Dataset Information

Is admission blood glucose concentration a more powerful predictor of mortality after myocardial infarction than diabetes diagnosis? A retrospective cohort study.

ABSTRACT:

Objective

To explore the relative association of admission blood glucose levels and antecedent diabetes on early and long-term survival in a contemporary UK population of patients with ST elevation myocardial infarction (STEMI) and non-STEMI (NSTEMI).

Design

Retrospective cohort study based on the Myocardial Ischaemia National Audit Project dataset.

Setting

Tertiary care centre.

Participants

4111 (20.3% known diabetes) consecutive patients admitted with acute myocardial infarction (58.3% STEMI) between October 2002 and September 2008.

Primary and secondary outcome measures

All-cause mortality at 30 days and 1 year. The relative association of admission blood glucose and of antecedent diabetes with mortality was assessed using multivariate Cox regression analysis. Furthermore, we compared these relationships in patients with STEMI to those with NSTEMI.

Results

By 30 days and 1 year, 409 (9.9%) and 677 (16.5%) of patients died. After adjusting for covariates, diabetes did not show independent association with mortality at any time point, in the entire cohort (HR 30 days 0.93 (95% CI 0.63 to 1.38); 1 year 1.00 (0.77 to 1.30)) or in subgroups of STEMI (HR 30 days 1.03 (0.65 to 1.64); 1 year 1.08 (0.77 to 1.51)) and NSTEMI (HR 30 days 0.62 (0.26 to 1.50); 1 year 0.87 (0.56 to 1.36)). In contrast, after adjusting for covariates, admission glucose showed robust and independent association with mortality in the entire cohort (HR: 30 days 1.07 (1.04 to 1.10); 1 year 1.05 (1.03 to 1.08)), and in the subgroup of STEMI (30 days 1.07 (1.03 to 1.10); 1 year 1.07 (1.04 to 1.10)), and NSTEMI (HR 30 days 1.07 (1.00 to 1.14); 1 year 1.02 (0.97 to 1.06)).

Conclusions

Admission glucose is strongly associated with mortality in all presentations of acute myocardial infarction (AMI), irrespective of established diabetes diagnosis. The increased risk is maintained up to 1 year. Future studies are required to assess the impact of active management of elevated blood glucose in improving mortality in individuals admitted with AMI.

SUBMITTER: Gholap NN

PROVIDER: S-EPMC3467654 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Is admission blood glucose concentration a more powerful predictor of mortality after myocardial infarction than diabetes diagnosis? A retrospective cohort study.

Gholap Nitin Narayan NN Mehta Rajnikant Laxmishanker RL Ng Leong L Davies Melanie J MJ Khunti Kamlesh K Squire Iain B IB

BMJ open 20120925 5

<h4>Objective</h4>To explore the relative association of admission blood glucose levels and antecedent diabetes on early and long-term survival in a contemporary UK population of patients with ST elevation myocardial infarction (STEMI) and non-STEMI (NSTEMI).<h4>Design</h4>Retrospective cohort study based on the Myocardial Ischaemia National Audit Project dataset.<h4>Setting</h4>Tertiary care centre.<h4>Participants</h4>4111 (20.3% known diabetes) consecutive patients admitted with acute myocard ...[more]

PMID: 23015602

Similar Datasets

Project description:Background Dysglycemia at acute myocardial infarction (AMI) is common and is associated with mortality. Information on other outcomes is less well explored in patients without diabetes in a long-term perspective. We aimed to explore the relationship between admission glucose level and long-term outcomes in patients with AMI without diabetes in a nationwide setting. Methods and Results Patients without diabetes (n=45 468) with AMI registered in SWEDEHEART (Swedish Web-System for Enhancement and Development of Evidence-Based Care in Heart Disease Evaluated According to Recommended Therapies) and admission glucose ≤11 mmol/L (≤198 mg/dL) were followed for outcomes (AMI, heart failure, stroke, renal failure, and death) between 2012 and 2017 (mean follow-up time 3.3±1.7 years). The association between categorized glucose levels and outcomes was assessed in adjusted Cox proportional hazards regression analyses (glucose levels 4.0-6.0 mmol/L [72-109 mg/dL] as reference). Further nonfatal complications and their associated mortality were explored (patients without events served as a reference). A glucose level of 7.8-11.0 mmol/L (140-198 mg/dL) was associated with hospitalization for heart failure (hazard ratio [HR] 1.40 [95% CI, 1.30-1.51], P<0.001), renal failure (1.17; 1.04-1.33, P=0.009), and death (1.31; 1.20-1.43, P<0.001), but not with recurrent myocardial infarction (0.99; 0.92-1.07, P=0.849) or stroke (1.03; 0.88-1.19, P=0.742). Renal failure had the strongest association with future mortality (age-adjusted HR 4.93 [95% CI, 4.34-5.60], P<0.001), followed by heart failure (3.71; 3.41-4.04, P<0.001), stroke (3.39; 2.94-3.91, P<0.001), and myocardial infarction (2.08; 1.88-2.30, P<0.001). Conclusions Elevated glucose levels at AMI admission identifies patients without diabetes at increased risk of long-term complications: in particular, hospitalization for heart and renal failure. These results emphasize that glucose levels at admission could be useful in risk assessment after myocardial infarction.

Project description:PurposePeripheral differential leukocyte counts are accepted prognostic indicators in patients with acute myocardial infarction (AMI). Herein, we assessed the value of the admission (neutrophil+monocyte)/lymphocyte ratio (NMLR) in predicting in-hospital mortality in these patients.Materials and methodsSamples of patients from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database meeting the criteria were included. Receiver operating characteristic (ROC) curves were plotted to explore the predictive value and the optimum cut-off value of admission NMLR. Univariate and multivariate Cox regression analyses and restricted cubic spline (RCS) were performed to determine and visualize the association between admission NMLR and in-hospital mortality. The Kaplan-Meier (KM) method was used to plot survival curves of two groups with different admission NMLR levels.ResultsSamples in the non-survival group had higher admission NMLR values than samples in the survival group (12.11 [7.22-21.05] vs. 6.38 [3.96-11.25], P < 0.05). The area under the ROC curve (AUROC) [0.707 (95% Confidence Interval, 0.677-0.737)] was significantly better than those of other indicators related to peripheral differential leukocyte counts, and the optimal cut-off value was 8.518. Cox regression analysis identified that higher admission NMLR was an independent risk factor for in-hospital mortality. RCS visualized the uptrend and the non-linear relationship between admission NMLR and in-hospital mortality (P-value for non-linearity <0.05). The KM survival curve of the high admission NMLR group was significantly lower than that of the low admission NMLR group (P < 0.001), and the former was associated with an increased risk of in-hospital mortality compared to the latter (Hazard Ratio, 1.452; 95% Confidence Interval, 1.132-1.862; P < 0.05).ConclusionAn elevated admission NMLR is an independent predictor for high in-hospital mortality in patients with AMI. And it is superior to other leukocyte-related indexes.

Project description:BackgroundIn suspected myocardial infarction (MI), guidelines recommend using high-sensitivity cardiac troponin (hs-cTn)-based approaches. These require fixed assay-specific thresholds and timepoints, without directly integrating clinical information. Using machine-learning techniques including hs-cTn and clinical routine variables, we aimed to build a digital tool to directly estimate the individual probability of MI, allowing for numerous hs-cTn assays.MethodsIn 2,575 patients presenting to the emergency department with suspected MI, two ensembles of machine-learning models using single or serial concentrations of six different hs-cTn assays were derived to estimate the individual MI probability (ARTEMIS model). Discriminative performance of the models was assessed using area under the receiver operating characteristic curve (AUC) and logLoss. Model performance was validated in an external cohort with 1688 patients and tested for global generalizability in 13 international cohorts with 23,411 patients.ResultsEleven routinely available variables including age, sex, cardiovascular risk factors, electrocardiography, and hs-cTn were included in the ARTEMIS models. In the validation and generalization cohorts, excellent discriminative performance was confirmed, superior to hs-cTn only. For the serial hs-cTn measurement model, AUC ranged from 0.92 to 0.98. Good calibration was observed. Using a single hs-cTn measurement, the ARTEMIS model allowed direct rule-out of MI with very high and similar safety but up to tripled efficiency compared to the guideline-recommended strategy.ConclusionWe developed and validated diagnostic models to accurately estimate the individual probability of MI, which allow for variable hs-cTn use and flexible timing of resampling. Their digital application may provide rapid, safe and efficient personalized patient care.Trial registration numbersData of following cohorts were used for this project: BACC ( www.Clinicaltrialsgov ; NCT02355457), stenoCardia ( www.Clinicaltrialsgov ; NCT03227159), ADAPT-BSN ( www.australianclinicaltrials.gov.au ; ACTRN12611001069943), IMPACT ( www.australianclinicaltrials.gov.au , ACTRN12611000206921), ADAPT-RCT ( www.anzctr.org.au ; ANZCTR12610000766011), EDACS-RCT ( www.anzctr.org.au ; ANZCTR12613000745741); DROP-ACS ( https://www.umin.ac.jp , UMIN000030668); High-STEACS ( www.Clinicaltrialsgov ; NCT01852123), LUND ( www.Clinicaltrialsgov ; NCT05484544), RAPID-CPU ( www.Clinicaltrialsgov ; NCT03111862), ROMI ( www.Clinicaltrialsgov ; NCT01994577), SAMIE ( https://anzctr.org.au ; ACTRN12621000053820), SEIGE and SAFETY ( www.Clinicaltrialsgov ; NCT04772157), STOP-CP ( www.Clinicaltrialsgov ; NCT02984436), UTROPIA ( www.Clinicaltrialsgov ; NCT02060760).

Project description:BackgroundLittle is known about the role of interleukin (IL) in patients with acute myocardial infarction (MI), especially soluble IL-2 receptor (sIL-2R) and IL-8. We aim to evaluate, in MI patients, the predictive value of serum sIL-2R and IL-8 for future major adverse cardiovascular events (MACEs), and compare them with current biomarkers reflecting myocardial inflammation and injury.MethodsThis was a prospective, single-center cohort study. We measured serum concentrations of IL-1β, sIL-2R, IL-6, IL-8 and IL-10. Levels of current biomarkers for predicting MACEs were measured, including high-sensitivity C reactive protein, cardiac troponin T and N-terminal pro-brain natriuretic peptide. Clinical events were collected during 1-year and a median of 2.2 years (long-term) follow-up.ResultsTwenty-four patients (13.8%, 24/173) experienced MACEs during 1-year follow-up and 40 patients (23.1%, 40/173) during long-term follow-up. Of the five interleukins studied, only sIL-2R and IL-8 were independently associated with endpoints during 1-year or long-term follow-up. Patients with high sIL-2R or IL-8 levels (higher than the cutoff value) had a significantly higher risk of MACEs during 1-year (sIL-2R: HR 7.7, 3.3-18.0, p < 0.001; IL-8: HR 4.8, 2.1-10.7, p < 0.001) and long-term (sIL-2R: HR 7.7, 3.3-18.0, p < 0.001; IL-8: HR 4.8, 2.1-10.7, p < 0.001) follow-up. Receiver operator characteristic curve analysis regarding predictive accuracy for MACEs during 1-year follow-up showed that the area under the curve for sIL-2R, IL-8, sIL-2R combined with IL-8 was 0.66 (0.54-0.79, p = 0.011), 0.69 (0.56-0.82, p < 0.001) and 0.720 (0.59-0.85, p < 0.001), whose predictive value were superior to that of current biomarkers. The addition of sIL-2R combined with IL-8 to the existing prediction model resulted in a significant improvement in predictive power (p = 0.029), prompting a 20.8% increase in the proportion of correct classifications.ConclusionsHigh serum sIL-2R combined with IL-8 levels was significantly associated with MACEs during follow-up in patients with MI, suggesting that sIL-2R combined with IL-8 may be a helpful biomarker for identifying the increased risk of new cardiovascular events. IL-2 and IL-8 would be promising therapeutic targets for anti-inflammatory therapy.

Project description:BackgroundIt has not been verified whether there is a correlation between admission hyperlactatemia and outcomes in critically ill patients with acute myocardial infarction (AMI), especially in large data studies, which we aimed to do in this study.MethodsFor this retrospective study, we extracted analysis data from a famous online intensive care unit database, the Medical Information Mart for Intensive Care (MIMIC)-IV. Included patients were divided into four groups according to the serum lactate level on admission. Hospital mortality and mortality over time were the main outcomes. To explore the relationship between admission hyperlactatemia and outcomes in critically ill patients with AMI, logistic regression, Cox regression, Kaplan-Meier curves, and subgroup analyses were used.Results2171 patients matching the selection criteria were enrolled in this study. After adjusting for potential confounding factors, hyperlactatemia on admission contributed to increased short-term mortality in critically ill patients with AMI. The adjusted odds ratio for hospital mortality were 1.62, 3.46 and 5.28 in the mild, moderate, and severe hyperlactatemia groups (95% CI: 1.20-2.18, 2.15-5.58, and 2.20-12.70, respectively). The adjusted hazard ratio for 7-day and 30-day mortality were 1.99 and 1.35 (95% CI: 1.45-2.73 and 1.09-1.67) in the mild hyperlactatemia group, 3.33 and 2.31 (95% CI: 2.22-4.99 and 1.72-3.10) in the moderate hyperlactatemia group, 4.81 and 2.91 (95% CI: 2.86-8.08 and 1.88-4.50) in the severe hyperlactatemia group. The adjusted hazard ratio for 1-year and 5-year mortality were 2.03 and 1.93 (95% CI: 1.58-2.62 and 1.52-2.47) in the moderate hyperlactatemia group, 1.92 and 1.74 (95% CI: 1.28-2.89 and 1.17-2.59) in the severe hyperlactatemia group. Subgroup analyses indicated that the positive correlation between serum lactate level on admission and short-term mortality of critically ill patients with AMI was similar in the subgroups of cardiogenic shock and acute heart failure (P for interaction > 0.05).ConclusionHyperlactatemia, especially moderate and severe hyperlactatemia, on admission is closely related to higher short-term mortality incidence in critically ill patients with AMI. The relationship between serum lactate level on admission and short-term mortality of critical AMI patients is stable in subgroups of cardiogenic shock and acute heart failure.

Dataset Information

Is admission blood glucose concentration a more powerful predictor of mortality after myocardial infarction than diabetes diagnosis? A retrospective cohort study.

Objective

Design

Setting

Participants

Primary and secondary outcome measures

Results

Conclusions

Publications

Is admission blood glucose concentration a more powerful predictor of mortality after myocardial infarction than diabetes diagnosis? A retrospective cohort study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets