| 1. |
- Bergman, Lina, 1982, et al.
(author)
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Cerebral biomarkers in neurologic complications of preeclampsia
- 2022
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In: American Journal of Obstetrics and Gynecology. - : Elsevier BV. - 0002-9378 .- 1097-6868. ; 227:2, s. 298.e1-298.e10
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Journal article (peer-reviewed)abstract
- Background: There is no tool to accurately predict who is at risk of developing neurologic complications of preeclampsia, and there is no objective method to determine disease severity. Objective: We assessed whether plasma concentrations of the cerebral biomarkers neurofilament light, tau, and glial fibrillary acidic protein could reflect disease severity in several phenotypes of preeclampsia. Furthermore, we compared the cerebral biomarkers with the angiogenic biomarkers soluble fms-like tyrosine kinase 1, placental growth factor, and soluble endoglin. Study Design: In this observational study, we included women from the South African Preeclampsia Obstetric Adverse Events biobank. Plasma samples taken at diagnosis (preeclampsia cases) or admission for delivery (normotensive controls) were analyzed for concentrations of neurofilament light, tau, glial fibrillary acidic protein, placental growth factor, soluble fms-like tyrosine kinase 1, and soluble endoglin. The cerebrospinal fluid concentrations of inflammatory markers and albumin were analyzed in a subgroup of 15 women. Analyses were adjusted for gestational age, time from seizures and delivery to sampling, maternal age, and parity. Results: Compared with 28 women with normotensive pregnancies, 146 women with preeclampsia demonstrated 2.18-fold higher plasma concentrations of neurofilament light (95% confidence interval, 1.64–2.88), 2.17-fold higher tau (95% confidence interval, 1.49–3.16), and 2.77-fold higher glial fibrillary acidic protein (95% confidence interval, 2.06–3.72). Overall, 72 women with neurologic complications (eclampsia, cortical blindness, and stroke) demonstrated increased plasma concentrations of tau (2.99-fold higher; 95% confidence interval, 1.92–4.65) and glial fibrillary acidic protein (3.22-fold higher; 95% confidence interval, 2.06–5.02) compared with women with preeclampsia without pulmonary edema; hemolysis, elevated liver enzymes, and low platelet count; or neurologic complications (n=31). Moreover, angiogenic markers were higher, but to a lesser extent. Women with hemolysis, elevated liver enzymes, and low platelet count (n=20) demonstrated increased plasma concentrations of neurofilament light (1.64-fold higher; 95% confidence interval, 1.06–2.55), tau (4.44-fold higher; 95% confidence interval, 1.85–10.66), and glial fibrillary acidic protein (1.82-fold higher; 95% confidence interval, 1.32–2.50) compared with women with preeclampsia without pulmonary edema; hemolysis, elevated liver enzymes, and low platelet count; or neurologic complications. There was no difference shown in the angiogenic biomarkers. There was no difference between 23 women with preeclampsia complicated by pulmonary edema and women with preeclampsia without pulmonary edema; hemolysis, elevated liver enzymes, and low platelet count; or neurologic complications for any of the biomarkers. Plasma concentrations of tau and glial fibrillary acidic protein were increased in women with several neurologic complications compared with women with eclampsia only. Conclusion: Plasma neurofilament light, glial fibrillary acidic, and tau were candidate biomarkers for the diagnosis and possibly prediction of cerebral complications of preeclampsia.
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| 2. |
- Novakova, Lenka, et al.
(author)
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Searching for neurodegeneration in multiple sclerosis at clinical onset: Diagnostic value of biomarkers
- 2018
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In: PLoS ONE. - : Public Library of Science (PLoS). - 1932-6203 .- 1932-6203. ; 13:4
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Journal article (peer-reviewed)abstract
- Background Neurodegeneration occurs during the early stages of multiple sclerosis. It is an essential, devastating part of the pathophysiology. Tools for measuring the degree of neurodegeneration could improve diagnostics and patient characterization. Objective This study aimed to determine the diagnostic value of biomarkers of degeneration in patients with recent clinical onset of suspected multiple sclerosis, and to evaluate these biomarkers for characterizing disease course. Methods This cross-sectional study included 271 patients with clinical features of suspected multiple sclerosis onset and was the baseline of a prospective study. After diagnostic investigations, the patients were classified into the following disease groups: Patients with clinically isolated syndrome (n = 4) or early relapsing remitting multiple sclerosis (early RRMS; n = 93); patients with relapsing remitting multiple sclerosis with disease durations ≥2 years (established RRMS; n = 39); patients without multiple sclerosis, but showing symptoms (symptomatic controls; n = 89); and patients diagnosed with other diseases (n = 46). In addition, we included healthy controls (n = 51) and patients with progressive multiple sclerosis (n = 23). We analyzed six biomarkers of neurodegeneration: Cerebrospinal fluid neurofilament light chain levels; cerebral spinal fluid glial fibrillary acidic protein; cerebral spinal fluid tau; retinal nerve fiber layer thickness; macula volume; and the brain parenchymal fraction. Results Except for increased cerebral spinal fluid neurofilament light chain levels, median 670 ng/L (IQR 400-2110), we could not find signs of early degeneration in the early disease group with recent clinical onset. However, the intrathecal immunoglobin G production and cerebral spinal fluid neurofilament light chain levels showed diagnostic value. Moreover, elevated levels of cerebral spinal fluid glial fibrillary acidic protein, thin retinal nerve fiber layers, and low brain parenchymal fractions were associated with progressive disease, but not with the other phenotypes. Thin retinal nerve fiber layers and low brain parenchymal fractions, which indicated neurodegeneration, were associated with longer disease duration. Conclusions In clinically suspected multiple sclerosis, intrathecal immunoglobin G production and neurofilament light chain levels had diagnostic value. Therefore, these biomarkers could be included in diagnostic work-ups for multiple sclerosis. We found that the thickness of the retinal nerve fiber layer and the brain parenchymal fraction were not different between individuals that were healthy, symptomatic, or newly diagnosed with multiple sclerosis. This finding suggested that neurodegeneration had not reached a significant magnitude in patients with a recent clinical onset of multiple sclerosis.
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| 3. |
- Westman, Klara, et al.
(author)
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Variables associated with insulin production in persons with type 2 diabetes treated with multiple daily insulin injections
- 2021
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In: Primary Care Diabetes. - : Elsevier BV. - 1751-9918 .- 1878-0210. ; 15:3, s. 607-613
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Journal article (peer-reviewed)abstract
- From the MDI-liraglutide study, we evaluated variables associated with endogenous insulin production in persons with multiple daily insulin injections-treated type 2 diabetes by relating C-peptide, proinsulin and proinsulin/C-peptide ratio at baseline to baseline variables. Lower insulin production was related to longer diabetes duration, shorter abdominal sagittal diameter and more glycaemic variability.
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| 4. |
- Ahmadi, Shilan Seyed, et al.
(author)
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Effect of liraglutide on anthropometric measurements, sagittal abdominal diameter and adiponectin levels in people with type 2 diabetes treated with multiple daily insulin injections: evaluations from a randomized trial (MDI-liraglutide study 5)
- 2019
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In: Obesity Science and Practice. - : Wiley. - 2055-2238. ; 5:2, s. 130-140
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Journal article (peer-reviewed)abstract
- Aim Use of the glucagon-like peptide 1 receptor agonist liraglutide has been shown to reduce weight. Different types of anthropometric measurements can be used to measure adiposity. This study evaluated the effect of liraglutide on sagittal abdominal diameter, waist circumference, waist-to-hip ratio and adiponectin levels in people with type 2 diabetes (T2D) treated with multiple daily insulin injections (MDI). Materials and methods In the multicentre, double-blind, placebo-controlled MDI-liraglutide trial, 124 individuals with T2D treated with MDI were randomized to either liraglutide or placebo. Basal values of weight, waist circumference, waist-to-hip ratio, sagittal abdominal diameter and adiponectin were compared with measurements at 12 and 24 weeks after randomization. Results Baseline-adjusted mean weight loss was 3.8 +/- 2.9 kg greater in liraglutide than placebo-treated individuals (p < 0.0001). Waist circumference was reduced by 2.9 +/- 4.3 cm and 0.2 +/- 3.6 cm in the liraglutide and placebo groups, respectively, after 24 weeks (baseline-adjusted mean difference: 2.6 +/- 4.0 cm, p = 0.0005). Corresponding reductions in sagittal abdominal diameter were 1.1 +/- 1.7 cm and 0.0 +/- 1.8 cm (baseline-adjusted mean difference: 1.1 +/- 1.7 cm, p = 0.0008). Hip circumference was reduced in patients randomized to liraglutide (baseline-adjusted mean difference between treatment groups: 2.8 +/- 3.8 cm, p = 0.0001), but there was no significant difference between the groups in either waist-to-hip ratio (baseline-adjusted mean difference: 0.0 +/- 0.04 cm, p = 0.51) or adiponectin levels (baseline-adjusted mean difference: 0.8 +/- 3.3 mg L-1, p = 0.17). Lower HbA1c and mean glucose levels measured by masked continuous glucose monitoring at baseline were associated with greater effects of liraglutide on reductions in waist circumference and sagittal abdominal diameter. Conclusions In patients with T2D, adding liraglutide to MDI may reduce abdominal and hip obesity to a similar extent, suggesting an effect on both visceral and subcutaneous fat. Liraglutide had greater effects on reducing abdominal obesity in patients with less pronounced long-term hyperglycaemia but did not affect adiponectin levels.
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| 5. |
- Bergman, Lina, 1982, et al.
(author)
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Study for Improving Maternal Pregnancy And Child ouTcomes (IMPACT): a study protocol for a Swedish prospective multicentre cohort study
- 2020
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In: BMJ Open. - : BMJ. - 2044-6055 .- 2044-6055. ; 10:9, s. e033851-e033851
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Journal article (peer-reviewed)abstract
- Introduction First-trimester pregnancy risk evaluation facilitates individualised antenatal care, as well as application of preventive strategies for pre-eclampsia or birth of a small for gestational age infant. A range of early intervention strategies in pregnancies identified as high risk at the end of the first trimester has been shown to decrease the risk of preterm pre-eclampsia (<37 gestational weeks). The aim of this project is to create the Improving Maternal Pregnancy And Child ouTcomes (IMPACT) database; a nationwide database with individual patient data, including predictors recorded at the end of the first trimester and later pregnancy outcomes, to identify women at high risk of pre-eclampsia. A second aim is to link the IMPACT database to a biobank with first-trimester blood samples. Methods and analysis This is a Swedish prospective multicentre cohort study. Women are included between the 11th and 14th weeks of pregnancy. At inclusion, pre-identified predictors are retrieved by interviews and medical examinations. Blood samples are collected and stored in a biobank. Additional predictors and pregnancy outcomes are retrieved from the Swedish Pregnancy Register. Inclusion in the study began in November 2018 with a targeted sample size of 45 000 pregnancies by end of 2021. Creation of a new risk prediction model will then be developed, validated and implemented. The database and biobank will enable future research on prediction of various pregnancy-related complications. Ethics and dissemination Confidentiality aspects such as data encryption and storage comply with the General Data Protection Regulation and with ethical committee requirements. This study has been granted national ethical approval by the Swedish Ethical Review Authority (Uppsala 2018-231) and national biobank approval at Uppsala Biobank (18237 2 2018 231). Results from the current as well as future studies using information from the IMPACT database will be published in peer-reviewed journals.
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| 6. |
- Cluver, Catherine, et al.
(author)
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Impact of fetal growth restriction on pregnancy outcome in women undergoing expectant management for preterm pre-eclampsia
- 2023
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In: Ultrasound in Obstetrics and Gynecology. - 1469-0705 .- 0960-7692. ; 62:5, s. 660-667
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Journal article (peer-reviewed)abstract
- Objectives: To assess whether coexisting fetal growth restriction (FGR) influences pregnancy latency among women with preterm pre-eclampsia undergoing expectant management. Secondary outcomes assessed were indication for delivery, mode of delivery and rate of serious adverse maternal and perinatal outcomes. Methods: We conducted a secondary analysis of the Pre-eclampsia Intervention (PIE) and the Pre-eclampsia Intervention 2 (PI2) trial data. These randomized controlled trials evaluated whether esomeprazole and metformin could prolong gestation of women diagnosed with pre-eclampsia between 26 and 32 weeks of gestation undergoing expectant management. Delivery indications were deteriorating maternal or fetal status, or reaching 34 weeks' gestation. FGR (defined by Delphi consensus) at the time of pre-eclampsia diagnosis was examined as a predictor of outcome. Only placebo data from PI2 were included, as the trial showed that metformin use was associated with prolonged gestation. All outcome data were collected prospectively from diagnosis of pre-eclampsia to 6 weeks after the expected due date. Results: Of the 202 women included, 92 (45.5%) had FGR at the time of pre-eclampsia diagnosis. Median pregnancy latency was 6.8 days in the FGR group and 15.3 days in the control group (difference 8.5 days; adjusted 0.49-fold change (95% CI, 0.33–0.74); P < 0.001). FGR pregnancies were less likely to reach 34 weeks' gestation (12.0% vs 30.9%; adjusted relative risk (aRR), 0.44 (95% CI, 0.23–0.83)) and more likely to be delivered for suspected fetal compromise (64.1% vs 36.4%; aRR, 1.84 (95% CI, 1.36–2.47)). More women with FGR underwent a prelabor emergency Cesarean section (66.3% vs 43.6%; aRR, 1.56 (95% CI, 1.20–2.03)) and were less likely to have a successful induction of labor (4.3% vs 14.5%; aRR, 0.32 (95% CI, 0.10–1.00)), compared to those without FGR. The rate of maternal complications did not differ significantly between the two groups. FGR was associated with a higher rate of infant death (14.1% vs 4.5%; aRR, 3.26 (95% CI, 1.08–9.81)) and need for intubation and mechanical ventilation (15.2% vs 5.5%; aRR, 2.97 (95% CI, 1.11–7.90)). Conclusion: FGR is commonly present in women with early preterm pre-eclampsia and outcome is poorer. FGR is associated with shorter pregnancy latency, more emergency Cesarean deliveries, fewer successful inductions and increased rates of neonatal morbidity and mortality. © 2023 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.
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| 7. |
- Dahlqvist, S., et al.
(author)
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Variables associated with HbA1c and weight reductions when adding liraglutide to multiple daily insulin injections in persons with type 2 diabetes (MDI Liraglutide trial 3)
- 2018
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In: BMC Open Diabetes Research and Care. - : BMJ. - 2052-4897. ; 6:1
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Journal article (peer-reviewed)abstract
- Objective To evaluate variables associated with hemoglobin A1c (HbA1c) and weight reduction when adding liraglutide to persons with type 2 diabetes treated with multiple daily insulin injections (MDI). Research design and methods This was a reanalysis of a previous trial where 124 patients were enrolled in a double-blind, placebo-controlled, multicenter randomized trial carried out over 24 weeks. Predictors for effect on change in HbA1c and weight were analyzed within the treatment group and with concurrent interaction analyses. Correlation analyses for change in HbA1c and weight from baseline to week 24 were made. Results The mean age at baseline was 63.7 years, 64.8% were men, the mean number of insulin injections was 4.4 per day, the mean daily insulin dose was 105 units and the mean HbA1c was 74.5 mmol/mol (9.0%). The mean HbA1c and weight reductions were 12.3 mmol/mol (1.13%; P<0.001) and 3.8 kg (P<0.001) greater in liraglutide than placebo-Treated persons. There was no significant predictor for greater effect on HbA1c that existed in all analyses (univariate, multivariate and interaction analyses against controls). For a greater weight reduction when adding liraglutide, a lower HbA1c level at baseline was a predictor (liraglutide group P=0.002, P=0.020 for liraglutide group vs placebo). During follow-up in the liraglutide group, no significant correlation was found between change in weight and change in HbA1c (r=0.09, P=0.46), whereas a correlation existed between weight and insulin dose reduction (r=0.44, P<0.001). Conclusion Weight reduction becomes greater when adding liraglutide in patients with type 2 diabetes treated with MDI who had a lower HbA1c level compared with those with a higher HbA1c level. There was no correlation between reductions in HbA1c and weight when liraglutide was added, that is, different patient groups responded with HbA1c and weight reductions. Trial registration number EudraCT nr: 2012-001941-42. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
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| 8. |
- Imberg, Henrik, 1991, et al.
(author)
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Active sampling: A machine-learning-assisted framework for finite population inference with optimal subsamples
- 2022
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Journal article (other academic/artistic)abstract
- Data subsampling has become widely recognized as a tool to overcome computational and economic bottlenecks in analyzing massive datasets and measurement-constrained experiments. However, traditional subsampling methods often suffer from the lack of information available at the design stage. We propose an active sampling strategy that iterates between estimation and data collection with optimal subsamples, guided by machine learning predictions on yet unseen data. The method is illustrated on virtual simulation-based safety assessment of advanced driver assistance systems. Substantial performance improvements were observed compared to traditional sampling methods.
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| 9. |
- Imberg, Henrik, 1991, et al.
(author)
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Optimal sampling in unbiased active learning
- 2020
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In: Proceedings of Machine Learning Research. - 2640-3498. ; 108, s. 559-569
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Conference paper (peer-reviewed)abstract
- A common belief in unbiased active learning is that, in order to capture the most informative instances, the sampling probabilities should be proportional to the uncertainty of the class labels. We argue that this produces suboptimal predictions and present sampling schemes for unbiased pool-based active learning that minimise the actual prediction error, and demonstrate a better predictive performance than competing methods on a number of benchmark datasets. In contrast, both probabilistic and deterministic uncertainty sampling performed worse than simple random sampling on some of the datasets.
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| 10. |
- Imberg, Henrik, 1991, et al.
(author)
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Optimal subsampling designs
- 2023
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Journal article (other academic/artistic)abstract
- Subsampling is commonly used to overcome computational and economical bottlenecks in the analysis of finite populations and massive datasets. Existing methods are often limited in scope and use optimality criteria (e.g., A-optimality) with well-known deficiencies, such as lack of invariance to the measurement-scale of the data and parameterisation of the model. A unified theory of optimal subsampling design is still lacking. We present a theory of optimal design for general data subsampling problems, including finite population inference, parametric density estimation, and regression modelling. Our theory encompasses and generalises most existing methods in the field of optimal subdata selection based on unequal probability sampling and inverse probability weighting. We derive optimality conditions for a general class of optimality criteria, and present corresponding algorithms for finding optimal sampling schemes under Poisson and multinomial sampling designs. We present a novel class of transformation- and parameterisation-invariant linear optimality criteria which enjoy the best of two worlds: the computational tractability of A-optimality and invariance properties similar to D-optimality. The methodology is illustrated on an application in the traffic safety domain. In our experiments, the proposed invariant linear optimality criteria achieve 92-99% D-efficiency with 90-95% lower computational demand. In contrast, the A-optimality criterion has only 46% and 60% D-efficiency on two of the examples.
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