Combining glucose and high-sensitivity cardiac troponin in the early diagnosis of acute myocardial infarction

Glucose is a universally available inexpensive biomarker, which is increased as part of the physiological stress response to acute myocardial infarction (AMI) and may therefore help in its early diagnosis. To test this hypothesis, glucose, high-sensitivity cardiac troponin (hs-cTn) T, and hs-cTnI were measured in consecutive patients presenting with acute chest discomfort to the emergency department (ED) and enrolled in a large international diagnostic study (NCT00470587). Two independent cardiologists centrally adjudicated the final diagnosis using all clinical data, including serial hs-cTnT measurements, cardiac imaging and clinical follow-up. The primary diagnostic endpoint was index non-ST-segment elevation MI (NSTEMI). Prognostic endpoints were all-cause death, and cardiovascular (CV) death or future AMI, all within 730-days. Among 5639 eligible patients, NSTEMI was the adjudicated final diagnosis in 1051 (18.6%) patients. Diagnostic accuracy quantified using the area under the receiver-operating characteristics curve (AUC) for the combination of glucose with hs-cTnT and glucose with hs-cTnI was very high, but not higher versus that of hs-cTn alone (glucose/hs-cTnT 0.930 [95% CI 0.922–0.937] versus hs-cTnT 0.929 [95% CI 0.922–0.937]; glucose/hs-cTnI 0.944 [95% CI 0.937–0.951] versus hs-cTnI 0.944 [95% CI 0.937–0.951]). In early-presenters, a dual-marker strategy (glucose < 7 mmol/L and hs-cTnT < 5/hs-cTnI < 4 ng/L) provided very high and comparable sensitivity to slightly lower hs-cTn concentrations (cTnT/I < 4/3 ng/L) alone, and possibly even higher efficacy. Glucose was an independent predictor of 730-days endpoints. Our results showed that a dual marker strategy of glucose and hs-cTn did not increase the diagnostic accuracy when used continuously. However, a cutoff approach combining glucose and hs-cTn may provide diagnostic utility for patients presenting ≤ 3 h after onset of symptoms, also providing important prognostic information.


Clinical Assessment
Routine clinical assessment and patient management has been described in detail previously 1 .The estimated glomerular filtration rate (eGFR) was determined using the chronic kidney disease epidemiology collaboration (CKD-MDRD) formula 2 .

Blood sampling and laboratory methods
Glucose levels were measured from routine blood samples obtained at ED presentation on the clinical chemistry platform of each participating hospital.Blood sampling and methods for the determination of hs-cTnT (Elecsys) and hs-cTnI (Architect) concentrations have been previously reported 1,[3][4][5] .

Follow-up
Patients were interviewed by telephone or in written form after 3, 12 and 24 months.
Contact was established with the patient and the family physician.Information regarding mortality was also obtained from the national death registries, the electronic medical record of the hospital or family physicians records.

Statistical analysis
To evaluate whether the presence of diabetes could be an effect modifier of glucose, an interaction between glucose and diabetes was fitted.Considering the low number of events in each subgroup (diabetic/non-diabetic patients) for 30-days (short term) and to avoid overfitting, the interaction was only assessed for 2-year outcomes.To compute the hazard ratios (Y-axis) the reference was a glucose value of 5.6 mmol/L and non-diabetic.
The multivariable model had the same covariates used for the main analysis.The only difference was the interaction.Hence, a likelihood ratio test for nested models was used for evaluating the interaction between glucose and diabetes.In addition, effect modification of diabetes was assessed visually with dose-response plots.
Both prognostic outcomes (all-cause mortality and the composite of cardiovascular death and AMI) were plotted in Kaplan-Meier curves for 30 days and 730-days followup time according to hs-cTn and glucose baseline concentrations.The log rank test was used to assess differences between groups: • Group 1: hs-cTn concentrations below the 99 th percentile and glucose concentrations below 5.6 mmol/L.
• Group 3: hs-cTn concentrations over the 99 th percentile and glucose concentrations below 5.6mmol/L.
Cross-sectional study-Report numbers of outcome events or summary measures N.A.
Main results 16 (a) Give unadjusted estimates and, if applicable, confounder-adjusted estimates and their precision (eg, 95% confidence interval).Make clear which confounders were adjusted for and why they were included 10-14, Fig. 3 Fig. S1 NSTEMI= non-ST elevation myocardial infarction, SBP= systolic blood pressure, CPO = chest pain onset, DBP= diastolic blood pressure, CAD= coronary artery disease, AMI= acute myocardial infarction, ACE-inhibitor= angiotensin-converting-enzyme inhibitor, ARB= angiotensin receptor blocker, GFR-MDRD= glomerular filtration rate-modification of diet in renal disease equation.Supplementary Figure S2.ESC 0/1h hs-cTn Algorithm and concept outlining on how the 0h glucose concentration could be used in combination with the ESC 0/1h-algorithm.0h hs-cTnT < 5ng/L* OR 0h hs-cTnT <12ng/L and Delta hs-cTnT 0-1h <3ng/L 0h hs-cTnT ≥ 52ng/L OR Delta hs-cTnT 0-1h ≥ 5ng0h hs-cTnT < 5ng/L and 0h Glucose <5.6mmol/L * OR 0h hs-cTnT <12ng/L and Delta hs-cTnT 0-1h <3ng/L and 0h Glucose <5.6 mmol/L 0h hs-cTnT ≥ 52ng/L OR Glucose ≥ 11.1 mmol/L OR Delta hs-cTnT 0-1h ≥ 5ngindicates non-ST-Elevation myocardial infarction; hs-cTnT indicates high sensitivity cardiac troponin T; hs-cTnI indicates high sensitivity cardiac troponin I. Observe Rule-in Rule-out 0h hs-cTnI < 4ng/L* OR 0h hs-cTnI <5ng/L and Delta hs-cTnI 0-1h <2ng/L 0h hs-cTnI ≥ 64ng/L OR Delta hs-cTnI 0-1h ≥ 6ng0h hs-cTnT < 4ng/L and 0h Glucose <5.6mmol/L * OR 0h hs-cTnT <5ng/L and Delta hs-cTnT 0-1h <2ng/L and 0h Glucose <5.6 mmol/L 0h hs-cTnT ≥ 64ng/L OR Glucose ≥ 11.1 mmol/L OR Delta hs-cTnT 0-1h ≥ 6ng Cohort Cohort study-If applicable, explain how loss to follow-up was addressed Case-control study-If applicable, explain how matching of cases and controls was addressed Cross-sectional study-If applicable, describe analytical methods taking account of sampling strategy study-Give the eligibility criteria, and the sources and methods of selection of participants.Describe methods of follow-up Case-control study-Give the eligibility criteria, and the sources and methods of case ascertainment and control selection.Give the rationale for the choice of cases and controls Cross-sectional study-Give the eligibility criteria, and the sources and methods of selection of participants 4 + S.4 (b) Cohort study-For matched studies, give matching criteria and number of exposed and unexposed Case-control study-For matched studies, give matching criteria and the number of controls per case N.A. a) Report numbers of individuals at each stage of study-eg numbers potentially eligible, examined for eligibility, confirmed eligible, included in the study, completing follow-up, and analysed

Table 2 .
Baseline Characteristics of patients with and without NSTEMI of funding and the role of the funders for the present study and, if applicable, for the original study on which the present article is based 19 *Give information separately for cases and controls in case-control studies and, if applicable, for exposed and unexposed groups in cohort and cross-sectional studies.SupplementaryMan-Whitney U test for continuous variables (not normal distributed), expressed in medians and interquartile range (IQR) and Chi-square test for categorical variables, expressed in numbers and percentages.