Does a child’s language ability affect the correspondence between parent and teacher ratings of ADHD symptoms?

Background: Rating scales are often used to identify children with potential Attention-Deficit/Hyperactivity Disorder (ADHD), yet there are frequently discrepancies between informants which may be moderated by child characteristics. The current study asked whether correspondence between parent and teacher ratings on the Strengths and Weakness of ADHD symptoms and Normal behaviour scale (SWAN) varied systematically with child language ability. Method: Parent and teacher SWAN questionnaires were returned for 200 children (aged 61–81 months); 106 had low language ability (LL) and 94 had typically developing language (TL). After exploring informant correspondence (using Pearson correlation) and the discrepancy between raters, we report inter-class correlation coefficients, to assess inter-rater reliability, and Cohen’s kappa, to assess agreement regarding possible ADHD caseness. Results: Correlations between informant ratings on the SWAN were moderate. Children with LL were rated as having increased inattention and hyperactivity relative to children with TL; teachers, however, rated children with LL as having more inattention than parents. Inter-rater reliability of the SWAN was good and there were no systematic differences between the LL and TL groups. Case agreement between parent and teachers was fair; this varied by language group with poorer case agreement for children with LL. Conclusion: Children’s language abilities affect the discrepancy between informant ratings of ADHD symptomatology and the agreement between parents and teachers regarding potential ADHD caseness. The assessment of children’s core language ability would be a beneficial addition to the ADHD diagnostic process.</p

Sex Differences in Poststroke Cognitive Impairment: A Multicenter Study in 2343 Patients With Acute Ischemic Stroke

BACKGROUND: Poststroke cognitive impairment (PSCI) occurs in about half of stroke survivors. Cumulative evidence indicates that functional outcomes of stroke are worse in women than men. Yet it is unknown whether the occurrence and characteristics of PSCI differ between men and women. METHODS: Individual patient data from 9 cohorts of patients with ischemic stroke were harmonized and pooled through the Meta-VCI-Map consortium (n=2343, 38% women). We included patients with visible symptomatic infarcts on computed tomography/magnetic resonance imaging and cognitive assessment within 15 months after stroke. PSCI was defined as impairment in ≥1 cognitive domains on neuropsychological assessment. Logistic regression analyses were performed to compare men to women, adjusted for study cohort, to obtain odds ratios for PSCI and individual cognitive domains. We also explored sensitivity and specificity of cognitive screening tools for detecting PSCI, according to sex (Mini-Mental State Examination, 4 cohorts, n=1814; Montreal Cognitive Assessment, 3 cohorts, n=278). RESULTS: PSCI was found in 51% of both women and men. Men had a lower risk of impairment of attention and executive functioning (men: odds ratio, 0.76 [95% CI, 0.61-0.96]), and language (men: odds ratio, 0.67 [95% CI, 0.45-0.85]), but a higher risk of verbal memory impairment (men: odds ratio, 1.43 [95% CI, 1.17-1.75]). The sensitivity of Mini-Mental State Examination (<25) for PSCI was higher for women (0.53) than for men (0.27; P=0.02), with a lower specificity for women (0.80) than men (0.96; P=0.01). Sensitivity and specificity of Montreal Cognitive Assessment (<26.) for PSCI was comparable between women and men (0.91 versus 0.86; P=0.62 and 0.29 versus 0.28; P=0.86, respectively). CONCLUSIONS: Sex was not associated with PSCI occurrence but affected domains differed between men and women. The latter may explain why sensitivity of the Mini-Mental State Examination for detecting PSCI was higher in women with a lower specificity compared with men. These sex differences need to be considered when screening for and diagnosing PSCI in clinical practice

Network impact score is an independent predictor of post-stroke cognitive impairment: A multicenter cohort study in 2341 patients with acute ischemic stroke

BACKGROUND: Post-stroke cognitive impairment (PSCI) is a common consequence of stroke. Accurate prediction of PSCI risk is challenging. The recently developed network impact score, which integrates information on infarct location and size with brain network topology, may improve PSCI risk prediction. AIMS: To determine if the network impact score is an independent predictor of PSCI, and of cognitive recovery or decline. METHODS: We pooled data from patients with acute ischemic stroke from 12 cohorts through the Meta VCI Map consortium. PSCI was defined as impairment in ≥ 1 cognitive domain on neuropsychological examination, or abnormal Montreal Cognitive Assessment. Cognitive recovery was defined as conversion from PSCI 24 months) and cognitive recovery or decline using logistic regression. Models were adjusted for age, sex, education, prior stroke, infarct volume, and study site. RESULTS: We included 2341 patients with 4657 cognitive assessments. PSCI was present in 398/844 patients (47%) 24 months. Cognitive recovery occurred in 64/181 (35%) patients and cognitive decline in 26/287 (9%). The network impact score predicted PSCI in the univariable (OR 1.50, 95%CI 1.34-1.68) and multivariable (OR 1.27, 95%CI 1.10-1.46) GEE model, with similar ORs in the logistic regression models for specified post-stroke intervals. The network impact score was not associated with cognitive recovery or decline. CONCLUSIONS: The network impact score is an independent predictor of PSCI. As such, the network impact score may contribute to a more precise and individualized cognitive prognostication in patients with ischemic stroke. Future studies should address if multimodal prediction models, combining the network impact score with demographics, clinical characteristics and other advanced brain imaging biomarkers, will provide accurate individualized prediction of PSCI. A tool for calculating the network impact score is freely available at https://metavcimap.org/features/software-tools/lsm-viewer/

Logit tree models for discrete choice data with application to advice-seeking preferences among Chinese Christians

Logit models are popular tools for analyzing discrete choice and ranking data. The models assume that judges rate each item with a measurable utility, and the ordering of a judge’s utilities determines the outcome. Logit models have been proven to be powerful tools, but they become difficult to interpret if the models contain nonlinear and interaction terms. We extended the logit models by adding a decision tree structure to overcome this difficulty. We introduced a new method of tree splitting variable selection that distinguishes the nonlinear and linear effects, and the variable with the strongest nonlinear effect will be selected in the view that linear effect is best modeled using the logit model. Decision trees built in this fashion were shown to have smaller sizes than those using loglikelihood-based splitting criteria. In addition, the proposed splitting methods could save computational time and avoid bias in choosing the optimal splitting variable. Issues on variable selection in logit models are also investigated, and forward selection criterion was shown to work well with logit tree models. Focused on ranking data, simulations are carried out and the results showed that our proposed splitting methods are unbiased. Finally, to demonstrate the feasibility of the logit tree models, they were applied to analyze two datasets, one with binary outcome and the other with ranking outcome.School of Nursin

Attempted suicide and violent criminality among Danish second-generation immigrants according to parental place of origin

BACKGROUND: Immigrant populations in Western European countries have grown in their size and diversity, but little is known about risks of self-directed and externalised violence among second generation immigrants. AIMS: To compare risks for attempted suicides and violent offending among second generation immigrants to Denmark according to parental region of origin versus the native Danish population. METHODS: Data from interlinked national Danish registers were used (N=1,973,614). Parental origin outside Denmark was categorised thus: Asia, Africa, Middle East, Greenland, other Scandinavian countries, elsewhere in Europe, and all other regions. We estimated gender-specific cumulative incidence and incidence rate ratios (IRRs) versus native Danes. RESULTS: In virtually all subgroups of second generation immigrants, risk was elevated for the two adverse outcomes in both genders. Females generally had greater elevations in attempted suicide risk, and males had greater elevations in violent offending risk. For attempted suicide, especially large IRRs were observed for males and females whose parents emigrated from Greenland; for violent offending, risks were particularly raised for males and females of Middle Eastern, Greenlandic and African origin. Adjustment for socioeconomic status partially explained these associations. CONCLUSIONS: Western European nations should develop preventive programmes tailored toward specific second generation immigrant populations, with integrated approaches jointly tackling suicidality and violence