The core minimum dataset for measuring pain outcomes in pain services across Scotland. Developing and testing a brief multi-dimensional questionnaire

BACKGROUND: There is currently no agreed minimum dataset to inform specialist chronic pain service provision. We aimed to develop a Core Minimum Dataset (CMD) for pain services in Scotland and perform preliminary analysis to evaluate its psychometric properties in adults with chronic pain. METHODS: The questionnaire was developed following a review of existing relevant data collection instruments and national consultation. The CMD questionnaire was completed alongside a routine pre-clinic questionnaire by patients attending two pain services over 3 months. Concurrent validity was tested by comparing scores between the CMD and pre-existing questionnaires. Reliability was assessed by test-retest and discriminative validity via receiver operating characteristic (ROC) curves. RESULTS: The final CMD questionnaire consisted of five questions on four domains: pain severity (Chronic Pain Grade [CPG] Q1); pain interference (CPG Q5); emotional impact (Patient Health Questionnaire-2 [PHQ-2], two questions); and quality of life (Short Form Health Survey-36 [SF-36] Q1). 530 patients completed the questionnaire. Strong correlation was found with the Hospital Anxiety and Depression Scale (r(s) = 0.753, p < 0.001). Moderate correlations were found with the Brief Pain Inventory for pain interference (r(s) = 0.585, p < 0.001) and pain severity (r(s) = 0.644, p < 0.001). Moderate to good reliability was demonstrated (Intra-class Correlation Coefficient = 0.572–0.845). All items indicated good discrimination for relevant health states. CONCLUSIONS: The findings represent initial steps towards developing an accurate questionnaire that is feasible for assessing chronic pain in adults attending specialist pain clinics and measuring service improvements in Scotland. Further validation testing, in clinical settings, is now required

A Genome-Wide Association Study Provides New Evidence That CACNA1C Gene is Associated With Diabetic Cataract

PURPOSE: Diabetic cataract is one of the major eye complications of diabetes. It was reported that cataract occurs two to five times more frequently in patients with diabetes compared with those with no diabetes. The purpose of this study was to identify genetic contributors of diabetic cataract based on a genome-wide association approach using a well-defined Scottish diabetic cohort. METHODS: We adapted linked e-health records to define diabetic cataract. A diabetic cataract case in this study was defined as a type 2 diabetic patient who has ever been recorded in the linked e-health records to have cataracts in both eyes or who had previous cataract extraction surgeries in at least one eye. A control in this study was defined as a type 2 diabetic individual who has never been diagnosed as cataract in the linked e-health records and had no history of cataract surgeries. A standard genome-wide association approach was applied. RESULTS: Overall, we have 2341 diabetic cataract cases and 2878 controls in the genetics of diabetes audit and research in Tayside Scotland (GoDARTS) dataset. We found that the P value of rs2283290 in the CACNA1C gene was 8.81 × 10(−10), which has reached genome-wide significance. We also identified that the blood calcium level was statistically different between diabetic cataract cases and controls. CONCLUSIONS: We identified supporting evidence that CACNA1C gene is associated with diabetic cataract. The role of calcium in the cataractogenesis needs to be reevaluated in future studies

The Genetics of Neuropathic Pain from Model Organisms to Clinical Application.

Neuropathic pain (NeuP) arises due to injury of the somatosensory nervous system and is both common and disabling, rendering an urgent need for non-addictive, effective new therapies. Given the high evolutionary conservation of pain, investigative approaches from Drosophila mutagenesis to human Mendelian genetics have aided our understanding of the maladaptive plasticity underlying NeuP. Successes include the identification of ion channel variants causing hyper-excitability and the importance of neuro-immune signaling. Recent developments encompass improved sensory phenotyping in animal models and patients, brain imaging, and electrophysiology-based pain biomarkers, the collection of large well-phenotyped population cohorts, neurons derived from patient stem cells, and high-precision CRISPR generated genetic editing. We will discuss how to harness these resources to understand the pathophysiological drivers of NeuP, define its relationship with comorbidities such as anxiety, depression, and sleep disorders, and explore how to apply these findings to the prediction, diagnosis, and treatment of NeuP in the clinic

The genetics of neuropathic pain from model organisms to clinical application

Neuropathic pain (NeuP) arises due to injury of the somatosensory nervous system and is both common and disabling, rendering an urgent need for non-addictive, effective new therapies. Given the high evolutionary conservation of pain, investigative approaches from Drosophila mutagenesis to human Mendelian genetics have aided our understanding of the maladaptive plasticity underlying NeuP. Successes include the identification of ion channel variants causing hyper-excitability and the importance of neuro-immune signaling. Recent developments encompass improved sensory phenotyping in animal models and patients, brain imaging, and electrophysiology-based pain biomarkers, the collection of large well-phenotyped population cohorts, neurons derived from patient stem cells, and high-precision CRISPR generated genetic editing. We will discuss how to harness these resources to understand the pathophysiological drivers of NeuP, define its relationship with comorbidities such as anxiety, depression, and sleep disorders, and explore how to apply these findings to the prediction, diagnosis, and treatment of NeuP in the clinic

The epidemiology of neuropathic pain : an analysis of prevalence and associated factors in UK Biobank

Acknowledgements Supported by Diabetes UK under grant agreement 19/0005984, the European Union’s Horizon 2020 research and innovation programme under grant agreement No 633491 (DOLORisk) and the MRC and Versus Arthritis funding to the PAINSTORM consortium as part of the Advanced Pain Discovery Platform (MR/W002388/1). No funding body had any role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript. A. C.Themistocleous is supported by Academy of Medical Sciences Starter Grant SGL022\1086 and is a Honorary Senior Research Fellow and Carnegie-Wits Diaspora Fellow at the Brain Function Research Group, School of Physiology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg. D. L. H. Bennett and G. Baskozos are supported by the Wellcome Trust, grant reference 223149/Z/21/Z. Ethics: Data for this study were obtained from the UK Biobank for project “Risk factors for chronic pain,” Application ID: 49572. UK Biobank has approval from the North West Multicentre Research Ethics Committee (MREC) as a Research Tissue Bank (RTB) approval, REC reference: 21/NW/0157, IRAS project ID: 299116. This approval means that researchers do not require separatePeer reviewedPublisher PD