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Predicting patient-level new-onset atrial fibrillation from population-based nationwide electronic health records: protocol of FIND-AF for developing a precision medicine prediction model using artificial intelligence
Introduction Atrial fibrillation (AF) is a major cardiovascular health problem: it is common, chronic and incurs substantial healthcare expenditure because of stroke. Oral anticoagulation reduces the risk of thromboembolic stroke in those at higher risk; but for a number of patients, stroke is the first manifestation of undetected AF. There is a rationale for the early diagnosis of AF, before the first complication occurs, but population-based screening is not recommended. Previous prediction models have been limited by their data sources and methodologies. An accurate model that uses existing routinely collected data is n...
Source: BMJ Open - November 2, 2021 Category: General Medicine Authors: Nadarajah, R., Wu, J., Frangi, A. F., Hogg, D., Cowan, C., Gale, C. Tags: Open access, Cardiovascular medicine Source Type: research

Using electronic health records to develop and validate a machine-learning tool to predict type 2 diabetes outcomes: a study protocol
Introduction Type 2 diabetes mellitus (T2DM) is a major cause of blindness, kidney failure, myocardial infarction, stroke and lower limb amputation. We are still unable, however, to accurately predict or identify which patients are at a higher risk of deterioration. Most risk stratification tools do not account for novel factors such as sociodemographic determinants, self-management ability or access to healthcare. Additionally, most tools are based in clinical trials, with limited external generalisability. Objective The aim of this work is to design and validate a machine learning-based tool to identify patients with T2...
Source: BMJ Open - July 30, 2021 Category: General Medicine Authors: Neves, A. L., Pereira Rodrigues, P., Mulla, A., Glampson, B., Willis, T., Darzi, A., Mayer, E. Tags: Open access, Health informatics Source Type: research

How to prevent diabetes from sneaking up on your patients
An AMA Viewpoints post by AMA Board Chair Stephen R. Permut, MD A major health threat has been silently taking hold of 86 million Americans, with 90 percent of them unaware of it. A new public health campaign is about to change that—and you’re the key to helping these patients take their health back. A campaign to prevent type 2 diabetes If you’re not already talking to your patients about prediabetes and the risks associated with it, it’s time to start. People with prediabetes—more than 1 in 3 adults—are at higher risk of developing serious health problems such as type 2 diabetes, heart disease and s...
Source: AMA Wire - January 21, 2016 Category: Journals (General) Authors: Amy Farouk Source Type: news

How a public health solution is reducing hypertension disparities
Addressing health care disparities can help practices improve the health of patients in vulnerable at-risk populations. Learn how eight family medicine practices boosted hypertension control rates for diverse patients by more than 3 percentage points in just three months. A targeted pilot As part of the Million Hearts initiative, the Summit County Public Health department (SCPH) and several partners in Ohio launched a pilot project with several family medicine practices to help reduce hypertension rates among black men. In Ohio, 38.5 percent of black patients have a diagnosis of hypertension, compared to 33.7 percent...
Source: AMA Wire - February 16, 2016 Category: Journals (General) Authors: Lyndra Vassar Source Type: news

Prediction of Incident Hypertension Within the Next Year: Prospective Study Using Statewide Electronic Health Records and Machine Learning
Conclusions: With statewide EHR datasets, our study prospectively validated an accurate 1-year risk prediction model for incident essential hypertension. Our real-time predictive analytic model has been deployed in the state of Maine, providing implications in interventions for hypertension and related diseases and hopefully enhancing hypertension care.
Source: Journal of Medical Internet Research - January 30, 2018 Category: General Medicine Authors: Chengyin Ye Tianyun Fu Shiying Hao Yan Zhang Oliver Wang Bo Jin Minjie Xia Modi Liu Xin Zhou Qian Wu Yanting Guo Chunqing Zhu Yu-Ming Li Devore S Culver Shaun T Alfreds Frank Stearns Karl G Sylvester Eric Widen Doff McElhinney Xuefeng Ling Source Type: research