Patient-level and system-level barriers associated with treatment delays for ST elevation myocardial infarction in China.

OBJECTIVE: This study aims to understand the current ST elevated myocardial infarction (STEMI) treatment process in Guangdong Province and explore patient-level and system-level barriers associated with delay in STEMI treatment, so as to provide recommendations for improvement. METHODS: This is a qualitative study. Data were collected using semistructured, face-to-face individual interviews from April 2018 to January 2019. Participants included patients with STEMI, cardiologists and nurses from hospitals, emergency department doctors, primary healthcare providers, local health governors, and coordinators at the emergency medical system (EMS). An inductive thematic analysis was adopted to generate overarching themes and subthemes for potential causes of STEMI treatment delay. The WHO framework for people-centred integrated health services was used to frame recommendations for improving the health system. RESULTS: Thirty-two participants were interviewed. Patient-level barriers included poor knowledge in recognising STEMI symptoms and not calling EMS when symptoms occurred. Limited capacity of health professionals in hospitals below the tertiary level and lack of coordination between hospitals of different levels were identified as the main system-level barriers. Five recommendations were provided: (1) enhance public health education; (2) strengthen primary healthcare workforce; (3) increase EMS capacity; (4) establish an integrated care model; and (5) harness government's responsibilities. CONCLUSIONS: Barriers associated with delay in STEMI treatment were identified at both patient and system levels. The results of this study provide a useful evidence base for future intervention development to improve the quality of STEMI treatment and patient outcomes in China and other countries in a similar situation.

A Simple Modified Framingham Scoring System to Predict Obstructive Coronary Artery Disease.

Development of simple non-invasive risk prediction model would help in early prediction of coronary artery disease (CAD) reducing the burden on public health. This paper demonstrates a risk prediction scoring system to predict obstructive coronary artery disease (OCAD) in CAD patients. A total of 13,082 patients, referred for coronary angiography (CAG) in TRUST trial, were included in the development of a multivariable diagnostic prediction model. External validation of the model used 1009 patients from PRECOMIN study. The occurrence of OCAD was observed in 73.1% and 75.1% patients in TRUST (development) and PRECOMIN study (validation) cohorts, respectively. Good discrimination and calibration were obtained in both development and validation datasets (C-statistics 0.686 and 0.677; Hosmer-Lemeshow χ2 = 5.19, p = 0.74 and χ2 = 8.60, p = 0.38, respectively). The simple risk prediction model and risk scoring system developed on the basis of routine clinical variables showed good performance for estimation of OCAD in relative high-risk patients with suspected CAD.

Thrombocytopenia as a Preoperative Risk Assessment Tool in Patients With Rheumatic Heart Disease Undergoing Valve Replacement Surgery.

BACKGROUND: Postoperative thrombocytopenia has been reported to be correlated with adverse events, but the prognostic value of baseline thrombocytopenia is unclear. This study was undertaken to evaluate the relationship between preoperative thrombocytopenia and adverse outcomes in patients with rheumatic heart disease who underwent valve replacement surgery. METHODS AND RESULTS: A total of 1789 patients with rheumatic heart disease undergoing valve replacement surgery were consecutively enrolled and postoperatively followed up for 1 year. Patients were stratified on the basis of presence (n=495) or absence (n=1294) of thrombocytopenia (platelet count, <150×109/L), according to hospital admission platelet counts. During the hospitalization period, 69 patients (3.9%) died. The in-hospital all-cause mortality rate was significantly higher in the thrombocytopenic group (6.9% versus 2.7%; P<0.001). Multivariate analyses revealed that thrombocytopenia was independently associated with in-hospital all-cause mortality (odds ratio, 2.21; 95% confidence interval, 1.29-3.80; P=0.004). Platelet counts could predict in-hospital all-cause mortality for patients both with and without previous atrial fibrillation (areas under the curve, 0.708 [P<0.001] and 0.610 [P=0.025], respectively). One-year survival was significantly lower in patients with thrombocytopenia compared with controls (91.3% versus 96.1%; log-rank=14.65; P<0.001). In addition, thrombocytopenia was an independent predictor for postoperative 1-year all-cause mortality in multivariate Cox regression analysis. CONCLUSIONS: Platelet counts, as simple and inexpensive indexes, were reliable to be used as a preoperative risk assessment tool for patients with rheumatic heart disease undergoing valve replacement surgery.