BACKGROUND AND PURPOSE: Frontotemporal dementia (FTD) is a neurodegenerative disorder characterized by pervasive personality and behavioural disturbances with severe impact on patients and caregivers. In current clinical practice, treatment is based on nonpharmacological and pharmacological approaches. Unfortunately, trial-based evidence supporting symptomatic pharmacological treatment for the behavioural disturbances in FTD is scarce despite the significant burden this poses on the patients and caregivers. METHOD: The study examined drug management decisions for several behavioural disturbances in patients with FTD by 21 experts across European expert centres affiliated with the European Reference Network for Rare Neurological Diseases (ERN-RND). RESULTS: The study revealed the highest consensus on drug treatments for physical and verbal aggression, impulsivity and obsessive delusions. Antipsychotics (primarily quetiapine) were recommended for behaviours posing safety risks to both patients and caregivers (aggression, self-injury and self-harm) and nightly unrest. Selective serotonin reuptake inhibitors were recommended for perseverative somatic complaints, rigidity of thought, hyperphagia, loss of empathy and for impulsivity. Trazodone was specifically recommended for motor unrest, mirtazapine for nightly unrest, and bupropion and methylphenidate for apathy. Additionally, bupropion was strongly advised against in 10 out of the 14 behavioural symptoms, emphasizing a clear recommendation against its use in the majority of cases. CONCLUSIONS: The survey data can provide expert guidance that is helpful for healthcare professionals involved in the treatment of behavioural symptoms. Additionally, they offer insights that may inform prioritization and design of therapeutic studies, particularly for existing drugs targeting behavioural disturbances in FTD.

• MeSH
• agrese účinky léků   MeSH
• antipsychotika terapeutické užití   MeSH
• frontotemporální demence * farmakoterapie   MeSH
• impulzivní chování účinky léků   MeSH
• konsensus MeSH
• lidé MeSH
• selektivní inhibitory zpětného vychytávání serotoninu terapeutické užití   MeSH
• vzácné nemoci farmakoterapie   MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• Geografické názvy
• Evropa MeSH

Electronic health records naturally contain most of the medical information in the form of doctor's notes as unstructured or semi-structured texts. Current deep learning text analysis approaches allow researchers to reveal the inner semantics of text information and even identify hidden consequences that can offer extra decision support to doctors. In the presented article, we offer a new automated analysis of Polish summary texts of patient hospitalizations. The presented models were found to be able to predict the final diagnosis with almost 70% accuracy based just on the patient's medical history (only 132 words on average), with possible accuracy increases when adding further sentences from hospitalization results; even one sentence was found to improve the results by 4%, and the best accuracy of 78% was achieved with five extra sentences. In addition to detailed descriptions of the data and methodology, we present an evaluation of the analysis using more than 50,000 Polish cardiology patient texts and dive into a detailed error analysis of the approach. The results indicate that the deep analysis of just the medical history summary can suggest the direction of diagnosis with a high probability that can be further increased just by supplementing the records with further examination results.

• Publikační typ
• časopisecké články MeSH

This paper deals with a developed information system called a Personal Genetic Card (PGC). The system aims to integrate the known clinical knowledge (interpretations and recommendations) linked to genetic information with the analysis results of a patient. Genetic information has an increasing influence on the clinical decision of physicians as well as other medical and health services. All these services need to connect the genetic profile with the phenotypes such as drug metabolization, drug toxicity, drug dosing, or intolerance of some substances. It still applies that the best way to represent data of medical records is a structured form of record. Many approaches can be used to define the structure (syntax) of the record and the content (semantics) of the record and to exchange data in forms of various standards and terminologies. Moreover, the genetic analysis field has its terminology databases for representing genetic information (e.g. HGNC, NCBI). The next step is to connect the genetic analysis results with c clinical knowledge (interpretation, recommendation). This step is crucial because the genetic analysis results have clinical benefits if we can assign them to some valid clinical knowledge. And the best final result is when we can make a better recommendation based on the genetic results and clinical knowledge. Genetic knowledge databases (e.g. PharmGKB, SNPedia, ClinVar) contain many interpretations and even recommendations for genetic analysis results based on different purposes. This situation is appropriate for developing the PGC system that takes inspiration from case-based reasoning in purpose to allow integration of the assumptions and knowledge about phenotypes and the real genetic analysis results in the structured form.

• MeSH
• chorobopisy - počítačové systémy * MeSH
• fenotyp MeSH
• genetické testování * MeSH
• sémantika MeSH
• Publikační typ
• časopisecké články MeSH

Konzistence odpovídání, sémantická konzistence nebo variabilita odpovědí jsou jen některé z příkladů názvů, kterými je označována míra shody odpovědí na položky testů osobnosti o stejném významu. Podobné rozdíly panují jak v konkrétním pojetí této proměnné, tak ve způsobu, jakým je měřena. Článek shrnuje empirické poznatky týkající se konzistence odpovídání, způsobů, jakými byla různými autory zjišťována, a jejího vztahu k dalším proměnným. Uvedený přehled podporuje přes veškeré rozdíly tvrzení, že konzistence odpovídání je stabilní psychologickou proměnnou, která může mít vlastní psychodiagnostickou hodnotu, odlišnou od tradičního pojetí nekonzistence odpovídání jako chyby měření. Konzistence odpovídání může v širším smyslu souviset s integritou osobnosti.

The response consistency, semantic consistency and response variability are a few examples of terms, which are used for the extent of variability of responses to the items of personality tests with the same meaning. However, similar differences prevail both in the specific author's concept of this variable and in the manner in which it is measured. The article summarizes empiric knowledge concerning the response consistency, manners measured by various authors, and its relation to other variables. This overview supports the thesis that despite the differences in approaches to the topic, the response consistency is a stable psychological variable with possible psychodiagnostic value different from the prevalent interpretation of the inconsistency responding as a measurement error. Response consistency may be in a broader sense related to personal integrity.

• MeSH
• lidé MeSH
• osobnostní dotazník * MeSH
• pochopení klasifikace   MeSH
• psychologické testy MeSH
• rozhodování MeSH
• sociální žádoucnost MeSH
• testování osobnosti MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• práce podpořená grantem MeSH
• přehledy MeSH

BACKGROUND: Spatial and temporal resolution of brain network activity can be improved by combining different modalities. Functional Magnetic Resonance Imaging (fMRI) provides full brain coverage with limited temporal resolution, while electroencephalography (EEG), estimates cortical activity with high temporal resolution. Combining them may provide improved network characterization. NEW METHOD: We examined relationships between EEG spatiospectral pattern timecourses and concurrent fMRI BOLD signals using canonical hemodynamic response function (HRF) with its 1st and 2nd temporal derivatives in voxel-wise general linear models (GLM). HRF shapes were derived from EEG-fMRI time courses during "resting-state", visual oddball and semantic decision paradigms. RESULTS: The resulting GLM F-maps self-organized into several different large-scale brain networks (LSBNs) often with different timing between EEG and fMRI revealed through differences in GLM-derived HRF shapes (e.g., with a lower time to peak than the canonical HRF). We demonstrate that some EEG spatiospectral patterns (related to concurrent fMRI) are weakly task-modulated. COMPARISON WITH EXISTING METHOD(S): Previously, we demonstrated 14 independent EEG spatiospectral patterns within this EEG dataset, stable across the resting-state, visual oddball and semantic decision paradigms. Here, we demonstrate that their time courses are significantly correlated with fMRI dynamics organized into LSBN structures. EEG-fMRI derived HRF peak appears earlier than the canonical HRF peak, which suggests limitations when assuming a canonical HRF shape in EEG-fMRI. CONCLUSIONS: This is the first study examining EEG-fMRI relationships among independent EEG spatiospectral patterns over different paradigms. The findings highlight the importance of considering different HRF shapes when spatiotemporally characterizing brain networks using EEG and fMRI.

• MeSH
• dospělí MeSH
• elektroencefalografie metody   MeSH
• funkční zobrazování neurálních procesů metody   MeSH
• lidé MeSH
• magnetická rezonanční tomografie metody   MeSH
• mladý dospělý MeSH
• nervová síť diagnostické zobrazování   fyziologie   MeSH
• neurovaskulární vazba fyziologie   MeSH
• psycholingvistika MeSH
• velký mozek diagnostické zobrazování   fyziologie   MeSH
• zraková percepce fyziologie   MeSH
• Check Tag
• dospělí MeSH
• lidé MeSH
• mladý dospělý MeSH
• mužské pohlaví MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

Electroencephalography (EEG) oscillations reflect the superposition of different cortical sources with potentially different frequencies. Various blind source separation (BSS) approaches have been developed and implemented in order to decompose these oscillations, and a subset of approaches have been developed for decomposition of multi-subject data. Group independent component analysis (Group ICA) is one such approach, revealing spatiospectral maps at the group level with distinct frequency and spatial characteristics. The reproducibility of these distinct maps across subjects and paradigms is relatively unexplored domain, and the topic of the present study. To address this, we conducted separate group ICA decompositions of EEG spatiospectral patterns on data collected during three different paradigms or tasks (resting-state, semantic decision task and visual oddball task). K-means clustering analysis of back-reconstructed individual subject maps demonstrates that fourteen different independent spatiospectral maps are present across the different paradigms/tasks, i.e. they are generally stable.

• MeSH
• algoritmy MeSH
• analýza hlavních komponent MeSH
• elektroencefalografie metody   statistika a číselné údaje   MeSH
• interpretace obrazu počítačem metody   MeSH
• lidé MeSH
• magnetická rezonanční tomografie MeSH
• mapování mozku metody   MeSH
• mladý dospělý MeSH
• počítačové zpracování signálu MeSH
• psychomotorický výkon fyziologie   MeSH
• reprodukovatelnost výsledků MeSH
• rozhodování fyziologie   MeSH
• shluková analýza MeSH
• zraková percepce fyziologie   MeSH
• Check Tag
• lidé MeSH
• mladý dospělý MeSH
• mužské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

OBJECTIVES: Our main objective is to design a method of, and supporting software for, interactive correction and semantic annotation of narrative clinical reports, which would allow for their easier and less erroneous processing outside their original context: first, by physicians unfamiliar with the original language (and possibly also the source specialty), and second, by tools requiring structured information, such as decision-support systems. Our additional goal is to gain insights into the process of narrative report creation, including the errors and ambiguities arising therein, and also into the process of report annotation by clinical terms. Finally, we also aim to provide a dataset of ground-truth transformations (specific for Czech as the source language), set up by expert physicians, which can be reused in the future for subsequent analytical studies and for training automated transformation procedures. METHODS: A three-phase preprocessing method has been developed to support secondary use of narrative clinical reports in electronic health record. Narrative clinical reports are narrative texts of healthcare documentation often stored in electronic health records. In the first phase a narrative clinical report is tokenized. In the second phase the tokenized clinical report is normalized. The normalized clinical report is easily readable for health professionals with the knowledge of the language used in the narrative clinical report. In the third phase the normalized clinical report is enriched with extracted structured information. The final result of the third phase is a semi-structured normalized clinical report where the extracted clinical terms are matched to codebook terms. Software tools for interactive correction, expansion and semantic annotation of narrative clinical reports has been developed and the three-phase preprocessing method validated in the cardiology area. RESULTS: The three-phase preprocessing method was validated on 49 anonymous Czech narrative clinical reports in the field of cardiology. Descriptive statistics from the database of accomplished transformations has been calculated. Two cardiologists participated in the annotation phase. The first cardiologist annotated 1500 clinical terms found in 49 narrative clinical reports to codebook terms using the classification systems ICD 10, SNOMED CT, LOINC and LEKY. The second cardiologist validated annotations of the first cardiologist. The correct clinical terms and the codebook terms have been stored in a database. CONCLUSIONS: We extracted structured information from Czech narrative clinical reports by the proposed three-phase preprocessing method and linked it to electronic health records. The software tool, although generic, is tailored for Czech as the specific language of electronic health record pool under study. This will provide a potential etalon for porting this approach to dozens of other less-spoken languages. Structured information can support medical decision making, quality assurance tasks and further medical research.

• MeSH
• elektronické zdravotní záznamy normy   MeSH
• mezinárodní klasifikace nemocí MeSH
• psaní normy   MeSH
• řízený slovník * MeSH
• sémantika * MeSH
• směrnice jako téma MeSH
• smysluplné využití normy   MeSH
• software MeSH
• správnost dat MeSH
• strojové učení * MeSH
• uživatelské rozhraní počítače MeSH
• zpracování přirozeného jazyka * MeSH
• zpracování textu normy   MeSH
• Publikační typ
• časopisecké články MeSH

Introduction: In Germany, there is currently no consistent analytic structure within genomic diagnostics in oncological diseases. Within the framework of the project GENeALYSE, a standardized and interoperable specification for associated uses cases shall be developed. Intended Methods: Through process analysis and interface modeling, problems of the actual processes will be depicted between the involved actors. In the next step, the workflows and relevant findings will be displayed and adapted. In particular, the heterogeneous workflows in genome diagnostics will be represented by semantic annotation in an international terminology. The results of the semantic annotation build the basement for the creation of an implementation guide for standardized genome analytics, referring to HL7 Clinical Document Architecture (HL7 CDA). Discussion: The problems of heterogeneous genomic diagnostics as well as unstructured findings in oncology leave the actors face comparable challenges on a regional and supranational level. Interfaces, ambiguous semantics and manual activities inhibit interoperability, promote errors and lead to risks for patients and their sufficient medical treatment. A major challenge will be consistency between the heterogeneous terms to be found in genome analysis. The problem shall be addressed via using international terminologies as well as appropriate mapping techniques. Conclusions: The aim of the project is to create an implementation guide for standardized digital documentation and communication solutions between diagnostics, medical therapy and research in the field of genome analysis. GENeALYSE is intended to optimize the coordination between the diagnostic genome laboratory and the clinical therapy decision in order to increase the safety and success of medical treatment, as well as to improve the health-related quality of life of the affected patients.

• MeSH
• diagnostické techniky molekulární metody   normy   MeSH
• elektronické zdravotní záznamy normy   MeSH
• Health Level Seven MeSH
• terminologie jako téma MeSH
• výměna zdravotnických informací * normy   MeSH

Deciding on things is a knowledge-based activity. In the context of clinical decision support systems (DSS) this means that representation and management of the related knowledge about underlying concepts and processes is foundational for the decision-making process. A basic challenge to be mastered is the language problem. For expressing and sharing knowledge, we have to agree on terminologies specific for each of the considered domains. For guaranteeing semantic consistency, the concepts, their relation and underlying rules must be defined, deploying domain-specific as well as high-level ontologies. Ontology representation types range from glossaries and data dictionaries through thesauri and taxonomies, meta-data and data models up to formal ontologies, the latter represented by frames, formal languages and different types of logics. Based on the aforementioned principles, special knowledge representation and sharing languages relevant for health have been introduced. Examples are PROforma, Asbru, EON, Arden Syntax, GELLO, GLIF, Archetypes, HL7 Clinical Statements, and the recently developed FHIR approach. With increasing complexity and flexibility of decision challenges, DSS design has to follow a defined methodology, offered by the Generic Component Model Framework meanwhile internationally standardized. This paper deals in detail with the basics and instances for knowledge representation and management for DSS design and implementation, thereby referencing related work of the author.

• MeSH
• klinické rozhodování metody   MeSH
• management znalostí MeSH
• metody pro podporu rozhodování MeSH
• počítačové systémy * MeSH
• systémová teorie MeSH
• systémy pro podporu klinického rozhodování MeSH
• umělá inteligence MeSH
• znalostní báze * MeSH