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Article: Urological Services in the Era of COVID-19

Efthimiou, Ioannis

Urol J

Abstract: INTRODUCTION: On 11 March 2020, the World Health Organization (WHO) declared a pandemic. Since then hospitals have reduced inpatient and outpatient workflow and cancelled or suspended all non-emergent and routine surgical procedures. Our objective is to ... ...

Abstract	INTRODUCTION: On 11 March 2020, the World Health Organization (WHO) declared a pandemic. Since then hospitals have reduced inpatient and outpatient workflow and cancelled or suspended all non-emergent and routine surgical procedures. Our objective is to determine whether, during the COVID-19 period, there has been any modification in urological services. MATERIALS AND METHODS: We retrospectively studied the data from January-May 2020 and 2019 about the variables: number of operations, waiting list, visits in outpatient department, bladder instillations and urological emergencies and admission rates. RESULTS: Cancer cases high-risk for stage progression and surgical emergencies, were elected to proceed directly to treatment. The number of the operations was reduced by 43-65% from March-May 2020. Our surgical list had a waiting time of 6-8 weeks before the pandemic and now the waiting time has expanded to 12 weeks. Urological emergencies were reduced about 23-57%. Admission rates were dropped 10-51%. Visits in outpatient clinics were reduced 100-50% and outpatient procedures for elective cases were all deferred. Unfortunately, the hospital did not offer synchronous telehealth appointments. Bladder instillations of BCG or chemotherapeutics were not suspended but start of new cases had a delay of 2-3 weeks. There were no cases of COVID-19 in our department. CONCLUSION: All the variables of our urologic practice were affected during the COVID era. The impact of the reduced model of outpatient and inpatient workflow on the health of our patients is unknown. However, longer waiting lists are expected. It is obvious that healthcare providers should adopt a new healthcare model.
Keywords	covid19
Publisher	WHO
Document type	Article
Note	WHO #Covidence: #680830
Database	COVID19

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Article ; Online: Zygomaticus activation through facial neuromuscular electrical stimulation (fNMES) induces happiness perception in ambiguous facial expressions and affects neural correlates of face processing.

Efthimiou, Themis Nikolas / Baker, Joshua / Clarke, Alasdair / Elsenaar, Arthur / Mehu, Marc / Korb, Sebastian

Social cognitive and affective neuroscience

2024 Volume 19, Issue 1

Abstract: The role of facial feedback in facial emotion recognition remains controversial, partly due to limitations of the existing methods to manipulate the activation of facial muscles, such as voluntary posing of facial expressions or holding a pen in the ... ...

Abstract	The role of facial feedback in facial emotion recognition remains controversial, partly due to limitations of the existing methods to manipulate the activation of facial muscles, such as voluntary posing of facial expressions or holding a pen in the mouth. These procedures are indeed limited in their control over which muscles are (de)activated when and to what degree. To overcome these limitations and investigate in a more controlled way if facial emotion recognition is modulated by one's facial muscle activity, we used computer-controlled facial neuromuscular electrical stimulation (fNMES). In a pre-registered EEG experiment, ambiguous facial expressions were categorised as happy or sad by 47 participants. In half of the trials, weak smiling was induced through fNMES delivered to the bilateral Zygomaticus Major muscle for 500 ms. The likelihood of categorising ambiguous facial expressions as happy was significantly increased with fNMES, as shown with frequentist and Bayesian linear mixed models. Further, fNMES resulted in a reduction of P1, N170 and LPP amplitudes. These findings suggest that fNMES-induced facial feedback can bias facial emotion recognition and modulate the neural correlates of face processing. We conclude that fNMES has potential as a tool for studying the effects of facial feedback.
MeSH term(s)	Humans ; Happiness ; Emotions/physiology ; Facial Recognition/physiology ; Facial Muscles/physiology ; Facial Expression ; Bayes Theorem ; Electroencephalography ; Electric Stimulation
Language	English
Publishing date	2024-02-09
Publishing country	England
Document type	Journal Article
ZDB-ID	2236933-8
ISSN	1749-5024 ; 1749-5016
ISSN (online)	1749-5024
ISSN	1749-5016
DOI	10.1093/scan/nsae013
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Second-generation antipsychotics and seizures - a systematic review and meta-analysis of serious adverse events in randomized controlled trials.

Reichelt, Leonie / Efthimiou, Orestis / Leucht, Stefan / Schneider-Thoma, Johannes

European neuropsychopharmacology : the journal of the European College of Neuropsychopharmacology

2023 Volume 68, Page(s) 33–46

Abstract: Seizures are suspected to be side effects of antipsychotics. To examine a possible causal relationship, we compared the risk of seizures on second-generation antipsychotics to the risk on placebo in randomized controlled clinical trials (RCTs) across ... ...

Abstract	Seizures are suspected to be side effects of antipsychotics. To examine a possible causal relationship, we compared the risk of seizures on second-generation antipsychotics to the risk on placebo in randomized controlled clinical trials (RCTs) across diagnostic groups. The primary outcome was any seizure reported as International Conference on Harmonisation-Good Clinical Practice (ICH-GCP)-defined serious adverse event (SAEs). The risk ratio (RR) with antipsychotics versus placebo was synthesized in a pairwise common effects Mantel-Haenszel meta-analysis. For 314 of 597 idenitified placebo-controlled RCTs information about all SAEs could be retrieved from publications, original investigators, pharmaceutical companies and the European Medical Agency. In those, 37 seizures occurred in 42,600 participants on antipsychotics (0.09%) and 28 in 25,042 participants on placebo (0.11%). The meta-analytic results (RR 0,68; 95% Confidence Interval 0.41-1.12) indicated a reduced risk on antipsychotics with a confidence interval including no difference (i.e. RR=1). Neither in sensitivity analyses (excluding events in the safety-follow-up of trials or first-generation antipsychotics; using odds ratios) nor in subgroup analyses (on specific antipsychotics, drug combinations, diagnostic categories, age groups, and study duration) there was evidence for an increased risk on antipsychotics, except for some weak indications of an increased risk on antipsychotics in older and/or demented participants (RRs 1.11 and 1.48, respectively, but with 95% CIs of 0.35-3.49 and 0.41-5.26 including no difference and subgroup tests with p=0.54 and p=0.66 not indicating differences between age groups or diagnostic categories). Consequently, there are no indications that second-generation antipsychotics cause seizures in middle-aged adults and children in most diagnostic groups; rather our results provide some weak evidence for a protective effect. However, there was no data on SAEs available for clozapine, for which observational studies provide the strongest associations with increased seizure rates, and for older and/or demented patients a small additional risk on antipsychotics cannot be excluded.
MeSH term(s)	Adult ; Middle Aged ; Child ; Humans ; Aged ; Antipsychotic Agents/adverse effects ; Randomized Controlled Trials as Topic ; Clozapine ; Seizures/chemically induced ; Seizures/epidemiology ; Seizures/drug therapy
Chemical Substances	Antipsychotic Agents ; Clozapine (J60AR2IKIC)
Language	English
Publishing date	2023-01-12
Publishing country	Netherlands
Document type	Meta-Analysis ; Systematic Review ; Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	1082947-7
ISSN	1873-7862 ; 0924-977X
ISSN (online)	1873-7862
ISSN	0924-977X
DOI	10.1016/j.euroneuro.2022.12.010
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Article ; Online: Measurement of the N170 during facial neuromuscular electrical stimulation (fNMES).

Baker, J / Efthimiou, T / Scherer, R / Gartus, A / Elsenaar, A / Mehu, M / Korb, S

Journal of neuroscience methods

2023 Volume 393, Page(s) 109877

Abstract: Background: Studies on facial feedback effects typically employ props or posed facial expressions, which often lack temporal precision and muscle specificity.: New method: Facial Neuromuscular Electrical Stimulation (fNMES) allows for a controlled ... ...

Abstract	Background: Studies on facial feedback effects typically employ props or posed facial expressions, which often lack temporal precision and muscle specificity. New method: Facial Neuromuscular Electrical Stimulation (fNMES) allows for a controlled influence of contractions of facial muscles, and may be used to advance our understanding of facial feedback effects, especially when combined with Electroencephalography (EEG). However, electrical stimulation introduces significant interference that can mask underlying brain dynamics. Whether established signal processing methods can allow for a reduction of said interference whilst retaining effects of interest, remains unexplored. Results: We addressed these questions focusing on the classic N170 visual evoked potential, a face-sensitive brain component: 20 participants viewed images of houses, and of sad, happy, and neutral faces. On half of the trials, fNMES was delivered to bilateral lower-face muscles during the presentation of visual stimuli. A larger N170 amplitude was found for faces relative to houses. Interestingly, this was the case both without and during fNMES, regardless of whether the fNMES artefact was removed or not. Moreover, sad facial expressions elicited a larger N170 amplitude relative to neutral facial expressions, both with and without fNMES. Comparison with existing methods: fNMES offers a more precise way of manipulating proprioceptive feedback from facial muscles, which affords greater diversity in experimental design for studies on facial feedback effects. Conclusions: We show that the combining of fNMES and EEG can be achieved and may serve as a powerful means of exploring the impact of controlled proprioceptive inputs on various types of cognitive processing.
MeSH term(s)	Humans ; Evoked Potentials, Visual ; Electroencephalography/methods ; Brain ; Facial Expression ; Photic Stimulation/methods ; Evoked Potentials/physiology ; Emotions/physiology
Language	English
Publishing date	2023-05-09
Publishing country	Netherlands
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	282721-9
ISSN	1872-678X ; 0165-0270
ISSN (online)	1872-678X
ISSN	0165-0270
DOI	10.1016/j.jneumeth.2023.109877
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Article ; Online: Multiple imputation of incomplete multilevel data using Heckman selection models.

Muñoz, Johanna / Efthimiou, Orestis / Audigier, Vincent / de Jong, Valentijn M T / Debray, Thomas P A

Statistics in medicine

2023 Volume 43, Issue 3, Page(s) 514–533

Abstract: Missing data is a common problem in medical research, and is commonly addressed using multiple imputation. Although traditional imputation methods allow for valid statistical inference when data are missing at random (MAR), their implementation is ... ...

Abstract	Missing data is a common problem in medical research, and is commonly addressed using multiple imputation. Although traditional imputation methods allow for valid statistical inference when data are missing at random (MAR), their implementation is problematic when the presence of missingness depends on unobserved variables, that is, the data are missing not at random (MNAR). Unfortunately, this MNAR situation is rather common, in observational studies, registries and other sources of real-world data. While several imputation methods have been proposed for addressing individual studies when data are MNAR, their application and validity in large datasets with multilevel structure remains unclear. We therefore explored the consequence of MNAR data in hierarchical data in-depth, and proposed a novel multilevel imputation method for common missing patterns in clustered datasets. This method is based on the principles of Heckman selection models and adopts a two-stage meta-analysis approach to impute binary and continuous variables that may be outcomes or predictors and that are systematically or sporadically missing. After evaluating the proposed imputation model in simulated scenarios, we illustrate it use in a cross-sectional community survey to estimate the prevalence of malaria parasitemia in children aged 2-10 years in five regions in Uganda.
MeSH term(s)	Child ; Humans ; Cross-Sectional Studies ; Biomedical Research ; Uganda/epidemiology
Language	English
Publishing date	2023-12-11
Publishing country	England
Document type	Meta-Analysis ; Journal Article
ZDB-ID	843037-8
ISSN	1097-0258 ; 0277-6715
ISSN (online)	1097-0258
ISSN	0277-6715
DOI	10.1002/sim.9965
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Article ; Online: Partial volume correction of PET image data using geometric transfer matrices based on uniform B-splines.

Mandeville, Joseph B / Efthimiou, Nikos / Weigand-Whittier, Jonah / Hardy, Erin / Knudsen, Gitte M / Jørgensen, Louise M / Chen, Yin-Ching I

Physics in medicine and biology

2024 Volume 69, Issue 5

Abstract: ... ...

Abstract	Objective
MeSH term(s)	Humans ; Mice ; Animals ; Brain ; Algorithms ; Positron-Emission Tomography/methods ; Signal-To-Noise Ratio ; Raclopride ; Image Processing, Computer-Assisted/methods
Chemical Substances	Raclopride (430K3SOZ7G)
Language	English
Publishing date	2024-02-23
Publishing country	England
Document type	Journal Article
ZDB-ID	208857-5
ISSN	1361-6560 ; 0031-9155
ISSN (online)	1361-6560
ISSN	0031-9155
DOI	10.1088/1361-6560/ad22a0
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Article: Correction to: Use of non-Gaussian time-of-flight kernels for image reconstruction of Monte Carlo simulated data of ultra-fast PET scanners.

Efthimiou, Nikos / Thielemans, Kris / Emond, Elise / Cawthorne, Chris / Archibald, Stephen J / Tsoumpas, Charalampos

EJNMMI physics

2022 Volume 9, Issue 1, Page(s) 14

Language	English
Publishing date	2022-02-24
Publishing country	Germany
Document type	Published Erratum
ZDB-ID	2768912-8
ISSN	2197-7364
ISSN	2197-7364
DOI	10.1186/s40658-022-00441-7
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Article ; Online: Dual mechanism of action of T2 inhibitor therapies in virally induced exacerbations of asthma: evidence for a beneficial counter-regulation.

Efthimiou, John / Poll, Chris / Barnes, Peter J

The European respiratory journal

2019 Volume 54, Issue 1

Abstract: Biological agents such as omalizumab and monoclonal antibodies (mAbs) that inhibit type 2 (T2) immunity significantly reduce exacerbations, which are mainly due to viral infections, when added to inhaled corticosteroids in patients with severe asthma. ... ...

Abstract	Biological agents such as omalizumab and monoclonal antibodies (mAbs) that inhibit type 2 (T2) immunity significantly reduce exacerbations, which are mainly due to viral infections, when added to inhaled corticosteroids in patients with severe asthma. The mechanisms for the therapeutic benefit of T2 inhibitors in reducing virally induced exacerbations, however, remain to be fully elucidated. Pre-clinical and clinical evidence supports the existence of a close counter-regulation of the high-affinity IgE receptor and interferon (IFN) pathways, and a potential dual mechanism of action and therapeutic benefit for omalizumab and other T2 inhibitors that inhibit IgE activity, which may enhance the prevention and treatment of virally induced asthma exacerbations. Similar evidence regarding some novel T2 inhibitor therapies, including mAbs and small-molecule inhibitors, suggests that such a dual mechanism of action with enhancement of IFN production working through non-IgE pathways might also exist. The specific mechanisms for this dual effect could be related to the close counter-regulation between T2 and T1 immune pathways, and potential key underlying mechanisms are discussed. Further basic research and better understanding of these underlying counter-regulatory mechanisms could provide novel therapeutic targets for the prevention and treatment of virally induced asthma exacerbations, as well as T2- and non-T2-driven asthma. Future clinical research should examine the effects of T2 inhibitors on IFN responses and other T1 immune pathways, in addition to any effects on the frequency and severity of viral and other infections and related exacerbations in patients with asthma as a priority.
MeSH term(s)	Adrenal Cortex Hormones/therapeutic use ; Anti-Asthmatic Agents/therapeutic use ; Antibodies, Monoclonal, Humanized/therapeutic use ; Asthma/drug therapy ; Asthma/immunology ; Humans ; Immunoglobulin E/blood ; Immunoglobulin E/immunology ; Omalizumab ; Randomized Controlled Trials as Topic
Chemical Substances	Adrenal Cortex Hormones ; Anti-Asthmatic Agents ; Antibodies, Monoclonal, Humanized ; Omalizumab (2P471X1Z11) ; Immunoglobulin E (37341-29-0)
Keywords	covid19
Language	English
Publishing date	2019-07-04
Publishing country	England
Document type	Journal Article ; Review
ZDB-ID	639359-7
ISSN	1399-3003 ; 0903-1936
ISSN (online)	1399-3003
ISSN	0903-1936
DOI	10.1183/13993003.02390-2018
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Article: Measurement of the N170 during facial neuromuscular electrical stimulation (fNMES)

Baker, J. / Efthimiou, T. / Scherer, R. / Gartus, A. / Elsenaar, A. / Mehu, M. / Korb, S.

Journal of Neuroscience Methods

2023

Abstract: Background: Studies on facial feedback effects typically employ props or posed facial expressions, which often lack temporal precision and muscle specificity. New method: Facial Neuromuscular Electrical Stimulation (fNMES) allows for a controlled ... ...

Title translation	Messung des N170 während der neuromuskulären elektrischen Stimulation des Gesichts (fNMES)
Abstract	Background: Studies on facial feedback effects typically employ props or posed facial expressions, which often lack temporal precision and muscle specificity. New method: Facial Neuromuscular Electrical Stimulation (fNMES) allows for a controlled influence of contractions of facial muscles, and may be used to advance our understanding of facial feedback effects, especially when combined with Electroencephalography (EEG). However, electrical stimulation introduces significant interference that can mask underlying brain dynamics. Whether established signal processing methods can allow for a reduction of said interference whilst retaining effects of interest, remains unexplored. Results: We addressed these questions focusing on the classic N170 visual evoked potential, a face-sensitive brain component: 20 participants viewed images of houses, and of sad, happy, and neutral faces. On half of the trials, fNMES was delivered to bilateral lower-face muscles during the presentation of visual stimuli. A larger N170 amplitude was found for faces relative to houses. Interestingly, this was the case both without and during fNMES, regardless of whether the fNMES artefact was removed or not. Moreover, sad facial expressions elicited a larger N170 amplitude relative to neutral facial expressions, both with and without fNMES. Comparison with existing methods: fNMES offers a more precise way of manipulating proprioceptive feedback from facial muscles, which affords greater diversity in experimental design for studies on facial feedback effects. Conclusions: We show that the combining of fNMES and EEG can be achieved and may serve as a powerful means of exploring the impact of controlled proprioceptive inputs on various types of cognitive processing.
Keywords	Electrical Stimulation ; Electroencephalography ; Elektrische Stimulation ; Elektroenzephalographie ; Evoked Potentials ; Evozierte Potenziale ; Face Perception ; Facial Expressions ; Facial Muscles ; Gesichterwahrnehmung ; Gesichtsausdruck ; Gesichtsmuskeln ; Visual Evoked Potentials ; Visuell evozierte Potenziale
Language	English
Document type	Article
ZDB-ID	282721-9
ISSN	1872-678X ; 0165-0270
ISSN (online)	1872-678X
ISSN	0165-0270
DOI	10.1016/j.jneumeth.2023.109877
Database	PSYNDEX

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Article ; Online: Measuring the performance of prediction models to personalize treatment choice.

Efthimiou, Orestis / Hoogland, Jeroen / Debray, Thomas P A / Seo, Michael / Furukawa, Toshiaki A / Egger, Matthias / White, Ian R

Statistics in medicine

2023 Volume 42, Issue 8, Page(s) 1188–1206

Abstract: When data are available from individual patients receiving either a treatment or a control intervention in a randomized trial, various statistical and machine learning methods can be used to develop models for predicting future outcomes under the two ... ...

Abstract	When data are available from individual patients receiving either a treatment or a control intervention in a randomized trial, various statistical and machine learning methods can be used to develop models for predicting future outcomes under the two conditions, and thus to predict treatment effect at the patient level. These predictions can subsequently guide personalized treatment choices. Although several methods for validating prediction models are available, little attention has been given to measuring the performance of predictions of personalized treatment effect. In this article, we propose a range of measures that can be used to this end. We start by defining two dimensions of model accuracy for treatment effects, for a single outcome: discrimination for benefit and calibration for benefit. We then amalgamate these two dimensions into an additional concept, decision accuracy, which quantifies the model's ability to identify patients for whom the benefit from treatment exceeds a given threshold. Subsequently, we propose a series of performance measures related to these dimensions and discuss estimating procedures, focusing on randomized data. Our methods are applicable for continuous or binary outcomes, for any type of prediction model, as long as it uses baseline covariates to predict outcomes under treatment and control. We illustrate all methods using two simulated datasets and a real dataset from a trial in depression. We implement all methods in the R package predieval. Results suggest that the proposed measures can be useful in evaluating and comparing the performance of competing models in predicting individualized treatment effect.
MeSH term(s)	Humans ; Treatment Outcome ; Randomized Controlled Trials as Topic ; Precision Medicine ; Models, Statistical ; Clinical Decision Rules
Language	English
Publishing date	2023-01-26
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	843037-8
ISSN	1097-0258 ; 0277-6715
ISSN (online)	1097-0258
ISSN	0277-6715
DOI	10.1002/sim.9665
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