Developing a cognitive dysfunction risk score for use with opioid-dependent persons in drug treatment.
Brief inventory for neurocognitive impairment
Cognitive dysfunction
Medication for opioid use disorder
Opioid-dependent
Risk score
Journal
Drug and alcohol dependence
ISSN: 1879-0046
Titre abrégé: Drug Alcohol Depend
Pays: Ireland
ID NLM: 7513587
Informations de publication
Date de publication:
01 07 2021
01 07 2021
Historique:
received:
18
01
2021
revised:
28
02
2021
accepted:
17
03
2021
pubmed:
1
5
2021
medline:
15
9
2021
entrez:
30
4
2021
Statut:
ppublish
Résumé
Cognitive dysfunction is common in persons seeking medication for opioid use disorder (MOUD) and may hinder many addiction-related services. Brief but accurate screening measures are needed to efficiently assess cognitive dysfunction in these resource-limited settings. The study aimed to develop a brief predictive risk score tailored for use among patients in drug treatment. The present study examined predictors of mild cognitive impairment (MCI), objectively assessed via the NIH Toolbox, among 173 patients receiving methadone as MOUD at an urban New England drug treatment facility. Predictors of MCI were identified in one subsample using demographic characteristics, medical chart data, and selected items from the Brief Inventory of Neuro-Cognitive Impairment (BINI). Predictors were cross-validated in a second subsample using logistic regression. Receiver operating curve (ROC) analyses determined an optimal cut-off score for detecting MCI. A cognitive dysfunction risk score (CDRS) was calculated from patient demographics (age 50+, non-White ethnicity, less than high school education), medical and substance use chart data (history of head injury, overdose, psychiatric diagnosis, past year polysubstance use), and selected self-report items (BINI). The CDRS discriminated acceptably well, with a ROC curve area of 70.6 %, and correctly identified 78 % of MCI cases (sensitivity = 87.5 %; specificity = 55.6 %). The CDRS identified patients with cognitive challenges at a level likely to impede treatment engagement and/or key outcomes. The CDRS may assist in efficiently identifying patients with cognitive dysfunction while requiring minimal training and resources. Larger validation studies are needed in other clinical settings.
Sections du résumé
BACKGROUND
Cognitive dysfunction is common in persons seeking medication for opioid use disorder (MOUD) and may hinder many addiction-related services. Brief but accurate screening measures are needed to efficiently assess cognitive dysfunction in these resource-limited settings. The study aimed to develop a brief predictive risk score tailored for use among patients in drug treatment.
METHODS
The present study examined predictors of mild cognitive impairment (MCI), objectively assessed via the NIH Toolbox, among 173 patients receiving methadone as MOUD at an urban New England drug treatment facility. Predictors of MCI were identified in one subsample using demographic characteristics, medical chart data, and selected items from the Brief Inventory of Neuro-Cognitive Impairment (BINI). Predictors were cross-validated in a second subsample using logistic regression. Receiver operating curve (ROC) analyses determined an optimal cut-off score for detecting MCI.
RESULTS
A cognitive dysfunction risk score (CDRS) was calculated from patient demographics (age 50+, non-White ethnicity, less than high school education), medical and substance use chart data (history of head injury, overdose, psychiatric diagnosis, past year polysubstance use), and selected self-report items (BINI). The CDRS discriminated acceptably well, with a ROC curve area of 70.6 %, and correctly identified 78 % of MCI cases (sensitivity = 87.5 %; specificity = 55.6 %).
CONCLUSIONS
The CDRS identified patients with cognitive challenges at a level likely to impede treatment engagement and/or key outcomes. The CDRS may assist in efficiently identifying patients with cognitive dysfunction while requiring minimal training and resources. Larger validation studies are needed in other clinical settings.
Identifiants
pubmed: 33930640
pii: S0376-8716(21)00221-0
doi: 10.1016/j.drugalcdep.2021.108726
pmc: PMC8180490
mid: NIHMS1698231
pii:
doi:
Substances chimiques
Analgesics, Opioid
0
Pharmaceutical Preparations
0
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Langues
eng
Sous-ensembles de citation
IM
Pagination
108726Subventions
Organisme : NIDA NIH HHS
ID : R01 DA044867
Pays : United States
Organisme : NIDA NIH HHS
ID : R21 DA051934
Pays : United States
Organisme : NCATS NIH HHS
ID : UL1 TR001863
Pays : United States
Organisme : NIDA NIH HHS
ID : K24 DA051344
Pays : United States
Organisme : NIA NIH HHS
ID : R01 AG065432
Pays : United States
Organisme : NIMH NIH HHS
ID : T32 MH074387
Pays : United States
Organisme : NIDA NIH HHS
ID : R01 DA032290
Pays : United States
Organisme : NIDA NIH HHS
ID : K01 DA051346
Pays : United States
Informations de copyright
Copyright © 2021 Elsevier B.V. All rights reserved.
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