Pearls & Oy-sters: INO Plus From Downward Herniation-A Cautionary Tale Regarding Neuro-Ophthalmologic Signatures of Brainstem Compression.

Pupillary assessment is a quintessential part of the clinical examination in neuro-intensive care patients because it provides insight into the integrity of midbrain reflex arcs. Abnormal pupils, particularly anisocoria and later bilateral fixed mydriasis, are classically used to assess expansive intracranial processes because they are frequently considered early indicators of transtentorial midbrain compression due to elevated intracranial pressure. Complex ocular motor deficits mapping to the midbrain are rarely described in the setting of high transtentorial pressure. This is likely because ocular motor deficits typically occur in conjunction with decreased consciousness and corticospinal tract dysfunction reflecting advanced midbrain compromise. We present a case of left midbrain compression due to downward herniation in a patient with acute-on-chronic bilateral subdural hematoma. Ocular motor assessment demonstrated left internuclear ophthalmoplegia (INO) and an ocular tilt reaction, termed INO plus. However, pupillary, mental status, and sensorimotor examinations were unremarkable. Head magnetic resonance imaging revealed acute perforator ischemia in the left pontomesencephalic tegmentum, localizing to the ipsilateral medial longitudinal fasciculus and graviceptive oculocephalic circuits. Microvascular compromise secondary to mechanical pressure is discussed as a causative mechanism. We caution against overreliance on "telltale pupils" in suspected brainstem compression and recommend checking for other oculomotor signs.

Smartphone video nystagmography using convolutional neural networks: ConVNG.

BACKGROUND: Eye movement abnormalities are commonplace in neurological disorders. However, unaided eye movement assessments lack granularity. Although videooculography (VOG) improves diagnostic accuracy, resource intensiveness precludes its broad use. To bridge this care gap, we here validate a framework for smartphone video-based nystagmography capitalizing on recent computer vision advances. METHODS: A convolutional neural network was fine-tuned for pupil tracking using > 550 annotated frames: ConVNG. In a cross-sectional approach, slow-phase velocity of optokinetic nystagmus was calculated in 10 subjects using ConVNG and VOG. Equivalence of accuracy and precision was assessed using the "two one-sample t-test" (TOST) and Bayesian interval-null approaches. ConVNG was systematically compared to OpenFace and MediaPipe as computer vision (CV) benchmarks for gaze estimation. RESULTS: ConVNG tracking accuracy reached 9-15% of an average pupil diameter. In a fully independent clinical video dataset, ConVNG robustly detected pupil keypoints (median prediction confidence 0.85). SPV measurement accuracy was equivalent to VOG (TOST p < 0.017; Bayes factors (BF) > 24). ConVNG, but not MediaPipe, achieved equivalence to VOG in all SPV calculations. Median precision was 0.30°/s for ConVNG, 0.7°/s for MediaPipe and 0.12°/s for VOG. ConVNG precision was significantly higher than MediaPipe in vertical planes, but both algorithms' precision was inferior to VOG. CONCLUSIONS: ConVNG enables offline smartphone video nystagmography with an accuracy comparable to VOG and significantly higher precision than MediaPipe, a benchmark computer vision application for gaze estimation. This serves as a blueprint for highly accessible tools with potential to accelerate progress toward precise and personalized Medicine.

BDNF-related mutations in major depressive disorder: a systematic review.

OBJECTIVE: A better understanding of the genetic, molecular and cellular mechanisms of brain-derived neurotrophic factor (BDNF) and its association with neuroplasticity could play a pivotal role in finding future therapeutic targets for novel drugs in major depressive disorder (MDD). Because there are conflicting results regarding the exact role of BDNF polymorphisms in MDD still, we set out to systematically review the current evidence regarding BDNF-related mutations in MDD. METHODS: We conducted a keyword-guided search of the PubMed and Embase databases, using 'BDNF' or 'brain-derived neurotrophic factor' and 'major depressive disorder' and 'single-nucleotide polymorphism'. We included all publications in line with our exclusion and inclusion criteria that focused on BDNF-related mutations in the context of MDD. RESULTS: Our search yielded 427 records in total. After screening and application of our eligibility criteria, 71 studies were included in final analysis. According to present overall scientific data, there is a possibly major pathophysiological role for BDNF neurotrophic systems to play in MDD. However, on the one hand, the synthesis of evidence makes clear that likely no overall association of BDNF-related mutations with MDD exists. On the other hand, it can be appreciated that solidifying evidence emerged on specific significant sub-conditions and stratifications based on various demographic, clinico-phenotypical and neuromorphological variables. CONCLUSIONS: Further research should elucidate specific BDNF-MDD associations based on demographic, clinico-phenotypical and neuromorphological variables. Furthermore, biomarker approaches, specifically combinatory ones, involving BDNF should be further investigated.

Rapidly progressive dementia: Extending the spectrum of GFAP-astrocytopathies?

Autoimmune glial fibrillary acidic protein astrocytopathy (GFAP-A) is a steroid-responsive meningoencephalomyelitis, sometimes presenting with atypical clinical signs such as movement disorders or psychiatric and autonomic features. Beyond clinical presentation and imaging, diagnosis relies on detection of GFAP-antibodies (AB) in CSF. Using quantitative behavioral, serologic, and immunohistochemical analyses, we characterize two patients longitudinally over 18-24 months who presented with rapidly progressive neurocognitive deterioration in the context of GFAP-AB in CSF and unremarkable cranial MRI studies. Intensified immunotherapy was associated with clinical stabilization. The value of GFAP-AB screening in selected cases of rapidly progressive dementias is discussed.

Effects of Positive Reinforcement Training and Novel Object Exposure on Salivary Cortisol Levels under Consideration of Individual Variation in Captive African Elephants (Loxodonta africana).

Dealing with potential stress in species that have high husbandry requirements, such as elephants, is a challenge for zoos. The objective of the present study was to determine whether positive reinforcement training (PRT) and exposure to a novel object (NOV) for enrichment induced a salivary cortisol response indicative of activation of the hypothalamic-pituitary-adrenal (HPA) axis and which factors determine individual variation in this regard in captive African elephants. We repeatedly sampled the saliva of ten animals (three zoos) for the analysis of cortisol (SACort) before and up to 60 min (in 10-15 min intervals) after the onset of PRT (three repeats) or NOV (nine repeats), which lasted 10 min. There was considerable individual variation in SACort in response to PRT or NOV. Using mixed models, we were able to control these and to reveal that PRT was associated with high SACort before and relatively low SACort after PRT, while NOV induced a moderate SACort increase. The individual differences in SACort were related to age and sex (NOV), while the effects of zoo, handling method (free vs. protected contact) and reproductive and social status were variable. We conclude that positive affective states, such as anticipation or arousal, should be taken into account when interpreting the differences in the SACort responses between PRT and NOV. In addition, understanding the individuality of stress will support management decisions aimed at promoting captive elephant welfare.

Biological and environmental factors as sources of variation in nocturnal behavior of giraffe.

Upon a drastic decline of the giraffe population in the wild, conservation efforts and therefore the role of zoos have become more important than ever. With their unique opportunities, zoos provide excellent conditions to study animal behavior, expanding the knowledge about the giraffe's behavior repertoire and their ability to adapt. This study therefore examined the nocturnal behavior of 63 giraffe living in 13 different EAZA zoos across Germany and the Netherlands. Giraffe were observed and videos recorded via infrared sensitive cameras during the winter seasons 2015-2018. The observation period spanned nightly from 17:00 to 7:00. Thus, 198 nights, with a total of 2772 h were recorded and analyzed. Linear mixed models were then used to assess potential biological and environmental factors influencing behavior during the dark phase. Results show that individual variables such as age, subspecies and motherhood determined nocturnal activity and sleep behavior most. Among the variables studied, husbandry conditions and environmental factors complying with EAZA standards had no influence on the giraffe's nocturnal behavior. By combining nocturnal activity analyses and an assessment of potential influencing factors, our findings present a holistic approach to a better understanding of captive giraffe behavior and allow for management implications.

A semiparametric approach for item response function estimation to detect item misfit.

When scaling data using item response theory, valid statements based on the measurement model are only permissible if the model fits the data. Most item fit statistics used to assess the fit between observed item responses and the item responses predicted by the measurement model show significant weaknesses, such as the dependence of fit statistics on sample size and number of items. In order to assess the size of misfit and to thus use the fit statistic as an effect size, dependencies on properties of the data set are undesirable. The present study describes a new approach and empirically tests it for consistency. We developed an estimator of the distance between the predicted item response functions (IRFs) and the true IRFs by semiparametric adaptation of IRFs. For the semiparametric adaptation, the approach of extended basis functions due to Ramsay and Silverman (2005) is used. The IRF is defined as the sum of a linear term and a more flexible term constructed via basis function expansions. The group lasso method is applied as a regularization of the flexible term, and determines whether all parameters of the basis functions are fixed at zero or freely estimated. Thus, the method serves as a selection criterion for items that should be adjusted semiparametrically. The distance between the predicted and semiparametrically adjusted IRF of misfitting items can then be determined by describing the fitting items by the parametric form of the IRF and the misfitting items by the semiparametric approach. In a simulation study, we demonstrated that the proposed method delivers satisfactory results in large samples (i.e., N ≥ 1,000).

Deciding between the Covariance Analytical Approach and the Change-Score Approach in Two Wave Panel Data.

The manuscript focuses on effects in nonrandomized studies with two outcome measurement occasions and one explanatory variable, and in which groups already differ at the pretest. Such study designs are often encountered in educational and instructional research. Two prominent approaches to estimate effects are (1) covariance analytical approaches and (2) latent change-score models. In current practice, both approaches are applied interchangeably, without a clear rationale for when to use which approach. The aim of this contribution is to outline under which conditions the approaches produce unbiased estimates of the instruction effect. We present a theoretical data generating model in which we decompose the variances of the relevant variables, and examine under which data generating conditions the estimated instruction effect is unbiased. We show that, under specific assumptions, both methods can be used to answer the general question of whether instruction has an effect. Another implication from the results is that practitioners need to consider which underlying data generating assumptions the approaches make, since a violation of those assumptions will lead to biased effects. Based on our results, we give recommendations for preferable research designs.

Comparing Attitudes Across Groups: An IRT-Based Item-Fit Statistic for the Analysis of Measurement Invariance.

Questionnaires for the assessment of attitudes and other psychological traits are crucial in educational and psychological research, and item response theory (IRT) has become a viable tool for scaling such data. Many international large-scale assessments aim at comparing these constructs across countries, and the invariance of measures across countries is thus required. In its most recent cycle, the Programme for International Student Assessment (PISA 2015) implemented an innovative approach for testing the invariance of IRT-scaled constructs in the context questionnaires administered to students, parents, school principals, and teachers. On the basis of a concurrent calibration with equal item parameters across all groups (i.e., languages within countries), a group-specific item-fit statistic (root mean square deviance [RMSD]) was used as a measure for the invariance of item parameters for individual groups. The present simulation study examines the statistic's distribution under different types and extents of (non)invariance in polytomous items. Responses to five 4-point Likert-type items were generated under the generalized partial credit model (GPCM) for 1,000 simulees in 50 groups each. For one of the five items, either location or discrimination parameters were drawn from a normal distribution. In addition to the type of noninvariance, the extent of noninvariance was varied by manipulating the variation of these distributions. The results indicate that the RMSD statistic is better at detecting noninvariance related to between-group differences in item location than in item discrimination. The study's findings may be used as a starting point to sensitivity analysis aiming to define cutoff values for determining (non)invariance.

Classes of depression symptom trajectories in patients with major depression receiving a collaborative care intervention.

PURPOSE: Collaborative care is effective in improving symptoms of patients with depression. The aims of this study were to characterize symptom trajectories in patients with major depression during one year of collaborative care and to explore associations between baseline characteristics and symptom trajectories. METHODS: We conducted a cluster-randomized controlled trial in primary care. The collaborative care intervention comprised case management and behavioral activation. We used the Patient Health Questionnaire-9 (PHQ-9) to assess symptom severity as the primary outcome. Statistical analyses comprised latent growth mixture modeling and a hierarchical binary logistic regression model. RESULTS: We included 74 practices and 626 patients (310 intervention and 316 control recipients) at baseline. Based on a minimum of 12 measurement points for each intervention recipient, we identified two latent trajectories, which we labeled 'fast improvers' (60.5%) and 'slow improvers' (39.5%). At all measurements after baseline, 'fast improvers' presented higher PHQ mean values than 'slow improvers'. At baseline, 'fast improvers' presented fewer physical conditions, higher health-related quality of life, and had made fewer suicide attempts in their history. CONCLUSIONS: A notable proportion of 39.5% of patients improved only 'slowly' and probably needed more intense treatment. The third follow-up in month two could well be a sensible time to adjust treatment to support 'slow improvers'.

Practical Significance of Item Misfit in Educational Assessments.

Testing item fit is an important step when calibrating and analyzing item response theory (IRT)-based tests, as model fit is a necessary prerequisite for drawing valid inferences from estimated parameters. In the literature, numerous item fit statistics exist, sometimes resulting in contradictory conclusions regarding which items should be excluded from the test. Recently, researchers argue to shift the focus from statistical item fit analyses to evaluating practical consequences of item misfit. This article introduces a method to quantify potential bias of relationship estimates (e.g., correlation coefficients) due to misfitting items. The potential deviation informs about whether item misfit is practically significant for outcomes of substantial analyses. The method is demonstrated using data from an educational test.

Validation and reliability of a guideline appraisal mini-checklist for daily practice use.

BACKGROUND: The use of comprehensive instruments for guideline appraisal is time-consuming and requires highly qualified personnel. Since practicing physicians are generally busy, the rapid-assessment Mini-Checklist (MiChe) tool was developed to help them evaluate the quality and utility of guidelines quickly. The aim of this study was to validate the MiChe in comparison to the AGREE II instrument and to determine its reliability as a tool for guideline appraisal. METHODS: Ten guidelines that are relevant to general practice and had been evaluated by 2 independent reviewers using AGREE II were assessed by 12 GPs using the MiChe. The strength of the correlation between average MiChe ratings and AGREE II total scores was estimated using Pearson's correlation coefficient. Inter-rater reliability for MiChe overall quality ratings and endorsements was determined using intra-class correlations (ICC) and Kendall's W for ordinal recommendations. To determine the GPs' satisfaction with the MiChe, mean scores for the ratings on five questions were computed using a six-point Likert scale. RESULTS: The study showed a high level of agreement between MiChe and AGREE II in the quality rating of guidelines (Pearson's r = 0.872; P < 0.001). Inter-rater-reliability for overall MiChe ratings (ICC = 0.755; P < 0.001) and endorsements (Kendall's W = 0.73; P < 0.001) were high. The mean time required for guideline assessment was less than 15 min und user satisfaction was generally high. CONCLUSIONS: The MiChe performed well in comparison to AGREE II and is suitable for the rapid evaluation of guideline quality and utility in practice. TRIAL REGISTRATION: German Clinical Trials Register: DRKS00007480.

Emotional competencies in geriatric nursing: empirical evidence from a computer based large scale assessment calibration study.

The care of older people was described as involving substantial emotion-related affordances. Scholars in vocational training and nursing disagree whether emotion-related skills could be conceptualized and assessed as a professional competence. Studies on emotion work and empathy regularly neglect the multidimensionality of these phenomena and their relation to the care process, and are rarely conclusive with respect to nursing behavior in practice. To test the status of emotion-related skills as a facet of client-directed geriatric nursing competence, 402 final-year nursing students from 24 German schools responded to a 62-item computer-based test. 14 items were developed to represent emotion-related affordances. Multi-dimensional IRT modeling was employed to assess a potential subdomain structure. Emotion-related test items did not form a separate subdomain, and were found to be discriminating across the whole competence continuum. Tasks concerning emotion work and empathy are reliable indicators for various levels of client-directed nursing competence. Claims for a distinct emotion-related competence in geriatric nursing, however, appear excessive with a process-oriented perspective.

Factor structure and measurement invariance of the Patient Health Questionnaire-9 for female and male primary care patients with major depression in Germany.

BACKGROUND: Depression is characterized by gender-specific distinctions, with women being affected more often than men. The Patient Health Questionnaire-9 (PHQ-9) is frequently used to assess depression in primary healthcare. Previous research has yielded heterogeneous findings on the factor structure, and little is known of its measurement invariance across gender. The aim of this study was 1) to evaluate the fit of four previously hypothesized models of PHQ-9 factor structure in patients with major depression in German family practices, and 2) to test the measurement invariance of the best-fitting model across gender. METHODS: We used the baseline data from a cluster-randomized controlled trial. The diagnosis of major depression was based on the PHQ-9 and confirmed by the family physician. We calculated Confirmatory Factor Analyses (CFA) to assess which of the previously hypothesized factor structures (a one- and three different two-factor solutions) would best fit our data. We also calculated Complex Survey Analyses (CSA) and Multi Sample Analyses (MSA). RESULTS: We included 626 participants (75.4% women and 24.6% men). A two-factor model with five 'somatic' labeled items and four 'non-somatic' labeled items presented the best fit indices. The model measurement was invariant across gender. LIMITATIONS: The inclusion criteria used in the main trial mean the study sample was not representative of all patients with major depression in German family practices. CONCLUSIONS: The measurement invariance across gender revealed by this study is a precondition for the use of the PHQ-9 without gender-specific adaptation in patients with major depression in German family practices.

A Confirmatory Analysis of Item Reliability Trends (CAIRT): Differentiating True Score and Error Variance in the Analysis of Item Context Effects.

Numerous studies have shown increasing item reliabilities as an effect of the item position in personality scales. Traditionally, these context effects are analyzed based on item-total correlations. This approach neglects that trends in item reliabilities can be caused either by an increase in true score variance or by a decrease in error variance. This article presents the Confirmatory Analysis of Item Reliability Trends (CAIRT) that allows estimating both trends separately within a structural equation modeling framework. Results of a simulation study prove the CAIRT method to provide reliable and independent parameter estimates; the power exceeds the analysis of item-total correlations. We present an empirical application to self- and peer ratings collected in an Internet-based experiment. Results show that reliability trends are caused by increasing true score variance in self-ratings and by decreasing error variance in peer ratings.