Cargando…
Utilizing timed categorical recall (naming US cities) for rapid bedside dementia screening
The availability of fast validated screening for dementia is a critical clinical need to improve neurologic examination time efficiency. This study validated a 1-minute timed categorical recall (TCR) method, naming as many US cities as possible and compared TCR to the Folstein Minimental Status Exam...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Lippincott Williams & Wilkins
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9351842/ https://www.ncbi.nlm.nih.gov/pubmed/35945729 http://dx.doi.org/10.1097/MD.0000000000029518 |
_version_ | 1784762518895329280 |
---|---|
author | Joseph, Charles R. Cargill, Michael P. Lee, Chansoon D. |
author_facet | Joseph, Charles R. Cargill, Michael P. Lee, Chansoon D. |
author_sort | Joseph, Charles R. |
collection | PubMed |
description | The availability of fast validated screening for dementia is a critical clinical need to improve neurologic examination time efficiency. This study validated a 1-minute timed categorical recall (TCR) method, naming as many US cities as possible and compared TCR to the Folstein Minimental Status Exam (MMSE) as a preliminary cognitive screening tool. Random uncompensated 349 volunteers were recruited ages 18 to 97 from local free clinics, retirement homes, university faculty, and students in Lynchburg, Virginia 2015 to 2020. Participants’ demographic and medical information were collected. After 1 minute preparation, participants were rapidly named as many US cities as possible until they were told to stop (1 minute). The time limitation was withheld in advance. Number of cities and organizational strategies were recorded. Folstein MMSE administration immediately after TCR was administered to 122 subjects recruited in the final 2 study years as a comparison benchmark. A multiple linear regression model and a regression tree model were used to identify important variables for the number of cities named and determine subgroups and their thresholds. TCR resulted in accuracy rate (0.80), sensitivity (0.78), and specificity (0.81). The global TCR threshold (9 cities named) is superseded by 4 subgroup thresholds, categorized by statistically important variables (age, education level, and number of states visited) as follows: For those visiting ≥8 states and 1. 18 to 71 ages with a master’s degree or above, the threshold was naming 20 cities; 2. 18 to 29 ages with a bachelor’s degree or below, the threshold was naming 17 cities; 3. 30 to 71 ages with a bachelor’s degree or below, the threshold was naming 10 cities. For those visiting <8 states or for ages 72 to 97 (regardless of education levels and number of states visited), the threshold was naming 8 cities. American cities are common knowledge across ages and backgrounds, making it a useful bedside screen for dementia. In clinical practice, patients who report fewer cities than the threshold of 9 cities should receive further cognitive testing. If the patient meets the criteria for a subgroup, then the higher subgroup thresholds apply. TCR is a more time-efficient preliminary dementia screening tool with improved sensitivity and similar specificity compared with MMSE. |
format | Online Article Text |
id | pubmed-9351842 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Lippincott Williams & Wilkins |
record_format | MEDLINE/PubMed |
spelling | pubmed-93518422022-08-05 Utilizing timed categorical recall (naming US cities) for rapid bedside dementia screening Joseph, Charles R. Cargill, Michael P. Lee, Chansoon D. Medicine (Baltimore) Research Article The availability of fast validated screening for dementia is a critical clinical need to improve neurologic examination time efficiency. This study validated a 1-minute timed categorical recall (TCR) method, naming as many US cities as possible and compared TCR to the Folstein Minimental Status Exam (MMSE) as a preliminary cognitive screening tool. Random uncompensated 349 volunteers were recruited ages 18 to 97 from local free clinics, retirement homes, university faculty, and students in Lynchburg, Virginia 2015 to 2020. Participants’ demographic and medical information were collected. After 1 minute preparation, participants were rapidly named as many US cities as possible until they were told to stop (1 minute). The time limitation was withheld in advance. Number of cities and organizational strategies were recorded. Folstein MMSE administration immediately after TCR was administered to 122 subjects recruited in the final 2 study years as a comparison benchmark. A multiple linear regression model and a regression tree model were used to identify important variables for the number of cities named and determine subgroups and their thresholds. TCR resulted in accuracy rate (0.80), sensitivity (0.78), and specificity (0.81). The global TCR threshold (9 cities named) is superseded by 4 subgroup thresholds, categorized by statistically important variables (age, education level, and number of states visited) as follows: For those visiting ≥8 states and 1. 18 to 71 ages with a master’s degree or above, the threshold was naming 20 cities; 2. 18 to 29 ages with a bachelor’s degree or below, the threshold was naming 17 cities; 3. 30 to 71 ages with a bachelor’s degree or below, the threshold was naming 10 cities. For those visiting <8 states or for ages 72 to 97 (regardless of education levels and number of states visited), the threshold was naming 8 cities. American cities are common knowledge across ages and backgrounds, making it a useful bedside screen for dementia. In clinical practice, patients who report fewer cities than the threshold of 9 cities should receive further cognitive testing. If the patient meets the criteria for a subgroup, then the higher subgroup thresholds apply. TCR is a more time-efficient preliminary dementia screening tool with improved sensitivity and similar specificity compared with MMSE. Lippincott Williams & Wilkins 2022-08-05 /pmc/articles/PMC9351842/ /pubmed/35945729 http://dx.doi.org/10.1097/MD.0000000000029518 Text en Copyright © 2022 the Author(s). Published by Wolters Kluwer Health, Inc. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License 4.0 (CCBY) (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Joseph, Charles R. Cargill, Michael P. Lee, Chansoon D. Utilizing timed categorical recall (naming US cities) for rapid bedside dementia screening |
title | Utilizing timed categorical recall (naming US cities) for rapid bedside dementia screening |
title_full | Utilizing timed categorical recall (naming US cities) for rapid bedside dementia screening |
title_fullStr | Utilizing timed categorical recall (naming US cities) for rapid bedside dementia screening |
title_full_unstemmed | Utilizing timed categorical recall (naming US cities) for rapid bedside dementia screening |
title_short | Utilizing timed categorical recall (naming US cities) for rapid bedside dementia screening |
title_sort | utilizing timed categorical recall (naming us cities) for rapid bedside dementia screening |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9351842/ https://www.ncbi.nlm.nih.gov/pubmed/35945729 http://dx.doi.org/10.1097/MD.0000000000029518 |
work_keys_str_mv | AT josephcharlesr utilizingtimedcategoricalrecallnaminguscitiesforrapidbedsidedementiascreening AT cargillmichaelp utilizingtimedcategoricalrecallnaminguscitiesforrapidbedsidedementiascreening AT leechansoond utilizingtimedcategoricalrecallnaminguscitiesforrapidbedsidedementiascreening |