治験レーダーAI | ||
|---|---|---|
治験 NCT07307183（対象：糖尿病）は募集中です。詳細は治験レーダーのタイル表示と AI 発見ツールで確認するか、ここで質問してください。 | ||
フィルター基準に一致する試験が1件見つかりました
タイル表示
Prediction Model for the Risk of Developing Foot Ulcers in Diabetes 100,000 機械学習 予防的 予防
治験（臨床試験）の詳細は主に英語で提供されていますが、治験レーダーAIがサポートします！「治験解説」をクリックして、選択した言語で試験情報を表示し、議論してください。
治験番号 NCT07307183 は 観察研究 臨床試験 で、糖尿病 に関するものです。現在は 募集中 で、2014年1月30日 から開始しています。100,000 名の参加者 の募集が計画されています。この試験は Sahlgrenska University Hospital によって主導され、2027年12月30日 に完了予定です。ClinicalTrials.gov からの最新更新日は 2025年12月29日 です。
概要
Introduction Foot ulcers in diabetes mellitus (DM) are a common and serious complication that can lead to infection, amputation, and increased mortality. Early identification of patients at high risk is crucial in order to implement preventive measures at an early stage. The number of people with DM is increasing globally, from 540 million in 2021 to an estimated 780 million by 2045. Foot ulcers cause considerable su...もっと見る
詳細説明
In this register-based study, using data from Närhälsan's electronic health record system in the Västra Götaland Region (VGR) and linkage with data from Statistics Sweden (SCB), the research questions will be addressed through the development and validation of AI-based models. At a later stage of the process, the ability of the AI models to predict foot ulcers will be compared with that of statistical models.
From A...
もっと見る公式タイトル
Prediction Model for the Risk of Developing Foot Ulcers in Diabetes
疾患名
糖尿病その他の研究識別子
- Dnr 2025-03432-01
NCT番号
開始日
2014-01-30
最終更新日
2025-12-29
終了予定日
2027-12-30
目標参加者数
100,000
試験の種類
観察研究
状況
募集中
キーワード
Cohort
Retrospective
diabetic foot
foot ulcer
artificial intelligence
Retrospective
diabetic foot
foot ulcer
artificial intelligence
群（アーム）／介入
| 参加グループ/群 | 介入/治療法 |
|---|---|
Patients with diabetes with foot ulcers Patients with diabetes and foot ulcers registered in the electrical medical record system from primary care in Region Västragötaland. | 該当なし |
Patients with diabetes without foot ulcers Patients with diabetes without foot ulcers registered in the electrical medical record system from primary care in Region Västragötaland. | 該当なし |
主要評価項目
副次評価項目
| 評価指標 | 指標の説明 | 時間枠 |
|---|---|---|
Performance of machine learning-based prediction models for diabetic foot ulcer risk | The primary outcome is the predictive performance of machine learning-based models developed to estimate the risk of diabetic foot ulceration in patients with diabetes. Models will be trained using supervised machine learning techniques, with optimal hyperparameters identified through cross-validation.
In the initial evaluation phase, model performance will be assessed for the ability to discriminate between patients with and without existing diabetic foot ulcers. In a subsequent phase, the models' ability to prospectively predict the development of diabetic foot ulcers during follow-up will be evaluated.
Model robustness will be improved through an iterative process in which redundant variables are excluded and models are retrained. Predictive performance will be quantified using established metrics such as discrimination, calibration, and classification accuracy.
To account for uncertainty in individual predictions, the final models will be combined with Conformal Prediction meth | From study start to 2027-12-31 |
| 評価指標 | 指標の説明 | 時間枠 |
|---|---|---|
Identification and interpretability of risk factors for diabetic foot ulcer development | The secondary outcome is the identification and validation of clinical, demographic, and socioeconomic variables that are potential risk factors for diabetic foot ulcer development in patients with diabetes. Variables and risk factor categories will be identified using electronic health record data from the primary care information system Assynja Whisp in Region Västra Götaland, linked with national registry data from Statistics Sweden (SCB), together with established scientific and empirical evidence.
A case-control study design will be applied, in which patients with diabetes who develop foot ulcers are compared with a control group of patients with diabetes who do not develop foot ulcers. Population-level analyses will be conducted to examine associations and co-variation between the occurrence of diabetic foot ulcers and other relevant factors. | From study start to 2027-12-31 |
参加アシスタント
適格基準
対象年齢
成人, 高齢者
試験の最低年齢
18 Years
対象性別
全て
- Adult patients aged 18 years or older at the time of inclusion
- Patients with a diagnosis of diabetes mellitus according to ICD-10 codes E10-E14, and/or
- Patients who have been prescribed at least one diabetes-related medication after the age of 18
- Patients with relevant diagnoses and/or prescriptions recorded in the study data sources between 1 January 2014 and 30 June 2025
- Patients younger than 18 years of age at the time of diabetes diagnosis or prescription
- Patients with no recorded diagnosis of diabetes (ICD-10 E10-E14) and no prescription of diabetes medication after the age of 18
- Patients with incomplete or missing key data required for model development or validation (e.g. missing outcome or essential covariates)
Sahlgrenska University Hospital責任者
Ulla Hellstrand Tang, 主任研究者, Associate Professor, Sahlgrenska University Hospital
試験中央連絡先
連絡先: Ulla Hellstrand Tang, Associate Professor, +46706397913, [email protected]
連絡先: Thomas Fasth, BSc, [email protected]
1 1カ国の場所
Region Västra Götaland, Jonsered, 43375, Sweden
Ulla Hellstrand Tang, Associate Professor, 連絡先, 046706397913, [email protected]
Thomas Fasth, BSc, 連絡先, [email protected]
募集中