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Yang Q, Jiang M, Li C, Luo S, Crowley MJ, Shaw RJ. Predicting health outcomes with intensive longitudinal data collected by mobile health devices: a functional principal component regression approach. BMC Med Res Methodol 2024; 24:69. [PMID: 38494505 PMCID: PMC10944610 DOI: 10.1186/s12874-024-02193-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Accepted: 03/01/2024] [Indexed: 03/19/2024] Open
Abstract
BACKGROUND Intensive longitudinal data (ILD) collected in near real time by mobile health devices provide a new opportunity for monitoring chronic diseases, early disease risk prediction, and disease prevention in health research. Functional data analysis, specifically functional principal component analysis, has great potential to abstract trends in ILD but has not been used extensively in mobile health research. OBJECTIVE To introduce functional principal component analysis (fPCA) and demonstrate its potential applicability in estimating trends in ILD collected by mobile heath devices, assessing longitudinal association between ILD and health outcomes, and predicting health outcomes. METHODS fPCA and scalar-to-function regression models were reviewed. A case study was used to illustrate the process of abstracting trends in intensively self-measured blood glucose using functional principal component analysis and then predicting future HbA1c values in patients with type 2 diabetes using a scalar-to-function regression model. RESULTS Based on the scalar-to-function regression model results, there was a slightly increasing trend between daily blood glucose measures and HbA1c. 61% of variation in HbA1c could be predicted by the three preceding months' blood glucose values measured before breakfast (P < 0.0001, [Formula: see text]). CONCLUSIONS Functional data analysis, specifically fPCA, offers a unique tool to capture patterns in ILD collected by mobile health devices. It is particularly useful in assessing longitudinal dynamic association between repeated measures and outcomes, and can be easily integrated in prediction models to improve prediction precision.
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Affiliation(s)
- Qing Yang
- School of Nursing, Duke University, Durham, USA.
| | | | - Cai Li
- Department of Biostatistics, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Sheng Luo
- Biostatistics & Bioinformatics, Duke University, Durham, USA
| | - Matthew J Crowley
- Center of Innovation to Accelerate Discovery and Practice Transformation, Durham Veterans Affairs Medical Center, Durham, NC, USA
- Division of Endocrinology, Diabetes and Metabolism, Duke University School of Medicine, Durham, NC, USA
| | - Ryan J Shaw
- School of Nursing, Duke University, Durham, USA
- Center of Innovation to Accelerate Discovery and Practice Transformation, Durham Veterans Affairs Medical Center, Durham, NC, USA
- Center for Applied Genomics & Precision Medicine, School of Medicine, Duke University, Durham, NC, USA
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Mavragani A, Kim D, Hwang J, Kang JH, Kwon Y, Kwon JW. Association of Uncontrolled Hypertension or Diabetes Mellitus With Major Adverse Cardiovascular Events and Mortality in South Korea: Population-Based Cohort Study. JMIR Public Health Surveill 2023; 9:e42190. [PMID: 36735297 PMCID: PMC9938442 DOI: 10.2196/42190] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Revised: 11/27/2022] [Accepted: 01/06/2023] [Indexed: 02/04/2023] Open
Abstract
BACKGROUND Managing hypertension (HT) and diabetes mellitus (DM) is crucial to preventing cardiovascular diseases. Few studies have investigated the incidence and risk of cardiovascular diseases or mortality in uncontrolled HT or DM in the Asian population. Epidemiological studies of cardiovascular disease should be conducted with continuous consideration of the changing disease risk profiles, lifestyles, and socioeconomic status over time. OBJECTIVE We aimed to examine the association of uncontrolled HT or DM with the incidence of cardiovascular events or deaths from any cause. METHODS This population-based retrospective study was conducted using data from the Korean National Health Insurance Service-National Health Screening Cohort, including patients aged 40-79 years who participated in national screening from 2002 to 2003 and were followed up until 2015. The health screening period from 2002 to 2013 was stratified into 6 index periods in 2-year cycles, and the follow-up period from 2004 to 2015 was stratified accordingly into 6 subsequent 2-year periods. The incidence rates and hazard ratio (HR) for major adverse cardiovascular events (MACE) and death from any cause were estimated according to HT or DM control status. Extended Cox models with time-dependent variables updated every 2 years, including sociodemographic characteristics, blood pressure (BP), fasting blood glucose (FBG), medication prescription, and adherence, were used. RESULTS Among the total cohort of 440,249 patients, 155,765 (35.38%) were in the uncontrolled HT or DM group. More than 60% of the patients with HT or DM who were prescribed medications did not achieve the target BP or FBG. The incidence of MACE was 10.8-15.5 and 9.6-13.3 per 1000 person-years in the uncontrolled DM and uncontrolled HT groups, respectively, and increased with age. In the uncontrolled HT and DM group, the incidence of MACE was high (15.2-17.5 per 1000 person-years) at a relatively young age and showed no age-related trend. Adjusted HR for MACE were 1.28 (95% CI 1.23-1.32) for the uncontrolled DM group, 1.32 (95% CI 1.29-1.35) for the uncontrolled HT group, and 1.54 (95% CI 1.47-1.60) for the uncontrolled HT and DM group. Adjusted HR for death from any cause were 1.05 (95% CI 1.01-1.10) for the uncontrolled DM group, 1.13 (95% CI 1.10-1.16) for the uncontrolled HT group, and 1.17 (95% CI 1.12-1.23) for the uncontrolled HT and DM group. CONCLUSIONS This up-to-date evidence of cardiovascular epidemiology in South Korea serves as the basis for planning public health policies to prevent cardiovascular diseases. The high uncontrolled rates of HT or DM, regardless of medication prescription, have led us to suggest the need for a novel system for effective BP or glycemic control, such as a community-wide management program using mobile health technology.
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Affiliation(s)
| | - Dohyang Kim
- Department of Statistics, Daegu University, Gyeongbuk, Republic of Korea
| | - Jinseub Hwang
- Department of Statistics, Daegu University, Gyeongbuk, Republic of Korea
| | - Jae-Heon Kang
- Department of Family Medicine, Kangbuk Samsung Hospital, College of Medicine, Sungkyunkwan University, Seoul, Republic of Korea
| | - Yeongkeun Kwon
- Centre for Obesity and Metabolic Diseases, Korea University Anam Hospital, Seoul, Republic of Korea
| | - Jin-Won Kwon
- BK21 FOUR Community-Based Intelligent Novel Drug Discovery Education Unit, College of Pharmacy and Research Institute of Pharmaceutical Sciences, Kyungpook National University, Daegu, Republic of Korea
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Diabetes mellitus and poor glycemic control increase the occurrence of coronal and root caries: a systematic review and meta-analysis. Clin Oral Investig 2020; 24:3801-3812. [DOI: 10.1007/s00784-020-03531-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2020] [Accepted: 08/14/2020] [Indexed: 12/22/2022]
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Lee SH, Jang MU, Kim Y, Park SY, Kim C, Kim YJ, Sohn JH. Effect of Prestroke Glycemic Variability Estimated Glycated Albumin on Stroke Severity and Infarct Volume in Diabetic Patients Presenting With Acute Ischemic Stroke. Front Endocrinol (Lausanne) 2020; 11:230. [PMID: 32373074 PMCID: PMC7186307 DOI: 10.3389/fendo.2020.00230] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/25/2019] [Accepted: 03/30/2020] [Indexed: 12/15/2022] Open
Abstract
Background: We investigated whether prestroke glycemic variability, represented by glycated albumin (GA), affects the initial stroke severity and infarct volume in diabetic patients presenting with acute ischemic stroke. Methods: We evaluated a total of 296 acute ischemic stroke patients with diabetes mellitus who were hospitalized within 48 h of stroke onset. GA was measured in all acute ischemic stroke patients consecutively during the study period. The primary outcome was the initial National Institute Health Stroke Scale (NIHSS) score. The secondary outcome was infarct volume on diffusion-weighted imaging, which was performed within 24 h of stroke onset. Higher GA (≥16.0%) was determined to reflect glycemic fluctuation prior to ischemic stroke. Results: The number of patients with higher GA was 217 (73.3%). The prevalence of a severe initial NIHSS score (>14) was higher in patients with higher GA than in those with lower GA (3.8% vs. 15.7%, p = 0.01). The proportion of participants in the highest quartile of infarct volume was higher in the higher GA group (11.4% vs. 36.4%, p < 0.001). A multivariable analysis showed that higher GA was significantly associated with a severe NIHSS score (odds ratio, [95% confidence interval], 7.99 [1.75-36.45]) and large infarct volume (3.76 [1.05-13.45]). Conclusions: Prestroke glucose variability estimated by GA was associated with an increased risk of severe initial stroke severity and large infarct volume in acute ischemic stroke patients with diabetes mellitus.
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Affiliation(s)
- Sang-Hwa Lee
- Department of Neurology, Chuncheon Sacred Heart Hospital, Hallym University College of Medicine, Chuncheon, South Korea
| | - Min Uk Jang
- Department of Neurology, Dongtan Sacred Heart Hospital, Hallym University College of Medicine, Hwaseong, South Korea
| | - Yerim Kim
- Department of Neurology, Kangdong Sacred Heart Hospital, Hallym University College of Medicine, Seoul, South Korea
| | - So Young Park
- Department of Endocrinology and Metabolism, Kyung Hee University Hospital, Seoul, South Korea
| | - Chulho Kim
- Department of Neurology, Chuncheon Sacred Heart Hospital, Hallym University College of Medicine, Chuncheon, South Korea
| | - Yeo Jin Kim
- Department of Neurology, Chuncheon Sacred Heart Hospital, Hallym University College of Medicine, Chuncheon, South Korea
| | - Jong-Hee Sohn
- Department of Neurology, Chuncheon Sacred Heart Hospital, Hallym University College of Medicine, Chuncheon, South Korea
- *Correspondence: Jong-Hee Sohn
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Kim MK, Ko SH, Kim BY, Kang ES, Noh J, Kim SK, Park SO, Hur KY, Chon S, Moon MK, Kim NH, Kim SY, Rhee SY, Lee KW, Kim JH, Rhee EJ, Chun S, Yu SH, Kim DJ, Kwon HS, Park KS. 2019 Clinical Practice Guidelines for Type 2 Diabetes Mellitus in Korea. Diabetes Metab J 2019; 43:398-406. [PMID: 31441247 PMCID: PMC6712226 DOI: 10.4093/dmj.2019.0137] [Citation(s) in RCA: 155] [Impact Index Per Article: 31.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/16/2019] [Accepted: 07/22/2019] [Indexed: 12/14/2022] Open
Abstract
The Committee of Clinical Practice Guidelines of the Korean Diabetes Association revised and updated the 6th Clinical Practice Guidelines in 2019. Targets of glycemic, blood pressure, and lipid control in type 2 diabetes mellitus (T2DM) were updated. The obese and overweight population is increasing steadily in Korea, and half of the Koreans with diabetes are obese. Evidence-based recommendations for weight-loss therapy for obesity management as treatment for hyperglycemia in T2DM were provided. In addition, evidence from large clinical studies assessing cardiovascular outcomes following the use of sodium-glucose cotransporter-2 inhibitors and glucagon-like peptide 1 receptor agonists in patients with T2DM were incorporated into the recommendations.
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Affiliation(s)
- Mee Kyoung Kim
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Yeouido St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Seung Hyun Ko
- Division of Endocrinology and Metabolism, Department of Internal Medicine, St. Vincent's Hospital, College of Medicine, The Catholic University of Korea, Suwon, Korea
| | - Bo Yeon Kim
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Soonchunhyang University Bucheon Hospital, Soonchunhyang University College of Medicine, Bucheon, Korea
| | - Eun Seok Kang
- Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Korea
| | - Junghyun Noh
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Inje University Ilsan Paik Hospital, Inje University College of Medicine, Goyang, Korea
| | - Soo Kyung Kim
- Division of Endocrinology and Metabolism, Department of Internal Medicine, CHA Bundang Medical Center, CHA University, Seongnam, Korea
| | - Seok O Park
- Gwangmyeong Sungae Hospital, Gwangmyeong, Korea
| | - Kyu Yeon Hur
- Division of Endocrinology and Metabolism, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Suk Chon
- Department of Endocrinology and Metabolism, Kyung Hee University School of Medicine, Seoul, Korea
| | - Min Kyong Moon
- Department of Internal Medicine, Seoul Metropolitan Government Seoul National University Boramae Medical Center, Seoul National University College of Medicine, Seoul, Korea
| | - Nan Hee Kim
- Department of Internal Medicine, Korea University College of Medicine, Ansan, Korea
| | - Sang Yong Kim
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Chosun University College of Medicine, Gwangju, Korea
| | - Sang Youl Rhee
- Department of Endocrinology and Metabolism, Kyung Hee University School of Medicine, Seoul, Korea
| | - Kang Woo Lee
- Sejong St. Mary's Diabetes and Endocrine Clinic, Sejong, Korea
| | - Jae Hyeon Kim
- Division of Endocrinology and Metabolism, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Eun Jung Rhee
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - SungWan Chun
- Department of Internal Medicine, Soonchunhyang University Cheonan Hospital, Soonchunhyang University College of Medicine, Cheonan, Korea
| | - Sung Hoon Yu
- Department of Endocrinology and Metabolism, Hanyang University Guri Hospital, Hanyang University College of Medicine, Guri, Korea
| | - Dae Jung Kim
- Department of Endocrinology and Metabolism, Ajou University School of Medicine, Suwon, Korea
| | - Hyuk Sang Kwon
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Yeouido St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea.
| | - Kyong Soo Park
- Department of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, Korea
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Korea
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Steady-state relationship between average glucose, HbA1c and RBC lifespan. J Theor Biol 2018; 447:111-117. [PMID: 29559230 DOI: 10.1016/j.jtbi.2018.03.023] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2017] [Revised: 03/15/2018] [Accepted: 03/16/2018] [Indexed: 11/22/2022]
Abstract
HbA1c is used to estimate average glucose. Previous studies showed linear relationship between average glucose and HbA1c. We made a new theoretical relationship using recently proposed Γ-like function model of erythrocyte lifespan. We showed the relationship between average glucose and HbA1c; we approximated it into a simple hyperbolic function: HbA1c=MRBCkgAG/(1+(2/3)MRBCkgAG), whose inverse function is easily obtained. Apparent linear relationship is an approximation of the curved relationship. Hyperbolic function would provide a more accurate approximation than a linear equation. Physicians should keep in mind the curved relationship and be aware that extremely high HbA1c indicates acceleratingly high glucose level.
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