ECG-based Characteristics of Death or Re-infarction on the 12-Lead or 15-Lead ECG among UA/NSTEMI Patients: A Protocol for a Systematic Review and Meta-Analysis

The incidence of unstable angina/ non-ST elevation MI (UA/NSTEMI) continues to rise, and despite treatment advancements the risks of death and re-infarction persist. The electrocardiogram (ECG) remains the rst assessment of myocardial ischemia caused by UA/NSTEMI, and is performed within the rst 10-minutes of emergency presentation. Once ischemia is identied on the ECG, interventions are delivered timely to decrease the risk of death and re-infarction. Since the ECG informs intervention decisions, it is crucial providers understand the prognostic value of individual characteristics on the ECG. However, characteristics on ECG are limited due to low sensitivity though newer research has aimed to overcome these limitations. This is the protocol for a systematic review and meta-analysis that will assess the signicance of individual characteristics on the ECG for predicting death and re-infarction among UA/NSTEMI patients, and identify remaining gaps in clinical understanding of ECG.

More than 65% of all cases of acute coronary syndrome in the United States are diagnosed as unstable angina/ non-ST elevation myocardial infarction (UA/NSTEMI), a heterogeneous constellation of patient symptoms and diagnostic test results [1]. UA/NSTEMI is a dynamic condition causing myocardial ischemia due to a signi cant reduction in blood ow [2,3]. The most common and dangerous cause of UA/NSTEMI is due to the opening and closing of a coronary artery due to the erosion or rupture of an atherosclerotic plaque [2,3]. The de nition for UA/NSTEMI involves a presentation with or without chest pain, but with electrocardiographic (ECG) changes consistent with ischemia (e.g. ST-segment changes) and, in NSTEMI, an elevation in cardiac biomarkers for necrosis (e.g. troponin) [2]. The majority of UA/NSTEMI patients present with chest pain and other symptoms such as arm pain and back discomfort, and normal initial cardiac biomarkers [5,6]. Overall, the heterogeneity in patient symptoms and diagnostic test results make decisions around timing of interventions susceptible to error despite the fact that timely interventions are needed to reduce the risk of re-infarction and death [5][6][7][8].
The risk of death and re-infarction are serious concerns among UA/NSTEMI patients, and initial treatment is based on this acute risk. Among a cohort of 11,342 UA/NSTEMI patients followed for 2-years, the reinfarction rate was UA 3.9% and NSTEMI 5.6% and the all-cause mortality rate was UA 4.9% and NSTEMI 9.5% [9]. In a separate study analyzing two trial results which followed UA/NSTEMI patients for 30 days after hospitalization, the re-infarction rate was 2.2-4.6% UA and 3.1% NSTEMI and the all-cause mortality rate ranged from 0.5-0.7% for UA and 3.7%-7.4% for NSTEMI [10]. Despite growing emphasis on earlier interventions to prevent death and re-infarction, mortality rates have not signi cantly decreased [9,11]. This may be due to an initial underestimation of ischemic injury assessed on the ECG at presentation [6][7][8].
The ECG is crucial for informing initial treatments in UA/NSTEMI and has prognostic value for death and re-infarction, but has limitations and can be misinterpreted leading to an underestimation of ischemic injury [12]. The ECG is completed within the rst 10 minutes of patient presentation per current American Heart Association/ American College of Cardiology (AHA/ACC) guidelines which enable providers to rapidly stratify patients based on greatest risk for death and re-infarction [2]. This has improved the e ciency of delivering interventions to patients who need them most. However, ECG has a number of limitations which lead to an underestimation of ischemic injury. First, some common ECG characteristics such as ST-segment depression have a low sensitivity for acute infarction [13]. This low sensitivity occurs for a number of reasons including: 1) the dynamic nature of UA/NSTEMI in which blood ow can spontaneously return or be supplied through a collateral artery; 2) the limited 10-second duration of the standard ECG; and, 3) the lack of leads especially in the posterior wall of the myocardium making it di cult to detect ischemia [2,13]. Though AHA/ACC guidelines consider it reasonable to place leads over the posterior wall (V7-V9), it is not necessarily performed in clinical practice [2,14]. Lastly, the ECG is often misinterpreted by providers further leading to treatment delays [14,15]. Newer research has identi ed novel characteristics on the ECG related to UA/NSTEMI which have higher sensitivity and the potential to overcome these identi ed limitations [12,16]. Collectively, the rapidness of the ECG to assess ischemic in UA/NSTEMI is a signi cant advantage but a number of limitations contribute to an underestimation of ischemic injury.
This study aims to systematically review and meta-analyze published research assessing individual characteristics on the ECG prognostic of death and re-infarction among UA/NSTEMI patients in the emergency department. The purpose for this systematic review and meta-analysis is two-fold: to inform providers about the prognostic value of characteristics on the ECG, and to identify remaining gaps in clinical understanding of ECG. In this review, we will include both common and novel characteristics on the ECG and include both 12-lead and 15-lead ECGs.

Methods
The following protocol has been written in accordance to the Guidelines for Meta-Analyses and Systematic Reviews of Observational Studies (MOOSE) and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA-P) guidelines [17,18]. The PRISMA-P checklist is seen in Table 3.
The protocol is registered at the International Prospective Register of Systematic Reviews (PROSPERO; ID CRD42020158491) [19].

Research Question
The PIOT (Population, Indicator, Outcome, Time) research question guiding this systematic review and meta-analysis is: Among UA/NSTEMI patients in the emergency department (Population), do speci c characteristics on the ECG (Indicator) predict death and re-infarction (Outcome) in the rst 28 days after initial patient presentation (Time)? No comparison component will be used. The timeframe of 28 days will be used to be consistent with the de nition of re-infarction in the 4 th universal de nition of myocardial infarction [20].

Independent Variables
The independent variables for this protocol are speci c individual characteristics on the 12-lead or 15-lead ECG collected in the emergency department. We specify ECG in the emergency department to focus on initial emergency contact. Our expertise in this area have led us to hypothesize the following common and novel characteristics will likely be included: ST-segment depression, T-wave inversion, and QRS-T angle [12,13,16]. However, we will not limit our search to just these characteristics. Across different studies, measurement differences may exist. Although these characteristics have standardized measurements and corresponding normal values, individual studies may deviate from these published standards [21]. We will record details on how each characteristic is measured in this review and metaanalysis, and study the effects in a meta-regression (see below).

Dependent Variable
Re-infarction and death will be de ned as the following: Re-infarction will be de ned based on the 4 th universal de nition of myocardial infarction, and is de ned as an acute myocardial infarction that reoccurs within 28 days of the incident myocardial infarction [20].
Re-infarction is diagnosed based on new ECG changes (e.g. ST-elevation, new pathological Q waves, etc.), ischemic signs and symptoms, and a >20% increase between cardiac troponin measurements indicating myocardial necrosis [20].
Death will be de ned as a composite variable as either cardiovascular death or all-cause death. Cardiovascular death will be de ned according to the 10 th revision of International Classi cation of Disease codes I11 or I20-I25, or as death due to fatal or non-fatal myocardial infarction [22]. All-cause death will be de ned as death due to any cause so forth recorded on death certi cates, medical records, or national registries. Death will be a composite variable but we will perform a sub-group analysis between the two types of death if enough studies are collected.
If there is a difference in the de nition in re-infarction or death in individual studies, we will record this difference as this may introduce heterogeneity. We will also record differences in follow-up whether in the same publication or across several publications, and conduct a sensitivity analysis to investigate potential bias.

Moderator Variables
Age, sex, and race are important potential moderating variables which may in uence the presenting ECG [23,24]. Thus, we will collect information on the age, sex, and race distribution of the samples used in individual studies.

Covariates
The ECG is affected by a number of covariates which impact its interpretation and subsequently prognostic value for death and re-infarction. Such covariates include medications such as digoxin and antipsychotics, right and left bundle branch block, and left and right ventricular hypertrophy [25]. We will record these variables during data extraction as potential covariates for analysis.

Participants
The study population will be adults (>18 years) with UA/NSTEMI presented to the emergency department. No restrictions will be placed on participants' gender, ethnicity, or other demographic characteristics.
Since the aim of the study is to determine prognosis of characteristics on the ECG and re-infarction and death, known factors in uential such outcomes including age, sex, and race will be recorded and used as moderators in meta-analyses [23,24].

Inclusion and Exclusion Criteria
The inclusion criteria for this study will be: 1) full-text peer-reviewed publications; 2) English language; 3) adult (>18 years) patient with emergent UA/NSTEMI; 4) standard, resting ECG (12-lead or 15-lead) performed in the supine position in the emergency department and 5) reporting of hazard ratio (HR), odds ratio (OR) or risk ratio (RR) and the corresponding 95% con dence interval as the outcome measure or the data necessary to calculate these measures. To ensure validity, two reviewers (DJD and MGC) will independently adjudicate the diagnosis of UA/NSTEMI based on AHA/ACC guidelines [2]. We will only include papers which performed the ECG in the supine position to reduce the risk of misinterpretation related to positional effects which ultimately impact the sensitivity [26]. We will include studies that conducted serial ECG measurements which may improve the sensitivity of ECG characteristics due to a number of reasons described in the introduction [27]. Similarly, we will include papers that follow patients for more than the 28-day cutoff but focus on the rst 28-days for this review. Studies reporting on overlapping samples will only be included if they reported different characteristics and/or outcomes.
We will exclude studies which enrolled participants from either inpatient hospital units, outpatient clinics, or the general population to maintain focus on emergency medicine and rst medical contact. We will also exclude studies which performed ECGs greater than the standard 10-seconds such as continuous ECG monitoring because this is not the standard of care. There will be no limitation in terms of geographic region or racial background. The search period will be from the beginning of the computerization of the ECG, January 1 st , 1990 to June 1, 2020 [28].
For the meta-analysis portion, additional inclusion criteria will include a quality score of >5 on the Newcastle-Ottawa Quality Assessment Scale and a moderate rating on the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) criteria [29][30][31]. We applied this additional inclusion criteria to the meta-analysis to maintain the highest rigor in our quantitative results.

Data Sources, Search Terms, and Search Strategy
This literature review and meta-analysis will be based on systematic searches in multiple electronic literature databases, including Medline/PubMed, Web of Science, Embase, and CINAHL. Since ECG research appears in cardiovascular and emergency medicine journals, speci c searches to expand capture of relevant studies will be performed using the same key words in over 20 cardiology and emergency medicine journals including: Circulation, Journal of Electrocardiology, Annals of Noninvasive Electrocardiology, European Heart Journal, The American Journal of Cardiology, and American Journal of Emergency Medicine. Lastly, we will search ClinicalTrials.gov for potential grey literature. All journals and search terms are listed in Table 1. Systematic searches will be conducted by combining every possible combination of keywords. The medical librarian, co-author DHM, will be responsible for conducting searches in the electronic databases and ClinicalTrials.gov. The principal investigator DJD will be responsible for conducting searches in cardiovascular journals with the guidance of the medical librarian. Reference lists from included articles will be checked based on keywords in the title to identify any potentially eligible studies. This in-depth and librarian guided systematic procedure ensures a comprehensive and reproducible search strategy, and the inclusion of grey literature reduces the risk of selection and detection bias [32][33][34]. The search results will be exported to Endnote X9 (Clarivate Analytics, PA, USA). The librarian will save the search results in an Endnote le on an encrypted, frequently backed-up computer as a historical record.

Data Extraction
Following the search, all identi ed citations will be stored and assessed in EndNote X8. Next, duplicate articles will be removed. After removing all duplicates, the titles and abstracts will be screened against the inclusion and exclusion criteria. If necessary to determine inclusion, the full text will be assessed. Two reviewers (DJD and MGC) will independently assess each article to determine inclusion. Any disagreements that arise between the reviewers will be resolved through discussion and another content expert (PhD-prepared cardiac nurse) will be invited as a third reviewer to make the ultimate decision. Reasons for exclusion will be recorded and reported in the nal manuscript.
After deciding which articles to include, all data entry will be completed by the two reviewers (DJD and MGC) independently for each article. The two reviewers will use a standardized data extraction form to ensure consistent data retrieval of all variables from the included studies ( Table 2). The data extracted will include speci c details about the publication and authorship team, study population and demographics (e.g. age, sex, race), study design methods, type of ECG and number of leads, potential ECG covariates (e.g. medications, bundle branch blocks, etc.), and critical statistical ndings relevant to the purpose of this review. Importantly, we will also record information about the the measurement of speci c ECG characteristics, and the determination of re-infarction and death. We will also extract information on the follow-up of patients but for the primary analysis only focus on the rst 28-days. Similarly, if the study used serial ECG measurements we will extract information on each measurement but only use the most sensitive for this primary analysis. The data extraction process was piloted tested using 5 articles with an interrater reliability of 95% between the two reviewers. A third reviewer was not necessary during this pilot testing. If necessary, modi cations to the standardized data extraction form will be reported in detail in the full report. If required, we will contact the authors of included studies to request missing or additional data. We will record attempts to contact authors for missing or additional data. To ensure accuracy during this process, periodic data checking and entry will be conducted.

Assessment of Methodological Quality
In this systematic review we will use two different assessments of methodological quality: the Newcastle-Ottawa Quality Assessment Scale and the GRADE criteria. We will use two different assessments of methodological quality because the objectives of the two assessments signi cantly differ but are both relevant for this systematic review. The objective of the Newcastle-Ottawa Quality Assessment Scale is to evaluate the quality of individual case-control or cohort design studies. The objective of the GRADE criteria is for the systematic appraisal of research with the goal to advise evidence-based recommendations. The aims of this systematic review and meta-analysis will be two-part: to identify remaining gaps in clinical understanding of ECG which aligns with the Newcastle-Ottawa Quality Assessment Scale and to inform providers about the prognostic value of the ECG which t with the GRADE criteria.
The Newcastle-Ottawa Quality Assessment Scale was developed to assess the quality of non-randomized studies such as case-control and cohort studies [29]. The following characteristics will be assessed: (1) representativeness of the cohort; (2) selection of the non-exposed cohort; (3) ascertainment of exposure; (4) demonstration that outcome of interest was not present at the start of the study; (5) comparability of cohorts on the basis of the design or analysis; (6) assessment of outcomes; (7) follow-up period su ciently long for outcomes to occur; and (8) adequacy of follow-up of cohorts [29]. This scale ranges from 0 to 9 indicating that studies were graded as poor to good quality, and correlates to the Agency for Healthcare Research and Quality standards [29]. The two reviewers (DJD and MGC) will score each article independently using the scale. Afterwards, the two will discuss their independent evaluations and provide a justi cation. If a discrepancy between quality score arises, a third independent reviewer (a PhD-prepared cardiac registered nurse) will provide a score and the average of all three reviewer scores will be used to determine study inclusion in the meta-analysis section of this study. As previously noted, inclusion of a study in the meta-analysis will require an overall score of >5 which corresponds to good quality research [29]. Kappa (e.g. Kendall's tau) will be calculated to quantify the level of inter-rater agreement between the two or three reviewers.
GRADE is a recommended transparent framework for examining existing evidence in a systematic approach for making clinical practice recommendations [30,31]. The domains of GRADE include risk of bias, imprecision, inconsistency, indirectness, and publication bias [30,31]. We will use the GRADE handbook published by Cochrane to inform our evaluation of individual studies. The same protocol as described above will be followed.

Meta-Analytic Power Analysis
A random-effects meta-analytic power analysis was conducted to determine the necessary number of studies and study participants to answer the research question and achieve the speci c aims of this protocol [36]. Some have argued that a minimum number of studies to be included in a meta-analysis is two [36]. Assuming a small effect size (Cohen's d of 0.2), average number of participants per group (n=150 participants), and high study heterogeneity, a minimum of 1,050 study participants distributed across 7 individual studies will be necessary to achieve a type I and type II error rate of 5% and 10%, respectively [36]. A small effect size was assumed because individual ECG characteristics will be evaluated in this meta-analysis reducing the overall effect size. This proposal will target 12 individual studies for inclusion, yielding an estimated sample size of 1,800 subjects.

Meta-Analytic Statistical Approach
This meta-analysis will calculate relative risk as the main effect size estimate because relative risk is a cumulative and stable measure of hazard functions. Given our study has a de nitive and short 28-day endpoint, a relative risk is an appropriate measure of effect size. However, to reduce the risk of bias we will include studies reporting both odds ratio and hazard ratio in this meta-analysis. We will convert odds ratio to risk ratio as described by Zhang and Yu [37]. We will perform a log transformation and perform an inverse variance weighting to combine the relative risks and hazard ratios and the corresponding standard errors. This is possible because relative risk and hazard ratio are similar measures of effect. In studies which do not report either relative risk, odds ratio, or hazard ratio, we will extract the individual cell data and calculate the relative risk and 95% con dence interval when possible. After converting all measures to relative risk, we will perform a log transformation to satisfy the normality assumption and weight each study by the the inverse of their variance.
Heterogeneity will be computed using Cochran Q and I 2 statistic. An I 2 value of >50% will be considered to indicate signi cant heterogeneity; however, a random effects model will be used as the primary approach to due to the expected underlying methodological heterogeneity across studies [38,29].
Planned sub-group analyses will be conducted to assess differences across different patient groups. Subgroup analyses will be conducted between age (mean age <65 years vs. mean age >65 years), sex (mostly male >80% men vs. mostly female >80% women), and race (high racial diversity >40% non-white vs. low racial diversity <40% non-white). These moderators were chosen because they have been associated with worse UA/NSTEMI outcomes [23,24]. Dependent on the number of studies included in this review, other potential planned sub-group analysis will include: number of ECG leads (12-lead or 15lead), nal diagnosis (UA or NSTEMI), past medical history of UA/NSTEMI (yes or no), cause of death (cardiovascular death or all-cause death), time from presentation to ECG (<10 minutes or >10 minutes), and cardiac catheterization within 72 hours as recommended by AHA/ACC guidelines (yes or no) [2]. As recommended by the Cochrane handbook, a minimum number of studies to conduct these additional analyses will be 10 studies [38,39].
We will also conduct sensitivity analyses to assess the impact of different decisions on the results. First, we will change the model from random effects to xed effects so as long as I 2 value of <50%, Next, we will recalculate the relative risks by omitting one study at a time to assess for signi cant changes. We will assess study-level characteristics as potential sources of heterogeneity including: 1) study type (retrospective or prospective); 2) length of follow-up (<28 days or >29 days); 3) statistical measure (relative risk or hazard ratio; relative risk or odds ratio) and, 4) number of ECG leads (12-lead or 15-lead). We will also test the inclusion of less methodologically rigorous studies de ned as those with a quality score of <5 on the Newcastle-Ottawa Quality Assessment Scale and a low/very low rating on GRADE criteria (rigorous or not vigorous) [29][30][31]. Publication bias will be evaluated by inspecting funnel plots, and further tested with Begg's test and Egger's test [38,39].
Lastly, we will explore the heterogeneity across studies by performing a meta-regression analysis. We will perform this analysis because of the expected heterogeneity across studies in measurement with different individual characteristics on the ECG and the use of different covariates. The analysis will determine the effects of different de nitions for individual ECG characteristics, age, sex, race, length of follow-up, and listed covariates on the outcomes re-infarction and death. Each study will be weighted in the regression models using the inverse of its variance. Prior to conducting this analysis, we will ensure a minimum of 10 studies be included as recommended by Cochrane guidelines, and we will evaluate all regression-based assumptions of variable distribution, normality, and interactions [38,39]. All analyses will be performed using Meta-Essentials in Excel, and STATA 16 (STATA Software, TX) [40,41]. All statistical test will be two tailed, and statistical signi cance will be set at P=0.05.

Discussion
Herein, we have comprehensively described the protocol for a systematic review and meta-analysis that will evaluate and analyze characteristics on the ECG for re-infarction and death. We believe this systematic review and meta-analysis will inform providers on the prognostic signi cant of speci c characteristics on the ECG and result in more informed clinical decision in emergency medicine. Moreover, this review will identify remaining gaps in clinical understanding of ECG and explore both common and novel characteristics on the ECG.
Recently published studies report signi cant ndings for common (e.g. ST-segment changes) and novel (e.g. QRST angle) characteristics on the ECG prognostic of death and re-infarction with improved sensitivity [12,13,16]. Some characteristics of the ECG have a low sensitivity for a true infarction because the standard 10-second ECG is simply a snapshot of a very dynamic process [12,13,16]. Furthermore, the standard 12-lead ECG does not have posterior leads and can be easily misinterpreted [14,15]. Novel characteristics such as QRS-T angle on the 12-lead ECG have improved sensitivity and can overcome some of these other limitations [16]. For example, Strebel et al. (2018) reported QRS-T angle based on adjusted cutoff values based on the patient had an overall sensitivity of 69% and a speci city of 48% compared to common characteristics (e.g. ST-depression, T-wave inversion, and left bundle branch) which had an overall sensitivity of 45% and speci city of 86% [16]. Furthermore, Strebel et al. (2018) reported that QRS-T Angle predicted mortality (hazard ratio1.32 (95%CI [1.26, 1.40]) per 10°-unit increase [16]. Thus, the inclusion of novel characteristics on the ECG may overcome the low sensitivity and be prognostic of death and re-infarction, and a comprehensive review is therefore necessary to thorough evaluate all characteristics and inform clinical practice.
To be comprehensive in this review and draw the most evidence-based conclusions, we have described a through protocol. To be inclusive, we will not limit on the type of ECG characteristics and include 12-lead and 15-lead ECG as well as serial ECG measurements. To reduce selection bias, we include articles reporting risk ratio, odds ratio, and hazard ratio. We will perform two types of quality assessment to ensure the highest rigor for each of our objectives. We will conduct planned sub-group analyses across age, sex, and race because females and minority races have poorer outcomes after UA/NSTEMI [23,24].
By addressing these key points, we make the review make comprehensive and better able to achieve its objectives.
As outlined in this protocol, this thorough review will achieve its two-fold aims: to inform providers about the prognostic value of characteristics on the ECG, and to identify remaining gaps in clinical understanding of ECG.

Potential Limitations
There are two limitations to our protocol. First, we only include full-text peer reviewed published articles and will exclude other types of scholarly works such as presentation abstracts. Although some researchers have encouraged the inclusion of other scholarly works, the inclusion of such data can introduce bias [34,35]. In our review we will only include peer reviewed published studies but have recruited a medical librarian to improve the robustness and quality of the search [32,33]. Furthermore, we will assess for publication bias by inspecting funnel plots and performing Begg's test and Egger's test. Secondly, our review will include risk ratio, odds ratio, and hazard ratio which may introduce methodological error. We will perform additional analyses clustering studies based on whether they reported a risk ratio, odds ratio, or hazard ratio to detect potential differences. If differences arise, we will change the analysis to a time-to-event outcome and convert all measures to hazard ratios which may be a more stable measure [42]. We will use the well-cited method proposed by Tierney et al [42].

Protocol amendments
If the present protocol is substantially amended after an initiation that may impact on the conduct of the study (including eligibility criteria, study objectives, study design, study procedures, and analysis), then this amendment will be agreed upon by all collaborators prior to the implementation and will be documented in a note to a later publication or a report under the section titled "Differences between protocol and review".

Dissemination
The results of this review will be submitted for peer-reviewed publication and will be presented at relevant cardiology conferences. The project team has commenced searching relevant studies in the relevant databases. This review is expected to be complete by June 2021.

Consent for Publication
Not applicable. Data and materials are available for reviewers upon request.

Availability of Data and Materials
The datasets created and analyzed during the current study will be available from the corresponding author upon reasonable request.

Competing Interests
The authors declare no competing interests.
Funding DJD received the following funding for this review during his doctoral study: Sigma Theta Tau International Honor Society of Nursing Research Grant. The funder had no role in the study design; collections, analysis, or, interpretation of the data; writing of the report; or the decision to submit the ndings for publication.

Authors' Contributions
DJD is the principal investigator and responsible for conceiving the review, designing search strategy, modifying data extraction tool, selecting the appropriate tool for quality appraisal, conducting the journalspeci c searches, and drafting the protocol. He is the guarantor of this review, and initiated the publication of this protocol. DHM is the librarian responsible for re ning the search strategy, conducting the database searches, initially designing the data extraction tool, and providing librarian support. MGC is the senior investigator who provided content expertise on the topic, study assessment and appraisal, and reviewed the methodology. All authors read, reviewed, edited, and approved the nal manuscript. cience TS= ("emergency service*" OR "emergency room" OR emergency department* OR "emergency nurs*" OR emergency medicine OR triage OR "cardiovascular nurs*") TS=("myocardial infarction" OR "Non-ST elevated Myocardial infarction" OR "myocardial ischemia" OR "acute coronary syndrome" OR "unstable angina" OR " Angina Pectoris" OR "coronary artery disease" OR "coronary vessels" OR "coronary circulation" OR " atherosclerosis" OR "chest pain*" OR "coronary artery" OR "UA/NSTEMI" OR "re-infarction" OR "reinfarction") TS=("12 lead ECG" OR "15 lead ECG" OR "12 lead electrocardiogram" OR "15 lead electrocardiogram" OR "twelve lead ECG" OR "fifteen lead ECG" OR "twelve lead electrocardiogram" OR "fifteen electrocardiogram" OR "electrocardiogram" OR "electrocardiography" OR "ECG" OR "EKG" OR "diagnostic test*" OR "diagnostic measure*" OR "diagnostic procedure*" OR "diagnostic techniques") TS=( "death" OR "death" OR "mortality" OR "cause of death" OR "fatal outcome" OR "died" OR "die" OR "fatality" OR "fatal") TS=("sensitivity and specificity" OR "prognosis" OR "risk ratio" OR "risk" OR "odds ratio" OR "hazard ratio" OR "hazard" "probability" OR "harm reduction" OR "population*  Syndrome") OR "non-st-segment-elevation acute coronary syndrome" OR (MH "Coronary Arteriosclerosis") OR AB "chest pains" OR "atherosclerosis" OR "coronary arteries" OR "coronary circulation" OR "heart infarction" OR 're-infarction" OR "reinfarction" OR heart muscle ischemia" OR "heart muscle revascularization" OR "unstable Angina Pectoris" OR "coronary blood vessel" AND 3 (MH "Electrocardiography+") OR AB "electrocardiogram" OR "ecg" OR "ekg" OR "12 lead electrocardiogram" OR "15 lead electrocardiogram" OR "12 lead ecg" OR "15 lead ecg" OR "twelve lead ecg" OR "fifteen lead ecg" OR "twelve lead electrocardiogram" OR "fifteen lead electrocardiogram" AND 4 (MH "Death+") OR (MH "Fatal Outcome") OR (MH "Cause of Death") OR (MH "Mortality+") AND 5 (MH "Sensitivity and Specificity") OR (MH "Prognosis+") OR (MH "Odds Ratio") OR (MH "Harm Reduction") OR AB ""risk ratio" OR "risk" OR "hazard ratio" OR "hazard" OR "probability" OR "population at risk" 1 AND 2 AND 3 AND 4 AND 5 ASA Journals "ECG OR EKG OR Electrocardiogram" AND "Non-ST Elevation Myocardial Infarction OR Unstable Angina" AND "Risk Stratification OR Risk Management" AND ["Patient Outcomes" OR "Death" OR "Mortality" OR "Re-infarction" OR "Reinfarction"]