Archives of Academic Emergency Medicine. 2023; 11(1): e25 REV I EW ART I C L E Prognostic Value of The Leuko-Glycemic Index in Acute Myocardial Infarction; a Systematic Review and Meta- Analysis Roxana Sadeghi1,2, Shayan Roshdi Dizaji3, Mohammadhossein Vazirizadeh-Mahabadi3, Arash Sarveazad4,5∗, Seyed Ali Forouzannia3 † 1. Prevention of Cardiovascular Disease Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran. 2. School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran. 3. Physiology Research Center, Iran University of Medical Sciences, Tehran, Iran. 4. Colorectal Research Center, Iran University of Medical Sciences, Tehran, Iran. 5. Nursing Care Research Center, Iran University of Medical Sciences, Tehran, Iran. Received: January 2023; Accepted: February 2023; Published online: 1 March 2023 Abstract: Introduction: In recent years, studies have provided evidence on the prognostic value of the leuko-glycemic index (LGI) in acute myocardial infarction (MI), but there is a lack of consensus. In addition, various reported cut-offs for LGI have raised concern regarding its clinical applicability. So, to conclude, through this systematic review and meta-analysis, we aimed to investigate all available evidence on the prognostic value of LGI in acute MI. Methods: Two independent researchers summarized records available in the four main databases of Medline (Via PubMed), Embase, Scopus, and Web of Science until 15 Sep 2022. Articles studying the prognostic value of the LGI in acute MI were included. Finally, sensitivity, specificity, prognostic odds ratio, and the area under the curve (AUC) for LGI were analyzed and reported. Results: Eleven articles were included (3701 patients, 72.1% male). Based on the analyses, AUC, sensitivity, and speci- ficity for LGI in prediction of mortality following acute MI were 0.77 (95% CI: 0.73 to 0.80), 0.75 (95% CI: 0.62 to 0.84), and 0.66 (95% CI: 0.51 to 0.78), respectively. Positive and negative post-test probability of LGI in prediction of mortality were 21% and 5%, respectively. AUC, sensitivity, and specificity for LGI in prediction of major cardiac complications after acute MI were 0.81 (95% CI: 0.77 to 0.84), 0.84 (95% CI: 0.70 to 0.92), and 0.64 (95% CI: 0.49 to 0.84), respectively. Also, the Positive and negative post-test probability of LGI in this regard were 59% and 13%, respectively. Conclusion: Although the results demonstrated that the LGI could predict mortality and acute cardiac complication after MI, the low post-test probability of LGI in risk stratification of patients raises questions regarding its applicability. Nevertheless, as most of the available studies have been conducted in the Latino/Hispanic population, further evidence is warranted to generalize the validity of this tool to other racial populations. Keywords: Glycemic index; prognosis; acute coronary syndrome; myocardial ischemia; death; myocardial infarction Cite this article as: Sadeghi R, Roshdi Dizaji S, Vazirizadeh-Mahabadi M, Sarveazad A, Forouzannia SA. Prognostic Value of The Leuko- Glycemic Index in Acute Myocardial Infarction; a Systematic Review and Meta-Analysis. Arch Acad Emerg Med. 2023; 11(1): e25. https://doi.org/10.22037/aaem.v11i1.1915. ∗Corresponding Author: Arash Sarveazad, Colorectal Research Center, Rasool-e-Akram Hospital, Nyayesh St., Satarkhan St., Tehran, Iran. Email: arashsarveazad@gmail.com, ORCID: https://orcid.org/0000-0001-9273-1940. † Corresponding Author: Seyed Ali Forouzannia, Physiology Research Center, Hemmat Highway, P.O Box: 14665-354, Tehran, Iran. Email: s.ali.forouzannia@gmail.com, ORCID: https://orcid.org/0000-0003-1371- 7820. 1. Introduction Cardiovascular disease stands as the leading cause of death worldwide. The latest estimates in 2019 revealed an inci- dence of 523 million cardiovascular events, accounting for more than 18 million deaths and causing 32% of mortalities, globally. More than 75% of cardiovascular mortality is re- ported in middle- and low-income countries, with myocar- dial infarction (MI) being the etiology in about half of cases (1, 2). Identifying high-risk patients with poor prognoses suffering This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: https://journals.sbmu.ac.ir/aaem/index.php/AAEM/index R. Sadeghi et al. 2 from ischemic heart disease can assist physicians in pro- viding the most appropriate care and implementing preven- tive measures (3, 4). Utilizing blood biomarkers and deci- sion tools has been demonstrated to be promising in the risk stratification of patients (5-10). The temporal profile of inflammatory markers released as the primary systemic response to ischemic heart disease can be helpful in diag- nosing and estimating the severity of the ischemic injury. In this regard, multiple studies have revealed that increased concentration of specific inflammatory biomarkers is asso- ciated with the outcome of patients following acute MI (11- 13). However, low specificity, high cost, and unavailability of these biomarkers in some settings, hinder their clinical ap- plicability. In 2010, Quiroga Castro et al. introduced the leuko-glycemic index (LGI) as a prognostic model for acute MI (14). Syn- thesized through multiplying blood glucose level by leuko- cyte count, the LGI gained popularity for risk stratification of MI patients (15-17). The simplicity of calculation and rou- tine measurement of involved variables on admission among MI patients made the leuko-glycemic index an accessible and easily interpretable test with no significant costs for patients and health systems. Although, in recent years, studies have been conducted to validate the prognostic value of LGI among acute MI patients, there is still a lack of consensus (15-19). Furthermore, the di- versity of reported cut-offs among studies results in difficulty and uncertainty in the clinical use of this index. So, intend- ing to determine the prognostic value of this index in acute MI patients, we ran a systematic review and meta-analysis of all available studies in the literature. 2. Methods 2.1. Study design The present systematic review and meta-analysis compre- hensively explored all available studies on the prognostic value of the LGI among acute MI patients. Based on the study aims, the PICO has been defined as follows: P (population): patients with acute myocardial infarction I (intervention): the leuko-glycemic Index C (comparison): comparison with the non-outcome group O (outcome): mortality and major cardiac complications The protocol of the current meta-analysis was registered in the online management systems of research project for Shahid Beheshti University of Medical Science. The local ethics committee approved the protocol of the current meta- analysis (IR.SBMU.RETECH.REC.1401.533). 2.2. Search strategy In the beginning, relevant keywords were selected by experts in this field. Emtree and MeSH databases were extensively explored to find synonyms and other keywords. In addi- tion, the title and abstract of related articles were screened to explore further keywords and synonyms. Ultimately, us- ing the acquired keywords, a comprehensive search in on- line databases of Medline (via PubMed), Embase, Scopus, and Web of Science was conducted until Sep 15, 2022. Be- sides the systematic search, a manual search was performed on Google, Google Scholar, and Semantic Scholar search en- gines for preprints and other probable records not found dur- ing the systematic search. We didn’t apply any language re- strictions for selecting studies. The search queries of all ex- plored databases are provided in supplementary material 1. 2.3. Selection criteria Inclusion criteria consisted of human studies on prognos- tic value of LGI in acute MI patients, published in peer- reviewed journals, which calculated the leuko-glycemic in- dex for risk stratification. Studies on patients with other chief complaints rather than acute MI such as heart failure and COVID-19, reporting data or patients undergoing surgical in- terventions such as coronary artery bypass graft (CABG) and other cardiac surgeries, studies without primary outcome measurements or existence of the outcomes at baseline were excluded. The other exclusion criteria were animal studies, duplicated studies, retracted or withdrawn studies, reviews, and case reports. 2.4. Screening and data collection Records collected through systematic and manual searches were exported to Endnote software version 19.0 (Clarivate Analytics, Philadelphia, PA, USA), and duplicates were re- moved. Two independent reviewers screened the titles and abstracts of studies and retrieved the full texts of possibly related ar- ticles. Then, based on the predefined inclusion and exclu- sion criteria, eligible articles were included in the present study. Reviewer disagreements were addressed through dis- cussion and consultations with a third expert. Reporting data on study characteristics (first author name, publication and study year, country), type of study, sample size, age and gen- der distribution, reported outcomes, the timing of blood glu- cose and leukocyte measurements, reported cut-offs for the LGI, prognostic value indicators like sensitivity, specificity, and false and true positives and negatives (FP, TP, FN, TN) were extracted. Before the study initiation, we considered collecting odds ratio (OR), hazard ratio (HR), relative risk (RR), and the area under the curve (AUC) of LGI in prognosti- cation of acute MI in patients. However, we didn’t enter these values in our meta-analysis due to few studies reporting the above data and the inability to do pooled analysis on HR, OR, and RR of included studies. This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: https://journals.sbmu.ac.ir/aaem/index.php/AAEM/index 3 Archives of Academic Emergency Medicine. 2023; 11(1): e25 Table 1: Characteristics of included articles Study Data Study design Language Sam- ple size Mean age Male (n) Timing of LGI (hrs) Patients setting Outcome Cut off of LGI TP TN FP FN Cuesta- Mero, 2021, Ecuador 2015 to 2016 PCS Spanish 205 62.99± 12.2 142 24 ST- and non-ST- elevated MI In-hospital mortality 851.6 23 116 65 1 In-hospital MCC (cardiac arrest, HF, cardiogenic shock, severe dysrhythmia, re-MI, ventricular thrombus, angina) 656.8 117 42 17 6 ST- and non-ST- elevated MI (all pa- tients) 30-day mortality 1443 16 19 2 3 Diaz Ben- itez, 2016, Cuba 2012 to 2013 Cross Spanish 142 68.2± 10.3 83 24 ST- and non-ST- elevated MI (non- diabetic patients) 30-day MCC 1443 28 56 17 1 ST- and non-ST- elevated MI (diabetic patients) 30-day MCC 1443 16 19 2 3 In-hospital mortality 738 23 53 329 0 In-hospital mortality 975 17 184 198 6 Hirschson Prado, 2014, Ar- gentina 2011 PCS English 405 61±12 348 8 ST-elevated MI In-hospital mortality 1401 13 301 81 10 In-hospital MCC (Cardiac death and HF) 738 50 53 302 0 In-hospital MCC (Cardiac death and HF) 975 40 180 175 10 In-hospital MCC (Cardiac death and HF) 1401 29 290 65 21 Leon-Aliz, 2014, Cuba 2009 to 2010 RCS Spanish 128 68± 11.5 96 24 ST-elevated MI In-hospital mortality 1158 11 90 24 3 In-hospital MCC (cardiac arrest, HF, cardiogenic shock, severe dysrhythmia, re-MI, ventricular thrombus, angina) 1158 35 53 24 16 Martínez García, 2021, Cuba 2013 to 2020 PCS Spanish 507 68± 11.7 347 24 ST-elevated MI In-hospital MCC (cardiac arrest, HF, cardiogenic shock, severe dysrhythmia, re-MI, ventricular thrombus, angina) 1188 160 130 149 68 This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: https://journals.sbmu.ac.ir/aaem/index.php/AAEM/index R. Sadeghi et al. 4 Table 1: Characteristics of included articles Study Data Study design Language Sam- ple size Mean age Male (n) Timing of LGI (hrs) Patients setting Outcome Cut off of LGI TP TN FP FN Martínez Saldaña, 2018, Mex- ico 2016 to 2017 Cross Spanish 34 59.7± 13.2 29 0 ST- and non-ST- elevated MI 3-day mortality 1601 4 10 16 4 Padilla- Cueto, 2019, Cuba 2011 to 2015 Cross English 344 68 (58- 76) 226 0 ST-elevated MI One-year mortality 2200 44 219 37 44 Qi, 2022, China 214 to 2019 PCS English 1256 67 (53 to 78) 930 0 ST- and non-ST- elevated MI In-hospital mortality 1402 51 590 263 26 In-hospital mortality 3593 15 256 42 13 Quiroga Castro-a, 2010, Ar- gentina 2006 to 2007 PCS Spanish 101 60 85 0 ST-elevated MI In-hospital MCC (Cardiac death and HF) 1600 25 50 16 10 Quiroga Castro-b, 2010, Ar- gentina 2007 to 2009 Cross English 155 NR NR 0 ST-elevated MI In-hospital MCC (Cardiac death and HF) 1600 26 73 46 10 Rodríguez Jiménez, 2019, Cuba 2012 to 2015 PCS Spanish 424 67.8±14.5271 4 ST-elevated MI In-hospital mortality 2122 44 220 147 13 Cross: Cross-sectional; FN: False negative; FP: False positive; HF: Heart failure; LGI: Leuko-glycemic index; MCC: Major cardiac complications; MI: Myocardial infarction; PCS: Prospective cohort study; RCS: Retrospective cohort study ST: ST segment; TN: True negative; TP: True positive Table 2: Risk of bias assessment of included studies Author Risk of bias Applicability Overall Patient selection Index test Reference standard Flow and timing Patient selection Index test Reference standard Cuesta-Mero, 2021 Low Low Low Low Low Low Low Low risk Diaz Benitez, 2016 Low Low Unclear Low Low Low Unclear Some concern Hirschson Prado, 2014 Low Low Low Low Low Low Low Low risk Leon-Aliz; 2014 Unclear Low Low Low Low Low Low Low risk Martínez García, 2021 Low Low Low Low Low Low Low Low risk Martínez Saldaña, 2018 Unclear Low Unclear Low Low Low Low Some concern Padilla-Cueto, 2019 Unclear Low Low Low Low Low Low Low risk Qi, 2022, China Low Low Low Low Low Low Low Low risk Quiroga Castro-a, 2010 Low Low Low Low Low Low Low Low risk Quiroga Castro-b, 2010 Low Low Low Unclear Low Low Low Low risk Rodríguez Jiménez, 2019 Low Low Low Low Low Low Low Low risk 2.5. Outcomes The sought outcomes were mortality and major cardiac com- plications following acute MI. The definition of major cardiac complications varied upon studies and included cardiac ar- rest, cardiac death, heart failure, cardiogenic shock, severe dysrhythmia, re-MI, ventricular thrombus, and angina. 2.6. Risk of bias assessment Since all the included studies were observational and our aim was to investigate the prognostic value of the LGI using sen- sitivity and specificity, the risk of bias was assessed using the QUADAS-2 tool (20). Two reviewers independently evaluated the studies based on the items provided in the QUADAS-2 questionnaire and scored them as low, high, or unclear on each item. This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: https://journals.sbmu.ac.ir/aaem/index.php/AAEM/index 5 Archives of Academic Emergency Medicine. 2023; 11(1): e25 2.7. Level of evidence The level of evidence was determined utilizing the Grading of Recommendations, Assessment, Development, and Eval- uations (GRADE) framework (21). Through evaluation of the risk of bias, imprecision, inconsistency, indirectness, and publication bias as the items provided in the GRADE frame- work, the level of evidence was determined for each out- come. 2.8. Statistical Analysis The extracted data were analyzed in STATA 14.0 statistical program (Stata Corp, College Station, TX, USA). The entered data in TP, TN, FP, and FN format were analyzed using the “midas” command. All analyses were outcome-based. The prognostic value of the LGI in predicting mortality and major cardiac complications was evaluated by reporting the sensi- tivity, specificity, positive and negative likelihood ratio, and prognostic odds ratio with a 95% confidence interval. To as- sess the heterogeneity among included studies, the I2 statis- tic and Q-test were used. Publication bias was evaluated us- ing Deek’s funnel plot test. Ultimately, the Fagan plot dia- gram was depictured for the LGI in predicting mortality and major cardiac complications to assess the post-test probabil- ity and its clinical importance. We estimated pre-test proba- bility based on pooled prevalence of mortality or major car- diac complication among included studies. 3. Results 3.1. Article selection A systematic search in four databases yielded 1073 non- duplicated records. Following the primary screening of ti- tle and abstracts, 30 full-text articles were retrieved. In the second step, 19 articles were excluded, and the remaining 11 were selected as eligible for the meta-analysis (15, 16, 19, 22- 28). Moreover, in a manual search, 13 potentially relevant manuscript were found. All these 13 papers were theses and did not provide sufficient data. For example, some of the 13 theses had not reported data on acute MI, not measured the primary endpoints, and not reported the required data con- cerning our study aims. The reasons for excluding articles are provided in figure 1. 3.2. Summary of included studies Among 11 eligible studies, there were 6 prospective and 1 ret- rospective cohort studies, along with 4 cross-sectional stud- ies. There were 7 studies in Spanish, and the remaining 4 were published in English. These studies included 3701 pa- tients suffering from acute MI. 72.1% of enrolled patients were male. The mean age of recruited patients ranged from 59.7 years to 68.2 years. In all included studies, the LGI mea- surement was performed within the first 24 hours following symptoms and prior to initiation of treatments. Mortality was reported in 9 studies, and the combination of major car- diac complications was present in 7 studies. The determined cut-offs for the LGI varied from 656.6 to 3593 among studies. Most of the studies reported a cut-off between 1000 to 2000. The characteristics of all eligible studies have been presented in Table 1. 3.3. Value of the LGI in prediction of mortality Analysis showed that the area under the receiver operating characteristic (ROC) curve for the LGI in the prediction of mortality following acute MI was 0.77 (95% CI: 0.73 to 0.80), implicating the good value of this index (Figure 2). The sen- sitivity and specificity of the LGI in predicting mortality were 0.75 (95% CI: 0.62 to 0.84) and 0.66 (95% CI: 0.51 to 0.78), re- spectively (Supplementary figure 1). Positive and negative likelihood ratios (positive LR and neg- ative LR) and prognostic odds ratio were 2.20 (95% CI: 1.59 to 3.04), 0.38 (95% CI: 0.27 to 0.53), and 5.76 (95% CI: 3.60 to 9.22), respectively (Supplementary figure 2 and Figure 3). Drawn Fagan plot, based on the assumption of pre-test prob- ability of 11% for mortality derived from the studies, revealed that the LGI’s positive and negative post-test probability were 21% and 5%, respectively (Figure 4). 3.4. Value of the LGI in the prediction of major cardiac complications In this section, 10 studies were included in the analysis since one study reported all-cause mortality as outcome. Our Anal- yses demonstrated that the area under the ROC curve for the LGI in the prediction of major cardiac complications follow- ing acute MI was 0.81 (95% CI: 0.77 to 0.84), indicating an ac- ceptable prognostic value for this index (Figure 2). The sen- sitivity and specificity of the LGI in predicting major cardiac complications were 0.84 (95% CI: 0.70 to 0.92) and 0.64 (95% CI: 0.49 to 0.84), respectively (Supplementary figure 3). Posi- tive LR, Negative LR and prognostic odds ratio were 2.34 (95% CI: 2.21 to 3.34), 0.25 (95% CI: 0.13 to 0.45) and 9.52 (95% CI: 4.48 to 20.26), respectively (Supplementary figure 4 and Fig- ure 5). Drawn Fagan plot based on the assumption of pre-test prob- ability of 38% for mortality derived from the studies indicated that the LGI’s positive and negative post-test probability were 59% and 13%, respectively (Figure 4). 3.5. Risk of bias assessment Quality assessment of included studies showed that 3 studies had unclear risk of bias regarding patient selection because of their retrospective nature. There was no clear definition of the reference standard in 2 studies, which made their status unclear in this item. This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: https://journals.sbmu.ac.ir/aaem/index.php/AAEM/index R. Sadeghi et al. 6 Figure 1: Flow diagram of the current study. CABG: Coronary artery bypass graft; MCC: Major cardiac complications. Figure 2: Summary receiver operating characteristics (SROC) curves of leuko-glycemic index in predication of mortality and major cardiac complications following acute myocardial infarction. AUC: area under the curve; SPEC: specificity; SENS: sensitivity. Moreover, flow and timing could not be deduced from one study, causing it to be regarded as unclear. Finally, one study had not presented adequate data about the applicability of reference standards, which is thus considered unclear. In all remaining items, studies were low-risk. The overall risk of bias assessment was concluded as low in 9 studies and some concern in 2 studies (Table 2). This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: https://journals.sbmu.ac.ir/aaem/index.php/AAEM/index 7 Archives of Academic Emergency Medicine. 2023; 11(1): e25 Figure 3: Odds ratio of leuko-glycemic index in predication of mortality following acute myocardial infarction. CI: confidence interval. Table 3: Certainty of evidence based on GRADE framework Outcome Sample size Prognostic odds ratio Risk of bias Imprecision Inconsistency (I2) Indirectness Publication bias Judgment and level of evidence Mortality 3646 5.76 (95% CI: 3.60, 9.22) Not serious Not serious Serious Not serious Not present Moderate: Rated down 1 point • Presence of serious inconsistency Rated up 2 points • Very large magnitude of effect* Major cardiac complica- tions 2430 9.52 (95% CI: 4.48, 20.26) Not serious Not serious Serious Not serious Likely Low: Rated down 2 points • Presence of serious inconsistency • Possible publication bias Rated up 2 points • Very large magnitude of effect* *, according to prognostic odds ratio. GRADE: Grading of Recommendations, Assessment, Development, and Evaluations; CI: confidence interval. 3.6. Publication bias Deek’s funnel plot revealed no publication bias among stud- ies reporting the value of the LGI in predicting mortality fol- lowing acute MI (p=0.48). However, there was evidence of publication bias in articles that surveyed major cardiac com- plications (p=0.03) (Supplementary figure 5). This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: https://journals.sbmu.ac.ir/aaem/index.php/AAEM/index R. Sadeghi et al. 8 Figure 4: Fagan plots of leuko-glycemic index in predication of mortality and major cardiac complications following acute myocardial infarc- tion. LR: Likelihood ratio; Prob: Probability; Post-Prob-Pos: Positive post-test probability; Post-Prob-Neg: Negative post-test probability. 3.7. Certainty of evidence There was serious inconsistency in assessment of the prog- nostic value of LGI in prediction of mortality, while a very large magnitude of effect was observed (prognostic odds ra- tio=5.76). Therefore, level of evidence was graded as moder- ate. Presence of serious inconsistency and possible publication bias rated down certainty of evidence two points in assess- ment of prognostic value of LGI in predicting major cardiac complication. However, a very large magnitude of effect was observed (prognostic odds ratio=9.52). Therefore, the level of evidence was deemed low (Table 3). 4. Discussion Previous studies implicated a close link between admission hyperglycemia, regardless of diabetic status, and the short- term and long-term mortality among patients suffering from myocardial infarction (29, 30). Similarly, a greater leukocyte count on admission, which is representative of inflamma- tion in the body, was associated with poor outcomes in ST segment elevation MI (STEMI) patients (31). With the back- bone of mentioned findings, in 2010, Quiroga Castro et al. in- troduced the combination of two variables of blood glucose and leukocyte count as the leuko-glycemic index for pre- dicting mortality and complications among MI patients (14). Since then, multiple studies have been conducted to survey the predictive value of the leuko-glycemic index. Hence, for the first time, we conducted a systematic review and meta- analysis to assess all studies available on this subject. The present study demonstrated that the leuko-glycemic in- dex has favorable sensitivity and accepted specificity in pre- dicting in-hospital mortality among MI patients, irrespective of diabetes status. These results should be interpreted cau- tiously since the leuko-glycemic index is subject to limita- tions. Some studies demonstrated a difference in the predic- tive value of the leuko-glycemic index in diabetic and non- diabetic patients (15). Even though diabetes, per se, is as- This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: https://journals.sbmu.ac.ir/aaem/index.php/AAEM/index 9 Archives of Academic Emergency Medicine. 2023; 11(1): e25 Figure 5: Odds ratio of leuko-glycemic index in predication of major cardiac complications following acute myocardial infarction. CI: confi- dence interval. sociated with a higher burden of cardiovascular morbidity and mortality, it would be reasonable to use different cutoff points as baseline average blood glucose and its alteration in diabetic patients differ from nondiabetic patients. Neverthe- less, the detrimental effect of hyperglycemia, regardless of di- abetic status, persists even in response to treatment (32). According to the estimated results, the LGI had 84% sensi- tivity and 64% specificity in predicting major cardiac com- plications in patients suffering from myocardial infarction. But based on the pre-test and post-test probability, the leuko-glycemic index does not significantly impact clinical decision-making. In a systematic review and meta-analysis, admission hyperglycemia was associated with a higher risk of overall arrhythmias, which is the cause of early complica- tions following MI in diabetic and nondiabetic patients (35). Blood glucose levels and inflammatory markers are tethered together. Hyperglycemia is associated with higher concen- trations of inflammatory cytokines that play a significant role in the secondary perpetuation of myocardial damage after MI (16, 19, 34). Inflammatory markers’ increase after MI is linked to hypercoagulability, myocardial remodeling, and ox- idative stress, culminating in adverse clinical events (35). We acknowledge the presence of limitations in our study. Pri- mary endpoints of major cardiac complications and their follow-up periods varied among studies, and there was a lack of consensus. This heterogeneity in the definition of mea- sured outcomes contributes to the wide range of reported cutoff points among referred studies. The majority of studies included in the meta-analysis have a small sample size, with a maximum of 1256 patients in the most recent one. During our investigations, we found a sparsity of studies comparing the leuko-glycemic index with other prognostic indicators such as the TIMI, HEART, and GRACE scores. In addition, most of the studies found in the literature were conducted on the Hispanic/Latino popula- tions, which raised concerns about geographical and ethnic bias. Further studies with robust methodology and racial di- versity are warranted to address these limitations. This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: https://journals.sbmu.ac.ir/aaem/index.php/AAEM/index R. Sadeghi et al. 10 5. Conclusion In the absence of advanced diagnostic modalities, the leuko- glycemic index could be an assistive tool for predicting in- hospital mortality of MI patients due to its availability, rou- tine measurement, and low cost. However, the calcula- tion of the leuko-glycemic index would not be clinically im- pressive regarding the major cardiac complications after MI. These conclusions are made on studies mainly investigating Latino/Hispanic populations, and their applicability to other populations is under question. Future studies are required to compare the other well-known predictive scores with the leuko-glycemic index. 6. Declarations 6.1. Acknowledgments None. 6.2. Conflict of interest The authors declare that there is no conflict of interest. 6.3. 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Sadeghi et al. 12 Supplementary material 1: Full search syntax of the current study PubMed 1- "Glycemic index"[MeSH Terms] OR ("leuko*"[All Fields] AND "glycemic"[Title/Abstract]) OR "leuko-glycemic"[Title/Abstract] OR "leuko-glycemic"[Title/Abstract] OR "Leukoglycemic"[Title/Abstract] 2- “Myocardial Ischemia”[MeSH Terms] OR “Acute Coronary Syndrome”[MeSH Terms] OR “Angina Pectoris”[MeSH Terms] OR “Angina, Stable”[MeSH Terms] OR “Angina, Unstable”[MeSH Terms] OR “Coronary Artery Disease”[MeSH Terms] OR “Coro- nary Occlusion”[MeSH Terms] OR “Coronary Stenosis”[MeSH Terms] OR “Coronary Thrombosis”[MeSH Terms] OR “Coronary Va- sospasm”[MeSH Terms] OR “Myocardial Infarction”[MeSH Terms] OR “Anterior Wall Myocardial Infarction”[MeSH Terms] OR “In- ferior Wall Myocardial Infarction”[MeSH Terms] OR “Non-ST Elevated Myocardial Infarction”[MeSH Terms] OR “ST Elevation Myocardial Infarction”[MeSH Terms] OR “Myocardial Reperfusion Injury”[MeSH Terms] OR “Myocardial Ischemia”[Title/Abstract] OR “Ischemic Heart Disease”[Title/Abstract] OR “Acute Coronary Syndrome”[Title/Abstract] OR “Unstable Angina”[Title/Abstract] OR “Angina Pectoris”[Title/Abstract] OR “Angina Pectori”[Title/Abstract] OR “Preinfarction Angina”[Title/Abstract] OR “Coronary Heart Disease”[Title/Abstract] OR “Coronary Artery Disease”[Title/Abstract] OR “Coronary Arteriosclerosis”[Title/Abstract] OR “Coro- nary Atherosclerosis”[Title/Abstract] OR “Coronary Occlusion”[Title/Abstract] OR “Coronary Stenosis”[Title/Abstract] OR “Coro- nary Thrombosis”[Title/Abstract] OR “Coronary Vasospasm”[Title/Abstract] OR “Myocardial Infarction”[Title/Abstract] OR “Myocar- dial Infarct”[Title/Abstract] OR “Heart Attack”[Title/Abstract] OR “Myocardial Reperfusion Injury”[Title/Abstract] OR “Myocardial Is- chemic Reperfusion Injury”[Title/Abstract] OR “heart infarction”[Title/Abstract] OR “acute heart infarction”[Title/Abstract] OR “an- terior myocardial infarction”[Title/Abstract] OR “Dressler syndrome”[Title/Abstract] OR “heart muscle necrosis”[Title/Abstract] OR “inferior myocardial infarction”[Title/Abstract] OR “MINOCA”[Title/Abstract] OR “non ST segment elevation myocardial infarc- tion”[Title/Abstract] OR “posterior myocardial infarction”[Title/Abstract] OR “silent myocardial infarction”[Title/Abstract] OR “ST segment elevation myocardial infarction”[Title/Abstract] OR “acute coronary syndrome”[Title/Abstract] OR “non st segment eleva- tion acute coronary syndrome”[Title/Abstract] OR “acute coronary syndrome”[Title/Abstract] OR “angina pectoris”[Title/Abstract] OR “cardiac allograft vasculopathy”[Title/Abstract] OR “coronary artery atherosclerosis”[Title/Abstract] OR “coronary artery constric- tion”[Title/Abstract] OR “coronary artery obstruction”[Title/Abstract] OR “coronary artery thrombosis”[Title/Abstract] OR “coronary sub- clavian steal syndrome”[Title/Abstract] OR “heart infarction”[Title/Abstract] OR “ischemic cardiomyopathy”[Title/Abstract] OR “Kounis syndrome”[Title/Abstract] OR “myocardial hibernation”[Title/Abstract] OR “no reflow phenomenon”[Title/Abstract] OR “silent myocar- dial ischemia”[Title/Abstract] OR “takotsubo cardiomyopathy”[Title/Abstract] 3- #1 AND #2 Embase 1- ’glycemic index’/exp OR ’leuko*glycemic’:ab,ti OR ’leuko-glycemic’:ab,ti OR ’leukoglycemic’:ab,ti 2- ‘heart infarction’/exp OR ‘acute heart infarction’/exp OR ‘anterior myocardial infarction’/exp OR ‘Dressler syndrome’/exp OR ‘heart atrium infarction’/exp OR ‘heart infarction size’/exp OR ‘heart muscle necrosis’/exp OR ‘heart reinfarction’/exp OR ‘heart ventricle infarc- tion’/exp OR ‘impending heart infarction’/exp OR ‘inferior myocardial infarction’/exp OR ‘MINOCA’/exp OR ‘non ST segment elevation myocardial infarction’/exp OR ‘posterior myocardial infarction’/exp OR ‘silent myocardial infarction’/exp OR ‘ST segment elevation my- ocardial infarction’/exp OR ‘acute coronary syndrome’/exp OR ‘non st segment elevation acute coronary syndrome’/exp OR ‘acute coro- nary syndrome’/exp OR ‘angina pectoris’/exp OR ‘cardiac allograft vasculopathy’/exp OR ‘coronary artery atherosclerosis’/exp OR ‘coro- nary artery constriction’/exp OR ‘coronary artery obstruction’/exp OR ‘coronary artery thrombosis’/exp OR ‘coronary subclavian steal syn- drome’/exp OR ‘heart infarction’/exp OR ‘heart muscle ischemia’/exp OR ‘ischemic cardiomyopathy’/exp OR ‘Kounis syndrome’/exp OR ‘myocardial hibernation’/exp OR ‘no reflow phenomenon’/exp OR ‘silent myocardial ischemia’/exp OR ‘takotsubo cardiomyopathy’/exp OR ‘Myocardial Ischemia’:ab,ti OR ‘Ischemic Heart Disease’:ab,ti OR ‘Acute Coronary Syndrome’:ab,ti OR ‘Unstable Angina’:ab,ti OR ‘Angina Pectoris’:ab,ti OR ‘Angina Pectori’:ab,ti OR ‘Preinfarction Angina’:ab,ti OR ‘Preinfarction Anginas’:ab,ti OR ‘Coronary Heart Disease’:ab,ti OR ‘Coronary Artery Disease’:ab,ti OR ‘Coronary Arteriosclerosis’:ab,ti OR ‘Coronary Atherosclerosis’:ab,ti OR ‘Coronary Occlusion’:ab,ti OR ‘Coronary Stenosis’:ab,ti OR ‘Coronary Thrombosis’:ab,ti OR ‘Coronary Vasospasm’:ab,ti OR ‘Myocardial Infarction’:ab,ti OR ‘Myocardial Infarct’:ab,ti OR ‘Heart Attack’:ab,ti OR ‘Myocardial Reperfusion Injury’:ab,ti OR ‘Myocardial Ischemic Reperfusion Injury’:ab,ti OR ‘heart infarction’:ab,ti OR ‘acute heart infarction’:ab,ti OR ‘anterior myocardial infarction’:ab,ti OR ‘Dressler syndrome’:ab,ti OR ‘heart atrium in- farction’:ab,ti OR ‘heart infarction size’:ab,ti OR ‘heart muscle necrosis’:ab,ti OR ‘heart reinfarction’:ab,ti OR ‘heart ventricle infarction’:ab,ti OR ‘impending heart infarction’:ab,ti OR ‘inferior myocardial infarction’:ab,ti OR ‘MINOCA’:ab,ti OR ‘non ST segment elevation myocar- dial infarction’:ab,ti OR ‘posterior myocardial infarction’:ab,ti OR ‘silent myocardial infarction’:ab,ti OR ‘ST segment elevation myocar- dial infarction’:ab,ti OR ‘acute coronary syndrome’:ab,ti OR ‘non st segment elevation acute coronary syndrome’:ab,ti OR ‘acute coronary syndrome’:ab,ti OR ‘angina pectoris’:ab,ti OR ‘cardiac allograft vasculopathy’:ab,ti OR ‘coronary artery atherosclerosis’:ab,ti OR ‘coronary artery constriction’:ab,ti OR ‘coronary artery obstruction’:ab,ti OR ‘coronary artery thrombosis’:ab,ti OR ‘coronary subclavian steal syn- drome’:ab,ti OR ‘heart infarction’:ab,ti OR ‘heart muscle ischemia’:ab,ti OR ‘ischemic cardiomyopathy’:ab,ti OR ‘Kounis syndrome’:ab,ti OR ‘myocardial hibernation’:ab,ti OR ‘no reflow phenomenon’:ab,ti OR ‘silent myocardial ischemia’:ab,ti OR ‘takotsubo cardiomyopathy’:ab,ti 3- #1 AND #2 Scopus 1- TITLE-ABS-KEY(“glycemic index” OR “leuko*glycemic” OR “leuko-glycemic” OR “leukoglycemic”) 2- TITLE-ABS-KEY(“Myocardial Ischemia” OR “Ischemic Heart Disease” OR “Acute Coronary Syndrome” OR “Unstable Angina” OR “Angina Pectoris” OR “Angina Pectori” OR “Preinfarction Angina” OR “Preinfarction Anginas” OR “Coronary Heart Disease” OR “Coronary Artery Disease” OR “Coronary Arteriosclerosis” OR “Coronary Atherosclerosis” OR “Coronary Occlusion” OR “Coronary Stenosis” OR “Coronary Thrombosis” OR “Coronary Vasospasm” OR “Myocardial Infarction” OR “Myocardial Infarct” OR “Heart Attack” OR “Myocardial Reper- fusion Injury” OR “Myocardial Ischemic Reperfusion Injury” OR “heart infarction” OR “acute heart infarction” OR “anterior myocardial infarction” OR “Dressler syndrome” OR “heart atrium infarction” OR “heart infarction size” OR “heart muscle necrosis” OR “heart reinfarc- tion” OR “heart ventricle infarction” OR “impending heart infarction” OR “inferior myocardial infarction” OR “MINOCA” OR “non This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: https://journals.sbmu.ac.ir/aaem/index.php/AAEM/index 13 Archives of Academic Emergency Medicine. 2023; 11(1): e25 Supplementary material 1: Full search syntax of the current study ST segment elevation myocardial infarction” OR “posterior myocardial infarction” OR “silent myocardial infarction” OR “ST segment ele- vation myocardial infarction” OR “acute coronary syndrome” OR “non st segment elevation acute coronary syndrome” OR “acute coronary syndrome” OR “angina pectoris” OR “cardiac allograft vasculopathy” OR “coronary artery atherosclerosis” OR “coronary artery constric- tion” OR “coronary artery obstruction” OR “coronary artery thrombosis” OR “coronary subclavian steal syndrome” OR “heart infarction” OR “heart muscle ischemia” OR “ischemic cardiomyopathy” OR “Kounis syndrome” OR “myocardial hibernation” OR “no reflow phe- nomenon” OR “silent myocardial ischemia” OR “takotsubo cardiomyopathy”) 3- #1 AND #2 Web of Science (TS=(“glycemic index” OR “leuko*glycemic” OR “leuko-glycemic” OR “leukoglycemic”)) AND TS=( “Myocardial Ischemia” OR “Ischemic Heart Disease” OR “Acute Coronary Syndrome” OR “Unstable Angina” OR “Angina Pectoris” OR “Angina Pectori” OR “Preinfarction Angina” OR “Preinfarction Anginas” OR “Coronary Heart Disease” OR “Coronary Artery Disease” OR “Coronary Arteriosclerosis” OR “Coronary Atherosclerosis” OR “Coronary Occlusion” OR “Coronary Stenosis” OR “Coronary Thrombosis” OR “Coronary Vasospasm” OR “Myocardial Infarction” OR “Myocardial Infarct” OR “Heart Attack” OR “Myocardial Reperfusion Injury” OR “Myocardial Ischemic Reperfusion Injury” OR “heart infarction” OR “acute heart infarction” OR “anterior myocardial infarction” OR “Dressler syndrome” OR “heart atrium infarction” OR “heart infarction size” OR “heart muscle necrosis” OR “heart reinfarction” OR “heart ventricle infarction” OR “impending heart infarc- tion” OR “inferior myocardial infarction” OR “MINOCA” OR “non ST segment elevation myocardial infarction” OR “posterior myocardial infarction” OR “silent myocardial infarction” OR “ST segment elevation myocardial infarction” OR “acute coronary syndrome” OR “non st segment elevation acute coronary syndrome” OR “acute coronary syndrome” OR “angina pectoris” OR “cardiac allograft vasculopathy” OR “coronary artery atherosclerosis” OR “coronary artery constriction” OR “coronary artery obstruction” OR “coronary artery thrombosis” OR “coronary subclavian steal syndrome” OR “heart infarction” OR “heart muscle ischemia” OR “ischemic cardiomyopathy” OR “Kounis syndrome” OR “myocardial hibernation” OR “no reflow phenomenon” OR “silent myocardial ischemia” OR “takotsubo cardiomyopathy”) Supplementary figure 1: Sensitivity and specificity of leuko-glycemic index in predication of mortality following acute myocardial infarction. CI: confidence interval. This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: https://journals.sbmu.ac.ir/aaem/index.php/AAEM/index R. Sadeghi et al. 14 Supplementary figure 2: Positive and negative likelihood ratio (LR) of leuko-glycemic index in predication of mortality following acute my- ocardial infarction. CI: confidence interval. This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: https://journals.sbmu.ac.ir/aaem/index.php/AAEM/index 15 Archives of Academic Emergency Medicine. 2023; 11(1): e25 Supplementary figure 3: Sensitivity and specificity of leuko-glycemic index in predication of major cardiac complications following acute myocardial infarction. CI: confidence interval. This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: https://journals.sbmu.ac.ir/aaem/index.php/AAEM/index R. Sadeghi et al. 16 Supplementary figure 4: Positive and negative likelihood ratio (LR) of leuko-glycemic index in predication of major cardiac complications following acute myocardial infarction. CI: confidence interval. Supplementary figure 5: Publication bias in assessment of leuko-glycemic index in prediction of mortality and major cardiac complications following acute myocardial infarction. This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: https://journals.sbmu.ac.ir/aaem/index.php/AAEM/index Introduction Methods Results Discussion Conclusion Declarations References