Benjamin K I Helfand1,2,3, Douglas Tommet2,3, Elke Detroyer4,5, Koen Milisen4,5, Dimitrios Adamis6,7, Eran D Metzger8,9, Edward R Marcantonio10, Edwin D Boudreaux1, Sharon K Inouye10,11,12, Richard N Jones2,3. 1. Department of Emergency Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts, USA. 2. Department of Psychiatry and Human Behavior, Warren Alpert Medical School of Brown University, Rhode Island, Rhode Island, USA. 3. Department of Neurology, Warren Alpert Medical School of Brown University, Rhode Island, Rhode Island, USA. 4. Department of Public Health and Primary Care, Academic Centre for Nursing and Midwifery, KU Leuven, Leuven, Belgium. 5. Department of Geriatrics, University Hospitals Leuven, Leuven, Belgium. 6. Sligo Mental Health Services, Clarion Rd, Sligo, Ireland, University of Limerick Graduate Entry Medical School, Limerick, Ireland. 7. Cognitive Impairment Research Group, Centre for Interventions in Infection, Inflammation & Immunity, Graduate Entry Medical School, University of Limerick, Limerick, Ireland. 8. Medical Director of Psychiatry, Hebrew SeniorLife, Boston, Massachusetts, USA. 9. Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA. 10. Divisions of General Medicine and Gerontology, Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA. 11. Marcus Institute for Aging Research, Aging Brain Center, Hebrew SeniorLife, Boston, Massachusetts, USA. 12. Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA.
Abstract
INTRODUCTION: The large number of heterogeneous instruments in active use for identification of delirium prevents direct comparison of studies and the ability to combine results. In a recent systematic review we performed, we recommended four commonly used and well-validated instruments and subsequently harmonized them using advanced psychometric methods to develop an item bank, the Delirium Item Bank (DEL-IB). The goal of the present study was to find optimal cut-points on four existing instruments and to demonstrate use of the DEL-IB to create new instruments. METHODS: We used a secondary analysis and simulation study based on data from three previous studies of hospitalized older adults (age 65+ years) in the USA, Ireland, and Belgium. The combined dataset included 600 participants, contributing 1,623 delirium assessments, and an overall incidence of delirium of about 22%. The measurements included the Diagnostic and Statistical Manual of Mental Disorders, 5th Edition diagnostic criteria for delirium, Confusion Assessment Method (long form and short form), Delirium Observation Screening Scale, Delirium Rating Scale-Revised-98 (total and severity scores), and Memorial Delirium Assessment Scale (MDAS). RESULTS: We identified different cut-points for each existing instrument to optimize sensitivity or specificity, and compared instrument performance at each cut-point to the author-defined cut-point. For instance, the cut-point on the MDAS that maximizes both sensitivity and specificity was at a sum score of 6 yielding 89% sensitivity and 79% specificity. We then created four new example instruments (two short forms and two long forms) and evaluated their performance characteristics. In the first example short form instrument, the cut-point that maximizes sensitivity and specificity was at a sum score of 3 yielding 90% sensitivity, 81% specificity, 30% positive predictive value, and 99% negative predictive value. DISCUSSION/ CONCLUSION: We used the DEL-IB to better understand the psychometric performance of widely used delirium identification instruments and scorings, and also demonstrated its use to create new instruments. Ultimately, we hope that the DEL-IB might be used to create optimized delirium identification instruments and to spur the development of a unified approach to identify delirium.
INTRODUCTION: The large number of heterogeneous instruments in active use for identification of delirium prevents direct comparison of studies and the ability to combine results. In a recent systematic review we performed, we recommended four commonly used and well-validated instruments and subsequently harmonized them using advanced psychometric methods to develop an item bank, the Delirium Item Bank (DEL-IB). The goal of the present study was to find optimal cut-points on four existing instruments and to demonstrate use of the DEL-IB to create new instruments. METHODS: We used a secondary analysis and simulation study based on data from three previous studies of hospitalized older adults (age 65+ years) in the USA, Ireland, and Belgium. The combined dataset included 600 participants, contributing 1,623 delirium assessments, and an overall incidence of delirium of about 22%. The measurements included the Diagnostic and Statistical Manual of Mental Disorders, 5th Edition diagnostic criteria for delirium, Confusion Assessment Method (long form and short form), Delirium Observation Screening Scale, Delirium Rating Scale-Revised-98 (total and severity scores), and Memorial Delirium Assessment Scale (MDAS). RESULTS: We identified different cut-points for each existing instrument to optimize sensitivity or specificity, and compared instrument performance at each cut-point to the author-defined cut-point. For instance, the cut-point on the MDAS that maximizes both sensitivity and specificity was at a sum score of 6 yielding 89% sensitivity and 79% specificity. We then created four new example instruments (two short forms and two long forms) and evaluated their performance characteristics. In the first example short form instrument, the cut-point that maximizes sensitivity and specificity was at a sum score of 3 yielding 90% sensitivity, 81% specificity, 30% positive predictive value, and 99% negative predictive value. DISCUSSION/ CONCLUSION: We used the DEL-IB to better understand the psychometric performance of widely used delirium identification instruments and scorings, and also demonstrated its use to create new instruments. Ultimately, we hope that the DEL-IB might be used to create optimized delirium identification instruments and to spur the development of a unified approach to identify delirium.
Authors: Sarinnapha M Vasunilashorn; Dena Schulman-Green; Douglas Tommet; Tamara G Fong; Tammy T Hshieh; Edward R Marcantonio; Eran D Metzger; Eva M Schmitt; Patricia A Tabloski; Thomas G Travison; Yun Gou; Benjamin Helfand; Sharon K Inouye; Richard N Jones Journal: Dement Geriatr Cogn Disord Date: 2020-06-17 Impact factor: 2.959
Authors: Joost Witlox; Lisa S M Eurelings; Jos F M de Jonghe; Kees J Kalisvaart; Piet Eikelenboom; Willem A van Gool Journal: JAMA Date: 2010-07-28 Impact factor: 56.272
Authors: Benjamin K I Helfand; Elke Detroyer; Koen Milisen; Dimitrios Adamis; Eran D Metzger; Edwin D Boudreaux; Sharon K Inouye; Richard N Jones Journal: Am J Geriatr Psychiatry Date: 2021-07-29 Impact factor: 4.105
Authors: Wolfgang Hasemann; Debbie Tolson; Jon Godwin; Rebecca Spirig; Irena Anna Frei; Reto W Kressig Journal: J Gerontol Nurs Date: 2018-12-01 Impact factor: 1.254
Authors: Karin J Neufeld; Archana Nelliot; Sharon K Inouye; E Wesley Ely; O Joseph Bienvenu; Hochang Benjamin Lee; Dale M Needham Journal: Am J Geriatr Psychiatry Date: 2014-03-15 Impact factor: 4.105