| 1. |
- Hieronymus, M., et al.
(författare)
-
On the Application of Machine Learning Techniques to Regression Problems in Sea Level Studies
- 2019
-
Ingår i: Journal of Atmospheric and Oceanic Technology. - : American Meteorological Society. - 0739-0572 .- 1520-0426. ; 36:9, s. 1889-1902
-
Tidskriftsartikel (refereegranskat)abstract
- Long sea level records with high temporal resolution are of paramount importance for future coastal protection and adaptation plans. Here we discuss the application of machine learning techniques to some regression problems commonly encountered when analyzing such time series. The performance of artificial neural networks is compared with that of multiple linear regression models on sea level data from the Swedish coast. The neural networks are found to be superior when local sea level forcing is used together with remote sea level forcing and meteorological forcing, whereas the linear models and the neural networks show similar performance when local sea level forcing is excluded. The overall performance of the machine learning algorithms is good, often surpassing that of the much more computationally costly numerical ocean models used at our institute.
|
|
| 2. |
- Hieronymus, Fredrik, 1986, et al.
(författare)
-
Consistent superiority of selective serotonin reuptake inhibitors over placebo in reducing depressed mood in patients with major depression.
- 2016
-
Ingår i: Molecular psychiatry. - : Springer Science and Business Media LLC. - 1476-5578 .- 1359-4184. ; 21:4, s. 523-30
-
Tidskriftsartikel (refereegranskat)abstract
- The recent questioning of the antidepressant effect of selective serotonin reuptake inhibitors (SSRIs) is partly based on the observation that approximately half of company-sponsored trials have failed to reveal a significant difference between active drug and placebo. Most of these have applied the Hamilton depression rating scale to assess symptom severity, the sum score for its 17 items (HDRS-17-sum) serving as effect parameter. In this study, we examined whether the negative outcomes of many SSRI trials may be partly caused by the use of this frequently questioned measure of response. We undertook patient-level post-hoc analyses of 18 industry-sponsored placebo-controlled trials regarding paroxetine, citalopram, sertraline or fluoxetine, and including in total 6669 adults with major depression, the aim being to assess what the outcome would have been if the single item depressed mood (rated 0-4) had been used as a measure of efficacy. In total, 32 drug-placebo comparisons were reassessed. While 18 out of 32 comparisons (56%) failed to separate active drug from placebo at week 6 with respect to reduction in HDRS-17-sum, only 3 out of 32 comparisons (9%) were negative when depressed mood was used as an effect parameter (P<0.001). The observation that 29 out of 32 comparisons detected an antidepressant signal from the tested SSRI suggests the effect of these drugs to be more consistent across trials than previously assumed. Further, the frequent use of the HDRS-17-sum as an effect parameter may have distorted the current view on the usefulness of SSRIs and hampered the development of novel antidepressants.Molecular Psychiatry advance online publication, 28 April 2015; doi:10.1038/mp.2015.53.
|
|
| 3. |
- Hieronymus, Fredrik, 1986, et al.
(författare)
-
The alleged ineffectiveness of SSRIs in depression is an artefact caused by the use of an inappropriate measure of efficacy
- 2014
-
Ingår i: International Journal of Neuropsychopharmacology vol. 17 Supplement 1. 29th CINP World Congress of Neuropsychopharmacology, Vancouver, Canada, 22–26 June 2014. - New York : Cambridge University Press. - 1461-1457 .- 1469-5111.
-
Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Objective: Many studies have questioned if summation of the scores of the 17 disparate items constituting the Hamilton Depression Rating Scale (HDRS-17) is a reliable index of severity in depression; yet the cur- rent questioning of the ef fi cacy of antidepressant drugs is to a large extent based on the assumption that response to treatment is reliably re fl ected by this instrument. We aimed to investigate the possibility that the shortcom- ings of the HDRS may contribute to the failure of antidepressants to out- perform placebo in many trials. Methods: We analyzed thirteen industry-sponsored trials of selective serotonin reuptake inhibitors (SSRIs) comprising twenty-four drug- placebo comparisons and including patient-level data from 5381 subjects (administered paroxetine, citalopram, fl uoxetine, or placebo), the aim being to assess what the outcome would have been if the single item de- pressed mood (rated 0 – 4) had been used as measure of ef fi cacy. Results: While 12 out of 24 comparisons (50%) revealed a signi fi cant difference between active drug and placebo at week 6 with respect to re- duction in HDRS-17-sum, 23 out of 24 comparisons (96%) showed the ac- tive drug to be superior to placebo in reducing depressed mood. Correspondingly, a pooled analysis of all cases showed the effect size when assessed using the HDRS-17-sum to be 0.30, whereas it, when mea- sured using the depressed mood item alone, was 0.42. Conclusion: While not claiming that measuring one item only is the most appropriate way of recording symptom severity in depression, we do suggest that the inclusion of a number of varying symptoms in the as- sessment, some of which may be side-effects of treatment and/or are unre- lated to the disorder, reduces the sensitivity to detect a difference between active drug and placebo. This lack of sensitivity of HDRS-17 might partly explain why a high fraction of antidepressant trials fail to reveal a signi fi - cant difference between treatment groups
|
|
| 4. |
- Hieronymus, Magnus, et al.
(författare)
-
A Novel Machine Learning Based Bias Correction Method and Its Application to Sea Level in an Ensemble of Downscaled Climate Projections
- 2023
-
Ingår i: Tellus, Series A: Dynamic Meteorology and Oceanography. - : Stockholm University Press. - 0280-6495 .- 1600-0870. ; 75:1, s. 129-144
-
Tidskriftsartikel (refereegranskat)abstract
- A new machine learning based bias correction method is presented and applied to sea level in a regional climate model. The bias corrections derived using this method depend on the state of the model it corrects. This contrasts with conventional bias correction methods that operate on distributions of output variables. The dependence on model states allows for better performance on classical skill scores, but it also limits the applicability of the method to models that can perform hindcasts. A very large dataset of corrected hourly sea levels from many different emission scenarios is created. In total the dataset contains over 2600 model years and exists for seven different tide-gauge stations on the Swedish Baltic Sea coast. The prevalence of significant trends in yearly sea level maximum is found to be independent of emission scenario, suggesting that anthropogenic climate change is no significant driver of storm surge variability in the area. Lastly, the dataset is used to estimate return levels for very long return periods, and the block length used in the return level computation is found to affect the result at some stations. This suggests that the commonly used annual maximum approach is not always applicable for determining return levels for sea level.
|
|
| 5. |
- Hieronymus, M., et al.
(författare)
-
Southern Baltic sea level extremes: tide gauge data, historic storms and confidence intervals
- 2021
-
Ingår i: Boreal Environment Research. - 1239-6095. ; 26, s. 79-87
-
Tidskriftsartikel (refereegranskat)abstract
- Knowledge of extreme sea levels is important when planning housing developments and other infrastructure in coastal locations. The natural science basis of such plans are often return level-return period plots derived from tide gauge records that typically stretch from a few decades to a century. Coastal planners, however. often require return levels associated with return periods that are much longer than these tide gauge records in their planning. Moreover, return level estimates are known to be sensitive to outliers and can have significant biases. Here, we quantify different confidence intervals that arc applicable to such return level estimates. and discuss their usability for coastal planning in the context of historic data from the Baltic Sea flood in 1872. Two types of commonly used confidence intervals are found to be too narrow to capture a plausible range that includes the 1872 Baltic Sea flood. A parametric bootstrapping method is then introduced, which gives a reasonable range even when this extreme flood is considered.
|
|
| 6. |
- Näslund, Jakob, et al.
(författare)
-
Incidence of early anxiety aggravation in trials of selective serotonin reuptake inhibitors in depression
- 2017
-
Ingår i: Acta Psychiatrica Scandinavica. - : Wiley. - 0001-690X .- 1600-0447. ; 136:4, s. 343-351
-
Tidskriftsartikel (refereegranskat)abstract
- © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd Objective: Selective serotonin reuptake inhibitors (SSRIs) may aggravate anxiety and agitation during the first days of treatment but the frequency of such reactions remains unknown. Method: We analysed patient-level data from placebo-controlled trials of sertraline, paroxetine or citalopram in depressed adults. Somatic anxiety, psychic anxiety and psychomotor agitation as assessed using the Hamilton Depression Rating Scale (HDRS) were analysed in all trials (n=8262); anxiety-related adverse events were analysed in trials investigating paroxetine and citalopram (n=5712). Results: After one but not two weeks, patients on an SSRI were more likely than those on placebo to report enhanced somatic anxiety (adjusted risk 9.3% vs. 6.7%); likewise, mean rating of somatic anxiety was higher in the SSRI group. In contrast, patients receiving an SSRI were less likely to report aggravation of psychic anxiety (adjusted risk: 7.0% vs. 8.5%) with mean rating of psychic anxiety and agitation being lower in the SSRI group. The adverse event ‘nervousness’ was more common in patients given an SSRI (5.5% vs. 2.5%). Neither aggravation of HDRS-rated anxiety nor anxiety-related adverse events predicted poor antidepressant response. Conclusion: Whereas an anxiety-reducing effect of SSRIs is notable already during the first week of treatment, these drugs may also elicit an early increase in anxiety in susceptible subjects that however does not predict a poor subsequent response to treatment.
|
|
| 7. |
|
|
| 8. |
- Boschloo, L., et al.
(författare)
-
The complex clinical response to selective serotonin reuptake inhibitors in depression: a network perspective
- 2023
-
Ingår i: Translational Psychiatry. - : Springer Science and Business Media LLC. - 2158-3188. ; 13:1
-
Tidskriftsartikel (refereegranskat)abstract
- The clinical response to selective serotonin reuptake inhibitors (SSRIs) in depression takes weeks to be fully developed and is still not entirely understood. This study aimed to determine the direct and indirect effects of SSRIs relative to a placebo control condition on clinical symptoms of depression. We included data of 8262 adult patients with major depression participating in 28 industry-sponsored US Food and Drug Administration (FDA) registered trials on the efficacy of SSRIs. Clinical symptoms of depression were assessed by the 17 separate items of the Hamilton Depression Rating Scale (HDRS) after 1, 2, 3, 4 and 6 weeks of treatment. Network estimation techniques showed that SSRIs had quick and strong direct effects on the two affective symptoms, i.e., depressed mood and psychic anxiety; direct effects on other symptoms were weak or absent. Substantial indirect effects were found for all four cognitive symptoms, which showed larger reductions in the SSRI condition but mainly in patients reporting larger reductions in depressed mood. Smaller indirect effects were found for two arousal/somatic symptoms via the direct effect on psychic anxiety. Both direct and indirect effects on sleep problems and most arousal/somatic symptoms were weak or absent. In conclusion, our study revealed that SSRIs primarily caused reductions in affective symptoms, which were related to reductions in mainly cognitive symptoms and some specific arousal/somatic symptoms. The results can contribute to disclosing the mechanisms of action of SSRIs, and has the potential to facilitate early detection of responders and non-responders in clinical practice.
|
|
| 9. |
- Eckernäs, Daniel, 1985, et al.
(författare)
-
Acoustic white noise ameliorates reduced regional brain expression of CaMKII and ΔFosB in the spontaneously hypertensive rat model of ADHD
- 2019
-
Ingår i: IBRO Reports. - : Elsevier BV. - 2451-8301. ; 6, s. 31-39
-
Tidskriftsartikel (refereegranskat)abstract
- Loud (≥70dBA) acoustic white noise improves cognitive performance in children with ADHD as well as skilled reach and rotarod performance in the spontaneously hypertensive (SH) rat model of ADHD. To investigate how acoustic noise influences the brain activity in the SH rat model of ADHD, immunohistochemical staining of two neuronal activity and plasticity markers, Ca2+/Calmodulin dependent protein kinase II (CaMKII) and ΔFosB, was evaluated in Wistar (n = 24) and SH (n = 16) rats after repeated exposure to acoustic noise or ambient silence. Other SH rats (n = 6) were treated with repeated methylphenidate (MPH). Expression of CaMKII was reduced in the tuberomammillary nucleus (TMN) of the SH rat compared to Wistar but not in the nucleus accumbens (nAc) or the dorsolateral prefrontal cortex (DL-PFC). In the TMN, the expression of CaMKII was increased by noise in both strains. ΔFosB expression was reduced in nAc, DL-PFC and the dorsolateral striatum (DLS) of the SH rat compared to Wistar. Exposure to acoustic white noise significantly increased ΔFosB expression in the nAc and DL-PFC but not in the DLS of SH rats. The results indicate that acoustic noise shifts a reduced neuronal activity in the nAc, TMN and DL-PFC in SH rats toward the normal levels of activity in outbred rats. This may explain why noise has benefit selectively in ADHD. © 2018 The Authors
|
|
| 10. |
|
|
