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Thyroid stimulating hormone elevation as a predictor of long-term mortality in patients with acute myocardial infarction.

ABSTRACT: BACKGROUND:Hypothyroidism has been known to be associated with hyperlipidemia, endothelial dysfunction and atherosclerosis. Elevation of thyroid-stimulation hormone (TSH) is a gold standard to detect these conditions. However, no large studies have investigated the association between TSH elevation and long-term clinical outcomes in patients with acute myocardial infarction (AMI). HYPOTHESIS:Hypothyroidism is associated with higher mortality in patients with AMI. METHODS:A total of 4748 AMI patients undergoing percutaneous coronary intervention (PCI) with drug-eluting stents were consecutively enrolled. We analyzed 1977 patients whose thyroid function data available after the exclusion of hyperthyroidism and possible central hypothyroidism. Patients were divided into two groups; euthyroid group (n = 1846) with normal TSH and normal free thyroxine (FT4); hypothyroidism group (n = 131) with elevated TSH and normal or low FT4. The two groups were subsequently compared with their all-cause and cardiac mortalities. RESULTS:Median follow-up duration was 3.5 years. Hypothyroidism group were older, included in more females, and had higher incidences of atrial fibrillation, stroke, and renal dysfunction. Elevated TSH was associated with significantly higher all-cause mortality (26.0% vs 11.7%, P < 0.0001) and cardiac mortality (9.2% vs 4.6%, P = 0.014). The multivariate Cox proportional hazards model identified that TSH elevation was a significant predictor of all-cause mortality (adjusted hazard ratio 1.560, 95% confidence interval 1.017 to 2.392, P = 0.041). CONCLUSIONS:Our data suggest that AMI patients with TSH elevation had worse clinical outcome. Moreover, TSH elevation was a predictor of all-cause mortality in patients with AMI.

SUBMITTER: Seo SM

PROVIDER: S-EPMC6489767 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature

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Thyroid stimulating hormone elevation as a predictor of long-term mortality in patients with acute myocardial infarction.

Seo Suk Min SM Koh Yoon-Seok YS Park Hun-Jun HJ Kim Dong Bin DB Her Sung Ho SH Lee Jong Min JM Park Chul Soo CS Kim Pum-Joon PJ Kim Hee Yeol HY Yoo Ki Dong KD Jeon Doo Soo DS Ahn Young Keun YK Jeong Myung Ho MH Chung Wook Sung WS Seung Ki-Bae KB

Clinical cardiology 20181016 10

<h4>Background</h4>Hypothyroidism has been known to be associated with hyperlipidemia, endothelial dysfunction and atherosclerosis. Elevation of thyroid-stimulation hormone (TSH) is a gold standard to detect these conditions. However, no large studies have investigated the association between TSH elevation and long-term clinical outcomes in patients with acute myocardial infarction (AMI).<h4>Hypothesis</h4>Hypothyroidism is associated with higher mortality in patients with AMI.<h4>Methods</h4>A ...[more]

PMID: 30144126

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Project description:BackgroundConventional risk score for predicting short and long-term mortality following an ST-segment elevation myocardial infarction (STEMI) is often not population specific.ObjectiveApply machine learning for the prediction and identification of factors associated with short and long-term mortality in Asian STEMI patients and compare with a conventional risk score.MethodsThe National Cardiovascular Disease Database for Malaysia registry, of a multi-ethnic, heterogeneous Asian population was used for in-hospital (6299 patients), 30-days (3130 patients), and 1-year (2939 patients) model development. 50 variables were considered. Mortality prediction was analysed using feature selection methods with machine learning algorithms and compared to Thrombolysis in Myocardial Infarction (TIMI) score. Invasive management of varying degrees was selected as important variables that improved mortality prediction.ResultsModel performance using a complete and reduced variable produced an area under the receiver operating characteristic curve (AUC) from 0.73 to 0.90. The best machine learning model for in-hospital, 30 days, and 1-year outperformed TIMI risk score (AUC = 0.88, 95% CI: 0.846-0.910; vs AUC = 0.81, 95% CI:0.772-0.845, AUC = 0.90, 95% CI: 0.870-0.935; vs AUC = 0.80, 95% CI: 0.746-0.838, AUC = 0.84, 95% CI: 0.798-0.872; vs AUC = 0.76, 95% CI: 0.715-0.802, p < 0.0001 for all). TIMI score underestimates patients' risk of mortality. 90% of non-survival patients are classified as high risk (>50%) by machine learning algorithm compared to 10-30% non-survival patients by TIMI. Common predictors identified for short- and long-term mortality were age, heart rate, Killip class, fasting blood glucose, prior primary PCI or pharmaco-invasive therapy and diuretics. The final algorithm was converted into an online tool with a database for continuous data archiving for algorithm validation.ConclusionsIn a multi-ethnic population, patients with STEMI were better classified using the machine learning method compared to TIMI scoring. Machine learning allows for the identification of distinct factors in individual Asian populations for better mortality prediction. Ongoing continuous testing and validation will allow for better risk stratification and potentially alter management and outcomes in the future.

Project description:ObjectivesThis study sought to determine the association of chronic stress with long-term adverse outcomes after acute myocardial infarction (AMI).BackgroundChronic stress has been shown to be associated with the development of cardiovascular disease and, in the case of particular types of stress such as job and marital strain, with recurrent adverse events after AMI. Little is known, however, about the association of chronic stress with mortality and adverse health status outcomes in a general AMI population.MethodsIn a cohort of 4,204 AMI patients from 24 U.S. hospitals completing the Perceived Stress Scale-4 (sum scores ranging from 0 to 16) during hospitalization, moderate/high stress over the previous month was defined as scores in the top 2 quintiles (scores of 6 to 16). Detailed data on sociodemographics, psychosocial status, and clinical characteristics were collected at baseline. Outcomes included patients' 1-year health status, assessed with the Seattle Angina Questionnaire, Short Form-12, and EuroQol Visual Analog Scale, and 2-year mortality.ResultsAMI patients with moderate/high stress had increased 2-year mortality compared with those having low levels of stress (12.9% vs. 8.6%; p < 0.001). This association persisted after adjusting for sociodemographics, clinical factors (including depressive symptoms), revascularization status, and GRACE (Global Registry of Acute Coronary Events) discharge risk scores (hazard ratio: 1.42: 95% confidence interval: 1.15 to 1.76). Furthermore, moderate/high stress was independently associated with poor 1-year health status, including a greater likelihood of angina, worse disease-specific and generic health status, and worse perceived health (p < 0.01 for all).ConclusionsModerate/high perceived stress at the time of an AMI is associated with adverse long-term outcomes, even after adjustment for important confounding factors. Future studies need to examine whether stress mediates observed racial and socioeconomic disparities and whether novel interventions targeting chronic stress and coping skills can improve post-AMI outcomes.

Dataset Information

Thyroid stimulating hormone elevation as a predictor of long-term mortality in patients with acute myocardial infarction.

Publications

Thyroid stimulating hormone elevation as a predictor of long-term mortality in patients with acute myocardial infarction.

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