Maintenance of body weight is an important determinant for the risk of ischemic stroke: A nationwide population-based cohort study

Cho, Junghwan; Rhee, Eun-Jung; Park, Se Eun; Kwon, Hyemi; Jung, Jae-Hun; Han, Kyungdo; Park, Yong Gyu; Yoo, Soon‐Jib; Kim, Yang Hyun; Lee, Won Young

doi:10.1371/journal.pone.0210153

Cited by 13 publications

(11 citation statements)

References 32 publications

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“…Fluctuations, as measured by standard deviation, in BMI were positively correlated with stroke risk. These findings are consistent with several previous studies showing that the risk of stroke increases in individuals who lose or gain weight ( 41 ). The associations between BMI and stroke risk were inconclusive, possibly reflecting a previously observed weight paradox in stroke outcomes, particularly in the elderly (>75% of our study participants were over 60 years) ( 42 , 43 ).…”

Section: Discussionsupporting

confidence: 93%

Enriching the Study Population for Ischemic Stroke Therapeutic Trials Using a Machine Learning Algorithm

et al. 2022

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BackgroundStrokes represent a leading cause of mortality globally. The evolution of developing new therapies is subject to safety and efficacy testing in clinical trials, which operate in a limited timeframe. To maximize the impact of these trials, patient cohorts for whom ischemic stroke is likely during that designated timeframe should be identified. Machine learning may improve upon existing candidate identification methods in order to maximize the impact of clinical trials for stroke prevention and treatment and improve patient safety.MethodsA retrospective study was performed using 41,970 qualifying patient encounters with ischemic stroke from inpatient visits recorded from over 700 inpatient and ambulatory care sites. Patient data were extracted from electronic health records and used to train and test a gradient boosted machine learning algorithm (MLA) to predict the patients' risk of experiencing ischemic stroke from the period of 1 day up to 1 year following the patient encounter. The primary outcome of interest was the occurrence of ischemic stroke.ResultsAfter training for optimization, XGBoost obtained a specificity of 0.793, a positive predictive value (PPV) of 0.194, and a negative predictive value (NPV) of 0.985. The MLA further obtained an area under the receiver operating characteristic (AUROC) of 0.88. The Logistic Regression and multilayer perceptron models both achieved AUROCs of 0.862. Among features that significantly impacted the prediction of ischemic stroke were previous stroke history, age, and mean systolic blood pressure.ConclusionMLAs have the potential to more accurately predict the near risk of ischemic stroke within a 1-year prediction window for individuals who have been hospitalized. This risk stratification tool can be used to design clinical trials to test stroke prevention treatments in high-risk populations by identifying subjects who would be more likely to benefit from treatment.

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Section: Discussionsupporting

confidence: 93%

Enriching the Study Population for Ischemic Stroke Therapeutic Trials Using a Machine Learning Algorithm

et al. 2022

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“… 97 Alternatively, a cohort study also suggests that not only weight gain but also weight loss more than 5% should be emphasized to the increased incidence rate of Transient ischemic attack (TIA). 98 Therefore, weight management to be optimal to prevent a stroke rate.…”

Section: Discussionmentioning

confidence: 99%

Knowledge, Prevention Practice and Associated Factors of Stroke Among Hypertensive and Diabetic Patients – A Systematic Review

Melak¹,

Wondimsigegn²,

Kifle³

2021

RMHP

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Introduction Because of the inadequate level of public awareness of the disease, the incidence of stroke has been sharply rising. Eventually, due to the prehospital delay, many stroke cases could not be eligible for thrombolysis thereby poor rehabilitative outcome has been tremendously increased. Thus, this study aimed to review the level of knowledge, prevention practice, and associated factors of stroke among hypertensive and diabetic patients. Methods A systematic review of primarily published articles (2010–2020) related to knowledge and prevention practices of stroke was performed by searching online electronic databases like PubMed, Google Scholar, Refseek, Science direct, ResearchGate, and manual Google search by using the keywords and MeSH terms. Studies conducted on knowledge and prevention practices amongst hypertensive and/or diabetic patients were included. Results Out of 531 searched studies, 42 articles were identified to be reviewed. The reported overall knowledge of stroke was ranging from 4.4% to 79%. Knowledge to the signs/symptoms of stroke was 23.6% to 87%. However, 15% to 77% of subjects were also reported that they did not know any sign of stroke. The range of risk factor knowledge was 10.5% to 86.6%. The reported level of stroke prevention practice was 2.4% to 72% but physical activity and weight reduction practice were relatively low. Inadequate level of knowledge and prevention practice of stroke was related to elderly, female gender, uneducated, unmarried, rural residents, economically low, comorbidity and unemployed individuals. Conclusion The current finding revealed that the level of knowledge and prevention practice of stroke was inadequate. Hence, the finding highlights health educational programs should be planned as an important avenue to enhance stroke awareness among the high-risk populations.

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“…The current study has also found that obese and overweight individuals are at greater risk of developing stroke. The study conducted by Cho et al suggested that weight gain is associated with an increased incidence rate of TIA [ 24 ]. Thus, management of weight needs to be an optimal method for preventing stroke.…”

Section: Discussionmentioning

confidence: 99%

Frequency of Stroke and Factors Associated With It Among Old Age Hypertensive Patients in Karachi, Pakistan: A Cross-Sectional Study

Rupasinghe¹,

Bokhari²,

Lutfi³

et al. 2022

Cureus

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Introduction: Worldwide, stroke has become the major cause of mortality and morbidity among the old age population. Hypertension is one of the factors associated with stroke. Individuals with hypertension are at high risk of developing stroke. This study was conducted to determine the frequency of stroke factors associated with it among old-age hypertensive patients in Karachi, Pakistan.Methods: It was a cross-sectional study conducted in outpatient departments (OPD) of two tertiary care hospitals of Karachi, Pakistan, including Jinnah Postgraduate Medical Center (JPMC) and Ziauddin Hospital. Eligible patients were invited to be a part of the study, and informed consent was taken from them before data collection.Results: Multivariable logistic regression analysis showed that age (adjusted odds ratio [

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Maintenance of body weight is an important determinant for the risk of ischemic stroke: A nationwide population-based cohort study

Cited by 13 publications

References 32 publications

Enriching the Study Population for Ischemic Stroke Therapeutic Trials Using a Machine Learning Algorithm

Enriching the Study Population for Ischemic Stroke Therapeutic Trials Using a Machine Learning Algorithm

Knowledge, Prevention Practice and Associated Factors of Stroke Among Hypertensive and Diabetic Patients – A Systematic Review

Frequency of Stroke and Factors Associated With It Among Old Age Hypertensive Patients in Karachi, Pakistan: A Cross-Sectional Study

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