transcription polymerase chain reaction within 3 h of chest pain onset. UA patients were followed up for 5 years through phone calls and outpatient visits. The endpoints included second CAG and all-cause mortality. A total of 127 patients were enrolled, with 62 in the UA group and 65 in the non-UA group. MicroRNA-1, low-density lipoprotein cholesterol, and diabetes duration were significantly greater in the UA group than in the non-UA group. The area under the receiver operating characteristic curve for microRNA-1 in diagnosing UA was 0.811. Binary logistic regression analysis indicated that microRNA-1 and low-density lipoprotein cholesterol were predictive factors for UA. No UA patients were lost to follow-up or died during the follow-up period. Patients who underwent a second CAG had significantly higher microRNA-1 levels than those who did not. Binary logistic regression revealed that microRNA-1 and hemoglobin a1c were predictive factors for second CAG in UA patients during follow-up. Cox regression analysis revealed that microRNA-1 was an independent risk factor for a second CAG during follow-up in UA patients. Using the Youden index, the optimal cut-off value of microRNA-1 (2−ΔΔCt) for UA diagnosis was determined to be 1.510, which stratified UA patients into high- and low-expression groups. Kaplan-Meier survival analysis revealed that the microRNA-1 high-expression group had a significantly greater proportion of second CAG than did the microRNA-1 low-expression group. For type 2 diabetes patients with acute chest pain, no ST-T changes on electrocardiograms, and negative high-sensitivity cardiac troponin I, microRNA-1 may offer early diagnostic value for UA and could serve as an independent risk factor for the need for a second CAG within 5 years.

Objective:To investigate the relationship between plasma beta-2 microglobulin(β2M)levels and the total magnetic resonance imaging(MRI)burden of cerebral small-vessel disease(CSVD)in elderly patients with lacunar stroke.Methods:A total of 93 elderly patients with lacunar stroke admitted to the Department of Neurology, Changzhou Second People's Hospital form August 2018 to August 2019 were enrolled retrospectively, all with complete records of cranial magnetic resonance imaging and plasma β2M measurement.According to the total MRI CSVD burden, which ranges from an ordinal score of 0 to 4, patients were divided into 5 groups.Single-factor analysis was used to compare clinical data between the 5 groups.The association between the plasma β2M level and total MRI CSVD burden was analyzed by ordered multiple Logistic regression models.Results:Among elderly patients with lacunar infarction, 19 had a CSVD score of 0, 19 had a score of 1, 23 had a score of 2, 21 had a score of 3, and 11 had a score of 4, with statistically significant differences in age, percentage with diabetes, systolic blood pressure, diastolic blood pressure, glycosylated hemoglobin, plasma β2M, and eGFR between the 5 groups( P<0.05). Spearman correlation analysis showed that plasma β2M level was significantly positively correlated with total MRI CSVD burden( r=0.687, P<0.001). In ordered multivariate logistic regression models, after adjustment for possible confounding factors such as age, sex and hypertension, the results demonstrated that plasma β2M level( OR=5.253, 95% CI: 2.350-11.740, P<0.001)was an independent risk factor for total MRI CSVD burden. Conclusions:In elderly lacunar stroke patients, the plasma β2M level is closely related to the total MRI CSVD burden and can be used as a marker for predicting the severity of lesions.

[目的]分析新型冠状病毒肺炎(COVID-19)不同时期防控措施对非ST段抬高型心肌梗死(NSTEMI)住院患者并发肺部感染的诊断和预后影响.[方法]回顾性分析苏州大学附属第三医院在COVID-19不同防控措施下收治的126例NSTEMI患者,分为非新冠疫情流行组(2019年1月25日至2019年2月25日,非流行组,n=47),新冠疫情一级响应组(2020年1月25日至2020年2月25日,一级响应组,n=42)和新冠疫情常态化防控组(2021年1月25日至2021年2月25日,常态防控组,n=37).比较三组研究对象的临床特征、肺部感染以及院内病死率,分析疫情防控措施下NSTEMI住院患者并发肺部感染的影响因素.[结果]三组患者就诊时间、卧床时间、心率和心力衰竭比较,差异有统计学意义(P<0.05).非流行组、一级响应组和常态防控组肺部感染发生率比较差异有统计学意义(P<0.01).多因素二元Logistic回归分析显示,就诊时间、心力衰竭和卧床时间是NSTEMI患者发生肺部感染的影响因素(均P<0.05).[结论]COVID-19防控一级响应期间的救治措施提高了NSTEMI患者中肺部感染的诊断率,但未增加NSTEMI并发肺部感染患者院内不良预后.

OBJECTIVE To evaluate the diagnostic value of circulating microRNA-1 (miR-1) in early coronary artery plaque rupture in patients with stable coronary artery disease (SCAD). METHODS A prospective cohort study was conducted. Sixty-seven patients with SCAD admitted to the department of cardiology of the Third Affiliated Hospital of Soochow University from January to June in 2019 were enrolled. All patients had completed coronary angiography (CAG), percutaneous coronary intervention (PCI) single stent implantation or only CAG was performed according to the CAG results. Blood samples were collected before (0 hour) and 3 hours after the procedure. The expression of plasma miR-1 was detected by real-time quantitative reverse transcription-polymerase chain reaction (RT-PCR), and electrocardiogram was used to detect cardiac troponin I (cTnI) levels. The difference of miR-1 and cTnI levels in PCI or CAG patients before and after procedure were compared, and the value for early diagnosis of coronary artery plaque rupture in SCAD patients was evaluated. The diagnostic efficacy was evaluated by the receiver operating characteristic curve (ROC curve). RESULTS There were 38 CAG patients and 29 PCI patients. There were no significant differences in gender, age, previous history (without hypertension history) and baseline data of cardiac function between the two groups. The expression of miR-1 after PCI was significantly higher than that before PCI [2-ΔΔCt: 2.11 (1.56, 2.73) vs. 1.26 (1.07, 1.92), P < 0.01], and there was no significant difference in cTnI level before and after PCI [μg/L: 0.00 (0.00, 0.02) vs. 0.00 (0.00, 0.02), P > 0.05]. There were no significant differences in miR-1 and cTnI levels before and after procedure in the CAG group [miR-1 (2-ΔΔCt): 1.09 (1.00, 1.40) vs. 1.21 (1.00, 1.71), cTnI (μg/L): 0.00 (0.00, 0.02) vs. 0.00 (0.00, 0.02), both P > 0.05]. ROC curve analysis showed that the area under ROC curve (AUC) and 95% confidence interval (95%CI) of miR-1 in the diagnosis of coronary plaque rupture were 0.794 (0.687-0.900), P < 0.01, the sensitivity was 82.8%, the specificity was 68.4%, and the optimal cut-off value was 1.51. The AUC and 95%CI of the difference of miR-1 before and after operation (ΔmiR-1) were 0.704 (0.567-0.842), P = 0.004, the sensitivity was 62.1%, the specificity was 84.2%, and the optimal cut-off value was 0.39. The efficancy of miR-1 and ΔmiR-1 after procedure to diagnose coronary plaque rupture in patients with SCAD was similar (Z = 1.287, P = 0.198). However, baseline miR-1 might not predict whether patients with SCAD need PCI or not (AUC = 0.630, P > 0.05). Multivariate binary Logistic regression analysis showed that increased postoperative miR-1 expression was an independent risk factor for coronary plaque rupture in SCAD patients [odds ratios (OR) = 2.887, 95%CI was 1.044-7.978, P = 0.041]. CONCLUSIONS Circulating miR-1 might have the value for early diagnosis of coronary artery plaque rupture in SCAD patients.

Background To explore the significance of circulating miRNA-1 (miR-1) released within 3 h after the onset of acute chest pain in the diagnosis and prognosis of acute myocardial infarction (AMI). Methods A total of 337 patients with acute chest pain within 3 h were enrolled in this study and divided into AMI group and non-AMI group. The AMI diagnostic efficacy of miR-1 was determined and compared with that of cardiac troponin I (cTnI). The patients were followed up for 720 d after treatment. The significance of circulating miR-1 in AMI prognosis was assessed using univariate and COX regression analysis. Results There were 174 patients in AMI group, 163 in non-AMI group. Circulating miR-1 level was significantly higher in AMI group than in non-AMI group (P < 0.001). The AMI diagnostic efficacy of miR-1 and cTnI were similar (P > 0.05). We established two AMI diagnostic models, the AUC values of which were larger than that of cTnI or miR-1 (P < 0.05). When miR-1 combined with CK-MB, cTnI, and other clinical and laboratory parameters (model 2), the AUC was the largest (AUC: 0.961) and had the highest diagnostic efficiency. Circulating miR-1, Killip classification, and treatment method were influencing factors for AMI prognosis (P < 0.05). Conclusions Circulating miR-1 within 3 h of acute chest pain has the potential diagnostic value for AMI, and which is an independent risk factor for the prognosis of AMI and can be used to predict AMI prognosis.

To investigate the early diagnostic and prognostic value of microRNA-1 in patients with acute chest pain.

Background: The early diagnosis of non-ST-segment elevation myocardial infarction (NSTEMI) in patients with chronic kidney disease (CKD) remains a challenge. Methods: The study consecutively enrolled patients who had suffered from chest pain within 3 h whose electrocardiogram had no elevation in the ST segment. CKD was defined as an estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m2, and the diagnostic criteria for NSTEMI were defined according to the recommended guideline. Circulating microRNA-1 was collected and determined by quantitative real-time reverse transcription polymerase chain reaction. Results: A total of 456 patients with suspected NSTEMI were included. There were 115 patients in the CKD group, including 67 with NSTEMI, 20 with stable angina, 7 with unstable angina, 18 with heart failure, and 3 with other disorders. Compared with the NSTEMI group, the non-NSTEMI group just had significant differences in microRNA-1 and high-sensitivity cardiac troponin I (hs-cTnI) (both p < 0.05). The relative expression of microRNA-1 was significantly increased in the NSTEMI group as compared with that in the other disease groups (all p < 0.05). A receiver operating characteristic (ROC) curve analysis suggested that microRNA-1 and hs-cTnI had advantages in the early diagnosis of NSTEMI with CKD (AUC [area under the ROC curve] 0.879 and 0.812, respectively, both p < 0.05). Compared with that in the non-CKD group, the accuracy of microRNA-1 was almost as good in the CKD group (84.3 vs. 89.4%, p > 0.05). However, the diagnostic accuracy of hs-cTnI was significantly decreased (79.1 vs. 91.5%, p < 0.05), as was its specificity (75.0 vs. 95.5%, p < 0.05). There was no significant difference in the correlation between microRNA-1 and eGFR (p > 0.05), but a statistically significantly negative correlation between hs-cTnI and eGFR (p < 0.05). Conclusion: Circulating microRNA-1 is capable of early diagnosis of NSTEMI in patients with CKD suffering from chest pain.

心肌梗死是全球范围内死亡率和发病率均较高的常见心血管疾病之一.近年来研究了各种早期诊断心肌梗死的新型生物学标志物以及治疗靶点,其中包括微小RNA-1(microRNA-1,miR-1),它是首个发现与心血管病发展相关的miR,具有心肌细胞表达特异性.多项研究提示miR-1直接参与调控心肌梗死的整个病理过程,包括心肌细胞凋亡、炎症、血管生成、纤维化以及影响心肌细胞的存活和增殖活性,通过检测miR-1的表达量变化以及上游调节有助于改善心肌梗死患者的预后,本文将对miR-1诊疗心肌梗死展开如下综述.

Objective To evaluate the early diagnostic value of circulating microRNA-1 (miR-1) on acute myocardial infarction (AMI). Methods A prospective cohort study was conducted. The patients with chest pain admitted to the Second People's Hospital of Wuxi from November 2012 to June 2015 were enrolled. According to AMI diagnostic criteria, the patients were divided into AMI group and non-AMI group, and healthy individuals during the same period were served as heath controls. The venous samples of the onset patients were collected within 3 hours after admission. The plasma miR-1 was determined by real-time quantitative reverse transcription-polymerase chain reaction (RT-PCR), and the levels of plasma cardiac troponin I (cTnI) and MB isoenzyme of creatine kinase (CK-MB) were measured by electrochemiluminescence. The correlation between plasma miR-1 and cTnI as well as CK-MB was performed by Spearman analysis. The early diagnostic performance of plasma miR-1, cTnI, and CK-MB for AMI was estimated by receiver operating characteristic (ROC) curve analysis. Results There were 127 patients in AMI group, and 107 in non-AMI group, including 82 patients with angina pectoris, 2 with pulmonary embolism, 3 with aortic dissection, 2 with acute pericarditis, 3 with myocarditis, 13 with acute heart failure, and 2 with peptic ulcer. Ninety volunteers were served as healthy controls. There was no difference in clinical characteristics including gender and hyperlipidemia between AMI group and non-AMI group. The expressions of plasma miR-1, cTnI and CK-MB were significantly increased in AMI patients as compared with those of the healthy controls [miR-1 (2-ΔΔCt): 4.32±2.60 vs. 1.44±0.75 and 0.98±0.18, cTnI (μg/L): 3.23 (0.63, 10.70) vs. 0.02 (0.00, 0.17) and 0.00 (0.00, 0.00), CK-MB (U/L): 32.40 (14.20, 95.40) vs. 14.40 (11.20, 17.10) and 8.90 (8.28, 9.50), all P < 0.01]. The expression of plasma miR-1 had a significantly positive correlation with cTnI and CK-MB in AMI patients (r1 = 0.395, r2 = 0.490, both P < 0.000). It was demonstrated by ROC curve analysis that the area under ROC curve (AUC) for the diagnostic value of miR-1 on AMI was 0.905 [95% confidence interval (95%CI) = 0.860-0.950, P = 0.000], the sensitivity was 86.6%, and the specificity was 95.4%; the AUC for cTnI was 0.908 (95%CI = 0.870-0.946, P = 0.000), the sensitivity was 81.9%, and the specificity was 95.9%; the AUC for CK-MB was 0.795 (95%CI = 0.736-0.854, P = 0.000), the sensitivity was 63.0%, and the specificity was 92.9%. Conclusions Plasma miR-1 has the capacity in early diagnosis of AMI, superior to CK-MB, and equal to cTnI. It can provide additional diagnostic information beyond cTnI. The diagnostic accuracy for early AMI can be improved with the combination of plasma miR-1 and cTnI.