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- Klonoff, D. C., et al.
(författare)
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A Glycemia Risk Index (GRI) of Hypoglycemia and Hyperglycemia for Continuous Glucose Monitoring Validated by Clinician Ratings
- 2022
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Ingår i: Journal of Diabetes Science and Technology. - : SAGE Publications. - 1932-2968.
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Tidskriftsartikel (refereegranskat)abstract
- Background: A composite metric for the quality of glycemia from continuous glucose monitor (CGM) tracings could be useful for assisting with basic clinical interpretation of CGM data. Methods: We assembled a data set of 14-day CGM tracings from 225 insulin-treated adults with diabetes. Using a balanced incomplete block design, 330 clinicians who were highly experienced with CGM analysis and interpretation ranked the CGM tracings from best to worst quality of glycemia. We used principal component analysis and multiple regressions to develop a model to predict the clinician ranking based on seven standard metrics in an Ambulatory Glucose Profile: very low–glucose and low-glucose hypoglycemia; very high–glucose and high-glucose hyperglycemia; time in range; mean glucose; and coefficient of variation. Results: The analysis showed that clinician rankings depend on two components, one related to hypoglycemia that gives more weight to very low-glucose than to low-glucose and the other related to hyperglycemia that likewise gives greater weight to very high-glucose than to high-glucose. These two components should be calculated and displayed separately, but they can also be combined into a single Glycemia Risk Index (GRI) that corresponds closely to the clinician rankings of the overall quality of glycemia (r = 0.95). The GRI can be displayed graphically on a GRI Grid with the hypoglycemia component on the horizontal axis and the hyperglycemia component on the vertical axis. Diagonal lines divide the graph into five zones (quintiles) corresponding to the best (0th to 20th percentile) to worst (81st to 100th percentile) overall quality of glycemia. The GRI Grid enables users to track sequential changes within an individual over time and compare groups of individuals. Conclusion: The GRI is a single-number summary of the quality of glycemia. Its hypoglycemia and hyperglycemia components provide actionable scores and a graphical display (the GRI Grid) that can be used by clinicians and researchers to determine the glycemic effects of prescribed and investigational treatments.
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| 2. |
- Tobias, Deirdre K, et al.
(författare)
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Second international consensus report on gaps and opportunities for the clinical translation of precision diabetes medicine
- 2023
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Ingår i: Nature Medicine. - 1546-170X. ; 29:10, s. 2438-2457
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Forskningsöversikt (refereegranskat)abstract
- Precision medicine is part of the logical evolution of contemporary evidence-based medicine that seeks to reduce errors and optimize outcomes when making medical decisions and health recommendations. Diabetes affects hundreds of millions of people worldwide, many of whom will develop life-threatening complications and die prematurely. Precision medicine can potentially address this enormous problem by accounting for heterogeneity in the etiology, clinical presentation and pathogenesis of common forms of diabetes and risks of complications. This second international consensus report on precision diabetes medicine summarizes the findings from a systematic evidence review across the key pillars of precision medicine (prevention, diagnosis, treatment, prognosis) in four recognized forms of diabetes (monogenic, gestational, type 1, type 2). These reviews address key questions about the translation of precision medicine research into practice. Although not complete, owing to the vast literature on this topic, they revealed opportunities for the immediate or near-term clinical implementation of precision diabetes medicine; furthermore, we expose important gaps in knowledge, focusing on the need to obtain new clinically relevant evidence. Gaps include the need for common standards for clinical readiness, including consideration of cost-effectiveness, health equity, predictive accuracy, liability and accessibility. Key milestones are outlined for the broad clinical implementation of precision diabetes medicine.
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| 6. |
- Rosenblatt, A, et al.
(författare)
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Familial influence on age of onset among siblings with Huntington disease.
- 2001
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Ingår i: American Journal of Medical Genetics. - 0148-7299 .- 1096-8628. ; 105:5, s. 399-403
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Tidskriftsartikel (refereegranskat)abstract
- In order to provide data relevant to a search for modifying genes for age of onset in Huntington disease, we examined the relationship between CAG number and age of onset in a total of 370 individuals from 165 siblingships, in two cohorts of siblings with Huntington disease: an American group of 144 individuals from 64 siblingships, and a Canadian population of 255 individuals from 113 siblingships. Using a logarithmic model to regress the age of onset on the number of CAG triplets, we found that CAG number alone accounted for 65%-71% of the variance in age of onset. The siblingship an individual belonged to accounted for 11%-19% of additional variance. This adds to the previous evidence that there are familial modifiers of the age of onset, independent of the CAG number. Such modifiers may consist of additional genes, which could be the target of a linkage study. A linkage study is feasible with the cooperation of a number of major centers and may be made more efficient by concentrating on sibling pairs that are highly discordant for age of onset.
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| 9. |
- SHELDON, RW, et al.
(författare)
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NANOPLANKTON AND PICOPLANKTON GROWTH AND PRODUCTION IN THE BAY OF VILLEFRANCHE-SUR-MER (NW MEDITERRANEAN)
- 1992
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Ingår i: Hydrobiologia. - 0018-8158 .- 1573-5117. ; 241:2, s. 91-106
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Tidskriftsartikel (refereegranskat)abstract
- Plankton production in the Bay of Villefranche was relatively constant during March and April 1986 but the particle size at which the production occurred was more variable. At the beginning of the study, production was dominated by the larger (ca. 6 mum) flagellates but towards the end it was more or less equally divided between the nano- and picoplankton. There were considerable differences in the estimates of population growth rates, depending on the methods used, but on average the population doubling times were close to 12 hours for autotrophs and 24 hours for heterotrophs. As autotrophs do not grow during the night, each population was therefore doubling once per day. It seemed that each of the nano- or picoplankton populations could adversely affect the growth of the others. This could be either by simple predation or by some form of inhibition. Although nutrient levels in the bay were uniformly low, the addition of nutrients did not always stimulate algal growth. The plankton populations seemed to be both in a state of equilibrium and intense ecological competition.
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