| 1. |
- Andersson, Erik, et al.
(author)
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d-Cycloserine vs Placebo as Adjunct to Cognitive Behavioral Therapy for Obsessive-Compulsive Disorder and Interaction With Antidepressants A Randomized Clinical Trial
- 2015
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In: JAMA psychiatry. - : American Medical Association (AMA). - 2168-6238 .- 2168-622X. ; 72:7, s. 659-667
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Journal article (peer-reviewed)abstract
- IMPORTANCE It is unclear whether D-cycloserine (DCS), a partial N-methyl-D-aspartate agonist that enhances fear extinction, can augment the effects of exposure-based cognitive behavioral therapy (CBT) for obsessive-compulsive disorder (OCD). OBJECTIVES To examine whether DCS augments the effects of CBT for OCD and to explore (post hoc) whether concomitant antidepressant medication moderates the effects of DCS. DESIGN, SETTING, AND PARTICIPANTS A 12-week, double-blind randomized clinical trial with 3-month follow-up conducted at an academic medical center between September 4, 2012, and September 26, 2013. Participants included 128 adult outpatients with a primary diagnosis of OCD and a Yale-Brown Obsessive Compulsive Scale (Y-BOCS) score of 16 or higher. Concurrent antidepressant medication was permitted if the dose had been stable for at least 2 months prior to enrollment and remained unchanged during the trial. The main analysis was by intention-to-treat population. INTERVENTIONS All participants received a previously validated Internet-based CBT protocol over 12 weeks and were randomized to receive either 50 mg of DCS or placebo, administered 1 hour before each of 5 exposure and response prevention tasks. MAIN OUTCOMES AND MEASURES Clinician-administered Y-BOCS score at week 12 and at 3-month follow-up. Remission was defined as a score of 12 or lower on the Y-BOCS. RESULTS In the primary intention-to-treat analyses, DCS did not augment the effects of CBT compared with placebo (mean [SD] clinician-rated Y-BOCS score, DCS: 13.86 [6.50] at week 12 and 12.35 [7.75] at 3-month follow-up; placebo: 11.77 [5.95] at week 12 and 12.37 [6.68] at 3-month follow-up) but showed a significant interaction with antidepressants (clinician-rated Y-BOCS, B = -1.08; Z = -2.79; P = .005). Post hoc analyses revealed that antidepressants significantly impaired treatment response in the DCS group but not the placebo group, at both posttreatment and follow-up (clinician-rated Y-BOCS: t(62) = -3.00; P = .004; and t(61) = -3.49; P < .001, respectively). In the DCS group, a significantly greater proportion of antidepressant-free patients achieved remission status at follow-up (60% [95% CI, 45%-74%]) than antidepressant-medicated patients (24% [95% CI, 9%-48%]) (P = .008). Antidepressants had no effect in the placebo group (50% [95% CI, 36%-64%] remission rate in both groups). CONCLUSIONS AND RELEVANCE The findings suggest that antidepressants may interact with DCS to block its facilitating effect on fear extinction. Use of DCS may be a promising CBT augmentation strategy but only in antidepressant-free patients with OCD.
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| 2. |
- Zamora, Juan Carlos, et al.
(author)
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Considerations and consequences of allowing DNA sequence data as types of fungal taxa
- 2018
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In: IMA Fungus. - : INT MYCOLOGICAL ASSOC. - 2210-6340 .- 2210-6359. ; 9:1, s. 167-185
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Journal article (peer-reviewed)abstract
- Nomenclatural type definitions are one of the most important concepts in biological nomenclature. Being physical objects that can be re-studied by other researchers, types permanently link taxonomy (an artificial agreement to classify biological diversity) with nomenclature (an artificial agreement to name biological diversity). Two proposals to amend the International Code of Nomenclature for algae, fungi, and plants (ICN), allowing DNA sequences alone (of any region and extent) to serve as types of taxon names for voucherless fungi (mainly putative taxa from environmental DNA sequences), have been submitted to be voted on at the 11th International Mycological Congress (Puerto Rico, July 2018). We consider various genetic processes affecting the distribution of alleles among taxa and find that alleles may not consistently and uniquely represent the species within which they are contained. Should the proposals be accepted, the meaning of nomenclatural types would change in a fundamental way from physical objects as sources of data to the data themselves. Such changes are conducive to irreproducible science, the potential typification on artefactual data, and massive creation of names with low information content, ultimately causing nomenclatural instability and unnecessary work for future researchers that would stall future explorations of fungal diversity. We conclude that the acceptance of DNA sequences alone as types of names of taxa, under the terms used in the current proposals, is unnecessary and would not solve the problem of naming putative taxa known only from DNA sequences in a scientifically defensible way. As an alternative, we highlight the use of formulas for naming putative taxa (candidate taxa) that do not require any modification of the ICN.
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| 3. |
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- 2018
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In: Nuclear Fusion. - : IOP Publishing. - 1741-4326 .- 0029-5515. ; 58:1
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Research review (peer-reviewed)
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| 4. |
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| 5. |
- Andersson, Carina, et al.
(author)
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Understanding software processes through system dynamics simulation: a case study
- 2002
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In: Proceedings Ninth Annual IEEE International Conference and Workshop on the Engineering of Computer-Based Systems. - 0769515495 ; , s. 41-48
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Conference paper (peer-reviewed)abstract
- This paper presents a study with the intent to examine the opportunities provided by creating and using simulation models of software development processes. A model of one software development project was created through means of system dynamics, with data collected from documents, interviews and observations. The model was simulated in a commercial simulation tool. The simulation runs indicate that increasing the effort spent on the requirements phase, to a certain extent, will decrease the lead time and increase the quality in similar projects. The simulation model visualizes relations in the software process, and can be used by project managers when planning future projects. The study indicates that this type of simulation is a feasible way of modelling the process dynamically although the study calls for further investigations as to how project or process managers can benefit the most from using system dynamics simulations
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| 7. |
- Andersson, Lars Fredrik, Docent, 1974-, et al.
(author)
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Adverse selection in mutual benefit societies : an longitudinal approach
- 2021
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Reports (other academic/artistic)abstract
- Mutual benefit societies evolved as the major provider for illness, accident and burialinsurance in the late 19 th and early 20 th century in the Western world. One of themajor problems facing the insurers was the risk for adverse selection; that unhealthyindividuals had more incentive then healthy to insure when priced for the averagerisk. By empirically examine if the longevity among insured in mutual benefit societieswas different from uninsured, we seek to identify the presence of adverse section. Wefind no compelling evidence that unhealthy individuals was more likely to insure, orreasons to believe that adverse selection was behind the decline of mutual benefitsocieties in the twentieth century.
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| 8. |
- Andersson, Lars Fredrik, Docent, 1974-, et al.
(author)
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Pre-welfare state provision and adverse selection : enrolment in a Swedish nationwide health insurance society
- 2023
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In: Financial History Review. - : Cambridge University Press. - 0968-5650 .- 1474-0052. ; 30:1, s. 74-99
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Journal article (peer-reviewed)abstract
- Mutual benefit societies evolved as the major provider for sickness, accident and life insurance in the late nineteenth and early twentieth centuries on both sides of the Atlantic. One of the major problems facing insurers was the risk of adverse selection, i.e. that unhealthy individuals had more incentives than healthy individuals to insure when priced for the average risk. By empirically examining whether longevity among insured individuals in a nationwide mutual health society was different from a matched sample of uninsured individuals, we seek to identify the presence of adverse selection. We find no compelling evidence showing that unhealthy individuals were more likely to insure, or reasons to believe that problems related to adverse selection would have been a major reason for government intervention in the health insurance market in Sweden.
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| 9. |
- Andersson, Peder, et al.
(author)
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Predicting neurological outcome after out-of-hospital cardiac arrest with cumulative information; development and internal validation of an artificial neural network algorithm
- 2021
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In: Critical Care. - : Springer Science and Business Media LLC. - 1364-8535. ; 25:1
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Journal article (peer-reviewed)abstract
- BackgroundPrognostication of neurological outcome in patients who remain comatose after cardiac arrest resuscitation is complex. Clinical variables, as well as biomarkers of brain injury, cardiac injury, and systemic inflammation, all yield some prognostic value. We hypothesised that cumulative information obtained during the first three days of intensive care could produce a reliable model for predicting neurological outcome following out-of-hospital cardiac arrest (OHCA) using artificial neural network (ANN) with and without biomarkers.MethodsWe performed a post hoc analysis of 932 patients from the Target Temperature Management trial. We focused on comatose patients at 24, 48, and 72 h post-cardiac arrest and excluded patients who were awake or deceased at these time points. 80% of the patients were allocated for model development (training set) and 20% for internal validation (test set). To investigate the prognostic potential of different levels of biomarkers (clinically available and research-grade), patients' background information, and intensive care observation and treatment, we created three models for each time point: (1) clinical variables, (2) adding clinically accessible biomarkers, e.g., neuron-specific enolase (NSE) and (3) adding research-grade biomarkers, e.g., neurofilament light (NFL). Patient outcome was the dichotomised Cerebral Performance Category (CPC) at six months; a good outcome was defined as CPC 1-2 whilst a poor outcome was defined as CPC 3-5. The area under the receiver operating characteristic curve (AUROC) was calculated for all test sets.ResultsAUROC remained below 90% when using only clinical variables throughout the first three days in the ICU. Adding clinically accessible biomarkers such as NSE, AUROC increased from 82 to 94% (p<0.01). The prognostic accuracy remained excellent from day 1 to day 3 with an AUROC at approximately 95% when adding research-grade biomarkers. The models which included NSE after 72 h and NFL on any of the three days had a low risk of false-positive predictions while retaining a low number of false-negative predictions.ConclusionsIn this exploratory study, ANNs provided good to excellent prognostic accuracy in predicting neurological outcome in comatose patients post OHCA. The models which included NSE after 72 h and NFL on all days showed promising prognostic performance.
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