Article ID: CJ-22-0795
Background: The simple risk index recorded in the emergency room (ER-SRI), which is calculated using the formula (heart rate × [age / 10]2) / systolic blood pressure, was shown to be able to stratify the prognosis in ST-elevation myocardial infarction (STEMI) patients. However, the prognostic impact of the prehospital simple risk index (Pre-SRI) remains unknown.
Methods and Results: This study enrolled 2,047 STEMI patients from the Mie Acute Coronary Syndrome (ACS) registry. Pre-SRI was calculated using prehospital data and ER-SRI was calculated using emergency room data. The primary endpoint was 30-day all-cause mortality. The cut-off values of Pre-SRI and ER-SRI for predicting 30-day mortality were 34.8 and 34.1, with accuracies of 0.816 and 0.826 based on receiver operating characteristic analyses (P<0.001 for both). There was no difference in the accuracy of the 2 indices. Multivariate Cox regression analysis demonstrated that a High Pre-SRI (≥34) was a significant independent predictor of 30-day mortality. With combined Pre-SRI and ER-SRI assessment, patients with High Pre-SRI/High ER-SRI showed significantly higher mortality than those with High Pre-SRI/Low ER-SRI, Low Pre-SRI/High ER-SRI, and Low Pre-SRI/Low ER-SRI (P<0.001). The addition of High Pre-SRI to High ER-SRI showed incremental prognostic value of the Pre-SRI.
Conclusions: Pre-SRI can identify high-risk STEMI patients at an early stage and combined assessment with Pre-SRI and ER-SRI could be of incremental prognostic value for risk stratification in STEMI patients.
The prognosis of patients with ST-elevation myocardial infarction (STEMI) has improved markedly over the years, with early revascularization by percutaneous coronary intervention (PCI) and optimal medical therapy. However, some STEMI patients still have poor prognoses.1,2 Early identification of high-risk patients with poor prognoses enables optimal treatment to be administered at the right time.
The Killip class has long been used as an index of acute-phase risk stratification. In recent years, various indices have been developed for more detailed risk stratification. The Global Registry of Acute Coronary Events (GRACE) score has been reported to be useful for predicting the short- and long-term mortality of STEMI patients.3–5 However, calculation of the GRACE score requires a complex formula and invasive measurements after hospitalization, such as serum creatinine and cardiac enzyme levels. Therefore, it cannot be applied quickly and easily in clinical practice. The simple risk index (SRI), which is calculated using the formula (heart rate × [age / 10]2) / systolic blood pressure (SBP), was derived from a clinical study of STEMI patients and shown to be able to stratify the 30-day prognosis.6 As well as the SRI, several other indices, such as the shock index (SI), the modified SI (MSI), and age-SI (ASI), calculated using age, blood pressure, and heart rate, have been reported to predict short- and long-term prognoses of STEMI patients and compared with each other.7–9 Because these indices can be easily calculated and obtained during initial assessment by the first healthcare provider in the prehospital setting, a patient’s risk can be assessed at an earlier stage.
Prehospital (Pre-) risk stratification and 12-lead electrocardiogram (ECG) diagnosis are considered important factors in improving patient outcomes, including the selection of hospitals for more appropriate treatment, preparation for catheterization, and preparation of ventricular assist devices.10,11 However, there are limited data evaluating the clinical importance of Pre-risk indices such as the Pre-SRI. Therefore, the aim of the present study was to evaluate the clinical importance of the Pre-SRI and its prognostic impact on STEMI patients.
Between January 2013 and December 2017, 3,411 consecutive acute coronary syndrome (ACS) patients who underwent emergency PCI were enrolled in the Mie ACS Registry, a prospective and multicenter registry of Mie Prefecture, Japan.12,13 Of these, 715 (21%) non-STEMI patients, 306 (9%) patients with unstable angina pectoris, and 343 (10%) patients whose hemodynamic parameters were insufficient were excluded, leaving a total of 2,047 STEMI patients for analysis in this study (Supplementary Figure 1).
This registry was approved by the institutional review boards or ethics committees of Mie University Graduate School of Medicine (Reference no. 2881) and each of the participating institutes. The study was registered with the University Hospital Medical Information Network (UMIN) Clinical Trials Registry (ID: UMIN000036020). The study was conducted in accordance with the principles of the Declaration of Helsinki.
Definition of VariablesSTEMI was defined as follows: characteristic symptoms of myocardial ischemia in association with persistent ECG ST-elevation in at least 2 ECG leads or accompanying left bundle branch block morphology, and a subsequent increase in biomarkers of myocardial necrosis.14 Pre-hemodynamic parameters were recorded by the emergency medical service (EMS) at first contact with patients before arrival at the hospital, and hemodynamic parameters in the emergency room (ER-) were recorded on arrival at the hospital. The EMS transport time was defined as the time from first contact with patients to arrival at the hospital. The GRACE score was calculated using data obtained in the ER, and each variable was calculated as follows according to previous reports:6–9
SRI = (heart rate × [age / 10]2) / SBP
SI = heart rate / SBP
ASI = age × SI
MSI = heart rate / MAP
MAP = (SBP + 2 × DBP) / 3
where MAP is mean arterial pressure and DBP is diastolic blood pressure.
Clinical OutcomeThe primary endpoint of this study was 30-day all-cause mortality; the secondary endpoint was 2-year all-cause mortality. Clinical outcome data were collected from outpatient consultations, medical record reviews, and telephone interviews with patients and their families by a well-trained cardiologist.
Statistical AnalysisContinuous variables are presented as the mean±SD or median and interquartile range (IQR). Data were compared using the unpaired t-test or non-parametric Mann-Whitney test depending on the normality of data distribution. Categorical data are presented as percentages and were compared using the Chi-squared tests. Comparisons between groups were performed by 1-way analysis of variance (ANOVA) or the Kruskal-Wallis test with post hoc Bonferroni test. A receiver operating characteristic (ROC) curve was used to assess the accuracy of SRI, SI, ASI, MSI, and the GRACE score for predicting 30-day and 2-year all-cause mortality. The area under the ROC curve (AUC) for each variable was compared using the DeLong method.15 The Youden index was used to identify optimal cut-off values from the ROC curves.
Multivariate Cox proportional hazard ratio analysis was used to evaluate the independent prognostic value of the Pre-SRI. Three models were created for the multivariable Cox proportional hazard analysis using clinically significant variables from the univariate analysis. In Model 1 (Pre-SRI ≥34, left ventricular ejection fraction [LVEF] <40%, and symptom onset to balloon time ≥180 min), the number of variables was limited in the analysis due to the slightly higher number of missing values. Models 2 and 3 included male sex, dyslipidemia, prior heart failure admission, Pre-SRI ≥34, creatinine, hemoglobin, peak creatine phosphokinase (CK) per 100-IU/L increase, and left main trunk (LMT) culprit lesion plus multivessel disease, but not symptom onset to balloon time ≥180 min. LVEF <40% and TIMI flow Grade <3 were analyzed separately due to some missing values and confounding factors between the 2 variables.
The Kaplan-Meier time-to-event method was used to compare longitudinal curves among groups. The incremental prognostic value of High Pre-SRI over High ER-SRI was evaluated using the global Chi-squared test.
All tests were 2-sided, and significance was set at P<0.05. All analyses were performed using SPSS 24.0 (SPSS Inc., Chicago, IL, USA) and EZR version 1.52 (Saitama Medical Center, Jichi Medical University, Saitama, Japan), which is a graphical user interface for R version 4.02 (R Foundation for Statistical Computing, Vienna, Austria).16
In this study, 2,047 STEMI patients (median age 69 years [IQR 59–78 years]; 1,585 [77%] male patients) were analyzed. Among these patients, 104 (5.1%) patients died within 30 days of any cause and 219 (11%) patients died within 2 years of any cause.
Compared with surviving patients, those who died of any cause mortality were significantly older (median age 82 [IQR 72–86] vs. 69 [IQR 59–77] years; P<0.001) and predominantly female (Table 1). No significant difference in EMS transport time was observed between the 2 groups. In both prehospital and emergency room settings, SBP and DBP were lower, and heart rate was higher for patients who died within 30 days of any cause. Reflecting on these results, Pre-SRI was significantly higher in patients who died of any cause within 30 days than in those who survived (median 45 [IQR 36–67] vs. 25 [IQR 18–34], respectively). Similarly, Pre-SI, Pre-MSI, Pre-ASI, ER-SI, ER-MSI, ER-ASI, and ER-SRI were all higher in patients who died of any cause within 30 days. Compared with surviving patients, those who died of any cause within 30 days had a lower LVEF, lower hemoglobin and creatinine concentrations, and higher B-type natriuretic peptide (BNP) concentrations. In angiographic data and treatments, patients who died of any cause within 30 days had a longer symptom onset to balloon time, longer door to balloon time (DBT), more LMT culprit lesions, more multivessel disease, and a greater use of catecholamines and mechanical circulatory support (MCS). Patients who died of any cause within 30 days were less frequently treated with β-blockers, angiotensin-converting enzyme inhibitors or angiotensin receptor blockers, and calcium channel blockers, but more frequently treated with loop diuretics during hospitalization.
| Available data (n) |
All patients (n=2,047) |
Surviving patients (n=1,943) |
Patients who died within 30 days of any cause (n=104) |
P value | |
|---|---|---|---|---|---|
| Demographic parameters | |||||
| Age (years) | 2,047 | 69 [59–78] | 69 [59–77] | 82 [72–86] | <0.001 |
| Male sex | 2,047 | 1,585 (77) | 1,524 (78) | 61 (59) | <0.001 |
| BMI (kg/m2) | 1,890 | 23 [21–26] | 23 [21–26] | 22 [20–25] | 0.072 |
| Hypertension | 2,047 | 1,280 (63) | 1,214 (62) | 66 (63) | 0.840 |
| Diabetes | 2,047 | 656 (32) | 622 (32) | 34 (33) | 0.885 |
| Dyslipidemia | 2,047 | 981 (48) | 951 (49) | 30 (29) | <0.001 |
| Current smoker | 2,047 | 654 (32) | 634 (33) | 20 (19) | 0.004 |
| Hemodialysis | 2,047 | 21 (1) | 18 (0.9) | 3 (3) | 0.087 |
| Prior PCI | 2,047 | 170 (8) | 163 (8) | 7 (7) | 0.550 |
| Prior CABG | 2,047 | 12 (0.6) | 11 (0.6) | 1 (1) | 0.466 |
| Prior MI | 2,047 | 150 (7) | 144 (7) | 6 (6) | 0.531 |
| Prior HF admission | 2,047 | 33 (2) | 28 (1) | 5 (5) | 0.023 |
| Symptom onset to first contact time (min) | 1,153 | 60 [30–176] | 58 [29–163] | 157 [43–631] | <0.001 |
| EMS transport time (min) | 1,157 | 25 [19–35] | 25 [19–35] | 26 [19–32] | 0.338 |
| Symptom onset to door time (min) | 1,704 | 123 [67–274] | 122 [66–270] | 166 [71–416] | 0.17 |
| GRACE score | 2,047 | 159±42 | 156±39 | 228±42 | <0.001 |
| Hemodynamic data | |||||
| Prehospital | |||||
| SBP (mmHg) | 2,047 | 134±32 | 135±32 | 117±28 | <0.001 |
| DBP (mmHg) | 2,047 | 80 [64–94] | 80 [65–94] | 70 [53–82] | <0.001 |
| Heart rate (beats/min) | 2,047 | 74 [61–89] | 74 [61–88] | 89 [70–111] | <0.001 |
| Pre-SI | 2,047 | 0.56 [0.46–0.68] | 0.55 [0.45–0.67] | 0.76 [0.59–0.95] | <0.001 |
| Pre-MSI | 2,047 | 0.76 [0.64–0.93] | 0.76 [0.63–0.91] | 1.01 [0.83–1.25] | <0.001 |
| Pre-ASI | 2,047 | 37 [29–47] | 36 [29–46] | 59 [46–77] | <0.001 |
| Pre-SRI | 2,047 | 26 [18–35] | 25 [18–34] | 45 [36–67] | <0.001 |
| ER | |||||
| SBP (mmHg) | 2,047 | 132 [114–152] | 133 [115–153] | 111 [95–135] | <0.001 |
| DBP (mmHg) | 2,047 | 79 [66–92] | 80 [67–93] | 63 [51–80] | <0.001 |
| Heart rate (beats/min) | 2,047 | 78±20 | 77±19 | 90±27 | <0.001 |
| ER-SI | 2,047 | 0.57 [0.47–0.69] | 0.56 [0.47–0.68] | 0.79 [0.58–1.02] | <0.001 |
| ER-MSI | 2,047 | 0.78 [0.66–0.94] | 0.77 [0.65–0.91] | 1.09 [0.86–1.37] | <0.001 |
| ER-ASI | 2,047 | 38 [30–49] | 37 [30–47] | 62 [47–78] | <0.001 |
| ER-SRI | 2,047 | 27 [19–37] | 26 [18–35] | 47 [37–66] | <0.001 |
| LVEF, % | 1,852 | 55±12 | 56±12 | 42±14 | <0.001 |
| Killip classification | 2,044 | ||||
| Killip 1 | 1,622 (79) | 1,600 (82) | 22 (21) | <0.001 | |
| Killip 2/3 | 295 (14) | 255 (13) | 40 (38) | <0.001 | |
| Killip 4 | 127 (6) | 85 (4) | 42 (40) | <0.001 | |
| Laboratory data on admission | |||||
| Creatinine (mg/dL) | 2,047 | 0.85 [0.71–1.05] | 0.84 [0.71–1.03] | 1.09 [0.83–1.52] | <0.001 |
| Hemoglobin (g/dL) | 2,047 | 14±2 | 14±2 | 12±3 | <0.001 |
| LDL-C (mg/dL) | 1,817 | 121±38 | 122±38 | 108±37 | 0.002 |
| HbA1c (%) | 1,708 | 5.9 [5.6–6.7] | 5.9 [5.6–6.7] | 5.9 [5.6–6.8] | 0.879 |
| Peak CK (IU/L) | 2,045 | 1,630 [522–3,352] | 1,622 [525–3,255] | 1,915 [504–4,715] | 0.041 |
| BNP (pg/mL) | 1,066 | 86 [28–258] | 79 [26–225] | 521 [201–1,222] | <0.001 |
| Angiographic data and treatments | |||||
| Symptom onset to balloon time (min) | 1,704 | 215 [150–375] | 212 [149–370] | 300 [208–533] | <0.001 |
| Door to balloon time (min) | 1,704 | 76 [58–103] | 75 [58–101] | 100 [73–149] | <0.001 |
| Culprit lesion | 2,047 | ||||
| LMT | 30 (2) | 22 (1) | 8 (8) | <0.001 | |
| LAD | 1,005 (49) | 956 (49) | 49 (47) | 0.678 | |
| RCA | 778 (38) | 753 (39) | 25 (24) | 0.003 | |
| LCX | 190 (9) | 182 (9) | 8 (8) | 0.566 | |
| Others | 12 (1) | 11 (1) | 1 (1) | 0.466 | |
| Unknown | 32 (2) | 19 (1) | 13 (13) | <0.001 | |
| Multivessel disease | 2,025 | 602 (29) | 555 (29) | 47 (45) | <0.001 |
| TIMI Grade <3 | 1,877 | 193 (10) | 163 (9) | 30 (40) | <0.001 |
| Dopamine | 2,047 | 185 (9) | 152 (8) | 33 (32) | <0.001 |
| Dobutamine | 2,047 | 141 (7) | 104 (5) | 37 (36) | <0.001 |
| Norepinephrine | 2,047 | 95 (5) | 72 (4) | 23 (22) | <0.001 |
| CHDF usage | 2,047 | 34 (2) | 15 (0.8) | 19 (18) | <0.001 |
| IABP usage | 2,047 | 274 (13) | 222 (11) | 52 (50) | <0.001 |
| ECMO usage | 2,047 | 25 (1) | 9 (0.5) | 16 (15) | <0.001 |
| Medications during hospitalization | |||||
| β-blocker | 2,047 | 1,230 (60) | 1,203 (62) | 27 (26) | <0.001 |
| ACE-I/ARB | 2,047 | 1,706 (83) | 1,660 (85) | 46 (44) | <0.001 |
| Aldosterone antagonist | 2,047 | 180 (9) | 169 (9) | 11 (11) | 0.51 |
| Loop diuretics | 2,047 | 364 (18) | 322 (17) | 42 (40) | <0.001 |
| Calcium channel blocker | 2,047 | 293 (14) | 287 (15) | 6 (6) | 0.011 |
| Statin | 2,047 | 1,722 (84) | 1,678 (86) | 44 (42) | <0.001 |
| Antiplatelet agent | 2,047 | 2,016 (98) | 1,925 (99) | 91 (88) | <0.001 |
Unless indicated otherwise, data are presented as the mean±SD, median [interquartile range], or number (percentage). ACE-I, angiotensin-converting enzyme inhibitor; ARB, angiotensin II receptor blockers; ASI, age-shock index; BMI, body mass index; BNP, B-type natriuretic peptide; CABG, coronary artery bypass grafting; CHDF, continuous hemodiafiltration; CK, creatine phosphokinase; DBP, diastolic blood pressure; ECMO, extracorporeal membrane oxygenation; EMS, emergency medical service; ER, emergency room; GRACE, Global Registry of Acute Coronary Event; HF, heart failure; IABP, intra-aortic balloon pumping; LAD, left atrial dimension; LCX, left circumflex artery; LDL-C, low-density lipoprotein cholesterol; LMT, left main trunk; LVEF, left ventricular ejection fraction; MI, myocardial infarction; MSI, modified shock index; PCI, percutaneous coronary intervention; Pre-, prehospital; RCA, right coronary artery; SBP, systolic blood pressure; SI, shock index; SRI, simple risk index; TIMI, Thrombolysis in Myocardial Infarction.
The ROC and prognostic performance of prehospital and ER variables for 30-day all-cause mortality are shown in Figure 1. The Pre-SRI (AUC 0.816; 95% confidence interval [CI] 0.772–0.860) showed a significantly higher prognostic performance than the Pre-SI (AUC 0.755; 95% CI 0.706–0.805) and Pre-MSI (AUC 0.765; 95% CI 0.718–0.813), but was similar to the Pre-ASI (AUC 0.813; 95% CI 0.771–856; Figure 1A). The ER-SRI (AUC 0.827; 95% CI 0.782–0.871) also showed a significantly higher prognostic performance than the ER-SI (AUC 0.751; 95% CI 0.696–0.805) and ER-MSI (AUC 0.786; 95% CI 0.737–0.836), a similar prognostic performance to the ER-ASI (AUC 0.819; 95% CI 0.772–866), but a lower prognostic performance than the GRACE score (AUC 0.900; 95% CI 0.867–0.932; Figure 1B). The AUC of the Pre-SRI was similar to that of the ER-SRI (P=0.446). The cut-off values of the Pre-SRI and ER-SRI for predicting 30-day all-cause mortality were 34.8 (sensitivity 0.80, specificity 0.77) and 34.1 (sensitivity 0.82, specificity 0.74), respectively (Figure 2).
Receiver operating curves for different indices calculated using (A) prehospital (Pre-) and (B) emergency room (ER) variables, and comparisons of the prognostic performance of each index for 30-day all-cause mortality. ASI, age-shock index; AUC, area under the curve; GRACE, Global Registry of Acute Coronary Event; MSI, modified shock index; SI, shock index; SRI, simple risk index.
Comparisons of the prognostic performance and cut-off values of the (A) prehospital (Pre-) and (B) emergency room (ER) simple risk index (SRI) for 30-day all-cause mortality. AUC, area under the curve.
There were 219 deaths due to any cause at 2 years. For 2-year all-cause mortality, the Pre-SRI (AUC 0.800) and ER-SRI (AUC 0.809) showed the highest prognostic performance among the prehospital and ER variables, except for the GRACE score (AUC 0.852). The prognostic performances of the Pre-SRI and ER-SRI were comparable (P=0.362; Supplementary Figure 2).
Effects of the Pre-SRI on Prognosis and Treatment With MCSIn the Kaplan-Meier curve analysis, patients with a High (≥34) Pre-SRI had a poorer 30-day cumulative survival rate than patients with a Low (<34) Pre-SRI (85.2% vs. 98.6%, respectively; P<0.001), with similar results for 2-year cumulative survival (Figure 3). In a landmark analysis after 30 days, patients with a High Pre-SRI also had a lower cumulative survival rate than patients with a Low Pre-SRI (Supplementary Figure 3). Multivariate Cox regression analysis revealed that a High (≥34) Pre-SRI was a significant independent predictor of 30-day all-cause mortality in all 3 models (Model 1: hazard ratio [HR] 6.40, 95% CI 2.80–14.61; Model 2: HR 7.93, 95% CI 3.73–16.85; Model 3: HR 6.48, 95% CI 3.51–11.96). Low LVEF, low creatinine and hemoglobin concentrations, high peak CK per 100-IU/L increase, and TIMI Grade <3 also remained unfavorable in multivariate analysis (Table 2).
Kaplan-Meier curves of cumulative survival for (A) 30 days and (B) 2 years stratified by the prehospital simple risk index (Pre-SRI).
| Univariate | Multivariate | |||||||
|---|---|---|---|---|---|---|---|---|
| Model 1 | Model 2 | Model 3 | ||||||
| HR (95% CI) | P value | HR (95% CI) | P value | HR (95% CI) | P value | HR (95% CI) | P value | |
| Male sex | 0.40 (0.27–0.60) |
<0.001 | 0.83 (0.45–1.50) |
0.53 | 0.82 (0.48–1.40) |
0.473 | ||
| BMI | 0.97 (0.91–1.03) |
0.290 | ||||||
| Hypertension | 1.03 (0.69–1.54) |
0.872 | ||||||
| Diabetes | 1.03 (0.68–1.55) |
0.903 | ||||||
| Dyslipidemia | 0.43 (0.28–0.66) |
<0.001 | 0.84 (0.48–1.47) |
0.542 | 0.71 (0.44–1.18) |
0.184 | ||
| Hemodialysis | 2.93 (0.93–9.23) |
0.067 | ||||||
| Prior PCI | 0.79 (0.37–1.71) |
0.555 | ||||||
| Prior CABG | 1.67 (0.23–11.98) |
0.609 | ||||||
| Prior MI | 0.77 (0.34–1.77) |
0.543 | ||||||
| Prior HF admission | 3.27 (1.33–8.03) |
0.010 | 0.97 (0.23–4.04) |
0.966 | 1.56 (0.55–4.39) |
0.400 | ||
| Pre-SRI ≥34 | 11.73 (7.20–19.10) |
<0.001 | 6.40 (2.80–14.61) |
<0.001 | 7.93 (3.73–16.85) |
<0.001 | 6.48 (3.51–11.96) |
<0.001 |
| LVEF <40% | 8.09 (4.92–13.30) |
<0.001 | 5.68 (2.77–11.65) |
<0.001 | 4.24 (2.48–7.26) |
<0.001 | ||
| Creatinine | 1.27 (1.18–1.37) |
<0.001 | 1.24 (1.11–1.38) |
<0.001 | 1.25 (1.13–1.38) |
<0.001 | ||
| Hemoglobin | 0.71 (0.66–0.76) |
<0.001 | 0.85 (0.75–0.97) |
0.017 | 0.78 (0.70–0.88) |
<0.001 | ||
| Peak CK per 100-IU/L increase |
1.01 (1.01–1.02) |
<0.001 | 1.01 (1.00–1.02) |
0.002 | 1.01 (1.00–1.02) |
<0.001 | ||
| BNP per 100-pg/mL increase |
1.00 (1.00–1.01) |
0.065 | ||||||
| Symptom onset to balloon time ≥180 min |
3.40 (1.67–6.92) |
0.001 | 1.93 (0.79–4.72) |
0.149 | ||||
| TIMI Grade <3 | 6.25 (3.94–9.93) |
<0.001 | 4.30 (2.67–6.94) |
<0.001 | ||||
| LMT culprit lesion + multivessel disease |
3.18 (1.39–7.26) |
0.006 | 1.67 (0.58–4.79) |
0.343 | 1.30 (0.40–4.18) |
0.662 | ||
CI, confidence interval; HR, hazard ratio. Other abbreviations as in Table 1.
When all patients were categorized by Pre-SRI quartiles (Q1, 0–18.2; Q2, 18.2–25.6; Q3, 25.6–35.3; Q4, >35.3), the Q4 group had significantly higher rates of 30-day all-cause mortality and MCS usage than the other groups. In the Q1–Q3 groups, both rates tended to increase as Pre-SRI increased, but there was no significant difference among the 3 groups (Figure 4A). In patients after MCS placement, a similar trend was seen, and post-MCS 30-day all-cause mortality was approximately 2.6-fold higher in the Q4 than Q3 group (Figure 4B).
(A) Risk of 30-day all-cause mortality and the rate of mechanical circulatory support (MCS) and (B) the risk of post-MCS 30-day all-cause mortality stratified by prehospital simple risk index (Pre-SRI) quartiles.
All patients were divided into 4 groups according to whether the Pre-SRI and ER-SRI values were higher or lower than the cut-off value of 34: Group A, patients with Low Pre-SRI and Low ER-SRI (n=1,325; 65%); Group B, patients with High Pre-SRI and Low ER-SRI (n=115; 6%); Group C, patients with Low Pre-SRI and High ER-SRI (n=155; 8%); and Group D, patients with High Pre-SRI and High ER-SRI (n=452; 22%). In the Kaplan-Meier curve analysis, patients in Group D had a poorer cumulative survival rate (82.3%) than those in Groups A, B, and C (82.3% vs. 98.9%, 96.5%, and 96.8%, respectively; P<0.001). No prognostic differences were found between patients in Groups B and C (Figure 5A). The addition of High Pre-SRI to High ER-SRI resulted in a significantly increased global Chi-squared score (145 vs. 182, P<0.001), suggesting the incremental prognostic value of High Pre-SRI (Supplementary Figure 4A). Even for 2-year all-cause mortality, patients in Group D had a poorer cumulative survival rate (68.6%), followed by those in Groups C and B (86.5%, 89.6%) and Group A (96.7%; Figure 5B). A similar trend was shown in a landmark analysis after 30 days (Supplementary Figure 5). Combined assessment of Pre-SRI and ER-SRI showed the incremental prognostic value for 2-year all-cause mortality (Supplementary Figure 4B).
Kaplan-Meier curves of cumulative survival for (A) 30 days and (B) 2 years stratified by the combination of the prehospital (Pre-) and emergency room (ER) simple risk index (SRI). High SRI, scores ≥34; Low SRI, scores <34.
A comparison of patient backgrounds according to the combination of Pre-SRI and ER-SRI is presented in Table 3. Patients in Group D were older, had a lower BMI, higher prevalence of hypertension and hemodialysis, longer symptom onset to first contact time, symptom onset to door time, symptom onset to balloon time, and DBT, higher BNP concentrations, and more multivessel disease than patients in Group A. Compared with patients in Groups B and C, patients in Group D were significantly older and had a lower LVEF. The GRACE score was highest for patients in Group D, followed by patients in Groups C and B, and lowest in Group A, with significant differences among the groups. Patients in Group B and C were significantly older and had a lower hemoglobin level, lower percentage of Killip 1, higher percentage of Killip 4, and higher BNP concentrations, and tended to have a lower LVEF and greater use of MCS and ventilators than patients in Group A.
| Group A (n=1,325) |
Group B (n=115) |
Group C (n=155) |
Group D (n=452) |
P value | |
|---|---|---|---|---|---|
| Age (years) | 64 [54–70] | 76 [70–80]* | 75 [69–82]* | 82 [76–86]*,†,‡ | <0.001 |
| Male sex | 1,113 (84) | 74 (64)* | 119 (77) | 279 (62)*,‡ | <0.001 |
| BMI (kg/m2) | 24 [22–26] | 23 [20–25]* | 23 [21–25]* | 22 [20–24]*,†,‡ | <0.001 |
| Hypertension | 812 (61) | 76 (66) | 79 (51) | 313 (69)*,‡ | <0.001 |
| Diabetes | 436 (33) | 41 (36) | 38 (25) | 141 (31) | 0.150 |
| Dyslipidemia | 699 (53) | 46 (40) | 65 (42) | 171 (38)* | <0.001 |
| Current smoker | 539 (41) | 18 (16)* | 37 (24)* | 60 (13)*,‡ | <0.001 |
| Hemodialysis | 9 (0.7) | 1 (0.9) | 1 (0.6) | 10 (2.2)* | 0.044 |
| Prior PCI | 103 (8) | 8 (7) | 11 (7) | 48 (11) | 0.236 |
| Prior CABG | 4 (0.3) | 0 (0) | 2 (1.2) | 6 (1.3) | 0.044 |
| Prior MI | 92 (7) | 5 (4) | 9 (6) | 44 (10) | 0.103 |
| Prior HF admission | 13 (1) | 1 (0.9) | 2 (1) | 17 (4)* | 0.001 |
| Symptom onset to first contact time (min) | 55 [29–147] | 64 [25–180] | 65 [26–157] | 90 [37–360]* | 0.001 |
| EMS transportation time (min) | 25 [18–33] | 30 [23–40]* | 27 [21–35] | 26 [19–37] | 0.006 |
| Symptom onset to door time (min) | 117 [65–254] | 105 [60–260] | 128 [68–277] | 158 [74–373]* | 0.015 |
| GRACE score | 139±30 | 170±29* | 184±28*,† | 206±36*,†,‡ | <0.001 |
| Killip classification | |||||
| Killip 1 | 1,172 (88) | 88 (77)* | 118 (76)* | 244 (54)*,†,‡ | <0.001 |
| Killip 2/3 | 116 (9) | 17 (15) | 23 (15) | 139 (31)*,†,‡ | <0.001 |
| Killip 4 | 35 (3) | 10 (9)* | 13 (8)* | 69 (15)* | <0.001 |
| LVEF (%) | 57±11 | 56±12 | 53±11* | 49±13*,†,‡ | <0.001 |
| Creatinine (mg/dL) | 0.83 [0.7–0.97] | 0.94 [0.76–1.13]* | 0.85 [0.71–1.06] | 0.92 [0.74–1.28]* | <0.001 |
| Hemoglobin (g/dL) | 15±2 | 13±2* | 14±2* | 13±2*,‡ | <0.001 |
| HbA1c (%) | 5.9 [5.6–6.7] | 6.0 [5.6–6.7] | 5.9 [5.6–6.4] | 6.0 [5.7–6.6] | 0.263 |
| Peak CK (IU/L) | 1,702 [597–3,397] | 1,318 [426–3,152] | 1,907 [844–3,606] | 1,331 [396–3,245] | 0.017 |
| BNP (pg/mL) | 58 [20–153] | 134 [41–386]* | 108 [31–326]* | 219 [78–649]*,‡ | <0.001 |
| Symptom onset to balloon time (min) | 204 [145–354] | 200 [136–338] | 216 [159–362] | 255 [175–501]*,† | <0.001 |
| Door to balloon time (min) | 74 [57–98] | 76 [55–96] | 78 [61–113] | 82 [60–119]* | 0.002 |
| Culprit lesion | |||||
| LMT | 7 (0.5) | 1 (0.9) | 3 (1.9) | 19 (4)* | <0.001 |
| LAD | 634 (48) | 53 (46) | 80 (51) | 238 (53) | 0.27 |
| RCA | 538 (41) | 53 (46) | 57 (37) | 130 (29)*,† | <0.001 |
| LCX | 131 (10) | 7 (6) | 14 (9) | 38 (8) | 0.495 |
| Multivessel disease | 360 (27) | 37 (32) | 45 (29) | 160 (35)* | 0.003 |
| MCS | 124 (9) | 21 (18)* | 24 (16) | 109 (24)*,† | <0.001 |
| Ventilator | 31 (2) | 9 (8)* | 8 (5) | 53 (12)*,† | <0.001 |
Patients were divided into 4 groups based on the combination of the Pre- and ER-SRI scores using a cut-off value of 34 as follows: Group A, Low Pre-SRI/Low ER-SRI; Group B, High Pre-SRI/Low ER-SRI; Group C, Low Pre-SRI/High ER-SRI; Group D, High Pre-SRI/High ER-SRI. Unless indicated otherwise, data are presented as the mean±SD, median [interquartile range], or number (percentage). *P<0.05 compared with Group A; †P<0.05 compared with Group B; ‡P<0.05 compared with Group C (ANOVA or Kruskal-Wallis test with post hoc Bonferroni test). MCS, mechanical circulatory support. Other abbreviations as in Table 1.
The main findings of this study are as follows: (1) the Pre-SRI showed a higher prognostic performance than other indices using prehospital data, and was similar to the ER-SRI; (2) a High Pre-SRI was a significant independent predictor of 30-day all-cause mortality in STEMI patients; (3) patients with a high Pre-SRI (Q4 group) had higher rates of MCS usage and post-MCS 30-day mortality; and (4) combined assessment of the Pre-SRI and ER-SRI could stratify patient risk and provide incremental prognostic value. This is the first study to evaluate several indices using prehospital data and to investigate the prognostic impact of the Pre-SRI (with ER-SRI) in STEMI patients.
Morrow et al constructed the SRI, calculated as (heart rate × [age / 10]2) / SBP, as an easily assessed risk index on the basis of observed risk relationships among STEMI patients, and suggested that it was a strong predictor of death and heart failure at 30 days.6 As well as the SRI, several studies have evaluated a combined index of parameters such as age, blood pressure, and heart rate measured after hospitalization and reported it to be a predictor of short- and long-term prognoses of STEMI patients.7–9 Some retrospective analyses of trauma registries reported that prehospital SI and MSI could predict the severity of ongoing hemorrhage and the need for massive blood transfusions, and suggested that these prehospital indices could help provide timelier warnings and triage opportunities to the prehospital medical team.17,18 However, in STEMI patients, there have been limited studies evaluating the prognostic impact of these indices assessed in the prehospital setting. A single-center retrospective study compared the prognostic performance of the ASI, MSI, SI, and GRACE score using data recorded after admission in STEMI patients and demonstrated that the ASI had a similar predictive value to that of the GRACE score for short- and long-term mortality.19 Consistent with that study, the present study revealed that the ER-ASI and GRACE score showed higher prognostic performance than the ER-MSI and ER-SI. The present study also revealed that the ER-SRI had the highest prognostic performance for short- and long-term mortality among all the indices for ER variables, except for the GRACE score. For prehospital variables, the Pre-SRI had the highest prognostic performance for short- and long-term mortality among all the indices, and was comparable to that of ER-SRI. In patients with new-onset acute myocardial infarction (AMI), a series of neurohumoral reactions occur that result in sympathetic nerve hyperactivation, which was shown to be associated with the degree of left ventricular (LV) dysfunction.20 The SI may be associated with deterioration of the cardiac index, stroke volume, and LV stroke work.21 An increase in the SRI is also considered to reflect both the increase in heart rate due to sympathetic nerve hyperactivation and the decrease in blood pressure due to LV dysfunction. The present study suggests that these reactions already occur at an earlier stage after the onset of AMI in the prehospital setting.
Early prehospital assessment of STEMI patients can reduce the onset-to-device interval and allow selection of the best hospital to transport patients to. With the development of telecommunications, both the prehospital ECG and mobile telemedicine system, which continuously transmits real-time biological information, including ECG, vital signs, and in-vehicle images of a patient, have been shown to decrease the door-to-device interval, resulting in reduced mortality in patients with AMI.22,23 A retrospective cohort study of patients with undifferentiated chest pain demonstrated that a prehospital modified HEART score, calculated using prehospital patient information including history, ECG, age, risk factors, and troponin, has a high negative predictive value for major adverse cardiac events at 30 days.24 However, the HEART score involves invasive examination and requires training to calculate it quickly due to the complexity of the formula, especially for paramedics. In the present study, a High (≥34) Pre-SRI was a significant independent predictor of 30-day all-cause mortality in STEMI patients, and patients in the Q4 group, with a high Pre-SRI, were demonstrated to have significantly higher 30-day mortality, rate of MCS usage, and post-MCS 30-day mortality than patients in the Q1–Q3 groups, with a lower Pre-SRI. Recently, the Impella® (Abiomed Inc., Danvers, MA, USA), a new transcatheter micro-axial flow MCS device, was shown to provide powerful hemodynamic support and result in an improved prognosis when used early prior to PCI and in combination with veno-arterial extracorporeal membrane oxygenation (ECMO) in the treatment of AMI patients with cardiogenic shock.25,26 Several retrospective studies reported that, in patients with cardiopulmonary arrest or AMI, transport to a hospital with more advanced medical care improved patient outcomes, regardless of the transport time or distance.27–29 Patients with a Low Pre-SRI were less likely to need MCS placement in our study and may therefore be preferably transported to nearby PCI-capable hospitals where the onset-to-device interval can be shortened. Conversely, because patients with a High Pre-SRI show high 30-day mortality even when supported by ECMO and/or an intra-aortic balloon pump, they may need to be transported to high-volume hospitals with additional MCS devices available, such as the Impella. The present study suggests that patients with a High SRI may have prolonged DBT due to MCS replacement and ventilator use, resulting in myocardial damage and poor prognosis. Impella, which can be inserted in a relatively short time and may reduce myocardial damage by reducing reperfusion injury,30 could be useful for these patients. The SRI is an objective index that can be quickly and easily assessed not only by healthcare providers, but even by family members. Early assessment of the SRI combined with the diagnosis of STEMI by a prehospital ECG can be easily shared through local healthcare networks and may allow selection of the best hospital to transport the patient to, as well as shortening the time to device placement by preparation in advance.
Frequent assessments should be conducted to avoid misdiagnosing the severity of a patient’s condition by assessing hemodynamics at a single point, because hemodynamics during EMS transport after the onset of AMI are very unstable. The present study demonstrates that combined assessment of the Pre-SRI and ER-SRI could stratify STEMI patient risk and provide incremental prognostic value in both the short and long term. Two main factors may contribute to the high short- and long-term mortality affected by a High SRI. First, as previously reported for the SI,21 a High SRI may be associated with deterioration of the cardiac function and sympathetic hyperactivity. This LV dysfunction and concomitant sympathetic hyperactivity may keep the SRI high during EMS transport and lead to refractory heart failure, fatal arrhythmias, and extensive LV remodeling, resulting in both high short- and long-term mortality. Seconds, age is an important prognostic factor in the short and long term after myocardial infarction.3–5,24,31 Particularly with regard to long-term mortality, because elderly patients have many comorbidities and physical disabilities, intensive treatments, including MCS placement, could lead to marked progression of deconditioning and susceptibility to fatal multiorgan failure and infections, resulting in high long-term mortality.31,32 Our finding that patients in Group D were older and had a lower LVEF, higher BNP, and greater use of MCS than those in Groups B and C is consistent with these considerations. The longer symptom onset to first contact time and symptom onset to door time may have contributed to further LV dysfunction and exacerbation of heart failure, resulting in higher Pre-SRI and ER-SRI. Attention should also be paid to groups such as Groups B and C, where the SRI varies from prehospital to the ER, because assessment of the ER-SRI alone may misdiagnose the potential severity of a patient’s condition. Both patients with decreasing SRI (Group B) and increasing SRI (Group C) from prehospital to the ER were shown to have similar patient backgrounds (i.e., reduced LV function accompanied by cardiogenic shock and heart failure). Sympathetic hyperactivity due to LV dysfunction may also result in SRI instability, and further hyperactivity may keep the SRI much higher, such as in Group D. Our finding that patients in Group D had higher severity according to the Killip classification and a lower LVEF than those in Groups B and C may be explained as follows. Patients in Group D had the highest GRACE score, followed by those in Group C, Group B, and Group A. Unlike the GRACE score, which requires invasive examination and a complex formula, combined assessment of the Pre-SRI and ER-SRI can non-invasively and quickly stratify patient risk. This assessment of SRI over time from prehospital to the ER could optimize not only the selection of a hospital, but also treatment after admission at an early stage.
Study LimitationsSeveral study limitations must be acknowledged. First, this study was retrospective and observational in nature. Residual confounding variables and missing values may not have been completely adjusted for. In terms of analysis of registry data, missing values are unavoidable, but BNP, symptom onset to first contact time, and EMS transport time had slightly higher numbers of missing values. Second, there was no information regarding medications before admission. Some medications, such as β-blockers or antihypertensive drugs, may have influenced the results. Third, patients with arrhythmia, such as atrial fibrillation, were not excluded because of the lack of arrhythmia information at the onset of AMI. Even under arrhythmia, a high SRI with a decrease in blood pressure would be expected to reflect the severity of a patient’s condition, but further studies are needed regarding the evaluation of the SRI in the presence of arrhythmia.
The Pre-SRI can identify high-risk STEMI patients at an early stage, and combined assessment of the Pre-SRI and ER-SRI could be of the incremental prognostic value for risk stratification in STEMI patients. The assessment of the SRI over time from the early stage may help us formulate better treatment strategies and improve the prognosis of STEMI patients.
The authors thank all the participating facilities, the Mie ACS Registry Co-investigators, Mie CCU Network Support Center, and the Mie University Hospital Clinical Research Support Center.
This study was supported and funded by the Mie Cardiovascular and Renal Disease Network.
K. Dohi has received departmental research grant support from Otsuka Pharmaceutical Co., Ltd., Abbott Medical Japan LLC, Novartis Pharma K.K., Daiichi Sankyo Chemical Pharma Co., Ltd., Takeda Pharmaceutical Co., Ltd., Sumitomo Dainippon Pharma Co., Ltd., Kowa Co., Ltd., Takeda Pharmaceutical Co., Ltd., Ono Pharmaceutical Co., Ltd., and Shionogi Pharma Co., Ltd., as well as lecture fees from Otsuka Pharmaceutical Co., Ltd., Novartis Pharma K.K., Kowa Co., Ltd., AstraZeneca K.K., Daiichi Sankyo Chemical Pharma Co., Ltd., Nippon Boehringer Ingelheim Co., Ltd., and Bayer Yakuhin, Ltd. The other authors have no financial conflicts of interest to disclose.
This study was approved by the Mie University Hospital Institutional Review Board (Reference no. 2881).
Individual deidentified participant data (including data dictionaries) and the Microsoft Excel data used for analysis will be shared. Data for each table and figure will be shared upon request. The study protocol will also be shared. Data will be available for 1 year after acceptance and will be available to anyone who is interested in this article after acceptance from the corresponding author. The data will be shared as Microsoft Excel or CSV files via email.
Please find supplementary file(s);
https://doi.org/10.1253/circj.CJ-22-0795
