| 111. |
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| 113. |
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| 114. |
- Zheng, Jie, et al.
(författare)
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Lowering of Circulating Sclerostin May Increase Risk of Atherosclerosis and Its Risk Factors: Evidence From a Genome-Wide Association Meta-Analysis Followed by Mendelian Randomization.
- 2023
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Ingår i: Arthritis & rheumatology (Hoboken, N.J.). - 2326-5205. ; 75:10, s. 1781-1792
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Tidskriftsartikel (refereegranskat)abstract
- In this study, we aimed to establish the causal effects of lowering sclerostin, target of the antiosteoporosis drug romosozumab, on atherosclerosis and its risk factors.A genome-wide association study meta-analysis was performed of circulating sclerostin levels in 33,961 European individuals. Mendelian randomization (MR) was used to predict the causal effects of sclerostin lowering on 15 atherosclerosis-related diseases and risk factors.We found that 18 conditionally independent variants were associated with circulating sclerostin. Of these, 1 cis signal in SOST and 3 trans signals in B4GALNT3, RIN3, and SERPINA1 regions showed directionally opposite signals for sclerostin levels and estimated bone mineral density. Variants with these 4 regions were selected as genetic instruments. MR using 5 correlated cis-SNPs suggested that lower sclerostin increased the risk of type 2 diabetes mellitus (DM) (odds ratio [OR] 1.32 [95% confidence interval (95% CI) 1.03-1.69]) and myocardial infarction (MI) (OR 1.35 [95% CI 1.01-1.79]); sclerostin lowering was also suggested to increase the extent of coronary artery calcification (CAC) (β=0.24 [95% CI 0.02-0.45]). MR using both cis and trans instruments suggested that lower sclerostin increased hypertension risk (OR 1.09 [95% CI 1.04-1.15]), but otherwise had attenuated effects.This study provides genetic evidence to suggest that lower levels of sclerostin may increase the risk of hypertension, type 2 DM, MI, and the extent of CAC. Taken together, these findings underscore the requirement for strategies to mitigate potential adverse effects of romosozumab treatment on atherosclerosis and its related risk factors.
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| 115. |
- Abourraja, Mohamed Nezar, et al.
(författare)
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A Data-Driven Discrete Event Simulation Model to Improve Emergency Department Logistics
- 2022
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Ingår i: Proceedings of the 2022 Winter Simulation Conference. - : Institute of Electrical and Electronics Engineers (IEEE).
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Konferensbidrag (refereegranskat)abstract
- Demands for health care are becoming overwhelming for healthcare systems around the world regarding theavailability of resources, particularly, in emergency departments (EDs) that are continuously open and mustserve immediately any patient who comes in. Efficient management of EDs and their resources is requiredmore than ever. This could be achieved either by optimizing resource utilization or by the improvement ofhospital layout. This paper investigates, through data-driven simulation alternative designs of workflowsand layouts to operate the ED of the Uppsala University Hospital in Sweden. Results are analyzed tounderstand the requirements across the hospital for reduced waiting times in the ED. The main observationrevealed that introducing a new ward dedicated to patients having complex diagnoses with a capacity ofless than 20 beds leads to lower waiting times. Furthermore, the use of data-mining was of great help inreducing the efforts of building the simulation model.
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| 119. |
- Baumeister, Hannah, et al.
(författare)
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A generalizable data-driven model of atrophy heterogeneity and progression in memory clinic settings
- 2024
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Ingår i: Brain : a journal of neurology. - 1460-2156. ; 147:7, s. 2400-2413
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Tidskriftsartikel (refereegranskat)abstract
- Memory clinic patients are a heterogeneous population representing various aetiologies of pathological aging. It is unknown if divergent spatiotemporal progression patterns of brain atrophy, as previously described in Alzheimer's disease (AD) patients, are prevalent and clinically meaningful in this group of older adults. To uncover distinct atrophy subtypes, we applied the Subtype and Stage Inference (SuStaIn) algorithm to baseline structural MRI data from 813 participants enrolled in the DELCODE cohort (mean ± SD age = 70.67 ± 6.07 years, 52% females). Participants were cognitively unimpaired (CU; n = 285) or fulfilled diagnostic criteria for subjective cognitive decline (SCD; n = 342), mild cognitive impairment (MCI; n = 118), or dementia of the Alzheimer's type (n = 68). Atrophy subtypes were compared in baseline demographics, fluid AD biomarker levels, the Preclinical Alzheimer Cognitive Composite (PACC-5), as well as episodic memory and executive functioning. PACC-5 trajectories over up to 240 weeks were examined. To test if baseline atrophy subtype and stage predicted clinical trajectories before manifest cognitive impairment, we analysed PACC-5 trajectories and MCI conversion rates of CU and SCD participants. Limbic-predominant and hippocampal-sparing atrophy subtypes were identified. Limbic-predominant atrophy first affected the medial temporal lobes, followed by further temporal and, finally, the remaining cortical regions. At baseline, this subtype was related to older age, more pathological AD biomarker levels, APOE ε4 carriership, and an amnestic cognitive impairment. Hippocampal-sparing atrophy initially occurred outside the temporal lobe with the medial temporal lobe spared up to advanced atrophy stages. This atrophy pattern also affected individuals with positive AD biomarkers and was associated with more generalised cognitive impairment. Limbic-predominant atrophy, in all and in only unimpaired participants, was linked to more negative longitudinal PACC-5 slopes than observed in participants without or with hippocampal-sparing atrophy and increased the risk of MCI conversion. SuStaIn modelling was repeated in a sample from the Swedish BioFINDER-2 cohort. Highly similar atrophy progression patterns and associated cognitive profiles were identified. Cross-cohort model generalizability, both on the subject and group level, were excellent, indicating reliable performance in previously unseen data. The proposed model is a promising tool for capturing heterogeneity among older adults at early at-risk states for AD in applied settings. The implementation of atrophy subtype- and stage-specific end-points may increase the statistical power of pharmacological trials targeting early AD.
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