39 research outputs found
Characteristics of clinical-pharmacological recommendations in psychiatry
No full textOBJECTIVE
Psychiatric patients in general, and elderly psychiatric patients in particular, are at risk of adverse drug reactions due to comorbidities and inappropriate polypharmacy. Interdisciplinary and clinical-pharmacologist-led medication reviews may contribute to medication safety in the field of psychiatry. In this study, we reported the frequency and characteristics of clinical-pharmacological recommendations in psychiatry, with a particular focus on geriatric psychiatry.
METHOD
A clinical pharmacologist, in collaboration with the attending psychiatrists and a consulting neurologist, conducted interdisciplinary medication reviews in a general psychiatric ward with a geropsychiatric focus at a university hospital over a 25-week period. All clinical and pharmacological recommendations were recorded and evaluated.
RESULTS
A total of 316 recommendations were made during 374 medication reviews. Indications/contraindications of drugs were the most frequently discussed topics (59/316; 18.7 %), followed by dose reductions (37/316; 11.7 %), and temporary or permanent discontinuation of medications (36/316; 11.4 %). The most frequent recommendations for dose reduction involvedbenzodiazepines (9/37; 24.3 %). An unclear or absent indication was the most common reason for recommending temporary or permanent discontinuation of the medication (6/36; 16.7 %).
CONCLUSION
Interdisciplinary clinical pharmacologist-led medication reviews represented a valuable contribution to medication management in psychiatric patients, particularly the elderly ones
Chlorita tamaninii Wagner 1959
No full textChlorita cf. tamaninii Wagner, 1959 (Fig. 4) First record from Switzerland: Ticino, Ludiano, Ronco Pizzotti, vineyard, [46 ° 24 ’ 57.92 ’’ N; 8 ° 58 ’ 11.39 ’’ E, 459 m], 2 ♂♂, 1 ♀, 21.06. 2011, D-vac, leg. & det. Valeria. Trivellone Distribution in Europe:Italy, Switzerland. Remarks:In total 24 species of the genus Chlorita Fieber are known from the Palaeartic region. Four of them: C. subulata (Ribaut, 1933), C. viridula (Fallen, 1806), C. tamaninii Wagner, 1959 and C. paolii (Ossiannilsson, 1939) belong to the Chlorita viridula species group and are closely related. Wagner (1959) published a key to distinguish the above-mentioned species. Up to now, in Switzerland only C. viridula (Ribaut 1933, Cerutti 1939) and C. paolii (Trivellone &Pollini Paltrinieri 2011) were recorded. In 2011, the first author had collected specimens with aedeagus morphological characteristics quite different from C. viridula and C. paolii. According to the key after Wagner (1959), two main subgroups of species were recognized based on the characteristics of the appendages of the aedeagus: appendages without ablunt tooth and convergent in the viridula-subulata subgroup; and appendages with ablunt tooth and divergent in the paolii-tamaninii subgroup. The appendages of the examined specimens do neither coincide perfectly with the first, nor with the second subgroup. The following description of aspecimen is proposed as reference to further collections. Determination:The genital plate with parameres and the appendices of the anal tube are illustrated in Figs 4 A and 4 B, respectively; they are similar to C. viridula after Le Quesne &Payne (1981). In the male, aedeagus with apair of recurved appendages, longer than main stem, without tooth along outer margin; but hardly S-shaped in the middle (Fig. 4C) and ending in sharp-hooked apices (Fig. 4D).Published as part of Valeria Trivellone, Eva Knop, Tabea Turrini, Line Andrey, Jean-Yves Humbert & Gernot Kunz, 2015, New and remarkable leafhoppers and planthoppers (Hemiptera: Auchenorrhyncha) from Switzerland, pp. 273-284 in Mitteilungen Der Schweizerischen Entomologischen Gesellschaft 88 on page 278, DOI: 10.5281/zenodo.3399
TabeaSonnenschein/GenSynthPop: R-package for Generating Representative Spatially Explicit Synthetic Populations
No full textInstructions for R-package: GenSynthPop Author: Tabea Sonnenschein, Utrecht University
This package contains a set of functions that help prepare stratified census datasets to generate conditional propensities, combines the conditional propensities with spatial marginal distributions to generate a representative population and validates that the produced agents have a similar distribution as the initial spatial marginal datasets and the stratified datasets. The generated population is representative for a city or the spatial extent that is fed into the algorithms and can be used for simulation purposes, such as an agent-based model. The smaller the spatial units of the spatial marginal distributions, the more spatially resolved the agents will be too.
Overview of functions For Data Preparation
crosstabular_to_singleside_df: Crosstabular Stratified Table to Single Sided Variable Combination - Counts Table
restructure_one_var_marginal: Restructures a single-sided stratified dataframe so that the classes of one column/variable of interest are seperate columns
varclass_harmonization: Harmonize the classes of a variable across datasets
aggreg_stratdata_in_harmonclasses: Aggregating a stratified dataset into the newly added harmonised classes
add_spatial_units_to_agent_df: Add a new spatial unit to the agent dataframe based on a unit map
For Initiating the Agent Dataframe
gen_agent_df: Generating an agent dataframe of the population size and assigning a unique ID
distr_agent_neigh_age_group: Populating the agent_df with age_group and neigh_ID attributes distributed like a given neighborhood marginal distribution
For Conditional Propensity calculation
calc_propens_agents: Calculating the conditional propensity to have an attribute based on conditional variables
strat_prop_from_sep_cond_var: Creates a stratified propensity table from separate conditional variable joint distributions
For Attribute Assignment based on conditional and marginal distributions
distr_attr_strat_neigh_stats_binary: Distributing attributes across agent population based on conditional proabilities and neighborhood totals for binary attributes
distr_attr_strat_neigh_stats_3plus: Distributing attributes across agent population based on conditional proabilities and neighborhood totals for attributes with 3 or more classes
distr_attr_cond_prop: Assigning Attributes purely based on conditional probabilities
For Validation
crossvalid: Cross validation with the neighborhood and stratified marginal distributions
Installing package in R
install.packages("devtools")
library(devtools)
install_github("TabeaSonnenschein/GenSynthPop")
library(GenSynthPop)
Looking up documentation for a function There is extensive documentation for the functions within R
Example:
?crosstabular_to_singleside_df
help(crosstabular_to_singleside_df)
Should there be remaining questions, shoot me an email: [email protected]
Instructions
Start by collecting neighborhood marginal distributions of age_groups. It is recommended to go as spatially resolved as you can (smallest spatial unit) but it depends on what you want to use the synthetic agent population for. You theoretically can even use provincial or national administrative areas, if this is your project scope and goal. We go for neighborhoods because we want to create an urban ABM.
apply gen_agent_df for the sum of all age groups in all neighborhoods. This will be the population size.
use this new agent_df and the neighborhood marginal distribution dataframe in the distr_agent_neigh_age_group code to distribute the agents across neighborhoods and age groups.
Read the stratified dataframe with the conditional variable and the variable of interest (that you want to add), for example sex by agegroup, since we already added that one. Make sure that the classes of the conditional variables correspond to the ones in the agent_df. For that you can use varclass_harmonization. If the stratified dataset has been assigned larger harmosed classes, the marginal distributions have to be aggregated, for which you can use: aggreg_stratdata_in_harmonclasses. If instead of the stratified dataset, the agent_df was assigned larger harmonised classes, then no aggregation is necessary, because the new harmonised attribute can be used for calculating the propensities in step 5. Additionally to restructure and prepare the data so that it can be read by calc_propens_agents, you can use the data preparation functions: crosstabular_to_singleside_df and restructure_one_var_marginal
Use calc_propens_agents to generate propensities to have the attribute of interest based on the co-variance with the conditional variable that is already in the agent_df (e.g. the likelihood to be female based on the agegroup). This function takes the stratified dataframe, generates the propensities for the conditional variables and adds the given propensity for each agent to the agent_df. If you have a non-binary variable (3 or more classes) then calculate the propensities for every class of the variable (e.g. "low education", "middle education", "high education").
Depending on if your variable is binary or not, use distr_attr_strat_neigh_stats_binary or distr_attr_strat_neigh_stats_3plus by reading the neighborhood marginal distributions for the variable of interest, and the propensities calculated in step 5 to distribute the attribute of interest across the agent population accordingly.
Use crossvalid to validate that the generated distribution corresponds to the neighborhood and stratified distributions.
Repeat steps 4,5,6,7 for any new variable that you want to add to the agent dataframe. The more attributes are added, the more conditional variables can be use (e.g. using age, sex, migrationbackground, household size, as conditional variables for being "employed" or not). However, as many might assume the availability of census and stratified data has its limit :), but that depends on the geographic location and the year of interest.
you can look at the Example_Application_GenSynthPop.R script for an example application of the functions in the package
Longitudinal Data Collection in Continental Europe: Experiences from the Survey of Health, Ageing and Retirement in (SHARE)
No full textKetogenic diet does not promote triple-negative and luminal mammary tumor growth and metastasis in experimental mice
No full textVol.:(0123456789)1 3Clinical & Experimental Metastasis
https://doi.org/10.1007/s10585-023-10249-z
RESEARCH PAPER
Ketogenic diet does not promote triple-negative and luminal
mammary tumor growth and metastasis in experimental mice
Meret Grube1 · Arno Dimmler2 · Anja Schmaus1 · Rafael Saup1 · Tabea Wagner 1 · Boyan K. Garvalov 1 ·
Jonathan P. Sleeman1,3 · Wilko Thiele 1
Received: 17 October 2023 / Accepted: 21 November 2023
© The Author(s) 2023
Abstract
Ketogenic diets (KDs) can improve the well-being and quality of life of breast cancer patients. However, data on the effects
of KDs on mammary tumors are inconclusive, and the influence of KDs on metastasis in general remains to be investigated.
We therefore assessed the impact of a KD on growth and metastasis of triple negative murine 4T1 mammary tumors, and
on the progression of luminal breast tumors in an autochthonous MMTV-PyMT mouse model. We found that KD did not
influence the metastasis of 4T1 and MMTV-PyMT mammary tumors, but impaired 4T1 tumor cell proliferation in vivo, and
also temporarily reduced 4T1 primary tumor growth. Notably, the ketogenic ratio (the mass of dietary fat in relation to the
mass of dietary carbohydrates and protein) that is needed to induce robust ketosis was twice as high in mice as compared to
humans. Surprisingly, only female but not male mice responded to KD with a sustained increase in blood β-hydroxybutyrate
levels. Together, our data show that ketosis does not foster primary tumor growth and metastasis, suggesting that KDs can
be safely applied in the context of luminal breast cancer, and may even be advantageous for patients with triple negative
tumors. Furthermore, our data indicate that when performing experiments with KDs in mice, the ketogenic ratio needed to
induce ketosis must be verified, and the sex of the mice should also be taken into account
Engineering-Dienstleistungen in der Automobilindustrie: Verbreitung, Kooperationsformen und arbeitspolitische Konsequenzen
No full text"This contribution deals with the notion of wage labour in a fundamental perspective. Both the current theoretical debate as well as new empirical findings about the development of wage labour are summed up. The starting point of the reasoning is a short outline of the different forms as well as of the historical development of wage labour, which initially mainly was industrial work. The contribution then enters into the question how the fundamental coordination problems of work - the transformation and opportunism problem - are managed in the context of a power asymmetrical employment relation between labour and capital. And, how the achievement motivation of the employees can be secured under these circumstances. The thesis is proposed that the interaction of the company level - with its decision, negotiation and organisation processes - with the given labour market structures is of special significance for the regulation of the relations between wage labour and capital and the design of employment relations. To analyse these interrelationships, the author resort to newer concepts of 'company employment systems' for one thing and to considerations from the 'segmentation theory approach' to labour market research for another thing. In conclusion, the increased flexibility of hitherto standardised forms of regulating the employment relations and the decreasing importance of so-called normal employment relationships are identified as specific characteristics of new development trends of wage labour." (author's abstract
CGIAR Climate Impact Area Webinar Series: Webinar 4: About Adaptation and Carbon Dioxide Removalin a Warming World
No full textThe effectiveness of adaptation in reducing climate-related risks is known to decline at higher warming levels (Lissner et al., 2024). Carbon dioxide removal (CDR) is one way to stabilize temperature levels as stated in the latest CDR report, even though deep and sustained emissions reduction in all sectors remains the most important pathway for keeping within Paris-agreed goals.
From these two facts, we ask: What do we know about adaptation and CDR in a warming world?
The latest webinar from CGIAR’s Climate Impact Platform will explore this question, bringing together expert speakers from two different fields of climate research.
Adaptation actions are becoming less effective as the average global temperature continues to climb. Dr Tabea Lissner, Research Director, Global Solutions Initiative and a Lead Author of the 6th IPCC Assessment, has dedicated her career to understanding climate change adaptation, vulnerability, and risk. Her talk will spring from this study and this Carbon Brief blog post,
Table_2_Determinants of severe QTc prolongation in a real-world gerontopsychiatric setting.docx
No full textIntroductionQTc prolongation carries the risk of ventricular tachyarrhythmia (Torsades de Pointes) and sudden cardiac death. Psychotropic drugs can affect ventricular repolarization and thus prolong the QTc interval. The present study sought to investigate the risk factors (pharmacological and non-pharmacological) of severe QTc prolongation in gerontopsychiatric patients.MethodsElectrocardiograms of patients on a gerontopsychiatric ward were screened for QTc prolongation. Medication lists were examined utilizing the AzCERT classification. Potential drug interactions were identified with the electronic drug interaction program mediQ.ResultsThe overall prevalence of QTc prolongation was 13.6%, with 1.9% displaying severe QTc prolongation (≥ 500 ms). No statistically significant differences between patients with moderate and severe QTc prolongation were identified; however, patients with severe QTc prolongation tended to take more drugs (p = 0.063). 92.7% of patients with QTc prolongation took at least one AzCERT-listed drug, most frequently risperidone and pantoprazole. Risperidone and pantoprazole, along with pipamperone, were also most frequently involved in potential drug interactions. All patients displayed additional risk factors for QTc prolongation, particularly cardiac diseases.ConclusionIn addition to the use of potentially QTc-prolonging drugs, other risk factors, especially cardiac diseases, appear to be relevant for the development of QTc prolongation in gerontopsychiatric patients. Pantoprazole was frequently involved in potential drug interactions and should generally not be used for more than 8 weeks in geriatric populations. As clinical consequences of QTc prolongation were rare, potentially QTc-prolonging drugs should not be used overcautiously; their therapeutic benefit should be considered as well. It is paramount to perform diligent benefit–risk analyses prior to the initiation of potentially QTc-prolonging drugs and to closely monitor their clinical (side) effects.</p
Effects of continuation, frequency, and type of cannabis use on relapse in the first 2 years after onset of psychosis: an observational study
No full textSummaryBackgroundAlthough cannabis use after a first episode of psychosis has been associated with relapse, little is known about the determinants of this most preventable risk factor for relapse of psychosis. Here we aimed to study whether the effects on outcome vary depending on the type of cannabis consumed and usage pattern.MethodsIn this observational study, we prospectively recruited and followed up patients aged 18–65 years who presented with their first episode of psychosis to psychiatric services in south London, London, UK. Relapse of psychosis within 2 years after onset of psychosis was defined as risk of subsequent admission to hospital. We classified patients into different patterns of cannabis use based on continuity of use after onset of psychosis, potency of cannabis consumed, and frequency of use after the onset of their illness. We used multiple regression analyses (logistic or binominal) to compare the different cannabis use groups and propensity score analysis to validate the results.FindingsBetween April 12, 2002, and July 26, 2013, 256 patients presented with a first episode of psychosis. We did follow-up assessments for these patients until September, 2015. Simple analyses showed that former regular users of cannabis who stopped after the onset of psychosis had the most favourable illness course with regards to relapse. In multiple analysis, continued high-frequency users (ie, daily use in all 24 months) of high-potency (skunk-like) cannabis had the worst outcome, indexed as an increased risk for a subsequent relapse (odds ratio [OR] 3·28; 95% CI 1·22–9·18), more relapses (incidence rate ratio 1·77; 95% CI 0·96–3·25), fewer months until a relapse occurred (b −0·22; 95% CI −0·40 to −0·04), and more intense psychiatric care (OR 3·16; 95% CI 1·26–8·09) after the onset of psychosis.InterpretationAdverse effects associated with continued use of cannabis after the onset of a first episode of psychosis depend on the specific patterns of use. Possible interventions could focus on persuading cannabis-using patients with psychosis to reduce use or shift to less potent forms of cannabis.FundingNational Institute for Health Research (NIHR)
