Twenty Year Trends and Sex Differences in Young Adults Hospitalized With Acute Myocardial Infarction

Arora, Sameer; Stouffer, George A.; Kucharska‐Newton, Anna; Qamar, Arman; Vaduganathan, Muthiah; Pandey, Ambarish; Porterfield, Deborah S; Blankstein, Ron; Rosamond, Wayne D.; Bhatt, Deepak L.; Caughey, Melissa C.

doi:10.1161/circulationaha.118.037137

Cited by 515 publications

(359 citation statements)

References 36 publications

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“…Among patients with type 2 diabetes, which comprises more than 90% of all diabetes cases, women with type 2 diabetes were shown to be more likely obese, hypertensive and have hypercholesterolaemia but were less likely to be prescribed lipid-lowering medication and antihypertensive drugs, especially if they had cardiovascular disease in comparison with men [50]. Moreover, it was shown that admissions for acute myocardial infarctions steadily increased in the last two decades especially in younger patients whose history of diabetes and hypertension increased in parallel [51]. The proportion attributable to younger women was particularly high who also had lower probability of receiving guideline-directed therapy.…”

Section: Discussionmentioning

confidence: 99%

High-risk multimorbidity patterns on the road to cardiovascular mortality

Haug

Deischinger

Gyimesi

et al. 2020

BMC Med

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Background: Multimorbidity, the co-occurrence of two or more diseases in one patient, is a frequent phenomenon. Understanding how different diseases condition each other over the lifetime of a patient could significantly contribute to personalised prevention efforts. However, most of our current knowledge on the long-term development of the health of patients (their disease trajectories) is either confined to narrow time spans or specific (sets of) diseases. Here, we aim to identify decisive events that potentially determine the future disease progression of patients. Methods: Health states of patients are described by algorithmically identified multimorbidity patterns (groups of included or excluded diseases) in a population-wide analysis of 9,000,000 patient histories of hospital diagnoses observed over 17 years. Over time, patients might acquire new diagnoses that change their health state; they describe a disease trajectory. We measure the age-and sex-specific risks for patients that they will acquire certain sets of diseases in the future depending on their current health state. Results: In the present analysis, the population is described by a set of 132 different multimorbidity patterns. For elderly patients, we find 3 groups of multimorbidity patterns associated with low (yearly in-hospital mortality of 0.2-0.3%), medium (0.3-1%) and high in-hospital mortality (2-11%). We identify combinations of diseases that significantly increase the risk to reach the high-mortality health states in later life. For instance, in men (women) aged 50-59 diagnosed with diabetes and hypertension, the risk for moving into the high-mortality region within 1 year is increased by the factor of 1.96 ± 0.11 (2.60 ± 0.18) compared with all patients of the same age and sex, respectively, and by the factor of 2.09 ± 0.12 (3.04 ± 0.18) if additionally diagnosed with metabolic disorders. Conclusions: Our approach can be used both to forecast future disease burdens, as well as to identify the critical events in the careers of patients which strongly determine their disease progression, therefore constituting targets for efficient prevention measures. We show that the risk for cardiovascular diseases increases significantly more in females than in males when diagnosed with diabetes, hypertension and metabolic disorders.

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Section: Discussionmentioning

confidence: 99%

High-risk multimorbidity patterns on the road to cardiovascular mortality

Haug

Deischinger

Gyimesi

et al. 2020

BMC Med

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“…Acute myocardial infarction (AMI), a serious form of coronary artery disease (CAD), is a significant cause of death worldwide, particularly in the elderly population [1]. Actually, the elderly AMI patients who may have poor prognosis could be greatly improved by timely and appropriate intervention measures [2].…”

Section: Introductionmentioning

confidence: 99%

Neutrophil to high-density lipoprotein ratio has a superior prognostic value in elderly patients with acute myocardial infarction: a comparison study

Huang

Chen

et al. 2020

Lipids Health Dis

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Background: The importance of the lipid-related biomarkers has been implicated in the pathological process and prognosis of acute myocardial infarction (AMI). Our work was conducted to discuss and compare the predictive ability of the neutrophil to high-density lipoprotein cholesterol (HDL-C) ratio (NHR) with other existing prognostic indices, for instance, the monocyte to HDL-C ratio (MHR) and the low-density lipoprotein cholesterol (LDL-C) to HDL-C ratio (LDL-C/HDL-C) in elderly patients with AMI. Methods: Our population was 528 consecutive elderly AMI patients (65-85 years) who were enrolled from Tongji Hospital and grouped according to the cutoff points which were depicted by the receiver operating characteristic (ROC). The Kaplan-Meier curves were plotted with the survival data from the follow-up to investigate the difference between cutoff point-determined groups. Moreover, we assessed the impact of NHR, MHR, LDL-C/HDL-C on the long-term mortality and recurrent myocardial infarction (RMI) with Cox proportional hazard models. Results: Mean duration of follow-up was 673.85 ± 14.32 days (median 679.50 days). According to ROC curve analysis, NHR ≥ 5.74, MHR ≥ 0.67, LDL-C/HDL-C ≥ 3.57 were regarded as high-risk groups. Kaplan-Meier analysis resulted that the high-NHR, high-MHR and high-LDL-C/HDL-C groups presented higher mortality and RMI rate than the corresponding low-risk groups in predicting the long-term clinical outcomes (log-rank test: all P < 0.050). In multivariate analysis, compared with MHR and LDL-C/HDL-C, only NHR was still recognized as a latent predictor for long-term mortality (harzard ratio [HR]: 1.96, 95% confidence interval [CI]: 1.02 to 3.75, P = 0.044) and long-term RMI (HR: 2.23, 95% CI: 1.04 to 4.79, P = 0.040). Furthermore, the positive correlation between NHR and Gensini score (r = 0.15, P < 0.001) indicated that NHR was relevant to the severity of coronary artery to some extent.

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“…1 The number is estimated to triplicate by 2050 due to population aging and increase of cardiovascular diseases in younger population, related to adverse health behaviors. [1][2][3][4] Currently, there are different options for heart valve replacement therapy; the most commonly applied are mechanical and bio-prosthetic heart valves. Despite both heart valve therapies have good durability and hemodynamic performances in older patients, they present critical disadvantages which prevent their use for the treatment of young patients' dysfunctions.…”

Section: Introductionmentioning

confidence: 99%