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- Lorenz, M. W., et al.
(författare)
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Carotid Intima-Media Thickness Progression and Risk of Vascular Events in People With Diabetes: Results From the PROG-IMT Collaboration
- 2015
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Ingår i: Diabetes Care. - : American Diabetes Association. - 0149-5992 .- 1935-5548. ; 38:10, s. 1921-1929
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Tidskriftsartikel (refereegranskat)abstract
- OBJECTIVECarotid intima-media thickness (CIMT) is a marker of subclinical organ damage and predicts cardiovascular disease (CVD) events in the general population. It has also been associated with vascular risk in people with diabetes. However, the association of CIMT change in repeated examinations with subsequent CVD events is uncertain, and its use as a surrogate end point in clinical trials is controversial. We aimed at determining the relation of CIMT change to CVD events in people with diabetes.RESEARCH DESIGN AND METHODSIn a comprehensive meta-analysis of individual participant data, we collated data from 3,902 adults (age 33-92 years) with type 2 diabetes from 21 population-based cohorts. We calculated the hazard ratio (HR) per standard deviation (SD) difference in mean common carotid artery intima-media thickness (CCA-IMT) or in CCA-IMT progression, both calculated from two examinations on average 3.6 years apart, for each cohort, and combined the estimates with random-effects meta-analysis.RESULTSAverage mean CCA-IMT ranged from 0.72 to 0.97 mm across cohorts in people with diabetes. The HR of CVD events was 1.22 (95% CI 1.12-1.33) per SD difference in mean CCA-IMT, after adjustment for age, sex, and cardiometabolic risk factors. Average mean CCA-IMT progression in people with diabetes ranged between -0.09 and 0.04 mm/year. The HR per SD difference in mean CCA-IMT progression was 0.99 (0.91-1.08).CONCLUSIONSDespite reproducing the association between CIMT level and vascular risk in subjects with diabetes, we did not find an association between CIMT change and vascular risk. These results do not support the use of CIMT progression as a surrogate end point in clinical trials in people with diabetes.
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- Borgli, H, et al.
(författare)
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HyperKvasir, a comprehensive multi-class image and video dataset for gastrointestinal endoscopy
- 2020
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Ingår i: Scientific data. - : Springer Science and Business Media LLC. - 2052-4463. ; 7:1, s. 283-
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Tidskriftsartikel (refereegranskat)abstract
- Artificial intelligence is currently a hot topic in medicine. However, medical data is often sparse and hard to obtain due to legal restrictions and lack of medical personnel for the cumbersome and tedious process to manually label training data. These constraints make it difficult to develop systems for automatic analysis, like detecting disease or other lesions. In this respect, this article presents HyperKvasir, the largest image and video dataset of the gastrointestinal tract available today. The data is collected during real gastro- and colonoscopy examinations at Bærum Hospital in Norway and partly labeled by experienced gastrointestinal endoscopists. The dataset contains 110,079 images and 374 videos, and represents anatomical landmarks as well as pathological and normal findings. The total number of images and video frames together is around 1 million. Initial experiments demonstrate the potential benefits of artificial intelligence-based computer-assisted diagnosis systems. The HyperKvasir dataset can play a valuable role in developing better algorithms and computer-assisted examination systems not only for gastro- and colonoscopy, but also for other fields in medicine.
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