The Human Gene Mutation Database (HGMD®): optimizing its use in a clinical diagnostic or research setting.

The Human Gene Mutation Database (HGMD®) constitutes a comprehensive collection of published germline mutations in nuclear genes that are thought to underlie, or are closely associated with human inherited disease. At the time of writing (June 2020), the database contains in excess of 289,000 different gene lesions identified in over 11,100 genes manually curated from 72,987 articles published in over 3100 peer-reviewed journals. There are primarily two main groups of users who utilise HGMD on a regular basis; research scientists and clinical diagnosticians. This review aims to highlight how to make the most out of HGMD data in each setting.

The Human Gene Mutation Database: towards a comprehensive repository of inherited mutation data for medical research, genetic diagnosis and next-generation sequencing studies.

The Human Gene Mutation Database (HGMD®) constitutes a comprehensive collection of published germline mutations in nuclear genes that underlie, or are closely associated with human inherited disease. At the time of writing (March 2017), the database contained in excess of 203,000 different gene lesions identified in over 8000 genes manually curated from over 2600 journals. With new mutation entries currently accumulating at a rate exceeding 17,000 per annum, HGMD represents de facto the central unified gene/disease-oriented repository of heritable mutations causing human genetic disease used worldwide by researchers, clinicians, diagnostic laboratories and genetic counsellors, and is an essential tool for the annotation of next-generation sequencing data. The public version of HGMD ( http://www.hgmd.org ) is freely available to registered users from academic institutions and non-profit organisations whilst the subscription version (HGMD Professional) is available to academic, clinical and commercial users under license via QIAGEN Inc.

An investigation into the activities of the clinical nurse specialist.

AIM: To assess the activities of clinical nurse specialists (CNSs), examining work patterns, job plans and team structures, especially the balance of patient-facing and non-patient-facing activity. METHOD: A quantitative evaluation was conducted using diary cards at Imperial College Healthcare NHS Trust. CNSs were asked to record their activity for each ten-minute period of the working day over two weeks. RESULTS: Data were received from 236 of 261(90.4%) possible respondents and more than one million minutes of data were submitted. On average, CNSs spent 41% of their time in direct patient-facing activities and an additional 21.5% in patient-related activities. However, there was wide variation in how time was spent between individuals and teams, and across divisions within the trust. CNSs estimated that 16.4% of their clinical activity may have prevented an adverse event or patient attendance at hospital. CONCLUSION: Data generated from this evaluation will be used to develop coherent job plans for individuals and teams of CNSs and to identify which nurse-led activities are being reimbursed by commissioners of services.