https://orcid.org/0000-0003-0392-6370
Abstract
Background
The incidence of mortality is considerable after ST-elevation myocardial infarction (STEMI) hospitalization; risk assessment is needed to guide postdischarge management. Age shock index (SI) and age modified shock index (MSI) were described as useful prognosis instruments; nevertheless, their predictive effect on short and long-term postdischarge mortality has not yet been sufficiently confirmed.
Methods
This analysis included 3389 prospective patients enrolled from 2016 to 2018. Endpoints were postdischarge mortality within 30 days and from 30 days to 1 year. Hazard ratios (HRs) were evaluated by Cox proportional-hazards regression. Predictive performances were assessed by area under the curve (AUC), integrated discrimination improvement (IDI), net reclassification improvement (NRI) and decision curve analysis (DCA) and compared with TIMI risk score and GRACE score.
Results
The AUCs were 0.753, 0.746 for age SI and 0.755, 0.755 for age MSI for short- and long-term postdischarge mortality. No significant AUC differences and NRI were observed compared with the classic scores; decreased IDI was observed especially for long-term postdischarge mortality. Multivariate analysis revealed significantly higher short- and long-term postdischarge mortality for patients with high age SI (HR: 5.44 (2.73–10.85), 5.34(3.18–8.96)), high age MSI (HR: 4.17(1.78–9.79), 5.75(3.20–10.31)) compared to counterparts with low indices. DCA observed comparable clinical usefulness for predicting short-term postdischarge mortality. Furthermore, age SI and age MSI were not significantly associated with postdischarge prognosis for patients who received fibrinolysis.
Conclusions
Age SI and age MSI were valuable instruments to identify high postdischarge mortality with comparable predictive ability compared with the classic scores, especially for events within 30 days after hospitalization.
Introduction
ST-elevation myocardial infarction (STEMI) is the most urgent and serious coronary artery diseases [Citation1,Citation2]. With the adoption of evidence-based therapy, decreased in-hospital mortality has been documented in decades [Citation3–6], whereas, postdischarge mortality is still grim [Citation7–10]. It is indispensable to identify patients at high-risk of postdischarge death and subsequently provide more focused management.
Thrombolysis in myocardial infarction (TIMI) risk score and Global Registry of Acute Coronary Events (GRACE) score were classic scores to assess the prognosis of STEMI patients [Citation11,Citation12]. Due to the time-consuming calculations, their application was confined, and moreover, the lower awareness of diabetes and hypertension may decrease its accuracy in Chinese patients [Citation13]. Simple prognostic predictors are of great significance in adding adaptability, and age shock index (SI) and age-modified shock index (MSI) appear to be suitable candidates [Citation14–16]. However, there are few contemporary studies evaluating their predictive value of postdischarge mortality and previous studies lacked a high number of patients [Citation14,Citation15]. Furthermore, most studies only included patients undergoing percutaneous coronary intervention (PCI) [Citation14–16]. The patients who received fibrinolysis or conservative therapy, which is still the vast majority of STEMI patients in China [Citation17], were excluded.
Accordingly, we aimed to investigate the prognosis value of age SI and age MSI on the short- and long-term postdischarge mortality use real-world database from population-based registries and compared with the classic scores.
Methods
Study population
The data of this study were derived from the Henan STEMI registry (NCT 02641262), which was a multicentre, prospective, observational study in central China [Citation18,Citation19]. Patients who met the diagnostic criteria of the universal definition of myocardial infarction (2012) and were hospitalized within 30 days from symptom onset were consecutively enrolled. Diagnostic criteria of STEMI were defined as elevated biomarkers and new or presumed new ST-segment elevation >1 mm (0.1 mV) in two or more contiguous leads or new onset of left bundle branch block; patients diagnosed as types 4a and type 5 STEMI were excluded. The enrolled patients were treated according to the guideline [Citation3,Citation4,Citation20]. The protocol of the registry has been approved by the Ethics Committee of Henan Provincial People’s Hospital.
From September 2016 to August 2018, a total of 5059 STEMI patients were enrolled in 66 eligible hospitals. Patients died in-hospital (404 cases), with cardiogenic shock on admission (204 cases), out-of-hospital cardiac arrest (95 cases), atrioventricular block ≥ second degree (72 cases), with chronic renal insufficiency (severe renal failure, undergoing chronic peritoneal dialysis or haemodialysis) (20 cases), without GRACE score (375 cases), with missing survival status at 30 days after discharge (500 cases) were excluded. Among the 3389 survivor at 30 days after discharge, 42 patients died, giving a 1.2% postdischarge mortality within 30 days. After excluding the patients who died within 30 days after hospitalization (42 cases) and patients with missing survival status at 1 year after discharge (100 cases), 68 cases died giving 2.1% postdischarge mortality from 30 days to 1 year (Supplement Figure 1).
Data collection
Clinical data of the enrolled STEMI patients, including demographic, cardiovascular risk factors, medical histories, clinical characteristics at admission, reperfusion therapy and medications, as well as in-hospital outcomes, were prospectively collected by trained investigators through a standardized online reporting platform with automatic checks for invalid values, and a total of 53.84% of reported cases were audited for accuracy against medical records for onsite quality control.
Definition
Age SI was defined as age multiplied by SI, and SI was defined as the ratio of HR and SBP on admission. Age MSI was defined as age multiplied by MSI, and MSI was defined as the ratio of HR and mean arterial pressure (MAP) on admission. MAP was defined as double the DBP, the sum then being added to the SBP, and then divided by 3. Hypertension was defined as having a history of hypertension or receiving antihypertensive therapy. Dyslipidaemia was defined according to the guidelines. Diabetes mellitus was defined as having a previous diagnosis of diabetes mellitus, or a glycosylated haemoglobin level ≥6.5%. The current smoker was defined as smoking within the preceding year. The history of coronary heart disease was defined as having a clinical history of myocardial infarction or undergoing PCI or coronary artery bypass grafting before the current hospitalization. The wall location of the myocardial infarction was determined by an electrocardiogram. Admission time were divided into on- and off-hour according to the rules of working hours in China: on-hours (Monday–Friday 08:00 AM to 05:59 PM) and off-hours (Monday–Friday 06:00 PM to 07:59 AM, Saturday, Sunday and nonworking holidays).
Endpoints and follow-up
The endpoints of this study were postdischarge mortality within 30 days and postdischarge mortality from 30 days to 1 year. We reviewed hospital records to determine all-cause death events at discharge and excluded patients who died within hospital. With the consideration of the actual situation that most Chinese patients are reluctant to die in the hospital and the Chinese Government took death or treatment withdrawal as a quality measure for hospitals, we take withdrawal from treatment due to terminal status at discharge (referred to as treatment withdrawal) as in-hospital death. Researchers in the coordinating study sites adjudicated the clinical consequences of patients who withdrew from treatment according to medical records. All the surviving patients at discharge were followed up through telephone or clinic interviews by contacting the patients or their first-degree relatives to confirm their status.
Statistical analysis
The demographic, risk factors, medical history, clinical characteristics, in-hospital management, and pharmacotherapy at discharge were described between survivors and non-survivors. Categorical variables were summarized as numbers and percentages. Chi-square or Fisher’s exact tests were used for comparisons as appropriate, whereas numerical variables were reported as means and standard deviation (SD) or median and interquartile range (IQR) depending on the distribution of data. Student’s t-test or Mann–Whitney’s U-test was used as appropriate.
The area under the curve (AUC) was calculated and compared using a nonparametric test developed by DeLong et al with the use of MedCalc software for Windows, version 19.0.4 (MedCalc Software, Mariakerke, Belgium) [Citation21]. Cut-off points of age SI, and age MSI were determined based on the receiver operating curves (ROC). The Hosmer–Lemeshow (HL) test and the Nagelkerke-R2 from the regression modelling were used as indicators of goodness-of-fit of each index and to assess the calibration ability, higher HL p values and higher Nagelkerke-R2 indicate better calibration. The brier scores were also calculated, lower brier scores indicate better calibration. We also used the absolute integrated discrimination improvement (IDI) and category-free net reclassification improvement (NRI) to evaluate improvements in risk predictions quantified [Citation22]. Decision curve analysis (DCA) was conducted to determine the clinical usefulness by quantifying the net benefits at different threshold probabilities in the STEMI patients’ dataset [Citation23].
Cox proportional-hazards regression was performed to analyse the effect of age SI, and age MSI as continuous and categorized variables on postdischarge mortality and the results were reported as hazard ratios (HRs) with associated 95% confidence intervals (CIs), which account for clustering of patients within hospitals. This was repeated with additional adjustments for gender (women or men), risk factors and medical history (hypertension, diabetes, dyslipidaemia, current smoker, stroke), clinical characteristic (anterior myocardial infarction, Killip class (II or III vs. I) at admission), reperfusion therapy (fibrinolysis or PCI vs. none), onset-to-FMC time and hospital days, and medicine used after discharge (aspirin, P2Y12 antagonists, statin, β-blocker and ACEI)/ARB).
The Kaplan–Meier method was used to estimate cumulative rates of events from discharge to 30 days and from 30 days to 1-year follow-up. The associations between age SI and age MSI, as a continuous variable, with postdischarge mortality were modelled using restricted cubic splines. The five knots were placed at default positions according to percentiles of haemoglobin (5, 27.5, 50, 72.5 and 95 centiles).
Two-sided p values <.05 were considered statistically significant. Statistical analyses were performed with SAS 9.4 (SAS Institute Inc., Cary, NC) and R package (Version 4.2.1, R Foundation for Statistical Computing, Vienna, Austria).
Results
Clinical characteristics of STEMI patients
A total of 3389 and 3247 STEMI patients were identified for postdischarge mortality within 30 days and from 30 days to 1-year datasets. The postdischarge mortality reported within 30 days, and from 30 days to 1 year was 1.2% and 2.1%. The baseline and clinical characteristics between survivors and non-survivors are summarized in . The non-survivors were significantly older and had a higher proportion of diabetes, higher Killip class and HR, whereas their counterparts were more frequently to be current smokers. In terms of clinical therapy, the non-survivors were less likely to receive reperfusion therapy, and the proportion of underwent successful revascularization was significantly lower and performed delayed onset-to-FMC time. Meanwhile, the non-survivors within 30 days of discharge had a higher prevalence of female and anterior myocardial infarction and were less likely to receive guideline-recommended drugs after hospitalization. Compared with the survivors, the median of age SI and age MSI of the non-survivors were higher and statistically significant.
Table 1. Demographics and characteristics of STEMI patients.
Prognostic performance of age SI and age MSI
As shown in , the AUC of age SI, age MSI, TIMI risk score and GRACE score for predicting postdischarge mortality within 30 days () and postdischarge mortality from 30 days to 1 year () was similar. illustrates that the age SI had the maximal specificity and the minimum sensitivity, in contrast, the age MSI had the maximal sensitivity and the minimum specificity. All the risk indexes had good fitness (all p > .05) and the TIMI risk score had the maximal Nagelkerke-R2. All the risk indices shared a similar Brier score.
Figure 1. Receiver operating characteristic (ROC) curves of age SI, age MSI, TIMI risk score and GRACE score for STEMI patients. (A) ROC for postdischarge mortality within 30 days; (B) ROC for postdischarge mortality from 30 days to 1 year.
Table 2. Performance for the prognosis prediction of age SI, age MSI, TIMI risk score and GRACE score.
As shown in , no significant AUC differences and NRI were observed compared with the TIMI risk score and GRACE score both for postdischarge mortality within 30 days and postdischarge mortality from 30 days to 1 year. Whereas, the IDI of age MSI was observed smaller than the TIMI risk score (p = .005) for postdischarge mortality within 30 days. In terms of IDI for postdischarge mortality from 30 days to 1 year, the classic scores were observed improvement over age SI and age SI (all p < .05).
Table 3. Comparisons of the prognostic performance of age SI, age MSI versus TIMI risk score and GRACE score.
Effects of age SI and age MSI on clinical outcomes
To enhance the clinical utility, the indexes were categorized into two groups according to the cut-off point. As shown in and , the high-value group of age SI and age MSI had higher incidences of postdischarge mortality (all p < .001). indicates that after accounting for the clustering of patients within hospitals, continuous and categorized age SI and age MSI were significantly associated with postdischarge outcomes. Adjustments for gender, risk factors, clinical characteristics, reperfusion therapy, onset-to-FMC time and medicine used at discharge did not fundamentally alter the patterns observed in the unadjusted categorical or continuous analyses described above. The relationship between age SI and age MSI as a continuous variable and postdischarge mortality confirmed these patterns ().
Figure 2. Cumulative postdischarge mortality according to classified age SI and age MSI by cutoff points. (A) Age SI for postdischarge mortality within 30 days. (B) Age MSI for postdischarge mortality within 30 days. (C) Age SI for postdischarge mortality from 30 days to 1 year. (D) Age MSI for postdischarge mortality from 30 days to 1 year.
Figure 3. Effect of age SI and age MSI as continuous variable on postdischarge mortality. The baseline (red) line is hazard ratio, and the red shaded area represents the 95% CI. (A) Age SI for postdischarge mortality within 30 days. (B) Age MSI for postdischarge mortality within 30 days. (C) Age SI for postdischarge mortality from 30 days to 1 year. (D) Age MSI for postdischarge mortality from 30 days to 1 year.
Table 4. HR and corresponding 95% CI of categorized age SI and age MSI according to univariate and multivariate analyses based on Cox regression model.
Clinical usefulness of age SI and age MSI
The DCA of age SI and age MSI for postdischarge mortality within 30 days and from 30 days to 1 year is presented in . STEMI patients with a high risk of postdischarge death need focused management. The net benefit of the strategy of treating all patients means all STEMI patients need careful management (the grey line) to prevent death. The net benefit of the strategy of treating no patients indicates no STEMI patients need careful management (the black line in) to prevent death. For postdischarge mortality within 30 days (), the net benefit of scores was comparable. For postdischarge mortality from 30 days to 1 year (), the decision curve showed that if the threshold probability was in the interval of 0.04–0.10, TIMI risk score and GRACE risk score add more benefit, out of the above range, the curve overlapped and the net benefit was comparable.
Figure 4. Decision curve analysis (DCA) of age SI, age MSI, TIMI risk score and GRACE score for postdischarge mortality. (A) DCA for postdischarge mortality within 30 days; (B) DCA for postdischarge mortality from 30 days to 1 year. The x-axis indicates the threshold probability; the y-axis indicates the net benefit; the grey line displays the net benefit of the strategy of treating all patients; the black line illustrates the net benefit of the strategy of treating no patients.
Performance in subgroups
The discrimination ability and effects on postdischarge mortality of age SI and age MSI were exhibited after the patients were divided into subgroups according to age, gender, reperfusion therapy, renal function, onset-to-FMC time, Killip class on admission, on- and off-hour hospital admission, hospital approaching method, white blood cell count and anterior myocardial infarction.
As shown in , the postdischarge mortality within 30 days ranged from 0.55% to 3.36% in the subgroups, the AUCs of age SI ranged from 0.676 to 0.819 and the HR ranged from 1.60 to 11.13, the AUCs of age MSI ranged from 0.628 to 0.818 and the HR ranged from 2.78 to 33.08. For STEMI patients who receive reperfusion, and have Killip class ≥2, after accounting for confounding, the categorized age SI and age MSI were not significantly associated with postdischarge mortality within 30 days.
Table 5. Performance of age SI and age MSI for post-discharge mortality within 30 days in subgroups.
As shown in , the postdischarge mortality from 30 days to 1 year ranged from 1.18% to 7.23% in the subgroups, the AUCs of age SI ranged from 0.545 to 0.830 and the HR range from 1.88 to 20.06, the AUCs of age MSI ranged from 0.551 to 0.831 and the HR range from 2.68 to 18.11. For STEMI patients who receive fibrinolysis therapy, after accounting for confounding, the categorized age SI and age MSI were not significantly associated with postdischarge mortality from 30 days to 1 year.
Table 6. Performance of age SI and age MSI for post-discharge mortality from 30 days to 1 year in subgroups.
Discussion
This study revealed that age SI and age MSI were correlated with STEMI patients’ postdischarge prognosis, and were independent predictors for postdischarge mortality. The predictive performance of age SI and age MSI was equal to TIMI risk score and GRACE score with equivalent AUCs and NRI, whereas, age SI and age MSI did not gain IDI for postdischarge mortality from 30 days to 1 year. Age SI and age MSI can be easily calculated using readily available clinical variables and exhibited good discrimination and goodness-of-fit, and were useful tools for risk stratification in clinical practices, especially for STEMI patients who did not receive reperfusion therapy and with Killip 1 class.
Identification of high-risk patients is the best way to prevent complications. The reperfusion therapy including fibrinolysis and PCI, and the broad uptake of aspirin and P2Y12 inhibitors have improved the in-hospital prognosis of STEMI patients, whereas, the incidence of adverse events remained considerable after hospitalization [Citation24,Citation25]. Previous studies implied that a larger proportion of mortality occurred in the early phase after discharge [Citation26], and about 30% of patients with myocardial infarction undergoing PCI reported suboptimal adherence to prescribed medications in the first month after discharge [Citation27], which was a problem all over the world. Patients who lack secondary prevention medication not only suffer a higher risk of early mortality but might have poorer long-term prognosis [Citation28]. There is still much room for postdischarge management to improve the postdischarge prognosis of STEMI patients, which highlights the importance of postdischarge risk reassessment and offers assistance in decision-making of postdischarge therapeutic strategies. Considering the changing risk following STEMI, we chose 30 days mortality and mortality from 30 days to 1 year after discharge, which were also the routine follow-up points in clinical practice, as the endpoints of risk reassessment. TIMI risk score and GRACE score were efficient scales for the prediction of mortality in STEMI patients, despite their good predictive value of 6 months or even 12 months outcomes [Citation11,Citation12], the complex calculation of the index makes it inconvenient in large-scale clinical practices; nevertheless, a simple index without subjective information, diagnostic blood test results, or complicated algorithm may have a broader clinical application and help improve patient’s outcomes.
Blood pressure is the measured result of the interaction between peripheral vascular resistance and cardiac output. The higher value of blood pressure on admission indicates a preserved systolic ventricular function with less myocardial damage [Citation29]. HR is a fundamental physiological parameter, and elevated heart rate might reflect the myocardial dysfunction, sympathetic excitation and systemic increase in oxygen consumption after STEMI, and associated with the higher risk of in-hospital mortality [Citation30]. SBP and HR are easily determinable clinical parameters and have been adopted in numerous scores [Citation11,Citation12]. SI was calculated from SBP and HR, and MSI baked DBP into the index to enhance prediction accuracy, and previous studies confirmed its predictive value on short- and long-term prognosis [Citation31–33]. Age is a stable predictor of clinical outcomes in STEMI patients and is integrated into nearly all risk scores. Studies have shown the incidence of mortality is higher in elderly STEMI patients compared with their younger counterparts [Citation34]. Age SI and age MSI, which integrate age into the SI and MSI, may provide better discriminating power. Yu et al. demonstrated that age SI (AUC: 0.708), similar to GRACE score (AUC: 0.694), could identify patients at higher risk of death in AMI patients undergoing PCI [Citation14]. Zhou et al. reported that age SI and age MSI were stronger predictors than SI and MSI for in-hospital cardiovascular events, 6-month, and long-term all-cause mortality in STEMI patients undergoing emergency PCI [Citation15]. To the best of our knowledge, prior studies investigated the long-term prediction value of age SI and age MSI did not exclude patients who died within hospitalization [Citation14,Citation15], which accounted for most of all deaths; therefore, the long-term prognosis was almost entirely driven by deaths within hospitalization, which would imply that the good long-term prediction ability of age SI and age MSI may actually be restricted to a short period of time after the myocardial infarction onsets; whether the age SI and age MSI had good long-term or postdischarge prediction ability is still worth studying. Our study excluded patients who died within hospitalization and discovered that age SI and age MSI were independent predictors, and observed almost the same AUC with TIMI risk score and GRACE score, age SI and age MSI added equal NRI for both postdischarge 30-day mortality and mortality from 30 days to 1 year after hospitalization, while age SI and age MSI did not significantly add IDI for postdischarge mortality from 30 days to 1 year. The sensitivity of age SI and the specificity of age MSI were smaller than the TIMI risk score and GRACE score; during the application in clinical practice, the clinicians should take notice of the potential false positives and false negatives.
The previous research focused on the long-term prediction ability of age SI and age MSI in the past only included STEMI patients undergoing PCI. In developing countries, especially in rural areas, fibrinolysis was still the main reperfusion therapy, and the tougher situation is that despite the increase of the use of PCI (10.6% in 2001 vs. 28.1% in 2011), almost half of the STEMI patients who did not receive reperfusion (45.3% in 2001 vs. 44.8% in 2011) [Citation17]. Previous studies did not provide evidence of their long-term prediction ability on patient received deferent reperfusion therapy. Our study revealed that for patients who did not receive reperfusion, both age SI and age MSI had excellent ability for predicting postdischarge mortality, while for patients who received fibrinolysis therapy, the AUCs were smallest compared with patients who received PCI and no reperfusion, age SI and age MSI are probably a poor instrument for measuring postdischarge prognosis when fibrinolysis is given. More research is still needed to develop and validate risk scales suitable for this population [Citation35]. The STEMI patients with Killip ≥2 had a significantly higher prevalence of deaths and exhibited higher age and lower blood pressure values on admission [Citation36]. High Killip class itself is an important factor, possibly the comprehensive representation of advanced age and reduction of myocardial function after STEMI. The lower AUCs for Killip 2 and the less marked and expanded CIs of the HR for Killip 3 in the subgroup analysis indicated that, for patients with high Killip class, both the age SI and age MSI did not perform significant predictive value for postdischarge mortality, and this may be down to the small sample size of high Killip patients in this study, further large sample research still needs to be done to confirm their prognosis value.
Furthermore, the long-term prognosis of STEMI patients was influenced by many factors [Citation37]. The quality and success rate of PCI affect the prognosis of STEMI patients [Citation38]. The majority of involved patients of Henan STEMI registry were rural population, and the promotion and applying of PCI technology were at an initial stage in secondary hospitals during patient’s enrolment. The operators of secondary hospitals lack experience, and the periprocedural complications cannot be carefully monitored and managed, which results in the lower utilization rate of primary PCI and may affect the postdischarge mortality of the involved population [Citation39]. Factors including treatment therapy, treatment delays, on- and off-hour hospital admission [Citation40], and diagnostic blood test results can all affect prognosis. Despite age SI and age MSI contain only three parameters, the indices show comparable and satisfy prognosis value between subgroups [Citation41–43]. Various assessment systems including the TIMI risk score and GRACE scores have been applied for risk stratification in STEMI patients [Citation11,Citation12]. Although there was GRACE 2.0 and the ‘‘Mini-GRACE’’ algorithm, the time-consuming calculations make them impractical in daily clinical practice. What’s more, Chinese and Westerners differ in the term of the incidence of coronary spastic angina, physique and lifestyle, meanwhile, neither Chinese nor other Asian institutions took part in the establishment of these systems; whether the risk scoring systems devised in the Western countries were applicable in Chinese STEMI patients was worth discussing. Risk classification tools do not need to capture all variables affecting prognosis, but should provide an accurate preliminary estimate of risk. Although the predictive performance of age SI and age MSI was equivalent to TIMI risk score and GRACE score, they were likely to be useful practical tools for risk-stratify patients with STEMI and assist in decision-making of postdischarge management when the clinicians fail to get GRACE score or TIMI risk score. Prognostic models that included just enough variables, such as postdischarge information and PCI procedures details [Citation38,Citation39], may better assist in prognostic evaluation and decision-making of secondary prevention strategies.
Limitations
This study had several limitations. First, participation in the registry is voluntary and the data collection burden on investigators may be the greatest barrier which may lead to some enrolment bias. We have carefully considered each element to limit the burden and have quality control measures in the registry. Second, we are limited by the granularity of available data in our databases, as the registries were designed to study all patients admitted with STEMI, and not only those undergoing PCI. Although we attempted to address differences in patient and hospital-related characteristics in adjusted models, we cannot evaluate the effect of unmeasured confounding, such as periprocedural complications and operator experience. Third, the BP and HR used for calculating the indices were obtained on admission and changed over time as the patient’s condition changed; we did not explore the prognostic effect of indexes’ variability on the postdischarge mortality. Finally, although we included patients from multiple centres, they exist within the same province, and thus these findings may not be generalizable to all populations.
Conclusions
Age SI and age MSI were both independent predictors and had comparable discrimination and calibration abilities compared with the TIMI risk score and GRACE score. Age SI and age MSI were valuable and simple prognostic tools to identify STEMI patients at high risk of all-cause death after hospitalization, especially for predicting postdischarge mortality within 30 days.
Author contributions
SW: conceived the concept of this study, manuscript writing, data analysis and interpretation. YZ, CYG and DYH: conceived the concept of this study, data revising, data interpretation and approval of the version to be published. YZ and SW: data quality evaluation, data checking and management. DTQ, XPW, ZYZ, WY and MWL: ensuring questions related to the accuracy or integrity of the work are appropriately investigated and resolved. All authors reviewed the manuscript and approved the final version.
Ethics statement
Henan STEMI Registry was approved by the Ethics Committee of Henan Provincial People’s Hospital. For the reason that STEMI was life-threatening and patients lacked the capacity to provide meaningful prospective informed consent to participate in this research. Meanwhile, all the treatments applied to participants were in accordance with relevant guidelines and the Declaration of Helsinki, and no additional intervention was applied. According to waiver of informed consent (WIC) regulations (45 CFR 46.101), waiver of informed consent had been approved by the ethics committee in this registry-based study [No. 2015 (34)], and the other 65 participating institutes were covered by central ethics approval.
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Download MS Word (138.4 KB)Acknowledgements
We would like to thank all of the members of Scientific Committee, and Executive Committee for their contribution to the Henan STEMI registry. We also want to thank all of the study investigators and coordinators for their great work. Trial registration: [NCT02641262] [29 December 2015].
Disclosure statement
No potential conflict of interest was reported by the author(s).
Data availability statement
The identified participant data are not publicly available. All data generated or analysed during this study are included in this published article.
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