Towards greater transparency in neurodevelopmental disorders research: use of a proposed workflow and propensity scores to facilitate selection of matched groups

Background Matching is one commonly utilized method in quasi-experimental designs involving individuals with neurodevelopmental disorders (NDD). This method ensures two or more groups (e.g., individuals with an NDD versus neurotypical individuals) are balanced on pre-existing covariates (e.g., IQ), enabling researchers to interpret performance on outcome measures as being attributed to group membership. While much attention has been paid to the statistical criteria of how to assess whether groups are well-matched, relatively little attention has been given to a crucial prior step: the selection of the individuals that are included in matched groups. The selection of individuals is often an undocumented process, which can invite unintentional, arbitrary, and biased decision-making. Limited documentation can result in findings that have limited reproducibility and replicability and thereby have poor potential for generalization to the broader population. Especially given the heterogeneity of individuals with NDDs, interpretation of research findings depends on minimizing bias at all stages of data collection and analysis. Results In the spirit of open science, this tutorial demonstrates how a workflow can be used to provide a transparent, reproducible, and replicable process to select individuals for matched groups. Our workflow includes the following key steps: Assess data, Select covariates, Conduct matching, and Diagnose matching. Our sample dataset is from children with autism spectrum disorder (ASD; n = 25) and typically developing children (n = 43) but can be adapted to comparisons of any two groups in quasi-experimental designs. We work through this method to conduct and document matching using propensity scores implemented with the R package MatchIt. Data and code are publicly available, and a template for this workflow is provided in the Additional file 1 as well as on a public repository. Conclusions It is important to provide clear documentation regarding the selection process to establish matched groups. This documentation ensures better transparency in participant selection and data analysis in NDD research. We hope the adoption of such a workflow will ultimately advance our ability to replicate findings and help improve the lives of individuals with NDDs

Spanish-speaking caregivers’ use of referential labels with toddlers is a better predictor of later vocabulary than their use of referential gestures

Variation in how frequently caregivers engage with their children is associated with variation in children’s later language outcomes. One explanation for this link is that caregivers use both verbal behaviors, such as labels, and non-verbal behaviors, such as gestures, to help children establish reference to objects or events in the world. However, few studies have directly explored whether language outcomes are more strongly associated with referential behaviors that are expressed verbally, such as labels, or non-verbally, such as gestures, or whether both are equally predictive. Here, we observed caregivers from 42 Spanish-speaking families in the US engage with their 18-month-old children during 5-min lab-based, play sessions. Children’s language processing speed and vocabulary size were assessed when children were 25 months. Bayesian model comparisons assessed the extent to which the frequencies of caregivers’ referential labels, referential gestures, or labels and gestures together, were more strongly associated with children’s language outcomes than their total numbers of words, or overall talkativeness. The best-fitting models showed that children who heard more referential labels at 18 months were faster in language processing and had larger vocabularies at 25 months. Models including gestures, or labels and gestures together, showed weaker fits to the data. Caregivers’ total words predicted children’s language processing speed, but predicted vocabulary size less well. These results suggest that the frequency with which caregivers of 18-month-old children use referential labels, more so than referential gestures, is a critical feature of caregiver verbal engagement that contributes to language processing development and vocabulary growth

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Multiorgan MRI findings after hospitalisation with COVID-19 in the UK (C-MORE): a prospective, multicentre, observational cohort study

Introduction: The multiorgan impact of moderate to severe coronavirus infections in the post-acute phase is still poorly understood. We aimed to evaluate the excess burden of multiorgan abnormalities after hospitalisation with COVID-19, evaluate their determinants, and explore associations with patient-related outcome measures. Methods: In a prospective, UK-wide, multicentre MRI follow-up study (C-MORE), adults (aged ≥18 years) discharged from hospital following COVID-19 who were included in Tier 2 of the Post-hospitalisation COVID-19 study (PHOSP-COVID) and contemporary controls with no evidence of previous COVID-19 (SARS-CoV-2 nucleocapsid antibody negative) underwent multiorgan MRI (lungs, heart, brain, liver, and kidneys) with quantitative and qualitative assessment of images and clinical adjudication when relevant. Individuals with end-stage renal failure or contraindications to MRI were excluded. Participants also underwent detailed recording of symptoms, and physiological and biochemical tests. The primary outcome was the excess burden of multiorgan abnormalities (two or more organs) relative to controls, with further adjustments for potential confounders. The C-MORE study is ongoing and is registered with ClinicalTrials.gov, NCT04510025. Findings: Of 2710 participants in Tier 2 of PHOSP-COVID, 531 were recruited across 13 UK-wide C-MORE sites. After exclusions, 259 C-MORE patients (mean age 57 years [SD 12]; 158 [61%] male and 101 [39%] female) who were discharged from hospital with PCR-confirmed or clinically diagnosed COVID-19 between March 1, 2020, and Nov 1, 2021, and 52 non-COVID-19 controls from the community (mean age 49 years [SD 14]; 30 [58%] male and 22 [42%] female) were included in the analysis. Patients were assessed at a median of 5·0 months (IQR 4·2–6·3) after hospital discharge. Compared with non-COVID-19 controls, patients were older, living with more obesity, and had more comorbidities. Multiorgan abnormalities on MRI were more frequent in patients than in controls (157 [61%] of 259 vs 14 [27%] of 52; p<0·0001) and independently associated with COVID-19 status (odds ratio [OR] 2·9 [95% CI 1·5–5·8]; padjusted=0·0023) after adjusting for relevant confounders. Compared with controls, patients were more likely to have MRI evidence of lung abnormalities (p=0·0001; parenchymal abnormalities), brain abnormalities (p<0·0001; more white matter hyperintensities and regional brain volume reduction), and kidney abnormalities (p=0·014; lower medullary T1 and loss of corticomedullary differentiation), whereas cardiac and liver MRI abnormalities were similar between patients and controls. Patients with multiorgan abnormalities were older (difference in mean age 7 years [95% CI 4–10]; mean age of 59·8 years [SD 11·7] with multiorgan abnormalities vs mean age of 52·8 years [11·9] without multiorgan abnormalities; p<0·0001), more likely to have three or more comorbidities (OR 2·47 [1·32–4·82]; padjusted=0·0059), and more likely to have a more severe acute infection (acute CRP >5mg/L, OR 3·55 [1·23–11·88]; padjusted=0·025) than those without multiorgan abnormalities. Presence of lung MRI abnormalities was associated with a two-fold higher risk of chest tightness, and multiorgan MRI abnormalities were associated with severe and very severe persistent physical and mental health impairment (PHOSP-COVID symptom clusters) after hospitalisation. Interpretation: After hospitalisation for COVID-19, people are at risk of multiorgan abnormalities in the medium term. Our findings emphasise the need for proactive multidisciplinary care pathways, with the potential for imaging to guide surveillance frequency and therapeutic stratification

Workflow to Achieve Matched Groups

A workflow that can serve as a guide when trying to achieve matched groups

Evaluating the feasibility of an automated classifier for target-child-directed speech from LENA recordings

Recent advances in recording technology provide unique opportunities to observe children’s everyday speech environments using daylong audio recordings. A number of studies have proposed that speech may support learning differently when speech is directed to a child (target child directed speech, tCDS) than when that speech is directed to others (ODS) (Shneidman & Goldin-Meadow, 2012; Weisleder & Fernald, 2013). To identify periods of tCDS and ODS, researchers typically rely on the time-consuming and laborious work of human listeners who consider numerous features when making judgments. Human listeners are also used to identify periods when children are sleeping or awake. In this paper, we detail our efforts to automate these processes. We analyzed over 1,000 hours of audio from daylong recordings of 153 English- and Spanish-speaking families in the U.S. with 17- to 28-month-old children that had been previously coded for periods of sleep, tCDS, and ODS. We first explored patterns of features that characterized periods of tCDS and ODS. Then, we evaluated two classifiers that were trained using automated measures generated from LENATM, including frequency (AWC, CTC, CVC) and duration (meaningful speech, distant speech, TV, noise, silence) measures. Results revealed high sensitivity and specificity in classifying periods of sleep, and moderate sensitivity and specificity in classifying periods of tCDS and ODS. Model-derived predictions from our tCDS/ODS classifier yielded similar patterns of correlations as previously-published findings, with variation in tCDS, but not ODS, positively linked to children’s later vocabularies (Weisleder & Fernald, 2013). This work offers promising tools for streamlining work with daylong recordings, thereby facilitating research that aims to better understand how children learn from their everyday speech environments

Spanish-speaking caregivers’ use of referential labels with toddlers is a better predictor of later vocabulary than their use of referential gestures

Variation in how frequently caregivers engage with their children is associated with variation in children’s later language outcomes. One explanation for this link is that caregivers use both verbal behaviors, such as labels, and non-verbal behaviors, such as gestures, to help children establish reference to objects or events in the world. However, few studies have directly explored whether language outcomes are more strongly associated with referential behaviors that are expressed verbally, such as labels, or non-verbally, such as gestures, or whether both are equally predictive. Here, we observed caregivers from 42 Spanish-speaking families in the US engage with their 18-month-old children during 5-min lab-based, play sessions. Children’s language processing speed and vocabulary size were assessed when children were 25 months. Bayesian model comparisons assessed the extent to which the frequencies of caregivers’ referential labels, referential gestures, or labels and gestures together, were more strongly associated with children’s language outcomes than their total numbers of words, or overall talkativeness. The best-fitting models showed that children who heard more referential labels at 18 months were faster in language processing and had larger vocabularies at 25 months. Models including gestures, or labels and gestures together, showed weaker fits to the data. Caregivers’ total words predicted children’s language processing speed, but predicted vocabulary size less well. These results suggest that the frequency with which caregivers of 18-month-old children use referential labels, more so than referential gestures, is a critical feature of caregiver verbal engagement that contributes to language processing development and vocabulary growth