Can Sport Concussion Assessment Tool (SCAT) Symptom Scores Be Converted to Rivermead Post-concussion Symptoms Questionnaire (RPQ) Scores and Vice Versa? Findings From the Toronto Concussion Study

Background: The Rivermead Post-Concussion Symptoms Questionnaire (RPQ) and the Sports Concussion Assessment Tool (SCAT) are widely used self-report tools assessing the type, number, and severity of concussion symptoms. There are overlapping symptoms and domains, though they are scored differently. The SCAT consists of 22 questions with a 7-point Likert scale for a total possible score 132. The RPQ has 16 questions and a 5-point Likert scale for a total of 80 possible points. Being able to convert between the two scores would facilitate comparison of results in the concussion literature.Objectives: To develop equations to convert scores on the SCAT to the RPQ and vice versa.Methods: Adults (17–85 years) diagnosed with a concussion at a referring emergency department were seen in the Hull-Ellis Concussion and Research Clinic, a rapid access concussion clinic at Toronto Rehab–University Health Network (UHN) Toronto Canada, within 7 days of injury. The RPQ and SCAT symptom checklists as well as demographic questionnaires were administered to all participants at Weeks 1, 2, 3, 4, 5, 6, 7, 8, 12, 16.Results: 215 participants had 1,168 matched RPQ and SCAT assessments. Total scores of the RPQ and the SCAT had a rho = 0.91 (p < 0.001); correlations were lower for sub-scores of specific symptom domains (range 0.74–0.87, p < 0.001 for all domain comparisons). An equation was derived to calculate SCAT scores using the number and severity of symptoms on the RPQ. Estimated scores were within 3 points of the observed total score on the SCAT. A second equation was derived to calculate the RPQ from the proportion weighted total score of the SCAT. This equation estimated corresponding scores within 3 points of the observed score on the RPQ.Conclusions: The RPQ and SCAT symptom checklists total scores are highly correlated and can be used to estimate the total score on the corresponding assessment. The symptom subdomains are also strongly correlated between the 2 scales however not as strongly correlated as the total score. The equations will enable researchers and clinicians to quickly convert between the scales and to directly compare concussion research findings.

Multidimensional Data Integration Identifies Tumor Necrosis Factor Activation in Nephrotic Syndrome: A Model for Precision Nephrology

Background: Classification of nephrotic syndrome relies on clinical presentation and descriptive patterns of injury on kidney biopsies. This approach does not reflect underlying disease biology, limiting the ability to predict progression or treatment response. Methods: Systems biology approaches were used to categorize patients with minimal change disease (MCD) and focal segmental glomerulosclerosis (FSGS) based on kidney biopsy tissue transcriptomics across three cohorts and assessed association with clinical outcomes. Patient- level tissue pathway activation scores were generated using differential gene expression. Then, functional enrichment and non-invasive urine biomarker candidates were identified. Biomarkers were validated in kidney organoid models and single nucleus RNA-seq (snRNAseq) from kidney biopsies. Results: Transcriptome-based categorization identified three subgroups of patients with shared molecular signatures across independent North American, European and African cohorts. One subgroup demonstrated worse longterm outcomes (HR 5.2, p = 0.001) which persisted after adjusting for diagnosis and clinical measures (HR 3.8, p = 0.035) at time of biopsy. The molecular profile of this subgroup was largely (48%) driven by tissue necrosis factor (TNF) activation and could be predicted based on levels of TNF pathway urinary biomarkers TIMP-1 and MCP-1 and clinical features (correlation 0.63, p <0.001 for predicted vs observed score). Kidney organoids confirmed TNF-dependent increase in transcript and protein levels of these markers in kidney cells, as did snRNAseq from NEPTUNE biopsy samples. Conclusions: Molecular profiling identified a patient subgroup within nephrotic syndrome with poor outcome and kidney TNF pathway activation. Clinical trials using non-invasive biomarkers of pathway activation to target therapies are currently being evaluated.

Reading Comprehension Tests for Children: Test Equating and Specific Age-Interval Reports

Equating is used to directly compare alternate forms of tests. We describe the equating of two alternative forms of a reading comprehension test for Brazilian children (2nd to 5th grade), Form A (n = 427) and Form B (n = 321). We employed non-equivalent random groups design with internal anchor items. Local independence was attested via standardized residual Pearson's bivariate correlation. First, from 176 items, we selected 42 in each form (33 unique and 9 in common) using 2PL model, a one-dimensional item response theory (IRT) model. Using the equateIRT package for R, the anchor items were used to link both forms. Linking coefficients were estimated under two different methods (Haebara and Stocking–Lord), resulting in scores equating by two methods: observed score equating (OSE) and true score equating (TSE). We provided reference-specific age-intervals for the sample. The final version was informative for a wide range of theta abilities. We concluded that the forms could be used interchangeably.

Lord–Wingersky Algorithm Version 2.5 with Applications

Item response theory scoring based on summed scores is employed frequently in the practice of educational and psychological measurement. Lord and Wingersky (Appl Psychol Meas 8(4):453–461, 1984) proposed a recursive algorithm to compute the summed score likelihood. Cai (Psychometrika 80(2):535–559, 2015) extended the original Lord–Wingersky algorithm to the case of two-tier multidimensional item factor models and called it Lord–Wingersky algorithm Version 2.0. The 2.0 algorithm utilizes dimension reduction to efficiently compute summed score likelihoods associated with the general dimensions in the model. The output of the algorithm is useful for various purposes, for example, scoring, scale alignment, and model fit checking. In the research reported here, a further extension to the Lord–Wingersky algorithm 2.0 is proposed. The new algorithm, which we call Lord–Wingersky algorithm Version 2.5, yields the summed score likelihoods for all latent variables in the model conditional on observed score combinations. The proposed algorithm is illustrated with empirical data for three potential application areas: (a) describing achievement growth using score combinations across adjacent grades, (b) identification of noteworthy subscores for reporting, and (c) detection of aberrant responses.

Assessment of Item and Test parameters: Cosine Similarity Approach

The paper proposes new measures of difficulty and discriminating values of binary items and test consisting of such items and find their relationships including estimation of test error variance and thereby the test reliability, as per definition using cosine similarities. The measures use entire data. Difficulty value of test and item is defined as function of cosine of the angle between the observed score vector and the maximum possible score vector. Discriminating value of test and an item are taken as coefficient of variation (CV) of test score and item score respectively. Each ranges between 0 and 1 like difficulty value of test and an item. With increase in number of correct answer to an item, item difficulty curve increases and item discriminating curve decreases. The point of intersection of the two curves can be used for item deletion along with other criteria. Cronbach alpha was expressed and computed in terms of discriminating value of test and item. Relationship derived between test discriminating value and test reliability as per theoretical definition. Empirical verifications of proposed measures were undertaken. Future studies suggested.re to enter text.