Readability, Understandability, and Actionability of Online Cardiovascular Risk Assessment Tools and Patient Educational Material: A Systematic Review

Roshan, Ashraf; Choo, Jason Chon Jun; Lim, Cynthia Ciwei

doi:10.1159/000528118

Cited by 3 publications

(1 citation statement)

References 34 publications

(41 reference statements)

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“…Regarding the HHS, it serves as a valuable tool in predicting premature vascular risk, as evidenced by the CARDIA study [76] as well as the ENRICA study [77]. Due to its ease of interpretation, user-friendly tools such as the HHS can be effectively integrated into health education programs for individuals at risk of CVD [78].…”

Section: Discussionmentioning

confidence: 99%

Nutritional and Lifestyle Features in a Mediterranean Cohort: An Epidemiological Instrument for Categorizing Metabotypes Based on a Computational Algorithm

García-Perea,

Fernández-Cruz,

de la O-Pascual

et al. 2024

Medicina

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Background and Objectives: Modern classification and categorization of individuals’ health requires personalized variables such as nutrition, physical activity, lifestyle, and medical data through advanced analysis and clustering methods involving machine learning tools. The objective of this project was to categorize Mediterranean dwellers’ health factors and design metabotypes to provide personalized well-being in order to develop professional implementation tools in addition to characterizing nutritional and lifestyle features in such populations. Materials and Methods: A two-phase observational study was conducted by the Pharmacists Council to identify Spanish nutritional and lifestyle characteristics. Adults over 18 years of age completed questionnaires on general lifestyle habits, dietary patterns (FFQ, MEDAS-17 p), physical activity (IPAQ), quality of life (SF-12), and validated well-being indices (LS7, MEDLIFE, HHS, MHL). Subsequently, exploratory factor, clustering, and random forest analysis methods were conducted to objectively define the metabotypes considering population determinants. Results: A total of 46.4% of the sample (n = 5496) had moderate-to-high adherence to the Mediterranean diet (>8 points), while 71% of the participants declared that they had moderate physical activity. Almost half of the volunteers had a good self-perception of health (49.9%). Regarding lifestyle index, population LS7 showed a fair cardiovascular health status (7.9 ± 1.7), as well as moderate quality of life by MEDLIFE (9.3 ± 2.6) and MHL scores (2.4 ± 0.8). In addition, five metabotype models were developed based on 26 variables: Westernized Millennial (28.6%), healthy (25.1%), active Mediterranean (16.5%), dysmetabolic/pre-morbid (11.5%), and metabolically vulnerable/pro-morbid (18.3%). Conclusions: The support of tools related to precision nutrition and lifestyle integrates well-being characteristics and contributes to reducing the impact of unhealthy lifestyle habits with practical implications for primary care. Combining lifestyle, metabolic, and quality of life traits will facilitate personalized precision interventions and the implementation of targeted public health policies.

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Section: Discussionmentioning

confidence: 99%

Nutritional and Lifestyle Features in a Mediterranean Cohort: An Epidemiological Instrument for Categorizing Metabotypes Based on a Computational Algorithm

García-Perea,

Fernández-Cruz,

de la O-Pascual

et al. 2024

Medicina

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Both English and Spanish Anterior Cruciate Ligament Reconstruction Online Patient Education Materials are Written at Higher than Recommended Reading Levels

Ghahremani,

Chapek,

Xie

et al. 2024

Arthroscopy, Sports Medicine, and Rehabilitation

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A deep learning system for retinal vessel calibre improves cardiovascular risk prediction in Asians with chronic kidney disease

Lim,

Chong,

Tan

et al. 2023

Clinical Kidney Journal

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Background Cardiovascular disease (CVD) and mortality is elevated in chronic kidney disease (CKD). Retinal vessel calibre in retinal photographs is associated with cardiovascular risk and automated measurements may aid CVD risk prediction. Methods Retrospective cohort study of 860 Chinese, Malay and Indian participants aged 40–80 years with CKD (estimated glomerular filtration rate (eGFR) <60 ml/min/1.73 m2) who attended the baseline visit (2004–2011) of the Singapore Epidemiology of Eye Diseases Study. Retinal vessel calibre measurements were obtained by a deep learning system (DLS). Incident CVD (non-fatal acute myocardial infarction (MI) and stroke, and death due to MI, stroke and other CVD) in those who were free of CVD at baseline was ascertained until 31st December 2019. Risk factors (established, kidney and retinal features) were examined using Cox proportional hazards regression models. Model performance was assessed for discrimination, fit and net reclassification improvement (NRI). Results Incident CVD occurred in 289 (33.6%) over mean follow up of 9.3 (4.3) years. After adjusting for established cardiovascular risk factors, eGFR [adjusted HR 0.98 (95% CI: 0.97–0.99)] and retinal arteriolar narrowing [adjusted HR 1.40 (95% CI: 1.17–1.68)], but not venular dilation, were independent predictors for CVD in CKD. The addition of eGFR and retinal features to established cardiovascular risk factors improved model discrimination with significantly better-fit and better risk prediction according the low (<15%), intermediate (15–29.9%) and high (30% or more) risk categories (NRI 5.8%), and with higher risk thresholds (NRI 12.7%). Conclusions Retinal vessel calibre measurements by DLS were significantly associated with incident CVD independent of established CVD risk factors. Addition of kidney function and retinal vessel calibre parameters may improve CVD risk prediction among Asians with CKD.

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Readability, Understandability, and Actionability of Online Cardiovascular Risk Assessment Tools and Patient Educational Material: A Systematic Review

Cited by 3 publications

References 34 publications

Nutritional and Lifestyle Features in a Mediterranean Cohort: An Epidemiological Instrument for Categorizing Metabotypes Based on a Computational Algorithm

Nutritional and Lifestyle Features in a Mediterranean Cohort: An Epidemiological Instrument for Categorizing Metabotypes Based on a Computational Algorithm

Both English and Spanish Anterior Cruciate Ligament Reconstruction Online Patient Education Materials are Written at Higher than Recommended Reading Levels

A deep learning system for retinal vessel calibre improves cardiovascular risk prediction in Asians with chronic kidney disease

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