Assessing pressure injury risk using a single mobility scale in hospitalised patients: a comparative study using case-control design.

Background: Pressure injury is known to cause not only debilitating physical effects, but also substantial psychological and financial burdens. A variety of pressure injury risk assessment tools are in use worldwide, which include a number of factors. Evidence now suggests that assessment of a single factor, mobility, may be a viable alternative for assessing pressure injury risk. Aims: The aim of this study was to ascertain whether using the Braden mobility subscale alone is comparable to the full Braden scale for predicting the development of pressure injury. Methods: This study, a retrospective case-control design, was conducted in a large tertiary acute care hospital in Singapore. Medical records of 100 patients with hospital-acquired pressure injury were matched with 100 medical records of patients who had no pressure injury at a 1:1 ratio. Results: Patients who were assessed using the Braden mobility subscale as having 'very limited mobility' or worse were 5.23 (95% confidence interval (CI) 2.66-10.20) times more likely to develop pressure injury compared with those assessed as having 'slightly limited' mobility or 'no limitation'. Conversely, patients assessed using the Braden scale as having 'low risk' or higher were 3.35 (95% CI 1.77-6.33) times more likely to develop pressure injury compared with those assessed as 'no risk'. Using full model logistic regression analysis, the Braden mobility subscale was the only factor that was a significant predictor of pressure injury and it remained significant when analysed for the most parsimonious model using backward logistic regression. Conclusions: These findings provide the empirical evidence that using the Braden mobility subscale alone as an assessment tool for predicting pressure injury development is comparable to using the full Braden scale. Use of this single factor would simplify pressure injury risk assessment and support its use within busy clinical settings

Understanding the common inter-rater reliability measures

Health and rehabilitation professionals use a range of outcome instruments to evaluate the effectiveness of their interventions. In order to be evidenced-based practitioners, we need to understand the psychometric properties of these instruments and to be able to interpret the statistics used to test their psychometric properties. This paper focuses on inter-rater reliability. Different statistical methods for computing inter-rater reliability can be classified into one of three categories: consensus estimates, consistency estimates, and measurement estimates. The common statistical methods such as Kappa, intraclass correlation and Many-Facets Rasch Model are described along with the advantages and disadvantages of each approach. For each category of estimates, one paper has been chosen from the therapy and rehabilitation literature to illustrate the use of a number of commonly utilised inter-rater reliability measures. It is hoped that this overview will provide practitioners, students and/or new researchers with a ready reference of key measurements used for determining inter-rater reliability

Evaluating the clinical validity of hypertrophic cardiomyopathy genes

Background: Genetic testing for families with hypertrophic cardiomyopathy (HCM) provides a significant opportunity to improve care. Recent trends to increase gene panel sizes often mean variants in genes with questionable association are reported to patients. Classification of HCM genes and variants is critical, as misclassification can lead to genetic misdiagnosis. We show the validity of previously reported HCM genes using an established method for evaluating gene-disease associations. Methods: A systematic approach was used to assess the validity of reported gene-disease associations, including associations with isolated HCM and syndromes including left ventricular hypertrophy. Genes were categorized as having definitive, strong, moderate, limited, or no evidence of disease causation. We also reviewed current variant classifications for HCM in ClinVar, a publicly available variant resource. Results: Fifty-seven genes were selected for curation based on their frequent inclusion in HCM testing and prior association reports. Of 33 HCM genes, only 8 (24%) were categorized as definitive (MYBPC3, MYH7, TNNT2, TNNI3, TPM1, ACTC1, MYL2, and MYL3); 3 had moderate evidence (CSRP3, TNNC1, and JPH2; 33%); and 22 (66%) had limited (n=16) or no evidence (n=6). There were 12 of 24 syndromic genes definitively associated with isolated left ventricular hypertrophy. Of 4191 HCM variants in ClinVar, 31% were in genes with limited or no evidence of disease association. Conclusions: The majority of genes previously reported as causative of HCM and commonly included in diagnostic tests have limited or no evidence of disease association. Systematically curated HCM genes are essential to guide appropriate reporting of variants and ensure the best possible outcomes for HCM families