| 1. |
- Glasbey, JC, et al.
(författare)
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- 2021
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swepub:Mat__t
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| 2. |
- Tabiri, S, et al.
(författare)
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- 2021
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swepub:Mat__t
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| 3. |
- Bravo, L, et al.
(författare)
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- 2021
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swepub:Mat__t
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| 4. |
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| 5. |
- Khatri, C, et al.
(författare)
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Outcomes after perioperative SARS-CoV-2 infection in patients with proximal femoral fractures: an international cohort study
- 2021
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Ingår i: BMJ open. - : BMJ. - 2044-6055. ; 11:11, s. e050830-
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Tidskriftsartikel (refereegranskat)abstract
- Studies have demonstrated high rates of mortality in people with proximal femoral fracture and SARS-CoV-2, but there is limited published data on the factors that influence mortality for clinicians to make informed treatment decisions. This study aims to report the 30-day mortality associated with perioperative infection of patients undergoing surgery for proximal femoral fractures and to examine the factors that influence mortality in a multivariate analysis.SettingProspective, international, multicentre, observational cohort study.ParticipantsPatients undergoing any operation for a proximal femoral fracture from 1 February to 30 April 2020 and with perioperative SARS-CoV-2 infection (either 7 days prior or 30-day postoperative).Primary outcome30-day mortality. Multivariate modelling was performed to identify factors associated with 30-day mortality.ResultsThis study reports included 1063 patients from 174 hospitals in 19 countries. Overall 30-day mortality was 29.4% (313/1063). In an adjusted model, 30-day mortality was associated with male gender (OR 2.29, 95% CI 1.68 to 3.13, p<0.001), age >80 years (OR 1.60, 95% CI 1.1 to 2.31, p=0.013), preoperative diagnosis of dementia (OR 1.57, 95% CI 1.15 to 2.16, p=0.005), kidney disease (OR 1.73, 95% CI 1.18 to 2.55, p=0.005) and congestive heart failure (OR 1.62, 95% CI 1.06 to 2.48, p=0.025). Mortality at 30 days was lower in patients with a preoperative diagnosis of SARS-CoV-2 (OR 0.6, 95% CI 0.6 (0.42 to 0.85), p=0.004). There was no difference in mortality in patients with an increase to delay in surgery (p=0.220) or type of anaesthetic given (p=0.787).ConclusionsPatients undergoing surgery for a proximal femoral fracture with a perioperative infection of SARS-CoV-2 have a high rate of mortality. This study would support the need for providing these patients with individualised medical and anaesthetic care, including medical optimisation before theatre. Careful preoperative counselling is needed for those with a proximal femoral fracture and SARS-CoV-2, especially those in the highest risk groups.Trial registration numberNCT04323644
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| 6. |
- Bakker, G. J., et al.
(författare)
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Pancreatic 18 F-FDG uptake is increased in type 2 diabetes patients compared to non-diabetic controls
- 2019
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Ingår i: Plos One. - : Public Library of Science (PLoS). - 1932-6203. ; 14:3
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Tidskriftsartikel (refereegranskat)abstract
- Introduction Increasing evidence indicates that the development of type 2 diabetes is driven by chronic low grade beta-cell inflammation. However, it is unclear whether pancreatic inflammation can be noninvasively visualized in type 2 diabetes patients. We aimed to assess pancreatic 18 F-FDG uptake in type 2 diabetes patients and controls using 18 F-fluorodeoxylglucose positron emission tomography/computed tomography ( 18 F-FDG PET/CT). Material and methods In this retrospective cross-sectional study, we enrolled 20 type 2 diabetes patients and 65 controls who had undergone a diagnostic 18 F-FDG PET/CT scan and obtained standardized uptake values (SUVs) of pancreas and muscle. Pancreatic SUV was adjusted for background uptake in muscle and for fasting blood glucose concentrations. Results The maximum pancreatic SUVs adjusted for background muscle uptake (SUV max.m ) and fasting blood glucose concentration (SUV glucose ) were significantly higher in diabetes patients compared to controls (median 2.86 [IQR 2.24–4.36] compared to 2.15 [IQR 1.51–2.83], p = 0.006 and median 2.76 [IQR 1.18–4.34] compared to 1.91 [IQR 1.27–2.55], p<0.001, respectively). In linear regression adjusting for age and body mass index, diabetes remained the main predictor of SUV max.m and SUV glucose . Conclusion Pancreatic 18 F-FDG uptake adjusted for background muscle uptake and fasting blood glucose concentration was significantly increased in type 2 diabetes patients. © 2019 Bakker et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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| 7. |
- Bouter, K. E. C., et al.
(författare)
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Differential metabolic effects of oral butyrate treatment in lean versus metabolic syndrome subjects article
- 2018
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Ingår i: Clinical and Translational Gastroenterology. - : Ovid Technologies (Wolters Kluwer Health). - 2155-384X. ; 9:5
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Tidskriftsartikel (refereegranskat)abstract
- Background: Gut microbiota-derived short-chain fatty acids (SCFAs) have been associated with beneficial metabolic effects. However, the direct effect of oral butyrate on metabolic parameters in humans has never been studied. In this first in men pilot study, we thus treated both lean and metabolic syndrome male subjects with oral sodium butyrate and investigated the effect on metabolism. Methods: Healthy lean males (n = 9) and metabolic syndrome males (n = 10) were treated with oral 4 g of sodium butyrate daily for 4 weeks. Before and after treatment, insulin sensitivity was determined by a two-step hyperinsulinemic euglycemic clamp using [6,6-2H2]-glucose. Brown adipose tissue (BAT) uptake of glucose was visualized using 18F-FDG PET-CT. Fecal SCFA and bile acid concentrations as well as microbiota composition were determined before and after treatment. Results: Oral butyrate had no effect on plasma and fecal butyrate levels after treatment, but did alter other SCFAs in both plasma and feces. Moreover, only in healthy lean subjects a significant improvement was observed in both peripheral (median Rd: from 71 to 82 μmol/kg min, p < 0.05) and hepatic insulin sensitivity (EGP suppression from 75 to 82% p < 0.05). Although BAT activity was significantly higher at baseline in lean (SUVmax: 12.4 ± 1.8) compared with metabolic syndrome subjects (SUVmax: 0.3 ± 0.8, p < 0.01), no significant effect following butyrate treatment on BAT was observed in either group (SUVmax lean to 13.3 ± 2.4 versus metabolic syndrome subjects to 1.2 ± 4.1). Conclusions: Oral butyrate treatment beneficially affects glucose metabolism in lean but not metabolic syndrome subjects, presumably due to an altered SCFA handling in insulin-resistant subjects. Although preliminary, these first in men findings argue against oral butyrate supplementation as treatment for glucose regulation in human subjects with type 2 diabetes mellitus. © 2018 The Author(s).
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| 8. |
- Slart, Riemer H. J. A., et al.
(författare)
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Position paper of the EACVI and EANM on artificial intelligence applications in multimodality cardiovascular imaging using SPECT/CT, PET/CT, and cardiac CT
- 2021
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Ingår i: European Journal of Nuclear Medicine and Molecular Imaging. - : Springer. - 1619-7070 .- 1619-7089. ; 48:5, s. 1399-1413
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Tidskriftsartikel (refereegranskat)abstract
- In daily clinical practice, clinicians integrate available data to ascertain the diagnostic and prognostic probability of a disease or clinical outcome for their patients. For patients with suspected or known cardiovascular disease, several anatomical and functional imaging techniques are commonly performed to aid this endeavor, including coronary computed tomography angiography (CCTA) and nuclear cardiology imaging. Continuous improvement in positron emission tomography (PET), single-photon emission computed tomography (SPECT), and CT hardware and software has resulted in improved diagnostic performance and wide implementation of these imaging techniques in daily clinical practice. However, the human ability to interpret, quantify, and integrate these data sets is limited. The identification of novel markers and application of machine learning (ML) algorithms, including deep learning (DL) to cardiovascular imaging techniques will further improve diagnosis and prognostication for patients with cardiovascular diseases. The goal of this position paper of the European Association of Nuclear Medicine (EANM) and the European Association of Cardiovascular Imaging (EACVI) is to provide an overview of the general concepts behind modern machine learning-based artificial intelligence, highlights currently prefered methods, practices, and computational models, and proposes new strategies to support the clinical application of ML in the field of cardiovascular imaging using nuclear cardiology (hybrid) and CT techniques.
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