Comparing the Functional Independence Measure and the interRAI/MDS for use in the functional assessment of older adults: a review of the literature

<p>Abstract</p> <p>Background</p> <p>The rehabilitation of older persons is often complicated by increased frailty and medical complexity - these in turn present challenges for the development of health information systems. Objective investigation and comparison of the effectiveness of geriatric rehabilitation services requires information systems that are comprehensive, reliable, valid, and sensitive to clinically relevant changes in older persons. The Functional Independence Measure is widely used in rehabilitation settings - in Canada this is used as the central component of the National Rehabilitation Reporting System of the Canadian Institute of Health Information. An alternative system has been developed by the interRAI consortium. We conducted a literature review to compare the development and measurement properties of these two systems.</p> <p>Methods</p> <p>English language literature published between 1983 (initial development of the FIM) and 2008 was searched using Medline and CINAHL databases, and the reference lists of retrieved articles. Relevant articles were summarized and charted using the criteria proposed by Streiner. Additionally, attention was paid to the ability of the two systems to address issues particularly relevant to older rehabilitation clients, such as medical complexity, comorbidity, and responsiveness to small but clinically meaningful improvements.</p> <p>Results</p> <p>In total, 66 articles were found that met the inclusion criteria. The majority of FIM articles studied inpatient rehabilitation settings; while the majority of interRAI/MDS articles focused on nursing home settings. There is evidence supporting the reliability of both instruments. There were few articles that investigated the construct validity of the interRAI/MDS.</p> <p>Conclusion</p> <p><b>A</b>dditional psychometric research is needed on both the FIM and MDS, especially with regard to their use in different settings and with different client groups.</p

Genetic Drivers of Heterogeneity in Type 2 Diabetes Pathophysiology

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P \u3c 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care

Genetic drivers of heterogeneity in type 2 diabetes pathophysiology

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P &lt; 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.</p

Global assessment of migraine severity measure: preliminary evidence of construct validity

Abstract Background In persons with migraine, severity of migraine is an important determinant of several health outcomes (e.g., patient quality of life and health care resource utilization). This study investigated how migraine patients rate the severity of their disease and how these ratings correlate with their socio-demographic, clinical, and psycho-social characteristics. Methods This is a cohort of 263 adult migraine patients consecutively enrolled in the Neurological Disease and Depression Study (NEEDs). We obtained a broad range of clinical and patient-reported measures (e.g., patients’ ratings of migraine severity using the Global Assessment of Migraine Severity (GAMS), and migraine-related disability, as measured by the Migraine Disability Scale (MIDAS)). Depression was measured using the 9-item Patient Health Questionnaire (PHQ-9) and the 14-item Hospital Anxiety and Depression Scale (HADS). Median regression analysis was used to examine the predictors of patient ratings of migraine severity. Results The mean age for the patients was 42.5 years (SD = 13.2). While 209 (79.4%) patients were females, 177 (67.4%) participants reported “moderately severe” to “extremely severe” migraine on the GAMS, and 100 (31.6%) patients had chronic migraine. Patients’ report of severity on the GAMS was strongly correlated with patients’ ratings of MIDAS global severity question, overall MIDAS score, migraine type, PHQ-9 score, and frequency of migraine attacks. Mediation analyses revealed that MIDAS mediated the effect of depression on patient ratings of migraine severity, accounting for about 32% of the total effect of depression. Overall, migraine subtype, frequency of migraine, employment status, depression, and migraine-related disability were statistically significant predictors of patient-ratings of migraine severity. Conclusions This study highlights the impact of clinical and psychosocial determinants of patient-ratings of migraine severity. GAMS is a brief and valid tool that can be used to assess migraine severity in busy clinical settings