Knowledge of heart attack and stroke symptoms among US Native American Adults: a cross-sectional population-based study analyzing a multi-year BRFSS database

Hooser, Jared Van; Rouse, Krista L.; Meyer, Mandy L.; Siegler, Amanda M.; Fruehauf, Beth M.; Ballance, Elliot H.; Solberg, Sarah M.; Dibble, Michael J.; Lutfiyya, M. Nawal

doi:10.1186/s12889-020-8150-x

Cited by 8 publications

(4 citation statements)

References 37 publications

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“…Our study was conducted in patients living with diabetes and/or hypertension, and most of our participants were elderly. This is in contrast with previous studies [25][26][27] , in which they were population-based survey's; therefore, reporting on younger aged participants. Women outweighed the proportion of men in this study, which is the same as in the previous studies.…”

Section: Discussioncontrasting

confidence: 65%

Knowledge of Stroke and Planned Response among Patients Living with Diabetes Mellitus and Hypertension in a Primary Care Unit

Ananchaisarp

Sa-a

2022

Siriraj Med J

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Background: Stroke is an important worldwide public health problem. Lack of knowledge in prevention methods, warning symptoms and planned response of acute stroke are associated with a longer prehospital time, which affect the morbidity and mortality of patients.Objective: The primary objective was to assess knowledge of stroke prevention methods and warning symptoms among patients living with diabetes and/or hypertension. The secondary objectives were to define planned responses when suspecting acute stroke, and identify associated factors with stroke knowledge scores and planned responses.Materials and Methods: A cross-sectional study was conducted in patients living with diabetes and/or hypertension, who had continuous follow up at the primary care unit of Songklanagarind Hospital. The outcomes of this study were assessed by a questionnaire, which was developed from a literature review.Results: This study included 312 participants. Median age was 64.0 years (Q1, Q3 = 58.0, 71.0), and 59.6% were female. Median score of knowledge of stroke prevention methods were 9, from 12 points (Q1, Q3 = 8, 10), and warning symptoms were 7, from 10 points (Q1, Q3 = 6, 8); with 80.1% of them knowing all 3 warning symptoms, according to the acronym FAST. Only 22.8% of participants would go to the hospital immediately, by calling an ambulance when they experienced symptoms of a suspected acute stroke. Participants who had income had statistically significant higher knowledge of stroke prevention methods; while participants under 60 years of age, who had a longer duration of diagnosed diabetes mellitus were associated with appropriate planned responses when suspecting acute stroke.Conclusion: Patients living with diabetes mellitus and hypertension, who are at a high risk for developing cardiovascular diseases, still do not have enough knowledge about acute stroke and had little concern about developing a stroke; especially the elderly and those with a short duration of having been diagnosed with diabetes mellitus.

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Section: Discussioncontrasting

confidence: 65%

Knowledge of Stroke and Planned Response among Patients Living with Diabetes Mellitus and Hypertension in a Primary Care Unit

Ananchaisarp

Sa-a

2022

Siriraj Med J

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“…Heart disease is one of the leading causes of death globally [2]. Heart disease claimed the lives of 17.9 million people in 2019 [3], according to the World Health Organization (WHO). Heart disease is caused by a lack of oxygen and blood flow, lifestyle changes, and contemporary dietary habits [4].…”

Section: Introductionmentioning

confidence: 99%

An Efficient Stacked Ensemble Model for Heart Disease Detection and Classification

Abbas,

Sampedro,

Alsubai

et al. 2023

CMC

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Cardiac disease is a chronic condition that impairs the heart's functionality. It includes conditions such as coronary artery disease, heart failure, arrhythmias, and valvular heart disease. These conditions can lead to serious complications and even be life-threatening if not detected and managed in time. Researchers have utilized Machine Learning (ML) and Deep Learning (DL) to identify heart abnormalities swiftly and consistently. Various approaches have been applied to predict and treat heart disease utilizing ML and DL. This paper proposes a Machine and Deep Learning-based Stacked Model (MDLSM) to predict heart disease accurately. ML approaches such as eXtreme Gradient Boosting (XGB), Random Forest (RF), Naive Bayes (NB), Decision Tree (DT), and K-Nearest Neighbor (KNN), along with two DL models: Deep Neural Network (DNN) and Fine Tuned Deep Neural Network (FT-DNN) are used to detect heart disease. These models rely on electronic medical data that increases the likelihood of correctly identifying and diagnosing heart disease. Well-known evaluation measures (i.e., accuracy, precision, recall, F1-score, confusion matrix, and area under the Receiver Operating Characteristic (ROC) curve) are employed to check the efficacy of the proposed approach. Results reveal that the MDLSM achieves 94.14% prediction accuracy, which is 8.30% better than the results from the baseline experiments recommending our proposed approach for identifying and diagnosing heart disease.

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“…Recently many cases of heart attack occurred in hospitals and homes, especially in patients with heart disease and elderly people. The common symptoms and signs of heart attack among them are pain or discomfort in the jaw, neck, or back; feeling weak, lightheaded, or faint; chest pain or discomfort; pain or discomfort in the arms or shoulders; and shortness of breath [16]. The American Heart Association lists "uncomfortable pressure, squeezing, fullness, or pain in the centre of the chest" as the very first sign of a heart attack.…”

Section: Introductionmentioning

confidence: 99%

A review of technologies for heart attack monitoring systems

2023

IJATEE

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Knowledge of heart attack and stroke symptoms among US Native American Adults: a cross-sectional population-based study analyzing a multi-year BRFSS database

Cited by 8 publications

References 37 publications

Knowledge of Stroke and Planned Response among Patients Living with Diabetes Mellitus and Hypertension in a Primary Care Unit

Knowledge of Stroke and Planned Response among Patients Living with Diabetes Mellitus and Hypertension in a Primary Care Unit

An Efficient Stacked Ensemble Model for Heart Disease Detection and Classification

A review of technologies for heart attack monitoring systems

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