| 1. |
- Karyotaki, Eirini, et al.
(author)
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Internet-Based Cognitive Behavioral Therapy for Depression : A Systematic Review and Individual Patient Data Network Meta-analysis
- 2021
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In: JAMA psychiatry. - : American Medical Association. - 2168-6238 .- 2168-622X. ; 78:4, s. 361-371
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Research review (peer-reviewed)abstract
- IMPORTANCE: Personalized treatment choices would increase the effectiveness of internet-based cognitive behavioral therapy (iCBT) for depression to the extent that patients differ in interventions that better suit them.OBJECTIVE: To provide personalized estimates of short-term and long-term relative efficacy of guided and unguided iCBT for depression using patient-level information.DATA SOURCES: We searched PubMed, Embase, PsycInfo, and Cochrane Library to identify randomized clinical trials (RCTs) published up to January 1, 2019.STUDY SELECTION: Eligible RCTs were those comparing guided or unguided iCBT against each other or against any control intervention in individuals with depression. Available individual patient data (IPD) was collected from all eligible studies. Depression symptom severity was assessed after treatment, 6 months, and 12 months after randomization.DATA EXTRACTION AND SYNTHESIS: We conducted a systematic review and IPD network meta-analysis and estimated relative treatment effect sizes across different patient characteristics through IPD network meta-regression.MAIN OUTCOMES AND MEASURES: Patient Health Questionnaire-9 (PHQ-9) scores.RESULTS: Of 42 eligible RCTs, 39 studies comprising 9751 participants with depression contributed IPD to the IPD network meta-analysis, of which 8107 IPD were synthesized. Overall, both guided and unguided iCBT were associated with more effectiveness as measured by PHQ-9 scores than control treatments over the short term and the long term. Guided iCBT was associated with more effectiveness than unguided iCBT (mean difference [MD] in posttreatment PHQ-9 scores, -0.8; 95% CI, -1.4 to -0.2), but we found no evidence of a difference at 6 or 12 months following randomization. Baseline depression was found to be the most important modifier of the relative association for efficacy of guided vs unguided iCBT. Differences between unguided and guided iCBT in people with baseline symptoms of subthreshold depression (PHQ-9 scores 5-9) were small, while guided iCBT was associated with overall better outcomes in patients with baseline PHQ-9 greater than 9.CONCLUSIONS AND RELEVANCE: In this network meta-analysis with IPD, guided iCBT was associated with more effectiveness than unguided iCBT for individuals with depression, benefits were more substantial in individuals with moderate to severe depression. Unguided iCBT was associated with similar effectiveness among individuals with symptoms of mild/subthreshold depression. Personalized treatment selection is entirely possible and necessary to ensure the best allocation of treatment resources for depression.
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| 2. |
- Demichev, Vadim, et al.
(author)
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A time-resolved proteomic and prognostic map of COVID-19
- 2021
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In: Cell Systems. - : Elsevier BV. - 2405-4712 .- 2405-4720. ; 12:8, s. 780-794.e7
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Journal article (peer-reviewed)abstract
- COVID-19 is highly variable in its clinical presentation, ranging from asymptomatic infection to severe organ damage and death. We characterized the time-dependent progression of the disease in 139 COVID-19 inpatients by measuring 86 accredited diagnostic parameters, such as blood cell counts and enzyme activities, as well as untargeted plasma proteomes at 687 sampling points. We report an initial spike in a systemic inflammatory response, which is gradually alleviated and followed by a protein signature indicative of tissue repair, metabolic reconstitution, and immunomodulation. We identify prognostic marker signatures for devising risk-adapted treatment strategies and use machine learning to classify therapeutic needs. We show that the machine learning models based on the proteome are transferable to an independent cohort. Our study presents a map linking routinely used clinical diagnostic parameters to plasma proteomes and their dynamics in an infectious disease.
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| 3. |
- Furukawa, Toshi A., et al.
(author)
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Dismantling, optimising, and personalising internet cognitive behavioural therapy for depression : a systematic review and component network meta-analysis using individual data
- 2021
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In: Lancet psychiatry. - London, United Kingdom : Elsevier. - 2215-0374 .- 2215-0366. ; 8:6, s. 500-511
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Research review (peer-reviewed)abstract
- Findings We identified 76 RCTs, including 48 trials contributing individual participant data (11 704 participants) and 28 trials with aggregate data (6474 participants). The participants' weighted mean age was 42.0 years and 12 406 (71%) of 17 521 reported were women. There was suggestive evidence that behavioural activation might be beneficial (iMD -1.83 [95% credible interval (CrI) -2.90 to -0.80]) and that relaxation might be harmful (1.20 [95% CrI 0.17 to 2.27]). Baseline severity emerged as the strongest prognostic factor for endpoint depression. Combining human and automated encouragement reduced dropouts from treatment (incremental odds ratio, 0.32 [95% CrI 0.13 to 0.93]). The risk of bias was low for the randomisation process, missing outcome data, or selection of reported results in most of the included studies, uncertain for deviation from intended interventions, and high for measurement of outcomes. There was moderate to high heterogeneity among the studies and their components. 511
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| 4. |
- Bastos Lima, Mairon G., et al.
(author)
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Large-scale collective action to avoid an Amazon tipping point - key actors and interventions
- 2021
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In: Current Research in Environmental Sustainability. - : Elsevier BV. - 2666-0490. ; 3
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Journal article (peer-reviewed)abstract
- The destruction of the Amazon is a major global environmental issue, not only because of greenhouse gas emissions or direct impacts on biodiversity and livelihoods, but also due to the forest's role as a tipping element in the Earth System. With nearly a fifth of the Amazon already lost, there are already signs of an imminent forest dieback process that risks transforming much of the rainforest into a drier ecosystem, with climatic implications across the globe. There is a large body of literature on the underlying drivers of Amazon deforestation. However, insufficient attention has been paid to the behavioral and institutional microfoundations of change. Fundamental issues concerning cooperation, as well as the mechanisms facilitating or hampering such actions, can play a much more central role in attempts to unravel and address Amazon deforestation. We thus present the issue of preventing the Amazon biome from crossing a biophysical tipping point as a large-scale collective action problem. Drawing from collective action theory, we apply a novel analytical framework on Amazon conservation, identifying six variables that synthesize relevant collective action stressors and facilitators: information, accountability, harmony of interests, horizontal trust, knowledge about consequences, and sense of responsibility. Drawing upon literature and data, we assess Amazon deforestation and conservation through our heuristic lens, showing that while growing transparency has made information availability a collective action facilitator, lack of accountability, distrust among actors, and little sense of responsibility for halting deforestation remain key stressors. We finalize by discussing interventions that can help break the gridlock.
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| 5. |
- Biurrun, Idoia, et al.
(author)
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Benchmarking plant diversity of Palaearctic grasslands and other open habitats
- 2021
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In: Journal of Vegetation Science. - Oxford : John Wiley & Sons. - 1100-9233 .- 1654-1103. ; 32:4
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Journal article (peer-reviewed)abstract
- Journal of Vegetation Science published by John Wiley & Sons Ltd on behalf of International Association for Vegetation Science.Aims: Understanding fine-grain diversity patterns across large spatial extents is fundamental for macroecological research and biodiversity conservation. Using the GrassPlot database, we provide benchmarks of fine-grain richness values of Palaearctic open habitats for vascular plants, bryophytes, lichens and complete vegetation (i.e., the sum of the former three groups). Location: Palaearctic biogeographic realm. Methods: We used 126,524 plots of eight standard grain sizes from the GrassPlot database: 0.0001, 0.001, 0.01, 0.1, 1, 10, 100 and 1,000 m2 and calculated the mean richness and standard deviations, as well as maximum, minimum, median, and first and third quartiles for each combination of grain size, taxonomic group, biome, region, vegetation type and phytosociological class. Results: Patterns of plant diversity in vegetation types and biomes differ across grain sizes and taxonomic groups. Overall, secondary (mostly semi-natural) grasslands and natural grasslands are the richest vegetation type. The open-access file ”GrassPlot Diversity Benchmarks” and the web tool “GrassPlot Diversity Explorer” are now available online (https://edgg.org/databases/GrasslandDiversityExplorer) and provide more insights into species richness patterns in the Palaearctic open habitats. Conclusions: The GrassPlot Diversity Benchmarks provide high-quality data on species richness in open habitat types across the Palaearctic. These benchmark data can be used in vegetation ecology, macroecology, biodiversity conservation and data quality checking. While the amount of data in the underlying GrassPlot database and their spatial coverage are smaller than in other extensive vegetation-plot databases, species recordings in GrassPlot are on average more complete, making it a valuable complementary data source in macroecology. © 2021 The Authors.
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| 6. |
- Moschovitis, Giorgio, et al.
(author)
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Heart rate and adverse outcomes in patients with prevalent atrial fibrillation
- 2021
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In: Open Heart. - : BMJ. - 2053-3624. ; 8:1
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Journal article (peer-reviewed)abstract
- OBJECTIVE: The optimal target heart rate in patients with prevalent atrial fibrillation (AF) is not well defined. The aim of this study was to analyse the associations between heart rate and adverse outcomes in a large contemporary cohort of patients with prevalent AF.METHODS: From two prospective cohort studies, we included stable AF outpatients who were in AF on the baseline ECG. The main outcome events assessed during prospective follow-up were heart failure hospitalisation, stroke or systemic embolism and death. The associations between heart rate and adverse outcomes were evaluated using multivariable Cox regression models.RESULTS: The study population consisted of 1679 patients who had prevalent AF at baseline. Mean age was 74 years, and 24.6% were women. The mean heart rate on the baseline ECG was 78 (±19) beats per minute (bpm). The median follow-up was 3.9 years (IQR 2.2-5.0). Heart rate was not significantly associated with heart failure hospitalisation (adjusted HR (aHR) per 10 bpm increase, 1.00, 95% CI 0.94 to 1.07, p=0.95), stroke or systemic embolism (aHR 0.95, 95% CI 0.84 to 1.07, p=0.38) or death (aHR 1.02, 95% CI 0.95 to 1.09, p=0.66). There was no evidence of a threshold effect for heart rates <60 bpm or >100 bpm.CONCLUSIONS: In this large contemporary cohort of outpatients with prevalent AF, we found no association between heart rate and adverse outcome events. These data are in line with recommendations that strict heart rate control is not needed in otherwise stable outpatients with AF.
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| 7. |
- Qian, Frank, et al.
(author)
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n-3 Fatty Acid Biomarkers and Incident Type 2 Diabetes : An Individual Participant-Level Pooling Project of 20 Prospective Cohort Studies
- 2021
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In: Diabetes Care. - : American Diabetes Association. - 0149-5992 .- 1935-5548. ; 44:5, s. 1133-1142
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Journal article (peer-reviewed)abstract
- OBJECTIVE Prospective associations between n-3 fatty acid biomarkers and type 2 diabetes (T2D) risk are not consistent in individual studies. We aimed to summarize the prospective associations of biomarkers of alpha-linolenic acid (ALA), eicosapentaenoic acid (EPA), docosapentaenoic acid (DPA), and docosahexaenoic acid (DHA) with T2D risk through an individual participant-level pooled analysis.RESEARCH DESIGN AND METHODS For our analysis we incorporated data from a global consortium of 20 prospective studies from 14 countries. We included 65,147 participants who had blood measurements of ALA, EPA, DPA, or DHA and were free of diabetes at baseline. De novo harmonized analyses were performed in each cohort following a pre-specified protocol, and cohort-specific associations were pooled using inverse variance-weighted meta-analysis.RESULTS A total of 16,693 incident T2D cases were identified during follow-up (median follow-up ranging from 2.5 to 21.2 years). In pooled multivariable analysis, per interquintile range (difference between the 90th and 10th percentiles for each fatty acid), EPA, DPA, DHA, and their sum were associated with lower T2D incidence, with hazard ratios (HRs) and 95% CIs of 0.92 (0.87, 0.96), 0.79 (0.73, 0.85), 0.82 (0.76, 0.89), and 0.81 (0.75, 0.88), respectively (all P < 0.001). ALA was not associated with T2D (HR 0.97 [95% CI 0.92, 1.02]) per interquintile range. Associations were robust across prespecified subgroups as well as in sensitivity analyses.CONCLUSIONS Higher circulating biomarkers of seafood-derived n-3 fatty acids, including EPA, DPA, DHA, and their sum, were associated with lower risk of T2D in a global consortium of prospective studies. The biomarker of plant-derived ALA was not significantly associated with T2D risk.
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| 8. |
- Steghöfer, Jan-Philipp, 1983, et al.
(author)
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The MobSTr Dataset - An Exemplar for Traceability and Model-based Safety Assessment
- 2021
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In: Proceedings of the IEEE International Conference on Requirements Engineering. - 2332-6441 .- 1090-705X. ; RE 2021, s. 444-445
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Conference paper (peer-reviewed)abstract
- The MobSTr dataset contains a number of artifacts for an autonomous driver assistance system, ranging from textual requirements to models for system design and models relevant to safety assurance. The artifacts provided are connected with traceability links created and managed with Eclipse Capra, an open source traceability management tool. The dataset builds upon a custom traceability information model that provides type safety and semantics for the trace links.MobSTr is intended for researchers that work on software and systems traceability as well as on model-based safety assurance. It is already being used in a number of studies, including research on trace link consistency, change impact analysis, and automated analysis of safety and timing requirements.
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