Routine Serum Cortisol Does Not Predict Mortality or OMI/NOMI Differentiation in NSTEMI: A Prospective Emergency Department Cohort Study

Routine Serum Cortisol Does Not Predict Mortality or OMI/NOMI Differentiation in NSTEMI: A Prospective Emergency Department Cohort Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Routine Serum Cortisol Does Not Predict Mortality or OMI/NOMI Differentiation in NSTEMI: A Prospective Emergency Department Cohort Study Ali Cagatay Kaya, Mehmet Can Girgin, Ozlem Dikme, Erdem Kurt, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8948593/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 17 You are reading this latest preprint version Abstract Background/Objective: Risk stratification in non-ST-segment elevation myocardial infarction (NSTEMI) relies heavily on clinical parameters, while the prognostic utility of acute stress hormones remains unclear. This study aimed to evaluate the value of serum cortisol levels measured at emergency department (ED) presentation in predicting 30-day mortality and differentiating occlusion myocardial infarction (OMI) from non-occlusion myocardial infarction (NOMI). Methods This prospective observational cohort study included 150 consecutive patients presenting to a tertiary ED diagnosed with NSTEMI who underwent coronary angiography. Serum cortisol levels were measured upon admission. Patients were classified into OMI (TIMI 0–2, or TIMI 3 with specific criteria) and NOMI (TIMI 3) groups based on angiographic findings. The primary outcome was 30-day all-cause mortality. Results The cohort (mean age 59.9 ± 11.8 years; 71.3% male) comprised 125 (83.3%) OMI and 25 (16.7%) NOMI cases. 30-day mortality occurred in 8 (5.3%) patients. Median admission serum cortisol levels did not significantly differ between survivors and non-survivors (10.1 vs. 12.5 µg/dL, p = 0.298) or between the OMI and NOMI groups (10.2 vs. 10.8 µg/dL, p = 0.803). Conversely, mortality was significantly associated with elevated neutrophil-to-lymphocyte ratio (NLR) (p = 0.016), lymphopenia (p = 0.012), hypertension (p = 0.013), and higher GRACE scores (p < 0.001). Notably, the NOMI cohort had a significantly higher proportion of female patients compared to the OMI group (48.0% vs. 24.8%, p = 0.019). Conclusion Admission serum cortisol levels do not provide incremental diagnostic or prognostic value for OMI/NOMI differentiation or mortality prediction in NSTEMI patients. Routine clinical risk scores (GRACE) and hematological inflammatory indices (NLR, lymphopenia) offer significantly superior reliability. Therefore, routine cortisol measurement is not indicated for risk stratification in the fast-paced acute ED setting. NSTEMI Serum cortisol Emergency department Occlusion myocardial infarction Risk stratification Neutrophil-to-lymphocyte ratio Figures Figure 1 1. INTRODUCTION Non-ST-segment elevation myocardial infarction (NSTEMI) represents a significant proportion of acute coronary syndrome (ACS) cases, with its incidence rising from one-third of myocardial infarction cases in 1995 to more than half in 2015. The pathophysiology of NSTEMI involves myocardial ischemia due to acute coronary artery occlusion or severe stenosis, followed by cardiomyocyte necrosis, as evidenced by elevated high-sensitivity cardiac troponin (Hs-cTn) levels.¹ Current approaches have introduced the concepts of occlusion myocardial infarction (OMI) and non-occlusion myocardial infarction (NOMI), which may offer better prognostic value compared to the traditional STEMI/NSTEMI classification.² The stress response during acute myocardial infarction triggers activation of the hypothalamic-pituitary-adrenal axis, leading to high cortisol levels that reflect the severity of physiological stress. Cortisol, a glucocorticoid hormone produced by the adrenal cortex, plays important roles in maintaining homeostasis under stress conditions and has various effects on inflammation, metabolism, and cardiovascular health. ³ The clinical significance of cortisol measurement in acute coronary syndromes remains controversial, with limited evidence regarding its prognostic value in emergency department settings. Although epidemiological studies and Mendelian randomization analyses suggest that morning cortisol levels may be a risk factor for cardiovascular disease, the relationship between serum cortisol measurements and clinical outcomes in NSTEMI patients has not been extensively investigated. ³ Furthermore, the potential benefit of cortisol levels in distinguishing between OMI and NOMI subtypes represents an unexplored area that could improve risk stratification and therapeutic decision-making. We hypothesized that the profound ischemic burden and subsequent massive neurohormonal activation in complete acute occlusions (OMI) would generate a more pronounced cortisol surge compared to non-occlusive mechanisms (NOMI), potentially serving as an early differentiator. Current risk assessment tools, including the GRACE score, primarily rely on clinical parameters and cardiac biomarkers, but could benefit from the inclusion of stress hormone measurements to increase prognostic accuracy. ⁴⁻⁶ The identification of new biomarkers that can rapidly predict mortality and guide invasive management strategies remains a critical need in emergency cardiology practice. ⁷⁻⁹ The aim of this study was to determine the effect of serum cortisol levels on mortality in NSTEMI patients presenting to the emergency department and to assess their diagnostic value in distinguishing OMI from NOMI. 2. METHOD Prospective observational cohort study included patients who presented to a tertiary-care emergency department between June 1 and November 30, 2024, and were diagnosed with NSTEMI. Inclusion criteria Being over 18 years of age, presenting to the emergency department with chest pain, absence of ST elevation on ECG, elevated high-sensitivity troponin I levels, and undergoing coronary angiography. Exclusion criteria Being under 18 years of age, having a diagnosis of STEMI, pregnancy, history of trauma, elevated Hs-cTnI due to non-ACS causes, coronary angiography not being planned, need for emergency intervention at the time of presentation (cardiac arrest, respiratory arrest, shock, need for emergency surgery/catheterization), and refusal to participate in the study. Blood samples were collected from all patients during their emergency department visit to measure serum cortisol levels along with routine laboratory tests. Cortisol measurement was performed using the chemiluminescent microparticle immunoassay (CMIA) method on the Abbott Architect i2000SR device (Abbott Laboratories, Illinois, USA). This assay has a coefficient of variation of < 5%, a detection range of 0.4–56 µg/dL, and a reference range of 5–25 µg/dL for morning samples. Blood sampling time was recorded but not systematically controlled for circadian variation. Patients were classified as occlusion myocardial infarction (OMI) and non-occlusion myocardial infarction (NOMI) based on coronary angiography findings. OMI was defined as TIMI flow grade 0–2, OR TIMI flow grade 3 with Hs-cTnI > 5000 ng/L requiring coronary intervention during CAG, as the latter pattern typically represents recent spontaneous recanalization of an acute total occlusion. NOMI was defined as TIMI flow grade 3 without coronary intervention. The demographic characteristics, vital signs, laboratory results, ECG findings, echocardiography results, coronary angiography findings, and in-hospital outcomes of all patients were recorded. The GRACE risk score was calculated using the parameters of age, heart rate, systolic blood pressure, creatinine level, Killip class, history of cardiac arrest, ST segment changes, and elevated cardiac enzymes. Data were collected by a single researcher using standardized forms, and the researcher received training beforehand. Sample Size Calculation A power analysis was performed before the study began. It was assumed that the proportion of patients without occlusion (NOMI) would constitute approximately 20% of the total NSTEMI population and that the 30-day mortality rate would be 5%. The α error level was set at 0.05 and the β error level at 0.20 (power = 0.80). Under these assumptions, it was calculated that at least 25 patients would be required for the NOMI group and at least 125 patients for the OMI group, with a total of at least 150 patients being sufficient for mortality and OMI/NOMI comparisons. The 150 patients consecutively enrolled during the study period met this size requirement. However, this calculation was based on group comparison (OMI vs. NOMI) and did not account for the expected effect size of cortisol as a continuous predictor of outcomes. Consequently, the study may be underpowered to detect small-to-moderate effects of cortisol on mortality or OMI/NOMI differentiation. Statistical Analysis Continuous variables were expressed as mean ± standard deviation or median (interquartile range) according to the normal distribution. Categorical variables were presented as counts and percentages. The normality of distribution was assessed using the Kolmogorov-Smirnov test. The Student t-test was used for continuous variables that showed a normal distribution, and the Mann-Whitney U test was used for those that did not. The chi-square test or Fisher's exact test was applied for categorical variables. A P < 0.05 value was considered the threshold for statistical significance. The primary outcome was 30-day all-cause mortality, and the secondary outcomes were the distinction between OMI/NOMI and the prognostic value of cortisol levels. Mortality was assessed during hospitalization and up to 30 days post-discharge through the hospital information management system and structured telephone interviews with patients or their relatives. Ethical Approval and Consent The study was approved by the local Institutional Scientific Research Ethics Committee (approval obtained prior to study initiation). All participants were informed about the purpose and procedures of the study, and written informed consent was obtained. The study was conducted in accordance with the Declaration of Helsinki; patient data were anonymized and confidentiality was maintained. 3. RESULTS Of the 127,867 patients who presented to the Istanbul SUAM Emergency Medicine Clinic, 384 met the criteria for NSTEMI. Of these, 234 patients (those under 18 years of age, pregnant women, trauma patients, patients with elevated Hs-cTnI levels not due to ACS, patients without planned CAG, cardiac arrest patients, patients requiring emergency catheterization, and patients who refused treatment) were excluded from the study, leaving a total of 150 patients included in the study. Study Flow Chart Participants The study included 150 patients who presented to the emergency department between June 1, 2024, and November 30, 2024, and were diagnosed with NSTEMI. The demographic and baseline clinical characteristics of the participants are summarized in Table 1 . The mean age of the patients was 59.9 ± 11.8 years, and 71.3% (n = 107) were male. The most common comorbidity was hypertension, with a rate of 58% (n = 87). Table 1 Demographic and Clinical Characteristics of Participants (n = 150) Characteristic Value Demographic Characteristics Age (years), mean ± SD 59.9 ± 11.8 Age range 32–93 Male gender, n (%) 107 (71.3) Vital Signs Systolic blood pressure (mmHg), median 157.5 Diastolic blood pressure (mmHg), median 85 Pulse (beats/min), median 85 Clinical Presentation Chest pain, n (%) 129 (86.0) Angina in the last 24 hours, n (%) 62 (41.3) Presence of additional symptoms, n (%) 57 (38.0) Comorbidity Hypertension, n (%) 87 (58.0) Diabetes mellitus, n (%) 54 (36.0) Hyperlipidemia, n (%) 46 (30.7) Coronary artery disease, n (%) 69 (46.0) Laboratory Values Neutrophils (x10⁹/L), median 5.8 Lymphocyte (x10⁹/L), median 2.2 NLR, median 2.7 Glucose (mg/dL), median 126.5 Urea (mg/dL), median 36.7 Creatinine (mg/dL), median 1.0 Hs-cTnI 0 hours (pg/mL), median 52.9 Hs-cTnI 2 hours (pg/mL), median 269.2 Cortisol (µg/dL), median 10.3 Risk Scoring GRACE score, median 84 Coronary Angiography Percentage of stenosis (%), median 95 TIMI 0–2 flow (OMI), n (%) 125 (83.3) TIMI 3 flow (NOMI), n (%) 25 (16.7) Outcome Mortality, n (%) 8 (5.3) SD: Standard deviation; NLR: Neutrophil-lymphocyte ratio; Hs-cTnI: High-sensitivity cardiac troponin I; OMI: Occlusive myocardial infarction; NOMI: Non-occlusive myocardial infarction Descriptive Data When the basic descriptive data of the patients included in the study were examined, the mean age of the patients was found to be 59.9 ± 11.8 years (range: 32–93). 71.3% of the participants (n = 107) were male. The median systolic blood pressure at the time of presentation was 157.5 mmHg (range: 90–265 mmHg), the median diastolic blood pressure was 85 mmHg (range: 53–145 mmHg), and the median pulse rate was 85 beats/minute (range: 61–149 beats/minute). Laboratory findings showed a median neutrophil count of 5.8 x10⁹/L, a median lymphocyte count of 2.2 x10⁹/L, and a median NLR of 2.7. The median GRACE score was 84 (range: 32–143) and the median coronary artery stenosis percentage was 95% (range: 0-100%). The median serum cortisol level was 10.3 µg/dL (range: 0.4–56). Chest pain was present at presentation in 86% of patients (n = 129), and 41.3% (n = 62) reported two or more anginal symptoms within the previous 24 hours. Main Results The primary endpoint of the study, mortality, was observed in 8 of 150 patients (5.3%). Significant differences were found between patients who developed mortality and those who survived (Table 2 ). The mortality group had a statistically significantly higher proportion of female patients (62.5% vs. 26.8%, p = 0.030) and a higher prevalence of hypertension (100% vs. 55.6%, p = 0.013). In the survivor group, the absence of heart failure according to the Killip Classification was significantly higher (90.8% vs. 62.5%, p = 0.040). In terms of numerical variables, the mean NLR (7.45 vs. 3.18, p = 0.016), mean urea (54.4 mg/dL vs. 39 mg/dL, p = 0.004), and mean GRACE score (117 vs. 84.7, p < 0.001) were significantly higher than in the survivor group, while the mean lymphocyte count (1.43 x10⁹/L vs. 2.41 x10⁹/L, p = 0.012) was significantly lower. No statistically significant difference was found between the two groups in terms of serum cortisol levels measured at the time of admission (18.1 vs. 11.9, p = 0.298). Table 2 Comparison of Factors Associated with Mortality Variable Survival (n = 142) Mortality (n = 8) p-value Categorical Variables Female gender, n (%) 38 (26.8) 5 (62.5) 0.030 Hypertension, n (%) 79 (55.6) 8 (100.0) 0.013 Killip Class I (no heart failure), n (%) 129 (90.8) 5 (62.5) 0.040 Numeric Variables Lymphocytes (x10⁹/L), median (IQR) 2.2 (1.5-3.0) 1.4 (0.9–1.8) 0.012 NLR, median (IQR) 2.7 (1.8–4.2) 6.8 (3.2–12.1) 0.016 Urea (mg/dL), median (IQR) 36.7 (28–48) 54.4 (42–68) 0.004 GRACE score, median (IQR) 84 (68–102) 117 (110–124) < 0.001 Cortisol (µg/dL), median (IQR) 10.1 (6.2–15.8) 12.5 (8.1–24.2) 0.298 HF: Heart failure; NLR: Neutrophil-lymphocyte ratio; IQR: Interquartile range Statistical analysis: Chi-square test was used for categorical variables, Mann-Whitney U test was used for numerical variables. Other Analyses Patients were divided into two subgroups based on coronary angiography findings: OMI (n = 125, 83.3%) and NOMI (n = 25, 16.7%). Significant differences were found when comparing these two groups (Table 3 ). The proportion of female patients in the NOMI group (48% vs. 24.8%, p = 0.019) was significantly higher than in the OMI group. Furthermore, the median creatinine level (0.8 mg/dL vs. 1.1 mg/dL, p = 0.001) and median coronary artery stenosis percentage (23.6% vs. 93.1%, p < 0.001) were significantly lower in the NOMI group compared to the OMI group. Other variables including comorbidities (hypertension, diabetes mellitus, hyperlipidemia, coronary artery disease), smoking status, presence of chest pain, anginal symptoms within 24 hours, additional symptoms, Killip classification, and ECG findings showed no significant differences between OMI and NOMI groups (all p > 0.05). No statistically significant difference was found between the OMI and NOMI groups in terms of serum cortisol levels (12.0 vs. 13.5, p = 0.803). This finding does not support the main hypothesis of the study. There was also no significant difference in mortality rates between the two groups (4.8% vs. 8.0%, p = 0.621). Table 3 Comparison of OMI and NOMI Groups Variable OMI (n = 125) NOMI (n = 25) p-value Categorical Variables Female gender, n (%) 31 (24.8) 12 (48.0) 0.019 Obstructive CAD (≥ 50% stenosis), n (%) 124 (99.2) 1 (4.0) < 0.001 Complete occlusion, n (%) 50 (40.0) 0 (0.0) < 0.001 Mortality, n (%) 6 (4.8) 2 (8.0) 0.621 Numeric Variables Creatinine (mg/dL), median (IQR) 1.0 (0.8–1.3) 0.8 (0.7–0.9) 0.001 Narrowing percentage (%), median (IQR) 95 (90–100) 25 (10–40) < 0.001 Cortisol (µg/dL), median (IQR) 10.2 (6.1–15.7) 10.8 (6.8–17.2) 0.803 OMI: Occlusive myocardial infarction; NOMI: Non-occlusive myocardial infarction; CAD: Coronary artery disease; IQR: Interquartile range Statistical analysis: Chi-square test was used for categorical variables, Mann-Whitney U test was used for numerical variables. 4. DISCUSSION This study investigated the effect of serum cortisol levels on mortality and OMI/NOMI differentiation in NSTEMI patients. The principal finding of this study is that serum cortisol levels were not effective in distinguishing OMI/NOMI or predicting mortality. However, female gender, hypertension, high NLR, lymphopenia, high urea levels, and high GRACE score were identified as important factors associated with mortality The lack of association between cortisol and clinical outcomes warrants mechanistic consideration. HPA axis activation during acute myocardial infarction demonstrates considerable inter-individual heterogeneity, influenced by baseline cortisol variability, chronic stress exposure, comorbidities such as diabetes and chronic kidney disease, and concurrent medications. 3 This biological variability may obscure consistent associations between cortisol levels and clinical outcomes across patient populations. Our reliance on single time-point measurements represents an important methodological constraint. Cortisol secretion follows a dynamic pattern during acute stress, and single measurements may inadequately capture the cumulative burden of HPA axis activation. Serial measurements or area-under-the-curve analysis might better reflect the integrated stress response and reveal associations not apparent with single time-point assessment. Additionally, cortisol elevation is inherently non-specific, occurring in response to pain, anxiety, and systemic inflammation independent of myocardial ischemia severity. This lack of specificity may limit cortisol's discriminative capacity in the acute coronary syndrome setting. The timing of blood sampling introduces further complexity. We did not systematically control for circadian rhythm variation or time elapsed since symptom onset, both of which substantially influence cortisol concentrations. This measurement variability may have attenuated potential associations between cortisol and clinical outcomes. Approximately 25–30% of NSTEMI patients have acute total occlusion (OMI), where delayed reperfusion leads to irreversible myocardial damage. 10,11 Early OMI recognition remains critically important for improving clinical outcomes. A systematic review by Khan and colleagues showed that NSTEMI OMI patients have a higher mortality risk. 12 A recent study reported that 40% of OMI patients did not meet the STEMI criteria on ECG. 2 The study by Aslanger et al. emphasized the importance of new ECG findings in the diagnosis of OMI. 13 However, our study found that ECG findings were not effective in predicting mortality and distinguishing between OMI and NOMI. Schulte and colleagues systematic review reported that atypical symptoms were more common in women. 14 We also found that mortality was more common in female patients, which is consistent with the literature. Notably, our angiographic analysis revealed a significantly higher proportion of female patients in the NOMI group compared to the OMI cohort (48.0% vs. 24.8%). This aligns with the pathophysiological understanding that women more frequently present with non-obstructive coronary mechanisms, such as microvascular dysfunction or plaque erosion, which might also contribute to the complex clinical presentation and higher mortality observed in this demographic. Armillotta and colleagues demonstrated the prognostic value of the Killip classification in MINOCA patients. 15 Similarly, Carvalho and colleagues showed in their long-term follow-up study that the presence of heart failure was a predictor of mortality. 16 Zafrir and colleagues demonstrated in their retrospective analysis that lymphopenia was associated with an increased risk of mortality in patients undergoing PCI. 17 In this study, consistent with the literature, lymphopenia and elevated NLR were found to be predictive factors for mortality. When comparing the prognostic utility of these markers, NLR and lymphopenia appear superior to serum cortisol. While cortisol acts as a highly sensitive but largely non-specific acute-phase reactant to generalized pain and emergency department anxiety, elevated NLR reflects a more sustained, specific cellular immune and inflammatory response to myocardial necrosis. This study has several important limitations. The single-center design limits external validity and generalizability to different populations and healthcare settings. Although our sample size was adequately powered to detect differences in the primary clinical endpoints, it may not be sufficient to capture minor fluctuations in cortisol levels. Therefore, these findings should be validated in larger, multi-center cohorts to definitively establish the boundaries of cortisol's prognostic utility in ACS. Several methodological limitations affected the validity of cortisol measurement. Blood samples were not controlled for time of day, creating potential bias from circadian rhythm variation, as cortisol levels in healthy individuals vary significantly between morning and evening. However, this methodological approach inherently reflects the unpredictable nature and real-world conditions of emergency department admissions, providing a pragmatic perspective on the feasibility of routine biomarker testing in acute settings Additionally, we relied on single-time-point measurements rather than serial assessments or area-under-the-curve analysis, which may not adequately capture the dynamic nature of HPA axis activation during acute myocardial infarction. Furthermore, we did not systematically collect data on medications that could affect cortisol levels, including exogenous corticosteroids and beta-blockers. The emergency department symptom assessment was partially based on patient self-report, which introduced potential measurement error. Concurrent infections or autoimmune conditions known to affect inflammatory markers were not systematically controlled, preventing independent evaluation of lymphocyte count and NLR as predictors of mortality. The exclusion of patients requiring emergency intervention may have eliminated the highest-risk subgroup, in which cortisol's prognostic value was most pronounced, potentially biasing the results toward zero. Despite these limitations, this prospective study provides valuable evidence that routine cortisol measurement does not improve risk stratification in NSTEMI patients beyond standard clinical parameters. 5. CONCLUSION This prospective cohort study demonstrated that serum cortisol levels measured in the emergency department have limited clinical value in predicting mortality and distinguishing between OMI and NOMI in NSTEMI patients. Cortisol levels did not show a significant correlation with mortality or the presence of angiographic occlusion. Female gender, presence of hypertension, high neutrophil-lymphocyte ratio, and GRACE scores were identified as strong predictors of mortality, while lymphopenia was identified as a risk factor for mortality. In conclusion, existing clinical parameters particularly the GRACE score and inflammatory markers like NLR provide significantly more reliable prognostic information than single time-point cortisol measurements for risk stratification in NSTEMI patients. Consequently, our findings suggest that routine cortisol testing in the fast-paced emergency department setting does not add incremental diagnostic or prognostic value, and clinical focus should remain on established risk assessment tools. Abbreviations ACS: Acute coronary syndrome; CAD: Coronary artery disease; CAG: Coronary angiography; CMIA: Chemiluminescent microparticle immunoassay; CV: Coefficient of variation; ECG: Electrocardiogram; ED: Emergency department; eGFR: Estimated glomerular filtration rate; GRACE: Global Registry of Acute Coronary Events; HF: Heart failure; HPA: Hypothalamic-pituitary-adrenal; Hs-cTn: High-sensitivity cardiac troponin; Hs-cTnI: High-sensitivity cardiac troponin I; IQR: Interquartile range; MINOCA: Myocardial infarction with non-obstructive coronary arteries; NLR: Neutrophil-lymphocyte ratio; NOMI: Non-occlusive myocardial infarction; NSTEMI: Non-ST-segment elevation myocardial infarction; OMI: Occlusive myocardial infarction; PCI: Percutaneous coronary intervention; ROC: Receiver operating characteristic; SD: Standard deviation; STEMI: ST-segment elevation myocardial infarction; TIMI: Thrombolysis in Myocardial Infarction Declarations Ethics approval and consent to participate This study was approved by the Scientific Research Ethics Committee of Istanbul Health Application and Research Center (SUAM), Health Sciences University, Istanbul, Turkey (approval number 90, dated 08.05.2024). All participants provided written informed consent prior to enrollment. The study was conducted in accordance with the principles of the Declaration of Helsinki. Consent for publication Not applicable. Availability of data and materials The datasets used and analyzed during the current study are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Authors' contributions A.C.K. and E.K. conceived and designed the study. A.C.K., M.C.G., O.D., F.K., and O.G.D. collected the data. A.C.K. performed the statistical analysis and wrote the main manuscript text. E.K. supervised the study. M.C.G., O.D., F.K., and O.G.D. critically reviewed and edited the manuscript. All authors read and approved the final manuscript. Acknowledgements The authors would like to thank the nursing staff of the Emergency Department of Istanbul Training and Research Hospital for their assistance with patient enrollment and data collection. References Collet JP, Thiele H, Barbato E, et al. 2020 ESC Guidelines for the management of acute coronary syndromes in patients presenting without persistent ST-segment elevation. Eur Heart J. 2021;42(14):1289–367. Kola M, Shuka N, Meyers HP, Zaimi E, Smith SW. OMI/NOMI: Time for a New Classification of Acute Myocardial Infarction. J Clin Med. 2024;13(17):5201. Aladio JM, Costa D, Matsudo M, Perez de la Hoz A, Gonzalez D, Brignoli A et al. Cortisol-Mediated Stress Response and Mortality in Acute Coronary Syndrome. Curr Probl Cardiol. 2020;100623. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8948593","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":613365632,"identity":"5f4e1af3-4d76-4494-bbd0-2c57c4ecf8df","order_by":0,"name":"Ali Cagatay Kaya","email":"data:image/png;base64,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","orcid":"","institution":"İstanbul Eğitim ve Araştırma Hastanesi","correspondingAuthor":true,"prefix":"","firstName":"Ali","middleName":"Cagatay","lastName":"Kaya","suffix":""},{"id":613365633,"identity":"9f3d6e9b-54b4-40f0-abf3-88bba55fbf1e","order_by":1,"name":"Mehmet Can Girgin","email":"","orcid":"","institution":"Beykent University","correspondingAuthor":false,"prefix":"","firstName":"Mehmet","middleName":"Can","lastName":"Girgin","suffix":""},{"id":613365634,"identity":"a5f83bab-13b2-4685-939a-f0b9553e0d22","order_by":2,"name":"Ozlem Dikme","email":"","orcid":"","institution":"İstanbul Eğitim ve Araştırma Hastanesi","correspondingAuthor":false,"prefix":"","firstName":"Ozlem","middleName":"","lastName":"Dikme","suffix":""},{"id":613365635,"identity":"b739f27b-a502-495d-80b6-544098ba9648","order_by":3,"name":"Erdem Kurt","email":"","orcid":"","institution":"İstanbul Eğitim ve Araştırma Hastanesi","correspondingAuthor":false,"prefix":"","firstName":"Erdem","middleName":"","lastName":"Kurt","suffix":""},{"id":613365636,"identity":"17cb1f91-3bee-4b0d-aeed-4385ff1fb55f","order_by":4,"name":"Fırat Kaya","email":"","orcid":"","institution":"Ağrı Training and Research Hospital","correspondingAuthor":false,"prefix":"","firstName":"Fırat","middleName":"","lastName":"Kaya","suffix":""},{"id":613365637,"identity":"4c30127c-9d90-4814-b7bf-db30edb3ba19","order_by":5,"name":"Ozgur Dikme","email":"","orcid":"","institution":"İstanbul Eğitim ve Araştırma Hastanesi","correspondingAuthor":false,"prefix":"","firstName":"Ozgur","middleName":"","lastName":"Dikme","suffix":""}],"badges":[],"createdAt":"2026-02-23 15:23:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8948593/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8948593/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":105877465,"identity":"d13f5d71-b9a5-4a7e-9ac3-508bf8ba89ba","added_by":"auto","created_at":"2026-04-01 06:03:47","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":108835,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eStudy Flow Chart\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8948593/v1/5f174b8c025fce4cf58288fc.jpg"},{"id":105904642,"identity":"63c74118-1833-4f84-9491-208c6c29e26c","added_by":"auto","created_at":"2026-04-01 10:10:03","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":861884,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8948593/v1/3a8b1d55-c8b1-4537-af08-278f56ac54d5.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Routine Serum Cortisol Does Not Predict Mortality or OMI/NOMI Differentiation in NSTEMI: A Prospective Emergency Department Cohort Study","fulltext":[{"header":"1. INTRODUCTION","content":"\u003cp\u003eNon-ST-segment elevation myocardial infarction (NSTEMI) represents a significant proportion of acute coronary syndrome (ACS) cases, with its incidence rising from one-third of myocardial infarction cases in 1995 to more than half in 2015. The pathophysiology of NSTEMI involves myocardial ischemia due to acute coronary artery occlusion or severe stenosis, followed by cardiomyocyte necrosis, as evidenced by elevated high-sensitivity cardiac troponin (Hs-cTn) levels.\u0026sup1; Current approaches have introduced the concepts of occlusion myocardial infarction (OMI) and non-occlusion myocardial infarction (NOMI), which may offer better prognostic value compared to the traditional STEMI/NSTEMI classification.\u0026sup2; The stress response during acute myocardial infarction triggers activation of the hypothalamic-pituitary-adrenal axis, leading to high cortisol levels that reflect the severity of physiological stress. Cortisol, a glucocorticoid hormone produced by the adrenal cortex, plays important roles in maintaining homeostasis under stress conditions and has various effects on inflammation, metabolism, and cardiovascular health. \u0026sup3;\u003c/p\u003e \u003cp\u003eThe clinical significance of cortisol measurement in acute coronary syndromes remains controversial, with limited evidence regarding its prognostic value in emergency department settings. Although epidemiological studies and Mendelian randomization analyses suggest that morning cortisol levels may be a risk factor for cardiovascular disease, the relationship between serum cortisol measurements and clinical outcomes in NSTEMI patients has not been extensively investigated. \u0026sup3; Furthermore, the potential benefit of cortisol levels in distinguishing between OMI and NOMI subtypes represents an unexplored area that could improve risk stratification and therapeutic decision-making. We hypothesized that the profound ischemic burden and subsequent massive neurohormonal activation in complete acute occlusions (OMI) would generate a more pronounced cortisol surge compared to non-occlusive mechanisms (NOMI), potentially serving as an early differentiator.\u003c/p\u003e \u003cp\u003eCurrent risk assessment tools, including the GRACE score, primarily rely on clinical parameters and cardiac biomarkers, but could benefit from the inclusion of stress hormone measurements to increase prognostic accuracy. ⁴⁻⁶ The identification of new biomarkers that can rapidly predict mortality and guide invasive management strategies remains a critical need in emergency cardiology practice. ⁷⁻⁹\u003c/p\u003e \u003cp\u003eThe aim of this study was to determine the effect of serum cortisol levels on mortality in NSTEMI patients presenting to the emergency department and to assess their diagnostic value in distinguishing OMI from NOMI.\u003c/p\u003e"},{"header":"2. METHOD","content":"\u003cp\u003eProspective observational cohort study included patients who presented to a tertiary-care emergency department between June 1 and November 30, 2024, and were diagnosed with NSTEMI.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eInclusion criteria\u003c/strong\u003e \u003cp\u003eBeing over 18 years of age, presenting to the emergency department with chest pain, absence of ST elevation on ECG, elevated high-sensitivity troponin I levels, and undergoing coronary angiography.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eExclusion criteria\u003c/strong\u003e \u003cp\u003eBeing under 18 years of age, having a diagnosis of STEMI, pregnancy, history of trauma, elevated Hs-cTnI due to non-ACS causes, coronary angiography not being planned, need for emergency intervention at the time of presentation (cardiac arrest, respiratory arrest, shock, need for emergency surgery/catheterization), and refusal to participate in the study.\u003c/p\u003e \u003c/p\u003e \u003cp\u003eBlood samples were collected from all patients during their emergency department visit to measure serum cortisol levels along with routine laboratory tests. Cortisol measurement was performed using the chemiluminescent microparticle immunoassay (CMIA) method on the Abbott Architect i2000SR device (Abbott Laboratories, Illinois, USA). This assay has a coefficient of variation of \u0026lt;\u0026thinsp;5%, a detection range of 0.4\u0026ndash;56 \u0026micro;g/dL, and a reference range of 5\u0026ndash;25 \u0026micro;g/dL for morning samples. Blood sampling time was recorded but not systematically controlled for circadian variation.\u003c/p\u003e \u003cp\u003ePatients were classified as occlusion myocardial infarction (OMI) and non-occlusion myocardial infarction (NOMI) based on coronary angiography findings. OMI was defined as TIMI flow grade 0\u0026ndash;2, OR TIMI flow grade 3 with Hs-cTnI\u0026thinsp;\u0026gt;\u0026thinsp;5000 ng/L requiring coronary intervention during CAG, as the latter pattern typically represents recent spontaneous recanalization of an acute total occlusion. NOMI was defined as TIMI flow grade 3 without coronary intervention.\u003c/p\u003e \u003cp\u003eThe demographic characteristics, vital signs, laboratory results, ECG findings, echocardiography results, coronary angiography findings, and in-hospital outcomes of all patients were recorded. The GRACE risk score was calculated using the parameters of age, heart rate, systolic blood pressure, creatinine level, Killip class, history of cardiac arrest, ST segment changes, and elevated cardiac enzymes.\u003c/p\u003e \u003cp\u003eData were collected by a single researcher using standardized forms, and the researcher received training beforehand.\u003c/p\u003e \u003cp\u003e \u003cb\u003eSample Size Calculation\u003c/b\u003e \u003c/p\u003e \u003cp\u003eA power analysis was performed before the study began. It was assumed that the proportion of patients without occlusion (NOMI) would constitute approximately 20% of the total NSTEMI population and that the 30-day mortality rate would be 5%. The α error level was set at 0.05 and the β error level at 0.20 (power\u0026thinsp;=\u0026thinsp;0.80). Under these assumptions, it was calculated that at least 25 patients would be required for the NOMI group and at least 125 patients for the OMI group, with a total of at least 150 patients being sufficient for mortality and OMI/NOMI comparisons. The 150 patients consecutively enrolled during the study period met this size requirement. However, this calculation was based on group comparison (OMI vs. NOMI) and did not account for the expected effect size of cortisol as a continuous predictor of outcomes. Consequently, the study may be underpowered to detect small-to-moderate effects of cortisol on mortality or OMI/NOMI differentiation.\u003c/p\u003e \u003cp\u003e \u003cb\u003eStatistical Analysis\u003c/b\u003e \u003c/p\u003e \u003cp\u003eContinuous variables were expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation or median (interquartile range) according to the normal distribution. Categorical variables were presented as counts and percentages.\u003c/p\u003e \u003cp\u003eThe normality of distribution was assessed using the Kolmogorov-Smirnov test. The Student t-test was used for continuous variables that showed a normal distribution, and the Mann-Whitney U test was used for those that did not. The chi-square test or Fisher's exact test was applied for categorical variables. A P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 value was considered the threshold for statistical significance.\u003c/p\u003e \u003cp\u003eThe primary outcome was 30-day all-cause mortality, and the secondary outcomes were the distinction between OMI/NOMI and the prognostic value of cortisol levels. Mortality was assessed during hospitalization and up to 30 days post-discharge through the hospital information management system and structured telephone interviews with patients or their relatives.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eEthical Approval and Consent\u003c/strong\u003e \u003cp\u003e The study was approved by the local Institutional Scientific Research Ethics Committee (approval obtained prior to study initiation). All participants were informed about the purpose and procedures of the study, and written informed consent was obtained. The study was conducted in accordance with the Declaration of Helsinki; patient data were anonymized and confidentiality was maintained.\u003c/p\u003e \u003c/p\u003e"},{"header":"3. RESULTS","content":"\u003cp\u003eOf the 127,867 patients who presented to the Istanbul SUAM Emergency Medicine Clinic, 384 met the criteria for NSTEMI. Of these, 234 patients (those under 18 years of age, pregnant women, trauma patients, patients with elevated Hs-cTnI levels not due to ACS, patients without planned CAG, cardiac arrest patients, patients requiring emergency catheterization, and patients who refused treatment) were excluded from the study, leaving a total of 150 patients included in the study.\u003c/p\u003e \u003cp\u003e \u003cb\u003eStudy Flow Chart\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eParticipants\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe study included 150 patients who presented to the emergency department between June 1, 2024, and November 30, 2024, and were diagnosed with NSTEMI. The demographic and baseline clinical characteristics of the participants are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The mean age of the patients was 59.9\u0026thinsp;\u0026plusmn;\u0026thinsp;11.8 years, and 71.3% (n\u0026thinsp;=\u0026thinsp;107) were male. The most common comorbidity was hypertension, with a rate of 58% (n\u0026thinsp;=\u0026thinsp;87).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographic and Clinical Characteristics of Participants (n\u0026thinsp;=\u0026thinsp;150)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eValue\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDemographic Characteristics\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years), mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e59.9\u0026thinsp;\u0026plusmn;\u0026thinsp;11.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge range\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32\u0026ndash;93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale gender, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e107 (71.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVital Signs\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSystolic blood pressure (mmHg), median\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e157.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiastolic blood pressure (mmHg), median\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e85\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePulse (beats/min), median\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e85\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eClinical Presentation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChest pain, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e129 (86.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAngina in the last 24 hours, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e62 (41.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePresence of additional symptoms, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e57 (38.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eComorbidity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e87 (58.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes mellitus, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e54 (36.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHyperlipidemia, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46 (30.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCoronary artery disease, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69 (46.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLaboratory Values\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeutrophils (x10⁹/L), median\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLymphocyte (x10⁹/L), median\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNLR, median\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGlucose (mg/dL), median\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e126.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrea (mg/dL), median\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCreatinine (mg/dL), median\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHs-cTnI 0 hours (pg/mL), median\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e52.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHs-cTnI 2 hours (pg/mL), median\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e269.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCortisol (\u0026micro;g/dL), median\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRisk Scoring\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGRACE score, median\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e84\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCoronary Angiography\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePercentage of stenosis (%), median\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e95\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTIMI 0\u0026ndash;2 flow (OMI), n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e125 (83.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTIMI 3 flow (NOMI), n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25 (16.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOutcome\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMortality, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (5.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003e\u003cem\u003eSD: Standard deviation; NLR: Neutrophil-lymphocyte ratio; Hs-cTnI: High-sensitivity cardiac troponin I; OMI: Occlusive myocardial infarction; NOMI: Non-occlusive myocardial infarction\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\u003cp\u003e\u003cb\u003eDescriptive Data\u003c/b\u003e\u003c/p\u003e \u003cp\u003eWhen the basic descriptive data of the patients included in the study were examined, the mean age of the patients was found to be 59.9\u0026thinsp;\u0026plusmn;\u0026thinsp;11.8 years (range: 32\u0026ndash;93). 71.3% of the participants (n\u0026thinsp;=\u0026thinsp;107) were male. The median systolic blood pressure at the time of presentation was 157.5 mmHg (range: 90\u0026ndash;265 mmHg), the median diastolic blood pressure was 85 mmHg (range: 53\u0026ndash;145 mmHg), and the median pulse rate was 85 beats/minute (range: 61\u0026ndash;149 beats/minute).\u003c/p\u003e \u003cp\u003eLaboratory findings showed a median neutrophil count of 5.8 x10⁹/L, a median lymphocyte count of 2.2 x10⁹/L, and a median NLR of 2.7. The median GRACE score was 84 (range: 32\u0026ndash;143) and the median coronary artery stenosis percentage was 95% (range: 0-100%). The median serum cortisol level was 10.3 \u0026micro;g/dL (range: 0.4\u0026ndash;56). Chest pain was present at presentation in 86% of patients (n\u0026thinsp;=\u0026thinsp;129), and 41.3% (n\u0026thinsp;=\u0026thinsp;62) reported two or more anginal symptoms within the previous 24 hours.\u003c/p\u003e \u003cp\u003e \u003cb\u003eMain Results\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe primary endpoint of the study, mortality, was observed in 8 of 150 patients (5.3%). Significant differences were found between patients who developed mortality and those who survived (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The mortality group had a statistically significantly higher proportion of female patients (62.5% vs. 26.8%, p\u0026thinsp;=\u0026thinsp;0.030) and a higher prevalence of hypertension (100% vs. 55.6%, p\u0026thinsp;=\u0026thinsp;0.013). In the survivor group, the absence of heart failure according to the Killip Classification was significantly higher (90.8% vs. 62.5%, p\u0026thinsp;=\u0026thinsp;0.040).\u003c/p\u003e \u003cp\u003eIn terms of numerical variables, the mean NLR (7.45 vs. 3.18, p\u0026thinsp;=\u0026thinsp;0.016), mean urea (54.4 mg/dL vs. 39 mg/dL, p\u0026thinsp;=\u0026thinsp;0.004), and mean GRACE score (117 vs. 84.7, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) were significantly higher than in the survivor group, while the mean lymphocyte count (1.43 x10⁹/L vs. 2.41 x10⁹/L, p\u0026thinsp;=\u0026thinsp;0.012) was significantly lower. No statistically significant difference was found between the two groups in terms of serum cortisol levels measured at the time of admission (18.1 vs. 11.9, p\u0026thinsp;=\u0026thinsp;0.298).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of Factors Associated with Mortality\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSurvival (n\u0026thinsp;=\u0026thinsp;142)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMortality (n\u0026thinsp;=\u0026thinsp;8)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCategorical Variables\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale gender, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38 (26.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (62.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.030\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e79 (55.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKillip Class I (no heart failure), n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e129 (90.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (62.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.040\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNumeric Variables\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLymphocytes (x10⁹/L), median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.2 (1.5-3.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.4 (0.9\u0026ndash;1.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNLR, median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.7 (1.8\u0026ndash;4.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.8 (3.2\u0026ndash;12.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.016\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrea (mg/dL), median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36.7 (28\u0026ndash;48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54.4 (42\u0026ndash;68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGRACE score, median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e84 (68\u0026ndash;102)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e117 (110\u0026ndash;124)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCortisol (\u0026micro;g/dL), median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.1 (6.2\u0026ndash;15.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.5 (8.1\u0026ndash;24.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.298\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003cem\u003eHF: Heart failure; NLR: Neutrophil-lymphocyte ratio; IQR: Interquartile range\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eStatistical analysis: Chi-square test was used for categorical variables, Mann-Whitney U test was used for numerical variables.\u003c/em\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eOther Analyses\u003c/b\u003e \u003c/p\u003e \u003cp\u003ePatients were divided into two subgroups based on coronary angiography findings: OMI (n\u0026thinsp;=\u0026thinsp;125, 83.3%) and NOMI (n\u0026thinsp;=\u0026thinsp;25, 16.7%). Significant differences were found when comparing these two groups (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The proportion of female patients in the NOMI group (48% vs. 24.8%, p\u0026thinsp;=\u0026thinsp;0.019) was significantly higher than in the OMI group. Furthermore, the median creatinine level (0.8 mg/dL vs. 1.1 mg/dL, p\u0026thinsp;=\u0026thinsp;0.001) and median coronary artery stenosis percentage (23.6% vs. 93.1%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) were significantly lower in the NOMI group compared to the OMI group.\u003c/p\u003e \u003cp\u003eOther variables including comorbidities (hypertension, diabetes mellitus, hyperlipidemia, coronary artery disease), smoking status, presence of chest pain, anginal symptoms within 24 hours, additional symptoms, Killip classification, and ECG findings showed no significant differences between OMI and NOMI groups (all p\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003eNo statistically significant difference was found between the OMI and NOMI groups in terms of serum cortisol levels (12.0 vs. 13.5, p\u0026thinsp;=\u0026thinsp;0.803). This finding does not support the main hypothesis of the study. There was also no significant difference in mortality rates between the two groups (4.8% vs. 8.0%, p\u0026thinsp;=\u0026thinsp;0.621).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of OMI and NOMI Groups\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOMI (n\u0026thinsp;=\u0026thinsp;125)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNOMI (n\u0026thinsp;=\u0026thinsp;25)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCategorical Variables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale gender, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31 (24.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (48.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.019\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObstructive CAD (\u0026ge;\u0026thinsp;50% stenosis), n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e124 (99.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (4.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComplete occlusion, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50 (40.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMortality, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (4.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (8.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.621\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNumeric Variables\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCreatinine (mg/dL), median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.0 (0.8\u0026ndash;1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.8 (0.7\u0026ndash;0.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNarrowing percentage (%), median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e95 (90\u0026ndash;100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25 (10\u0026ndash;40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCortisol (\u0026micro;g/dL), median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.2 (6.1\u0026ndash;15.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.8 (6.8\u0026ndash;17.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.803\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003cem\u003eOMI: Occlusive myocardial infarction; NOMI: Non-occlusive myocardial infarction; CAD: Coronary artery disease; IQR: Interquartile range\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eStatistical analysis: Chi-square test was used for categorical variables, Mann-Whitney U test was used for numerical variables.\u003c/em\u003e \u003c/p\u003e"},{"header":"4. DISCUSSION","content":"\u003cp\u003eThis study investigated the effect of serum cortisol levels on mortality and OMI/NOMI differentiation in NSTEMI patients. The principal finding of this study is that serum cortisol levels were not effective in distinguishing OMI/NOMI or predicting mortality. However, female gender, hypertension, high NLR, lymphopenia, high urea levels, and high GRACE score were identified as important factors associated with mortality\u003c/p\u003e \u003cp\u003eThe lack of association between cortisol and clinical outcomes warrants mechanistic consideration. HPA axis activation during acute myocardial infarction demonstrates considerable inter-individual heterogeneity, influenced by baseline cortisol variability, chronic stress exposure, comorbidities such as diabetes and chronic kidney disease, and concurrent medications. \u003csup\u003e3\u003c/sup\u003e This biological variability may obscure consistent associations between cortisol levels and clinical outcomes across patient populations. Our reliance on single time-point measurements represents an important methodological constraint. Cortisol secretion follows a dynamic pattern during acute stress, and single measurements may inadequately capture the cumulative burden of HPA axis activation. Serial measurements or area-under-the-curve analysis might better reflect the integrated stress response and reveal associations not apparent with single time-point assessment. Additionally, cortisol elevation is inherently non-specific, occurring in response to pain, anxiety, and systemic inflammation independent of myocardial ischemia severity. This lack of specificity may limit cortisol's discriminative capacity in the acute coronary syndrome setting. The timing of blood sampling introduces further complexity. We did not systematically control for circadian rhythm variation or time elapsed since symptom onset, both of which substantially influence cortisol concentrations. This measurement variability may have attenuated potential associations between cortisol and clinical outcomes.\u003c/p\u003e \u003cp\u003eApproximately 25\u0026ndash;30% of NSTEMI patients have acute total occlusion (OMI), where delayed reperfusion leads to irreversible myocardial damage. \u003csup\u003e10,11\u003c/sup\u003e Early OMI recognition remains critically important for improving clinical outcomes.\u003c/p\u003e \u003cp\u003eA systematic review by Khan and colleagues showed that NSTEMI OMI patients have a higher mortality risk. \u003csup\u003e12\u003c/sup\u003e A recent study reported that 40% of OMI patients did not meet the STEMI criteria on ECG. \u003csup\u003e2\u003c/sup\u003e The study by Aslanger et al. emphasized the importance of new ECG findings in the diagnosis of OMI. \u003csup\u003e13\u003c/sup\u003e However, our study found that ECG findings were not effective in predicting mortality and distinguishing between OMI and NOMI. Schulte and colleagues systematic review reported that atypical symptoms were more common in women. \u003csup\u003e14\u003c/sup\u003e We also found that mortality was more common in female patients, which is consistent with the literature.\u003c/p\u003e \u003cp\u003eNotably, our angiographic analysis revealed a significantly higher proportion of female patients in the NOMI group compared to the OMI cohort (48.0% vs. 24.8%). This aligns with the pathophysiological understanding that women more frequently present with non-obstructive coronary mechanisms, such as microvascular dysfunction or plaque erosion, which might also contribute to the complex clinical presentation and higher mortality observed in this demographic.\u003c/p\u003e \u003cp\u003eArmillotta and colleagues demonstrated the prognostic value of the Killip classification in MINOCA patients.\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e Similarly, Carvalho and colleagues showed in their long-term follow-up study that the presence of heart failure was a predictor of mortality.\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e Zafrir and colleagues demonstrated in their retrospective analysis that lymphopenia was associated with an increased risk of mortality in patients undergoing PCI. \u003csup\u003e17\u003c/sup\u003e In this study, consistent with the literature, lymphopenia and elevated NLR were found to be predictive factors for mortality.\u003c/p\u003e \u003cp\u003eWhen comparing the prognostic utility of these markers, NLR and lymphopenia appear superior to serum cortisol. While cortisol acts as a highly sensitive but largely non-specific acute-phase reactant to generalized pain and emergency department anxiety, elevated NLR reflects a more sustained, specific cellular immune and inflammatory response to myocardial necrosis.\u003c/p\u003e \u003cp\u003eThis study has several important limitations. The single-center design limits external validity and generalizability to different populations and healthcare settings. Although our sample size was adequately powered to detect differences in the primary clinical endpoints, it may not be sufficient to capture minor fluctuations in cortisol levels. Therefore, these findings should be validated in larger, multi-center cohorts to definitively establish the boundaries of cortisol's prognostic utility in ACS.\u003c/p\u003e \u003cp\u003eSeveral methodological limitations affected the validity of cortisol measurement. Blood samples were not controlled for time of day, creating potential bias from circadian rhythm variation, as cortisol levels in healthy individuals vary significantly between morning and evening.\u003c/p\u003e \u003cp\u003eHowever, this methodological approach inherently reflects the unpredictable nature and real-world conditions of emergency department admissions, providing a pragmatic perspective on the feasibility of routine biomarker testing in acute settings\u003c/p\u003e \u003cp\u003eAdditionally, we relied on single-time-point measurements rather than serial assessments or area-under-the-curve analysis, which may not adequately capture the dynamic nature of HPA axis activation during acute myocardial infarction.\u003c/p\u003e \u003cp\u003eFurthermore, we did not systematically collect data on medications that could affect cortisol levels, including exogenous corticosteroids and beta-blockers.\u003c/p\u003e \u003cp\u003eThe emergency department symptom assessment was partially based on patient self-report, which introduced potential measurement error. Concurrent infections or autoimmune conditions known to affect inflammatory markers were not systematically controlled, preventing independent evaluation of lymphocyte count and NLR as predictors of mortality. The exclusion of patients requiring emergency intervention may have eliminated the highest-risk subgroup, in which cortisol's prognostic value was most pronounced, potentially biasing the results toward zero.\u003c/p\u003e \u003cp\u003eDespite these limitations, this prospective study provides valuable evidence that routine cortisol measurement does not improve risk stratification in NSTEMI patients beyond standard clinical parameters.\u003c/p\u003e"},{"header":"5. CONCLUSION","content":"\u003cp\u003eThis prospective cohort study demonstrated that serum cortisol levels measured in the emergency department have limited clinical value in predicting mortality and distinguishing between OMI and NOMI in NSTEMI patients. Cortisol levels did not show a significant correlation with mortality or the presence of angiographic occlusion. Female gender, presence of hypertension, high neutrophil-lymphocyte ratio, and GRACE scores were identified as strong predictors of mortality, while lymphopenia was identified as a risk factor for mortality.\u003c/p\u003e \u003cp\u003eIn conclusion, existing clinical parameters particularly the GRACE score and inflammatory markers like NLR provide significantly more reliable prognostic information than single time-point cortisol measurements for risk stratification in NSTEMI patients. Consequently, our findings suggest that routine cortisol testing in the fast-paced emergency department setting does not add incremental diagnostic or prognostic value, and clinical focus should remain on established risk assessment tools.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eACS: Acute coronary syndrome; CAD: Coronary artery disease; CAG: Coronary\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eangiography; CMIA: Chemiluminescent microparticle immunoassay; CV: Coefficient\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eof variation; ECG: Electrocardiogram; ED: Emergency department; eGFR: Estimated\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eglomerular filtration rate; GRACE: Global Registry of Acute Coronary Events;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHF: Heart failure; HPA: Hypothalamic-pituitary-adrenal; Hs-cTn: High-sensitivity\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ecardiac troponin; Hs-cTnI: High-sensitivity cardiac troponin I; IQR: Interquartile\u0026nbsp;\u003c/p\u003e\n\u003cp\u003erange; MINOCA: Myocardial infarction with non-obstructive coronary arteries;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNLR: Neutrophil-lymphocyte ratio; NOMI: Non-occlusive myocardial infarction;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNSTEMI: Non-ST-segment elevation myocardial infarction; OMI: Occlusive myocardial\u0026nbsp;\u003c/p\u003e\n\u003cp\u003einfarction; PCI: Percutaneous coronary intervention; ROC: Receiver operating\u0026nbsp;\u003c/p\u003e\n\u003cp\u003echaracteristic; SD: Standard deviation; STEMI: ST-segment elevation myocardial\u0026nbsp;\u003c/p\u003e\n\u003cp\u003einfarction; TIMI: Thrombolysis in Myocardial Infarction\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Scientific Research Ethics Committee of Istanbul\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHealth Application and Research Center (SUAM), Health Sciences University,\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIstanbul, Turkey (approval number 90, dated 08.05.2024). All participants\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eprovided written informed consent prior to enrollment. The study was conducted\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ein accordance with the principles of the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and analyzed during the current study are available from the\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ecorresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research received no specific grant from any funding agency in the public,\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ecommercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA.C.K. and E.K. conceived and designed the study. A.C.K., M.C.G., O.D., F.K.,\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eand O.G.D. collected the data. A.C.K. performed the statistical analysis and\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ewrote the main manuscript text. E.K. supervised the study. M.C.G., O.D., F.K.,\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eand O.G.D. critically reviewed and edited the manuscript. All authors read and\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eapproved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank the nursing staff of the Emergency Department\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eof Istanbul Training and Research Hospital for their assistance with patient\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eenrollment and data collection.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eCollet JP, Thiele H, Barbato E, et al. 2020 ESC Guidelines for the management of acute coronary syndromes in patients presenting without persistent ST-segment elevation. Eur Heart J. 2021;42(14):1289\u0026ndash;367.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKola M, Shuka N, Meyers HP, Zaimi E, Smith SW. OMI/NOMI: Time for a New Classification of Acute Myocardial Infarction. J Clin Med. 2024;13(17):5201.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAladio JM, Costa D, Matsudo M, Perez de la Hoz A, Gonzalez D, Brignoli A et al. Cortisol-Mediated Stress Response and Mortality in Acute Coronary Syndrome. Curr Probl Cardiol. 2020;100623.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRoffi M, Patrono C, Collet JP, Mueller C, Valgimigli M, Andreotti F, ESC Scientific Document Group, et al. 2015 ESC Guidelines for the management of acute coronary syndromes in patients presenting without persistent ST-segment elevation: Task Force for the Management of Acute Coronary Syndromes in Patients Presenting without Persistent ST-Segment Elevation of the European Society of Cardiology (ESC). Eur Heart J. 2016;37:267\u0026ndash;315.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBing R, Goodman SG, Yan AT, Fox K, Gale CP, Hyun K, et al. Use of clinical risk stratification in non-ST elevation acute coronary syndromes: an analysis from the CONCORDANCE registry. Eur Heart J Qual Care Clin Outcomes. 2018;4:309\u0026ndash;17.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFox KAA, Dabbous OH, Goldberg RJ, et al. Prediction of risk of death and myocardial infarction in the six months after presentation with acute coronary syndrome: prospective multinational observational study (GRACE). BMJ. 2006;333(7578):1091.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMueller C, Giannitsis E, Mockel M, Huber K, Mair J, Plebani M, et al. Rapid rule out of acute myocardial infarction: novel biomarker-based strategies. Eur Heart J Acute Cardiovasc Care. 2017;6:218\u0026ndash;22.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eM\u0026ouml;ckel M, Giannitsis E, Mueller C, Huber K, Jaffe AS, Mair J, et al. editors. 's choice\u0026mdash;rule-in of acute myocardial infarction: focus on troponin. Eur Heart J Acute Cardiovasc Care. 2017;6:212\u0026ndash;217.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKaier TE, Twerenbold R, Puelacher C, Marjot J, Imambaccus N, Boeddinghaus J, et al. Direct comparison of cardiac myosin-binding protein C with cardiac troponins for the early diagnosis of acute myocardial infarction. Circulation. 2017;136:1495\u0026ndash;508.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eThygesen K, Alpert JS, Jaffe AS, et al. Fourth universal definition of myocardial infarction. Circulation. 2018;138(20):e618\u0026ndash;51.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBhat T, Teli S, Rijal J, et al. Neutrophil to lymphocyte ratio and cardiovascular diseases: a review. Expert Rev Cardiovasc Ther. 2013;11(1):55\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKhan AR, Golwala H, Tripathi A, Bin Abdulhak AA, Bavishi C, Riaz H, et al. Impact of total occlusion of culprit artery in acute non-ST elevation myocardial infarction: a systematic review and meta-analysis. Eur Heart J. 2017;38(41):3082\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAslanger E, Yıldırımt\u0026uuml;rk \u0026Ouml;, Şimşek B, Sungur A, T\u0026uuml;rer Cabbar A, Bozbeyoğlu E, et al. A new electrocardiographic pattern indicating inferior myocardial infarction. J Electrocardiol. 2020;61:41\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchulte KJ, Mayrovitz HN. Myocardial Infarction Signs and Symptoms: Females vs. Males Cureus. 2023;15(4):e37522.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eArmillotta M, Amicone S, Bergamaschi L, Angeli F, Rinaldi A, Paolisso P, et al. Predictive value of Killip classification in MINOCA patients. Eur J Intern Med. 2023;117:57\u0026ndash;65.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ede Carvalho LP, Gao F, Chen Q, Sim LL, Koh TH, Foo D, et al. Long-term prognosis and risk heterogeneity of heart failure complicating acute myocardial infarction. Am J Cardiol. 2015;115(7):872\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZafrir B, Hussein S, Jaffe R, Barnett-Griness O, Saliba W. Lymphopenia and mortality among patients undergoing coronary angiography: Long-term follow-up study. Cardiol J. 2022;29(4):637\u0026ndash;46.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-emergency-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"emmd","sideBox":"Learn more about [BMC Emergency Medicine](http://bmcemergmed.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/emmd","title":"BMC Emergency Medicine","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"NSTEMI, Serum cortisol, Emergency department, Occlusion myocardial infarction, Risk stratification, Neutrophil-to-lymphocyte ratio","lastPublishedDoi":"10.21203/rs.3.rs-8948593/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8948593/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground/Objective:\u003c/h2\u003e \u003cp\u003eRisk stratification in non-ST-segment elevation myocardial infarction (NSTEMI) relies heavily on clinical parameters, while the prognostic utility of acute stress hormones remains unclear. This study aimed to evaluate the value of serum cortisol levels measured at emergency department (ED) presentation in predicting 30-day mortality and differentiating occlusion myocardial infarction (OMI) from non-occlusion myocardial infarction (NOMI).\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis prospective observational cohort study included 150 consecutive patients presenting to a tertiary ED diagnosed with NSTEMI who underwent coronary angiography. Serum cortisol levels were measured upon admission. Patients were classified into OMI (TIMI 0\u0026ndash;2, or TIMI 3 with specific criteria) and NOMI (TIMI 3) groups based on angiographic findings. The primary outcome was 30-day all-cause mortality.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe cohort (mean age 59.9\u0026thinsp;\u0026plusmn;\u0026thinsp;11.8 years; 71.3% male) comprised 125 (83.3%) OMI and 25 (16.7%) NOMI cases. 30-day mortality occurred in 8 (5.3%) patients. Median admission serum cortisol levels did not significantly differ between survivors and non-survivors (10.1 vs. 12.5 \u0026micro;g/dL, p\u0026thinsp;=\u0026thinsp;0.298) or between the OMI and NOMI groups (10.2 vs. 10.8 \u0026micro;g/dL, p\u0026thinsp;=\u0026thinsp;0.803). Conversely, mortality was significantly associated with elevated neutrophil-to-lymphocyte ratio (NLR) (p\u0026thinsp;=\u0026thinsp;0.016), lymphopenia (p\u0026thinsp;=\u0026thinsp;0.012), hypertension (p\u0026thinsp;=\u0026thinsp;0.013), and higher GRACE scores (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Notably, the NOMI cohort had a significantly higher proportion of female patients compared to the OMI group (48.0% vs. 24.8%, p\u0026thinsp;=\u0026thinsp;0.019).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eAdmission serum cortisol levels do not provide incremental diagnostic or prognostic value for OMI/NOMI differentiation or mortality prediction in NSTEMI patients. Routine clinical risk scores (GRACE) and hematological inflammatory indices (NLR, lymphopenia) offer significantly superior reliability. Therefore, routine cortisol measurement is not indicated for risk stratification in the fast-paced acute ED setting.\u003c/p\u003e","manuscriptTitle":"Routine Serum Cortisol Does Not Predict Mortality or OMI/NOMI Differentiation in NSTEMI: A Prospective Emergency Department Cohort Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-01 06:03:43","doi":"10.21203/rs.3.rs-8948593/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-05-15T11:43:50+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-14T17:54:11+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"321509616399976048755362245670680140862","date":"2026-05-09T05:21:54+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-05T19:39:21+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"208314906050084119943695702931772405890","date":"2026-05-03T08:08:01+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"261658396547529836073775866526010573515","date":"2026-05-02T14:43:39+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-02T06:11:24+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-30T07:36:02+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"3935421912253448048044513006517691011","date":"2026-04-28T07:43:45+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"142279670135195077177041548272431863295","date":"2026-04-26T21:39:24+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"88394177802102649850040129879809042516","date":"2026-04-24T21:02:15+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"208251518913502788588144035242930571231","date":"2026-04-22T01:39:00+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-27T12:15:40+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-12T03:58:31+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-03-03T04:49:57+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-28T16:21:15+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Emergency Medicine","date":"2026-02-28T16:14:12+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-emergency-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"emmd","sideBox":"Learn more about [BMC Emergency Medicine](http://bmcemergmed.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/emmd","title":"BMC Emergency Medicine","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"fbe165fd-00c9-420a-99b9-c810b534f7ce","owner":[],"postedDate":"April 1st, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-15T11:43:50+00:00","index":213,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-14T17:54:11+00:00","index":212,"fulltext":""},{"type":"reviewerAgreed","content":"321509616399976048755362245670680140862","date":"2026-05-09T05:21:54+00:00","index":211,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-05T19:39:21+00:00","index":209,"fulltext":""},{"type":"reviewerAgreed","content":"208314906050084119943695702931772405890","date":"2026-05-03T08:08:01+00:00","index":203,"fulltext":""},{"type":"reviewerAgreed","content":"261658396547529836073775866526010573515","date":"2026-05-02T14:43:39+00:00","index":200,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-02T06:11:24+00:00","index":181,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-30T07:36:02+00:00","index":174,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-01T06:03:43+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-01 06:03:43","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8948593","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8948593","identity":"rs-8948593","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}