Eesti arstide arusaamu üleminekueast ja vastutuse jagunemisest selle käsitlemisel

Üheks oluliseks naiste tervishoiu valdkonnaks on üleminekueaga kaasnevate häirete käsitlus ja ravi. Arstide suhtumine klimakteeriumisse ja ravi vajalikkusesse sellel perioodil on erinev. Samuti pole selge, kas klimakteerilisi häireid peaks ravima günekoloog või perearst. Artiklis on analüüsitud Eesti naistearstide ja perearstide suhtumist üleminekueasse, nende hinnanguid erinevate ravimeetodite, omavahelise tööjaotuse ja erialase koolituse kohta. Eesti Arst 2002; 81 (11): 705–70

Eesti naistearstide ja perearstide arusaamu vastutuse jagunemisest naiste tervise probleemidega tegelemisel

Seoses perearstisüsteemi juurutamisega Eestis on paljudel meditsiinierialadel esile kerkinud küsimus, kuidas jaotada töövaldkondi perearsti ja erialaspetsialisti vahel. Seejuures on oluliseks aspektiks, millisel määral suudavad perearstid hakkama saada küsimustega, mis varem kuulusid eriarstide kompetentsi. Artiklis on selgitatud naiste- ja perearstide arusaamu omavahelisest tööjaotusest naiste tervishoiu alal, nende hinnanguid üld- ja erialasele ettevalmistusele ning täienduskoolituse vajadusele. Eesti Arst 2002; 81 (11): 700–70

Symptom reporting and quality of life in the Estonian Postmenopausal Hormone Therapy Trial

RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are.Abstract Background The aim of the study was to determine the effect of postmenopausal hormone therapy on women's symptom reporting and quality of life in a randomized trial. Methods 1823 women participated in the Estonian Postmenopausal Hormone Therapy (EPHT) Trial between 1999 and 2004. Women were randomized to open-label continuous combined hormone therapy or no treatment, or to blind hormone therapy or placebo. The average follow-up period was 3.6 years. Prevalence of symptoms and quality of life according to EQ-5D were assessed by annually mailed questionnaires. Results In the hormone therapy arms, less women reported hot flushes (OR 0.20; 95% CI: 0.14–0.28), sweating (OR 0.56; 95% CI: 0.44–0.72), and sleeping problems (OR 0.66; 95% CI: 0.52–0.84), but more women reported episodes of vaginal bleeding (OR 19.65; 95% CI: 12.15–31.79). There was no difference between the trial arms in the prevalence of other symptoms over time. Quality of life did not depend on hormone therapy use. Conclusion Postmenopausal hormone therapy decreased vasomotor symptoms and sleeping problems, but increased episodes of vaginal bleeding, and had no effect on quality of life. Trial registration number ISRCTN35338757Published versio

Time-resolved classification of dog brain signals reveals early processing of faces, species and emotion

Dogs process faces and emotional expressions much like humans, but the time windows important for face processing in dogs are largely unknown. By combining our non-invasive electroencephalography (EEG) protocol on dogs with machine-learning algorithms, we show category-specific dog brain responses to pictures of human and dog facial expressions, objects, and phase-scrambled faces. We trained a support vector machine classifier with spatiotemporal EEG data to discriminate between responses to pairs of images. The classification accuracy was highest for humans or dogs vs. scrambled images, with most informative time intervals of 100-140 ms and 240-280 ms. We also detected a response sensitive to threatening dog faces at 30-40 ms; generally, responses differentiating emotional expressions were found at 130-170 ms, and differentiation of faces from objects occurred at 120-130 ms. The cortical sources underlying the highest-amplitude EEG signals were localized to the dog visual cortex.Peer reviewe

Mild Traumatic Brain Injury Affects Cognitive Processing and Modifies Oscillatory Brain Activity during Attentional Tasks

Despite the high prevalence of mild traumatic brain injury (mTBI), current diagnostic tools to objectively assess cognitive complaints after mTBI continue to be inadequate. Our aim was to identify neuronal correlates for cognitive difficulties in mTBI patients by evaluating the possible alterations in oscillatory brain activity during a behavioral task known to be sensitive to cognitive impairment after mTBI. We compared oscillatory brain activity during rest and cognitive tasks (Paced Auditory Serial Addition Test [PASAT] and a vigilance test [VT]) with magnetoencephalography between 25 mTBI patients and 20 healthy controls. Whereas VT induced no significant differences compared with resting state in either group, patients exhibited stronger attenuation of 8- to 14-Hz oscillatory activity during PASAT than healthy controls in the left parietotemporal cortex (pPeer reviewe

Spontaneous sensorimotor cortical activity is suppressed by deep brain stimulation in patients with advanced Parkinson's disease

Advanced Parkinson's disease (PD) is characterized by an excessive oscillatory beta band activity in the sub thalamic nucleus (STN). Deep brain stimulation (DBS) of STN alleviates motor symptoms in PD and suppresses the STN beta band activity. The effect of DBS on cortical sensorimotor activity is more ambiguous; both increases and decreases of beta band activity have been reported. Non-invasive studies with simultaneous DBS are problematic due to DBS-induced artifacts. We recorded magnetoencephalography (MEG) from 16 advanced PD patients with and without STN DBS during rest and wrist extension. The strong magnetic artifacts related to stimulation were removed by temporal signal space separation. MEG oscillatory activity at 5-25 Hz was suppressed during DBS in a widespread frontoparietal region, including the sensorimotor cortex identified by the cortico-muscular coherence. The strength of suppression did not correlate with clinical improvement. Our results indicate that alpha and beta band oscillations are suppressed at the frontoparietal cortex by STN DBS in PD.Peer reviewe

Alterations in Spontaneous Brain Oscillations during Stroke Recovery

Peer reviewe

The effects of postmenopausal hormone therapy on social activity, partner relationship, and sexual life – experience from the EPHT trial

<p>Abstract</p> <p>Background</p> <p>With the exception of sexual functioning and weight, social and behavioural effects of postmenopausal hormone therapy (HT) have not been reported from trials. This paper reports such results from the EPHT-trial in Estonia.</p> <p>Methods</p> <p>A randomized trial, with a blind and non-blind sub-trial in Estonia. From 1999–2001, 1778 women were recruited. The mean follow-up was 3.6 years. Women's experiences were asked in the first and final study year by mailed questionnaires (74 and 81% response rates). Comparisons of the groups were made by cross-tabulation and logistic regression, adjusting for age.</p> <p>Results</p> <p>There were no differences between the HT and non-HT groups in regard to being employed, the extent of social involvement or marital status or opinions on aging. There was no difference in the frequency of free-time exercise, or overweight. Some of the indicators suggested less sexual inactivity, but the differences were small.</p> <p>Conclusion</p> <p>In a trial setting, postmenopausal hormone therapy did not influence work or social involvement or health behaviour.</p> <p>Trial registration</p> <p>ISRCTN35338757</p

#Metahdomme tasa-arvoisen avioliittolain; Diskurssianalyysi suomalaisten yritysten viestinnän politisoitumisesta

The purpose of this thesis is to observe and analyze how companies can use discursive legitimation to engage in public debates beyond their immediate field of business and in doing so, gain legitimacy for themselves. The study aims to extend theory on the politicization of companies and how this can be advanced through discursive means, thus also contributing to a wider discussion on the role and form of corporate social responsibility in 2017. The study is carried out as a critical discourse analysis of Finnish companies’ Twitter responses to the Finnish marriage equality debate between 2013–2017. My data consists of 59 tweets collected during three distinct periods of the debate – the initial signing period of the Citizen’s Initiative in 2013; the #metahdomme -corporate campaign period in late 2014; and the period when the legislation came into effect in spring 2017. The discourses are analyzed and contrasted across the three periods. Three distinct discourses are uncovered and identified as discourses of equality, discourses of love and discourses of championship. Whilst these discourses are used rather interchangeably, I find that the strength with which companies legitimize marriage equality increases over the four-year observation period. By 2017, companies are employing their existing products and narratives to strongly legitimize the debate. Based on my findings, I argue that companies are gradually transitioning towards a new role in society – a role that both allows and encourages them to participate in public debates beyond their immediate field of business. The thesis argues that while companies may adopt various discourses to do so, in order to gain moral legitimacy, companies select discourses that are rooted in values that the company wants to uphold and broadcast more widely to the surrounding society

Synkroniset neuraaliset vuorovaikutukset neurologisten tilojen luokittelussa: kliinisen data-analyysimenetelmän kokeellinen arviointi

Important information about the state of the brain, e.g., hallmarks of several neurological diseases, may be present in the brain-originated magnetic fields, measured using MEG. To extract this potentially disease-specific information from the measured raw data, sophisticated data analysis methods are needed. However, this kind of reliable and verified diagnostic analysis methods have not been successfully developed so far. This Master's Thesis examines a recently proposed data analysis method which is developed for the classification of several neurological conditions based on the spontaneous MEG data. The aim of this study is to evaluate the potential of the method as a clinical application of MEG. For this purpose, original study is repeated using similar computational methods, i.e., the linear discriminant analysis which classifies partial correlation values of the ARIMA model residuals of the sensor-level MEG signals. This analysis is implemented and applied to 48 spontaneous MEG data sets of patients suffering from stroke, migraine, and Parkinson's disease, as well as of healthy controls. In addition, different stages of the analysis method are examined separately using MEG data from controls and empty room measurements. This study has manifested the proposed method to be incompatible in the analysis of MEG data. The physical nature of the magnetic fields measured by MEG has not been taken into account in the method development, which might have caused inappropriate approaches in the analysis. Thus, this method most likely removes major part of the brain-related information present in the MEG data. Consequently, the classification of the proposed analysis method might rely on the signals mostly reflecting device-originated artifacts. This Thesis indicates that it is highly unlikely that the proposed clinical MEG data analysis method could be used to reveal reliable disease-specific information about the neurological conditions. Nevertheless, the result does not exclude the clinical potential of an analysis of spontaneous MEG data.Useiden neurologisten sairauksien uskotaan aiheuttavan aivojen toiminnassa muutoksia, jotka voidaan havaita korkean aikaresoluution kuvantamismenetelmillä, mm. magnetoenkefalografialla (MEG). Näiden tautitiloihin liittyvien muutosten löytämiseksi datasta tarvitaan kuitenkin hienostuneita data-analyysimenetelmiä, joiden tulisi olla luotettavia soveltuakseen kliiniseen käyttöön. Yrityksistä huolimatta tämänkaltaiseen analyysiin soveltuvaa menetelmää ei vielä ole onnistuttu kehittämään MEG:lle. Tämä diplomityö tarkastelee äskettäin ehdotettua data-analyysimenetelmää, joka pyrkii erottelemaan useita neurologisia potilasryhmiä toisistaan spontaanin MEG-datan perusteella. Työn tavoitteena on arvioida menetelmän käyttökelpoisuutta MEG-datan käsittelyssä, sekä sen mahdollisuuksia kliinisenä sovelluksena. Tarkastelu on suoritettu toteuttamalla alkuperäistä tutkimusta vastaavat laskennalliset menetelmät, eli anturitason MEG-datan ARIMA-mallin jäännöstermien osittaiskorrelaatioiden lineaarinen erotteluanalyysi geneettistä algoritmia käyttäen. Menetelmää on sovellettu yhteensä 48 spontaaniin MEG-dataan potilaista, jotka kärsivät Parkinsonin taudista, aivoverenkiertohäiriöstä tai tietyntyyppisestä migreenistä, sekä dataan terveistä koehenkilöistä. Menetelmän yksittäisiä vaiheita on myös tutkittu erikseen tarkastelemalla kontrollidataa koehenkilöistä sekä tyhjän huoneen mittauksista. Tämän tutkimuksen tarkastelut ovat osoittaneet useita ongelmakohtia ehdotetussa analyysimenetelmässä. Useat näistä virheellisistä lähestymistavoista johtuvat selkeästi siitä, että magneettikenttien luonnetta ei ole huomioitu menetelmän kehitysvaiheessa. Tämän seurauksena menetelmän jotkin vaiheet poistavat aivoperäistä magneettikenttää datasta, ja lopputuloksessa on mitä luultavimmin jäljellä lähinnä laiteperäisiä häiriösignaaleja. Ehdotetun luokittelumenetelmä ei siis luultavimmin tuota kliinisesti merkittävää informaatiota aivojen tilasta. Tämän diplomityön tulos ei kuitenkaan sulje pois mahdollisuutta kehittää spontaaniin MEG-dataan ja toisenlaiseen datankäsittelyyn perustuvaa diagnostista analyysimenetelmää