Masaru Kitazawa 研究室

主宰者：Masaru Kitazawa

新潟大学

AI 要約（直近 5 年の研究成果）

本研究室では、生活習慣病と心血管疾患の関連性を明らかにするための大規模臨床研究を展開しています。特に、血糖値異常、肥満、脂質代謝異常、肝脂肪化などの代謝異常がどのように心筋梗塞や脳卒中といった重大な心血管イベントのリスクを高めるかを調査しています。また、糖尿病の寛解や改善によって心血管疾患の発症リスクがどう変化するかについても、長期追跡研究で検討しています。研究手法としては、日本全国の医療保険請求データや健康診断データベースを活用した大規模コホート研究が中心です。数十万人規模の参加者を数年にわたって追跡し、複数の検査値や生活習慣情報から疾患発症リスクを多変量解析で評価しています。筋力や運動機能を含む身体機能の指標と疾患発症の関連も調べており、簡便で実用的な予測モデルの開発に取り組んでいます。さらに、糖尿病や肝臓病などの条件下で、従来の治療指標がリスク予測にどう機能するかを層別化して分析し、個人の特性に応じた最適な治療標的を提案することを目指しています。

※ AI（Claude）が、公開されている論文要旨から研究の問い・手法・主要な発見を事実情報として抽出・再構成して自動生成しています。誤りを含む可能性があるため、正確性は研究室公式情報でご確認ください。

外部リンク

研究成果（61 件）

[2026] Alcohol and Steatotic Liver Disease Exhibit Divergent Associations with High Plasma Small Dense LDL-C Concentration
DOI: https://doi.org/10.1210/clinem/dgag234
[2026] 2193-P: The Role of Diabetes in the Relationship between Muscle Strength and Atrial Fibrillation
DOI: https://doi.org/10.2337/db26-2193-p
[2026] Association between Changes in Status Based on Multiple Metabolic Syndrome Criteria and Cardiovascular Disease Risk
DOI: https://doi.org/10.4093/dmj.2025.0197
[2026] Incidence and Associated Factors of Hypertension and Dyslipidemia Improvement in People With Type 2 Diabetes Remission: A Multicenter Real‐World Retrospective Cohort Study (JDDM84)
DOI: https://doi.org/10.1111/dom.70889
[2025] 410-P: Development and Validation of a Risk Score for Predicting the Initiation of Dialysis in People with and without Diabetes Mellitus
DOI: https://doi.org/10.2337/db25-410-p
[2025] Periodontitis and Mild Cognitive Impairment Risk in Diabetic Patients: Insights from an Exploratory Analysis
DOI: https://doi.org/10.3390/dj13110505
[2025] Impact of diabetes remission or progression on the incidence of cardiovascular disease in Japan: historical cohort study using a nationwide claims database
DOI: https://doi.org/10.1186/s12933-025-02578-y
[2025] The associations of body mass index and waist circumference with the risk of diabetic complications in people with type 2 diabetes mellitus
DOI: https://doi.org/10.1111/dom.16461
[2025] 1316-P: Prediction of the Development of Diabetes and Comorbidities by Time Spent in a Unipodal Stance with Eyes Closed
DOI: https://doi.org/10.2337/db25-1316-p
[2024] 1319-P: Assessment of a Comprehensive Physical Fitness Index to Predict Various Metabolic Diseases
DOI: https://doi.org/10.2337/db24-1319-p

続きを表示（残り 51 件）

[2024] 1278-P: Changes in Cardiovascular Disease (CVD) Incidence Due to Remission of Diabetes and Metabolic Dysfunction–Associated Steatotic Liver Disease (MASLD)
DOI: https://doi.org/10.2337/db24-1278-p
[2024] 1281-P: Impact of Estimated Glomerular Filtration Rate (eGFR) on New-Onset Heart failure (HF) according to Glucose Tolerance Status
DOI: https://doi.org/10.2337/db24-1281-p
[2024] 30-PUB: Difference in Glycemic Control between Ipragliflozin (Ipra) and Sitagliptin (Sita) according to Fatty Liver Index (FLI)—Post Hoc Analysis of the Results of the Niigata Ipragliflozin and Sitagliptin with Metformin (NISM) Study
DOI: https://doi.org/10.2337/db24-30-pub
[2024] 1259-P: Relationship between Number of Multiple Risk Factors and Functional Disability (FD) in Those With and Without Diabetes Mellitus (DM)
DOI: https://doi.org/10.2337/db24-1259-p
[2024] 183-OR: Risk Factors for Combined Severe Diabetic Complications (CSDC) in Patients with Type 2 Diabetes Mellitus (T2DM)
DOI: https://doi.org/10.2337/db24-183-or
[2024] 1229-P: Blood Glycated Albumin or Fructosamine (GA/Fruc) Rather Than Hemoglobin A1c (A1C) Is Useful for Specifying Individuals Having a Macrosomic Baby—Meta-analysis
DOI: https://doi.org/10.2337/db24-1229-p
[2024] Impact of health practice index and cardiovascular health metrics on incident cardiovascular disease according to glucose tolerance status
DOI: https://doi.org/10.1007/s13340-024-00708-7
[2024] Achieving normoglycaemia with tirzepatide: Post hoc exploratory analysis of the <scp>SURPASS</scp> J‐mono and J‐combo studies
DOI: https://doi.org/10.1111/dom.15887
[2024] Coronary artery disease risk prediction by combined stratification of low‐density lipoprotein‐cholesterol and high‐density lipoprotein‐cholesterol levels across different glucose statuses
DOI: https://doi.org/10.1111/dom.15956
[2024] Risk stratification for cardiovascular disease based on prior coronary artery disease, cerebrovascular disease and type 2 diabetes mellitus
DOI: https://doi.org/10.1111/jdi.14277
[2024] Healthy lifestyle factors as predictors of the initiation of dialysis in people with and without diabetes
DOI: https://doi.org/10.1007/s13340-024-00739-0
[2024] 435-P: Prediabetes and Cardiovascular Disease (CVD) Risk—Insights from a Large-Scale Japanese Cohort Investigating the Impact of Regular Hospital Visits
DOI: https://doi.org/10.2337/db24-435-p
[2024] 1282-P: Prediction of Coronary Artery Disease by Traditional Risk Factors according to Glucose Tolerance Status
DOI: https://doi.org/10.2337/db24-1282-p
[2024] 1286-P: Impact of Changes in Glucose Tolerance Status on Incidence of Cardiovascular Disease in Japan—Historical Cohort Study Using a Nationwide Claims Database
DOI: https://doi.org/10.2337/db24-1286-p
[2024] 1351-P: Relationship between Body Mass Index (BMI) or Waist Circumference (WC) and Risk of Severe Diabetic Complications in Patients with Diabetes (DM)
DOI: https://doi.org/10.2337/db24-1351-p
[2023] 1243-P: Usefulness of New Criteria for Metabolic Syndrome Optimized for Prediction of Cardiovascular Diseases in Japanese
DOI: https://doi.org/10.2337/db23-1243-p
[2023] Prognostic impact of tumour location in stage II/III ulcerative colitis-associated colon cancer: subgroup analysis of a nationwide multicentre retrospective study in Japan
DOI: https://doi.org/10.1093/bjs/znad386
[2023] Lifestyle Intervention With Smartphone App and isCGM for People at High Risk of Type 2 Diabetes: Randomized Trial
DOI: https://doi.org/10.1210/clinem/dgad639
[2023] 454-P: Risk Stratification of Cerebrocardiovascular Disease (CVD) according to HbA1c, Fasting Plasma Glucose (FPG), and Their Combinations in People with Prediabetes (preDM)
DOI: https://doi.org/10.2337/db23-454-p
[2023] 551-P: Healthy Lifestyle Behaviors as Predictors of Initiation of Hemodialysis (HD) in People With and Without Diabetes Mellitus (DM)
DOI: https://doi.org/10.2337/db23-551-p
[2023] 590-P: Assessment of a Comprehensive Physical Fitness Index to Predict Future Diabetes Mellitus (DM) and Metabolic Syndrome (MetS)
DOI: https://doi.org/10.2337/db23-590-p
[2023] 738-P: Lifestyle Intervention Program with Smartphone App Augmented by Intermittently Scanned Continuous Glucose Monitoring for People at High Risk of Diabetes—Randomized Controlled Trial
DOI: https://doi.org/10.2337/db23-738-p
[2023] 463-P: Risk Stratification of Coronary Artery Disease (CAD) according to LDL-C, HDL-C Levels, and Glucose Status
DOI: https://doi.org/10.2337/db23-463-p
[2023] 329-OR: Accuracy of Dietary Records (DR) Using a Smartphone App Is Greatly Improved by User’s Adjustments Compared with Artificial Intelligence (AI) Alone
DOI: https://doi.org/10.2337/db23-329-or
[2023] Utility of a Physical Fitness Score in Screening for Chronic Diseases
DOI: https://doi.org/10.52082/jssm.2023.98
[2023] Combined effects of blood pressure and glycemic status on risk of heart failure: a population-based study
DOI: https://doi.org/10.1097/hjh.0000000000003362
[2022] Association of the estimated glomerular filtration rate (eGFR) and/or proteinuria to predict the risk of initiation of dialysis in people with and without diabetes
DOI: https://doi.org/10.1007/s13340-022-00603-z
[2022] Fast walking and physical activity are independent contributors to improved physical function
DOI: https://doi.org/10.1093/fampra/cmac087
[2022] Impact of metabolic syndrome and metabolic dysfunction-associated fatty liver disease on cardiovascular risk by the presence or absence of type 2 diabetes and according to sex
DOI: https://doi.org/10.1186/s12933-022-01518-4
[2022] 1439-P: Association between Sleep Duration, Bedtime, and Hyperglycemia or Overweight/Obesity among Japanese Children
DOI: https://doi.org/10.2337/db22-1439-p
[2022] 1091-P: Impact of Metabolic Syndrome and Metabolic Dysfunction-Associated Fatty Liver Disease on Cardiovascular Risk in People with and without Type 2 Diabetes
DOI: https://doi.org/10.2337/db22-1091-p
[2022] 1214-P: Use of American Heart Association’s “Life's Simple 7” as a Predictor for Initiation of Dialysis
DOI: https://doi.org/10.2337/db22-1214-p
[2022] 539-P: Evaluation of a Comprehensive Physical Fitness Index to Predict Future Prediabetes and Metabolic Syndrome (MetS)
DOI: https://doi.org/10.2337/db22-539-p
[2022] 1165-P: Combined Severe Diabetic Complications: The New Life-Altering Outcome
DOI: https://doi.org/10.2337/db22-1165-p
[2022] 472-P: Sex Differences in the Effect of High Serum Uric Acid on the Incidence of Vision-Threatening Retinopathy in Those with Type 2 Diabetes
DOI: https://doi.org/10.2337/db22-472-p
[2022] 529-P: Impact of Medication Adherence (MA) to Oral Glycemic Agents (OHAs) on Initiation of Dialysis in Patients with Moderately Impaired Renal Function
DOI: https://doi.org/10.2337/db22-529-p
[2022] Differences in occupational stress by smoking intensity and gender in cross-sectional study of 59 355 Japanese employees using the Brief Job Stress Questionnaire (BJSQ): the Niigata Wellness Study
DOI: https://doi.org/10.1136/bmjopen-2021-055577
[2021] Impact of Medication Adherence and Glycemic Control on the Risk of Micro- and Macrovascular Diseases in Patients with Diabetes
DOI: https://doi.org/10.1016/j.amjmed.2021.10.018
[2021] Impact of prior cerebrovascular disease and glucose status on incident cerebrovascular disease in Japanese
DOI: https://doi.org/10.1186/s12933-021-01367-7
[2021] 795-P: Difference in Glycemic Control between Ipragliflozin (Ipr) and Sitagliptin (Sit) According to Changes in Energy Intake (EI) and Physical Activity (PA): Post-hoc Analysis of the NISM Study
DOI: https://doi.org/10.2337/db21-795-p
[2021] 1034-P: Association between Estimated Glomerular Filtration Rate (eGFR) and Proteinuria (UP) to Predict Risk of Start of Dialysis in People with and without Diabetes (DM)
DOI: https://doi.org/10.2337/db21-1034-p
[2021] 991-P: Association between Glucose Abnormality Status and Previous Cerebrovascular Disease (CVD) on Subsequent CVD in Japanese Men Using Real-World Data
DOI: https://doi.org/10.2337/db21-991-p
[2021] 480-P: Impact of Medication Adherence and Glycemic Control on the Risk of Micro/Macrovascular Diseases in Patients with Diabetes
DOI: https://doi.org/10.2337/db21-480-p
[2021] 434-P: Large Quantity of Alcohol Intake per Occasion was Positively Associated with Vision-Threatening Eye Diseases in Japanese Men with Type 2 Diabetes
DOI: https://doi.org/10.2337/db21-434-p
[2021] 1037-P: Poor Adherence to Medication and High HbA1c Predict Risk of Amputation in Diabetes Mellitus: Historical Cohort Study Using a Nationwide Claims Database
DOI: https://doi.org/10.2337/db21-1037-p
[2021] A 52‐week randomized controlled trial of ipragliflozin or sitagliptin in type 2 diabetes combined with metformin: The <scp>N‐ISM</scp> study
DOI: https://doi.org/10.1111/dom.14288
[2021] 1008-P: Utility of a Comprehensive Physical Fitness Score by the Tests of Physical Fitness in Screening of Metabolic Diseases
DOI: https://doi.org/10.2337/db21-1008-p
[2021] Associations of Systolic Blood Pressure and Diastolic Blood Pressure With the Incidence of Coronary Artery Disease or Cerebrovascular Disease According to Glucose Status
DOI: https://doi.org/10.2337/dc20-2252
[2021] Accuracy of Japanese claims data in identifying <scp>diabetes‐related</scp> complications
DOI: https://doi.org/10.1002/pds.5213
[2021] Ability of Current Machine Learning Algorithms to Predict and Detect Hypoglycemia in Patients With Diabetes Mellitus: Meta-analysis
DOI: https://doi.org/10.2196/22458
[2021] Rates and risk factors for amputation in people with diabetes in Japan: a historical cohort study using a nationwide claims database
DOI: https://doi.org/10.1186/s13047-021-00474-8

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AI 要約（直近 5 年の研究成果）

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関連研究室(8 件)

研究成果（61 件）

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