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- Glasbey, JC, et al.
(författare)
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- 2021
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swepub:Mat__t
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- Adams, D., et al.
(författare)
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Patisiran, an RNAi Therapeutic, for Hereditary Transthyretin Amyloidosis
- 2018
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Ingår i: New England Journal of Medicine. - : Massachusetts Medical Society. - 0028-4793 .- 1533-4406. ; 379:1, s. 11-21
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Patisiran, an investigational RNA interference therapeutic agent, specifically inhibits hepatic synthesis of transthyretin.METHODS: In this phase 3 trial, we randomly assigned patients with hereditary transthyretin amyloidosis with polyneuropathy, in a 2:1 ratio, to receive intravenous patisiran (0.3 mg per kilogram of body weight) or placebo once every 3 weeks. The primary end point was the change from baseline in the modified Neuropathy Impairment Score+7 (mNIS+7; range, 0 to 304, with higher scores indicating more impairment) at 18 months. Other assessments included the Norfolk Quality of Life-Diabetic Neuropathy (Norfolk QOL-DN) questionnaire (range, -4 to 136, with higher scores indicating worse quality of life), 10-m walk test (with gait speed measured in meters per second), and modified body-mass index (modified BMI, defined as [weight in kilograms divided by square of height in meters] x albumin level in grams per liter; lower values indicated worse nutritional status).RESULTS: A total of 225 patients underwent randomization (148 to the patisiran group and 77 to the placebo group). The mean (+/- SD) mNIS+7 at baseline was 80.9 +/- 41.5 in the patisiran group and 74.6 +/- 37.0 in the placebo group; the least-squares mean (+/- SE) change from baseline was -6.0 +/- 1.7 versus 28.0 +/- 2.6 (difference, -34.0 points; P<0.001) at 18 months. The mean (+/- SD) baseline Norfolk QOL-DN score was 59.6 +/- 28.2 in the patisiran group and 55.5 +/- 24.3 in the placebo group; the least-squares mean (+/- SE) change from baseline was -6.7 +/- 1.8 versus 14.4 +/- 2.7 (difference, -21.1 points; P<0.001) at 18 months. Patisiran also showed an effect on gait speed and modified BMI. At 18 months, the least-squares mean change from baseline in gait speed was 0.08 +/- 0.02 m per second with patisiran versus -0.24 +/- 0.04 m per second with placebo (difference, 0.31 m per second; P<0.001), and the least-squares mean change from baseline in the modified BMI was -3.7 +/- 9.6 versus -119.4 +/- 14.5 (difference, 115.7; P<0.001). Approximately 20% of the patients who received patisiran and 10% of those who received placebo had mild or moderate infusion-related reactions; the overall incidence and types of adverse events were similar in the two groups.CONCLUSIONS: In this trial, patisiran improved multiple clinical manifestations of hereditary transthyretin amyloidosis.
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| 7. |
- Martin, W. P., et al.
(författare)
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Obesity is common in chronic kidney disease and associates with greater antihypertensive usage and proteinuria: evidence from a cross-sectional study in atertiary nephrology centre
- 2020
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Ingår i: Clinical Obesity. - : Wiley. - 1758-8103 .- 1758-8111. ; 10:6
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Tidskriftsartikel (refereegranskat)abstract
- Obesity is a treatable risk factor for chronic kidney disease progression. We audited the reporting of body-mass index in nephrology outpatient clinics to establish the characteristics of individuals with obesity in nephrology practice. Body-mass index, clinical information and biochemical measures were recorded for patients attending clinics between 3(rd)August, 2018 and 18(th)January, 2019. Inferential statistics and Pearson correlations were used to investigate relationships between body-mass index, type 2 diabetes, hypertension and proteinuria. Mean +/- SD BMI was 28.6 +/- 5.8 kg/m(2)(n = 374). Overweight and obesity class 1 were more common in males (P= .02). Amongst n = 123 individuals with obesity and chronic kidney disease, mean +/- SD age, n (%) female and median[IQR] eGFR were 64.1 +/- 14.2 years, 52 (42.3%) and 29.0[20.5] mL/min/BSA, respectively. A positive correlation between increasing body-mass index and proteinuria was observed in such patients (r= 0.21,P= .03), which was stronger in males and those with CKD stages 4 and 5. Mean body-mass index was 2.3 kg/m(2)higher in those treated with 4-5 versus 0-1 antihypertensives (P= .03). Amongst n = 59 patients with obesity, chronic kidney disease and type 2 diabetes, 2 (3.5%) and 0 (0%) were prescribed a GLP-1 receptor analogue and SGLT2-inhibitor, respectively. Our data provides a strong rationale not only for measuring body-mass index but also for acting on the information in nephrology practice, although prospective studies are required to guide treatment decisions in people with obesity and chronic kidney disease.
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| 8. |
- Pöntinen, M., et al.
(författare)
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Euclid: Identification of asteroid streaks in simulated images using deep learning
- 2023
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Ingår i: Astronomy and Astrophysics. - : EDP Sciences. - 0004-6361 .- 1432-0746. ; 679
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Tidskriftsartikel (refereegranskat)abstract
- The material composition of asteroids is an essential piece of knowledge in the quest to understand the formation and evolution of the Solar System. Visual to near-infrared spectra or multiband photometry is required to constrain the material composition of asteroids, but we currently have such data, especially in the near-infrared wavelengths, for only a limited number of asteroids. This is a significant limitation considering the complex orbital structures of the asteroid populations. Up to 150 000 asteroids will be visible in the images of the upcoming ESA Euclid space telescope, and the instruments of Euclid will offer multiband visual to near-infrared photometry and slitless near-infrared spectra of these objects. Most of the asteroids will appear as streaks in the images. Due to the large number of images and asteroids, automated detection methods are needed. A non-machine-learning approach based on the Streak Det software was previously tested, but the results were not optimal for short and/or faint streaks. We set out to improve the capability to detect asteroid streaks in Euclid images by using deep learning. We built, trained, and tested a three-step machine-learning pipeline with simulated Euclid images. First, a convolutional neural network (CNN) detected streaks and their coordinates in full images, aiming to maximize the completeness (recall) of detections. Then, a recurrent neural network (RNN) merged snippets of long streaks detected in several parts by the CNN. Lastly, gradient-boosted trees (XGBoost) linked detected streaks between different Euclid exposures to reduce the number of false positives and improve the purity (precision) of the sample. The deep-learning pipeline surpasses the completeness and reaches a similar level of purity of a non-machine-learning pipeline based on the StreakDet software. Additionally, the deep-learning pipeline can detect asteroids 0.25–0.5 magnitudes fainter than StreakDet. The deep-learning pipeline could result in a 50% increase in the number of detected asteroids compared to the StreakDet software. There is still scope for further refinement, particularly in improving the accuracy of streak coordinates and enhancing the completeness of the final stage of the pipeline, which involves linking detections across multiple exposures.
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| 10. |
- Denoncourt, R. N., et al.
(författare)
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Burden of Illness for Patients with Hereditary Attr Amyloidosis with Polyneuropathy Begins with Symptom Onset and Increases with Disease Progression
- 2016
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Ingår i: Value in Health. - : Elsevier. - 1098-3015 .- 1524-4733. ; 19:7, s. A436-A436
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Tidskriftsartikel (refereegranskat)abstract
- Objectives: Hereditary ATTR amyloidosis with polyneuropathy (hATTR-PN), also known as familial amyloidotic polyneuropathy (FAP), is an inherited, progressive disease leading to death within 5-15 years. hATTR-PN is due to a mutation in the transthyretin (TTR) gene. Patisiran is an investigational, RNA interference (RNAi) therapeutic targeting TTR. This abstract aims to further characterize hATTR-PN burden of illness.Methods: The ongoing, patisiran Phase 3 APOLLO trial was utilized to collect patient-reported EQ-5D, Norfolk-DN, Rasch-built Overall Disability Scale (R-ODS), and healthcare resource utilization from hATTR-PN patients with symptomatic disease.Results: APOLLO included 225 patients; median age of 62 years (range: 24-82), median neurological impairment score (NIS) of 6-141.6 and representative of the global patient population (19 countries) with a broad range of mutations and disease severities. At baseline, 57 patients had a Polyneuropathy Disability (PND) Score I and 168 patients had a PND Score ≥ II. By FAP Stage, 104 were FAP Stage 1 and 121 were FAP Stage 2. 41 patients (PND Score ≥ II) reported ≥1 hospitalization of ≥3 nights in duration due to hATTR-PN in the 12 months prior to enrollment. Mean EQ-5D scores were 0.76 (PND Score I) and 0.59 (PND Score ≥ II). Patients reported perceived health status on the EQ-VAS with mean scores of 66.9 (PND Score I) and 51.3 (PND Score ≥ II). Mean Norfolk-QoL-DN scores were 35.5 (PND Score I) and 66.0 (PND Score ≥ II). 145 patients (131 PND Score ≥ II) reported they cannot work because of hATTR-PN. Mean R-ODS scores were 40.9 and 25.9 for PND Score I and PND Score ≥ II, respectively.Conclusions: These data, from the largest controlled study of patients with hATTR-PN to date, further demonstrate that patients experience considerable burden of illness early in the course of disease and this burden increases with disease progression.
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