|Year : 2018 | Volume
| Issue : 2 | Page : 77-83
Utility of ST score on admission as a marker for outcome in acute myocardial infarction in a resource constrained setting
Udit Narang1, OP Gupta2, Jyoti Jain2, SP Kalantri2, Sandeep Joshi1, Suyash Bhadoriya1
1 Department of Medicine, MMIMSR, Ambala, Haryana, India
2 Department of Medicine, Mahatma Gandhi Institute of Medical Sciences, Wardha, Maharashtra, India
|Date of Web Publication||11-Oct-2018|
Dr. Jyoti Jain
Department of Medicine, Mahatma Gandhi Institute of Medical Sciences, Sewagram, Maharashtra
Source of Support: None, Conflict of Interest: None
Introduction: An early and specific indicator is needed to prognosticate acute myocardial infarction (MI). This indicator should be simple, quick, reliable, non-invasive, inexpensive, and easily applicable to all the patients especially in a resource-constrained setting. The present study tried to evaluated efficacy of ST score on electrocardiography as a prognostic indicator in acute ST-elevated MI (STEMI). Materials and Methods: A prospective study was conducted on consecutive thrombolysed patients of STEMI admitted in teaching hospital. ST score defined as sum of ST-segment elevation in all leads related to infarct location was calculated in standard 12-lead electrocardiographic tracings immediately on admission and then serially postthrombolysis at 90 min, 6 h, 24 h, and day 3 and 5 of admission. Primary end-point was all-cause mortality at 30 days. Results: The mean ST score between survivor and nonsurvivor was 19.27 mm and 16.16 mm, respectively. The score on admission in patients who had poor outcome was significantly higher than those who had good outcome (poor = 20.27 mm vs. good outcome = 12.47 mm; P = 0.002). This difference persisted throughout but was maximum at 90-min postthrombolysis (13.82 mm vs. 7.39 mm; P = 0.0001). The optimal cutoff point maximizing sensitivity and specificity was found at 11 mm for both anterior- and inferior wall MI (IWMI) with a sensitivity of 73% and specificity of 58%. Conclusion: This study concludes that an increase of 1 mm in ST score increased the odds of complications by 1.06 (95% confidence interval [CI], 1.01–1.2) for anterior-wall MI and by 1.09 (95% CI, 0.96–1.2) for IWMI. In a resource-constrained health facility where electrocardiography may be the only available equipment, ST score can easily and effectively be used to stratify patients into high-risk and low-risk categories.
Keywords: Electrocardiogram, myocardial infarction, prognosis, ST-score
|How to cite this article:|
Narang U, Gupta O P, Jain J, Kalantri S P, Joshi S, Bhadoriya S. Utility of ST score on admission as a marker for outcome in acute myocardial infarction in a resource constrained setting. J Mahatma Gandhi Inst Med Sci 2018;23:77-83
|How to cite this URL:|
Narang U, Gupta O P, Jain J, Kalantri S P, Joshi S, Bhadoriya S. Utility of ST score on admission as a marker for outcome in acute myocardial infarction in a resource constrained setting. J Mahatma Gandhi Inst Med Sci [serial online] 2018 [cited 2018 Nov 19];23:77-83. Available from: http://www.jmgims.co.in/text.asp?2018/23/2/77/243127
| Introduction|| |
Ischemic heart disease is proven to be the major cause of mortality and loss of disability-adjusted life years (DALYs) worldwide, responsible for around 7 million mortalities and 129 million DALYs per annum.,, It has been seen that deaths due to cardiovascular diseases (CVD) related to age have decreased in many developed countries in the previous years, but on the other hand, incidence of CVD itself has increased grossly constituting a burden of 80% in low-income and middle-income countries. In India, of all deaths, nearly 24.8% deaths are due to CVD as estimated by Global Burden of Disease study (2010). Average age-standardized death rate in India due to CVD is 272/100000 population which is much higher than the rate of global deaths, i.e., 235/100000 population. Studies predict, with under status quo CVD prevention and treatment trends, the prevalence of CVD will increase by ≈10% over the next 20 years whereas the direct costs will increase by almost 3-fold. With remarkable frequency, investigators continue to propose additional indicators such as behavioral, biochemical, environmental, and genetic risk markers, to stratify patients into either low-or high-risk group for developing a cardiovascular event, i.e., arrhythmias, heart failure, reinfarction, or death. Determining infarct-related artery (IRA) patency is clinically important because there is substantial evidence that rescue angioplasty improves outcomes in patients with a persistently occluded IRA.,,, However, not all hospitals in this country, and more so in rural areas, have adequate facilities to perform urgent coronary angiography and therefore for taking the right clinical decision management in patients with acute myocardial infarction (AMI), an early and specific prognostic indicator is needed. Ideally, this indicator should be simple, quick, reliable, noninvasive, inexpensive, and easily applicable to all the patients. An assessment by the universally available ST score calculation in a 12-lead electrocardiogram (ECG) could help in stratifying patients into high-and low-risk group.
Thus, the present study was taken up with an aim to the evaluated efficacy of ST score as a prognostic indicator in acute ST-elevated MI (STEMI).
| Materials and Methods|| |
A prospective prognostic study was carried out on 102 consecutive patients of acute STEMI who underwent thrombolysis over a period of one and ½ years in the department of medicine in a rural tertiary care hospital in central India. The exclusion criteria were as follows:
- Patients with evidence of severe rhythm disturbances at the time of the initial ECG hampering the ability to read the ECG
- Patients with new onset left bundle branch block (LBBB) diagnosed to have AMI
- Patients with posterior AMI as well as elevations in the right ventricular leads only
- Patients refusing to give consent.
The study was cleared by Institutional Ethics Committee. Written consent was obtained from all patients. For all patients, baseline demographic characteristics and clinical data with respect to symptomatology, duration of symptoms, presence or absence of conventional risk factors and history of diabetes, hypertension, and stroke were obtained. They were subjected to detailed clinical examination to check for vital signs, Killip class on admission, and significant cardiovascular findings. All patients received the standard line of management for AMI in accordance with American Heart Association (AHA) guidelines. Diagnostic ST elevation in the absence of left ventricular hypertrophy or LBBB was defined as per definition by the European Society of Cardiology/ACCF/AHA/World Heart Federation Task Force as new ST elevation at the J point in at least 2 contiguous leads of ≥2 mm (0.2 mV) in men or ≥1.5 mm (0.15 mV) in women in leads V2–V3 and/or of ≥1 mm (0.1 mV) in other contiguous chest leads or the limb leads. In all patients, ST score was calculated in standard 12-lead electrocardiographic tracings immediately on admission and then serially postthrombolysis at 90 min, 6 h, 24 h, and day 3 and 5 of admission by two readers separately. The ST scores measured by both were averaged and used for analysis. In the case of difference, i.e., >2 mm difference, the ECG was re-analyzed together in an attempt to reach a consensus.
Anterior-wall Infaction (AWMI) was defined, as ST elevation of more than 2 mm in 2 or more leads from V1–V6 on ECG, whereas inferior wall MI (IWMI) was considered as ST elevation of ≥1 mm noted in 2 of the Leads: II, III, and aVF. When ST elevation was only confi ned to V5, V6, I, and aVL, the infarction was defined as anterior unless concomitant ST elevation was present in Lead II, III, and aVF.
ST score was defined as sum of ST-segment elevation in all leads related to infarct location. ST-segment elevation was measured (to the nearest 0.5 mm) 60 ms after J point and relative to PR segment.,,
During the hospital stay, patients were examined daily and were monitored for the early complications and mortality. The primary end-point was all-cause mortality at 30 days. Secondary endpoints were appearance or worsening of heart failure (diagnosed depending on patients symptoms and signs and confirmed on chest X-rays), life-threatening rhythm disturbance as diagnosed by the treating physician, cardiogenic shock defined as persistent hypotension (systolic blood pressure <90 mmHg) or need for inotropic support, reinfarction (diagnosed by appearance of new changes in ECG) and duration of hospital stay or re-admission. Patients were followed up for a period of 30 days.
We used Microsoft Excel to enter the data electronically and STATA software (Version 10, Stata Corporation, Texas, USA) to analyze it. We used Student's t-test to analyze normally distributed continuous variables, Chi-square test to analyze proportions, and Mann–Whitney test to analyze continuous variables with skewed distribution. We calculated standard deviation (SD) and interquartile range to express the variability of means and medians, respectively. As the variables like ST score were not normally distributed, we log transformed them. Our initial analysis included comparison of the frequencies of demographic variables and risk factors among patients with anterior and inferior STEMI and patients with good and poor outcome. For bivariate analysis, we evaluated risk factors to find out whether they were associated with outcome events. We assessed the statistical significance of the following variables in the univariate model: Age, sex, systolic and diastolic blood pressure, Killip class, creatinine phosphokinase (CPK) levels, ST scores and ST indices on admission, and then subsequently crude (unadjusted) odds ratio (OR) were computed to assess the strength of association between risk factors (covariates) and independent variable (outcome). The OR estimates were computed along with a 95% confidence interval (CI).
The threshold of P < 0.20 to identify statistically significant variables was used in the univariate model. We began building multivariate logistic regression model by a backward stepwise analysis and used a cut point of P < 0.05 to eliminate statistically insignificant variables from the final models. The initial full model included all the variables selected using the criteria described above. From this full model, variables that did not contribute significantly were dropped one at a time, until all those remaining contributed significantly. At each step, the variable with the smallest contribution to the model (largest P value) was dropped. We assessed the impact of the elimination of each variable on the model using the likelihood ratio test. We continued the backward stepwise process until the best fitting, most parsimonious final model was identified. We assessed the fit of the final model using the Hosmer–Lemeshow goodness-of-fit test. Finally, the calibration of the model and its ability to discriminate patients with good or poor outcome was assessed by plotting receiver operating characteristic (ROC) curve. The results of the final model are presented as adjusted OR with 95% CI.
| Results|| |
A total of 102 patients were enrolled in the study on the basis of inclusion criteria. All patients were followed up till death or 30 days from the date of admission whichever occurred earlier.
Of the 102 patients enrolled, 75 were men and 27 were women with a mean ≥ SD age of 58.6 years (SD 11.4); range: 32–85 years in the study. Women were older than men (62.9 years vs. 58 years; P = 0.02). There was no difference in the age of those with anterior or inferior MI (58.2 vs. 59.1 years; P = 0.68). On the basis of electrocardiographic findings, MI was located in the anterior wall in 63 patients and the inferior wall in 39 patients. The baseline characteristics were similar in both patients of anterior and IWMI with respect to profile for risk factors, medication, and clinical and biochemical parameters but for the fact that more number of patients of IWMI had diabetes on admission [Table 1]. Over a period of 30 days, a total of 18 patients died: 11 with anterior MI and 7 with inferior MI. Arrhythmias were significantly more in patients of IWMI; however, re-admissions were significantly less. The various outcomes during the study period have been shown in [Table 2]. In patients with evidence of complications, the sum of ST-segment elevation was significantly higher as compared with those without complications. The ST score in patients who had poor outcome was significantly higher than those who had good outcome (poor outcome: 20.27 mm vs. good outcome: 12.47 mm; P = 0.002) [Table 3].
Since the distribution of ST score was right-skewed, we log-transformed it for the analyses. On multivariate regression model, the ST score was found to be significant predictor of a composite outcome event for death, re-infarction, re-admission, rhythm disturbance, and heart failure (OR = 2.74; 95% [CI], 1.46–5.17; P = 0.002). The area under the ROC curve for this model was 0.70 and the model had a sensitivity of 73.5% and specificity of 58.7%; positive predictive value of 68.3% and negative predictive value of 64.2% [Figure 1].
|Figure 1: Receiver operator characteristics curve of ST score on admission|
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The mean ST score of those who died was 19.27 mm (SD 14.9) compared to those who survived 16.16 mm (SD 12.5). We used ROC curve to create a cut point that maximized sensitivity and specificity for different cut points of ST score on admission. We found that a cut point of 11 mm (sensitivity – 73% and specificity – 58%) was the best cut point to distinguish between those with good outcome and those with poor outcome (area under ROC 0.66; 95% [CI] 0.59–0.80) [Figure 2].
|Figure 2: Receiver operating characteristic curve for ST score (Cut point 11)|
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Multivariate logistic regression analysis [Table 4] showed that Killip class on admission (OR, 2.39; 95% [CI], 1.24–4.58), CPK-MB (OR, 1.008; 95% [CI], 1.002–1.014), and STS ≥11 mm (OR, 4.00; 95% [CI], 1.60–9.99) were the independent predictors of poor outcome at 30 days. Thus, a patient with STS >11 mm was four times likely to experience a poor outcome compared to one with STS <11 mm. This model had a sensitivity of 78.5% and specificity of 56.6%, positive predictive value of 68.7% and negative predictive value of 68.4%. It correctly identified 68.63% of all outcomes (area under ROC curve = 0.77) [Figure 3].
|Table 4: Odds ratio on univariate and multivariate logistic regression analysis|
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None of the other predictors that we adjusted in the multivariable logistic regression models were found to be significantly associated with the outcome.
| Discussion|| |
Time plays a major role in the management of AMI. Judging for prognosis is not only challenging but also important for the early management in patients. An early and specific prognostic indicator is needed which should be simple, quick, reliable, noninvasive, inexpensive, and easily applicable to all the patients, especially in a resource-constrained setting. It has been earlier suggested that patients with greater ST-segment elevation during the first 24 h after onset of symptoms are more likely to present with atrial fibrillation, first- and second-degree atrioventricular block, ventricular extrasystole, ventricular tachycardia, ventricular fibrillation, cardiogenic shock, and death.,, The present study was taken up with an aim to evaluated efficacy of ST score as a prognostic indicator in acute STEMI.
In the present study, the ST score was found to be significantly higher in patients with anterior-wall MI (AWMI). This was because more number of leads was taken into account in AWMI as compared to IWMI. In patients with complications, the ST score was significantly higher than those without complications. This difference was observed in both patients with anterior or IWMI. The ST score on admission in patients who had poor outcome was significantly higher than those who had good outcome (poor 20.27 mm vs. good outcome 12.47 mm; P = 0.002). This difference persisted throughout but was maximum at 90 min postthrombolysis (13.82 mm vs. 7.39 mm; P = 0.0001). A study done by Gwechenberger et al., in 1997, found similar results in both anterior and IWMI (AWMI with and without complications: 19.4 mm vs. 10.3 mm, respectively, P < 0.001; inferior MI with and without complication: 10.4 mm vs. 6.9 mm; P < 0.001).
Schreiber et al. compared ST score (SUMSTelev) and ST-segment deviation score (SUMSTdev), i.e., the sum of ST-segment elevation and depression in 382 patients with acute MI and found that SUMSTdev was significantly higher in patients with complications than in patients without complications (AWMI 23.9 mm vs. 11.5 mm, respectively, P < 0.001; IWMI 21.6 mm vs. 12.0 mm, respectively, for inferior wall, P < 0.001).
In the present study, the mean ST score for the patients who died was 19.27 mm compared to those who survived 16.16 mm. This score was comparable to the study done by Gwechenberger et al., in which the score was 21.3 mm. In the present study, ROC curves showed that ST score on admission performed best in predicting early complications in AMI. The mean area under the curve was 0.70. The optimal cutoff point maximizing sensitivity and specificity was found at 11 mm for both anterior and IWMI with a sensitivity of 73% and a specificity of 58%. The relative risk (RR) was significantly greater in patients above the cutoff value than in those below the cutoff (RR 3.88; 95% CI, 1.68–8.93).
Gwechenberger et al. in his study gave cut point of 13 mm for AWMI and 11 mm for IWMI which maximized sensitivity and specificity. The ROC for AWMI in their study showed the mean ≥ SD area under the curve as 0.80 ≥ 0.04 with sensitivity and specificity of 79% and 73%, respectively. The RR was 2.98 (95% CI, 1.9–4.8). ROC curves for IWMI showed mean ≥ SD area under the curve as 0.72 ≥ 0.05 with sensitivity and specificity of 64% and 68%, respectively. The RR was 2.1 (95% CI, 1.4–3.2). They showed that an increase of 1.0 mm in ST score increases the odds of complications by 1.1 (95% CI, 1.1–1.2) for AWMI and by 1.2 (95% CI, 1.1–1.4) for IWMI. We also used the above cutoff values for both AWMI and IWMI and found that ST score on admission with cutoff value of 13 had an odds of complication as 5.2, 95% CI, 1.8–15.2; P ≤ 0.0001) whereas cutoff value of 9 mm for IWMI had odds of complication as 4.2, 95% CI, 1.08–16.4; P = 0.003.
Schreiber et al. gave the optimal cutoff for the SUMSTdev as 16 mm for AWMI and 13 mm for IWMI which was much higher than the present study and the other studies done in the past. This difference was because the authors considered both ST elevation and the reciprocal changes of ST depression in the corresponding leads. The 30 days mortality in our study population was 17.6% (18 out of 102 patients). The in-hospital mortality was found to be 10.78% (11 out of 102) of which 3.92% (4 out of 102) died within 24 h. There was no statistical difference between the 30 days mortality among patients of AWMI and IWMI, i.e., 11 versus 7 (P = 0.95). Higher mortality in our population could be because of lower rate of percutaneous intervention in our study population. Absence of facility for early operative intervention at our center and non-affordability of the patients to get these interventions done was responsible for lower rate surgical interventions.
The present study concludes that an increase of 1.0 mm in ST score increased the odds of complications by 1.06 (95% CI, 1.01–1.2) for AWMI and by 1.09 (95% CI, 0.96–1.2) for IWMI which was comparable to the studies done in the past. It suggests that ST score alone on admission could be used for risk stratification. Neither serial estimation of ST score nor other parameters assessed on admission or serially, would help in better risk stratification. No other clinical variables available at the time of admission were significantly associated with the occurrence of early complications in patients with AWMI or IWMI.
The difference between good and poor outcome was observed in patients with both AWMI and IWMI, indicating that the ST score could be used independent of the infarct location. In patients with AWMI with early complications, higher ST score was due to not only by greater ST-segment elevation in each lead but also due to greater number of leads with ST-segment elevations. Indicating greater the number of leads greater was the area of infarction. Therefore, ST score may reflect the area of endangered myocardium in patients with AWMI. Our data are in line with the findings of previously published reports demonstrating a relationship between ST score and infarct size.,, These reports also showed a correlation between the amount of ST-segment elevation and serious complications or death.
The study reflects results from only a small group of people, but on the other hand being a single center study, it provides credibility to the results. The other weakness of the study was its small sample size which, although was adequate for analysis of mortality and for total outcome events, was, however, inadequate for the subgroup analysis. The study had few strengths as well. First, all consecutive patients with STEMI were included in the study, eliminating selection bias and second, the primary outcome variable was all-cause mortality which is a hard endpoint that eliminated bias.
| Conclusion|| |
From the above study, we conclude that ST score on admission proved to be an independent marker of prognostic importance. In an emergency department and in a resource constrain health facility where electrocardiography may be the only available equipment, ST score can easily and effectively be used to stratify patients into high-risk and low-risk categories. It is, therefore, recommended that aggressive treatment with close monitoring should be initiated in the patients who are found to have high values of ST score on admission.
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Conflicts of interest
There are no conflicts of interest.
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[Figure 1], [Figure 2], [Figure 3]
[Table 1], [Table 2], [Table 3], [Table 4]