Development of a Brief Cognitive Screening Tool for Predicting Postoperative Delirium in Patients with Parkinson's Disease: A Secondary Analysis.

Montreal Cognitive Assessment Parkinson’s disease mini-mental state examination postoperative delirium preoperative cognitive impairment

Journal

Clinical interventions in aging
ISSN: 1178-1998
Titre abrégé: Clin Interv Aging
Pays: New Zealand
ID NLM: 101273480

Informations de publication

Date de publication:
2023
Historique:
received: 26 04 2023
accepted: 04 09 2023
medline: 21 9 2023
pubmed: 20 9 2023
entrez: 20 9 2023
Statut: epublish

Résumé

A simple, rapid, and effective cognitive screening test appropriate for fast-paced settings with limited resources and staff is essential, especially preoperatively. This study aimed to develop and validate the short versions of Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) for predicting postoperative delirium (POD) in patients with Parkinson's disease (PD) who were scheduled for surgery. The current study was a secondary analysis of data collected from 128 inpatients scheduled for deep brain stimulation of the subthalamic nuclei (STN-DBS) lasting >60 min, at Tsinghua University Yuquan Hospital, China. Preoperative cognitive screening was performed during the preoperative visit using the MMSE and MoCA. The optimal MMSE and MoCA cut-off scores for detecting PD-MCI was 27 and 23 respectively. The POD was assessed twice a day on the first postoperative day until discharge by the confusion assessment method. The backward conditional logistic regression analysis was used to organize the reduced versions of the MMSE or MoCA. Also, the areas under the receiver operating characteristic curves (AUCs) were examined using the DeLong test. 125/128 PD patients were included in the analysis, and 27 (21.6%) developed POD. The MMSE reduced version (orientation to time, attention and calculation, and comprehension) demonstrated performance similar to the original MMSE in predicting POD ( Our simplified MMSE and MoCA could be efficiently used to identify patients at risk for POD. Also, short cognitive tests could be considered while predicting POD in fast-paced preoperative settings with limited resources and staff.

Sections du résumé

Background UNASSIGNED
A simple, rapid, and effective cognitive screening test appropriate for fast-paced settings with limited resources and staff is essential, especially preoperatively. This study aimed to develop and validate the short versions of Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) for predicting postoperative delirium (POD) in patients with Parkinson's disease (PD) who were scheduled for surgery.
Methods UNASSIGNED
The current study was a secondary analysis of data collected from 128 inpatients scheduled for deep brain stimulation of the subthalamic nuclei (STN-DBS) lasting >60 min, at Tsinghua University Yuquan Hospital, China. Preoperative cognitive screening was performed during the preoperative visit using the MMSE and MoCA. The optimal MMSE and MoCA cut-off scores for detecting PD-MCI was 27 and 23 respectively. The POD was assessed twice a day on the first postoperative day until discharge by the confusion assessment method. The backward conditional logistic regression analysis was used to organize the reduced versions of the MMSE or MoCA. Also, the areas under the receiver operating characteristic curves (AUCs) were examined using the DeLong test.
Results UNASSIGNED
125/128 PD patients were included in the analysis, and 27 (21.6%) developed POD. The MMSE reduced version (orientation to time, attention and calculation, and comprehension) demonstrated performance similar to the original MMSE in predicting POD (
Conclusion UNASSIGNED
Our simplified MMSE and MoCA could be efficiently used to identify patients at risk for POD. Also, short cognitive tests could be considered while predicting POD in fast-paced preoperative settings with limited resources and staff.

Identifiants

pubmed: 37727451
doi: 10.2147/CIA.S410687
pii: 410687
pmc: PMC10506594
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

1555-1564

Informations de copyright

© 2023 Zhou et al.

Déclaration de conflit d'intérêts

The authors declare no conflicts of interest.

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Auteurs

Yongde Zhou (Y)

Department of Anesthesiology, Tsinghua University Yuquan Hospital, Beijing, 100040, People's Republic of China.

Xiaoxiao Wang (X)

Department of Anesthesiology, Peking University Third Hospital, Beijing, 100191, People's Republic of China.
Research Center of Clinical Epidemiology, Peking University Third Hospital, Beijing, 100191, People's Republic of China.

Zhengqian Li (Z)

Department of Anesthesiology, Peking University Third Hospital, Beijing, 100191, People's Republic of China.
Beijing Center of Quality Control and Improvement on Clinical Anesthesia, Beijing, 100191, People's Republic of China.

Yu Ma (Y)

Department of Neurosurgery, Tsinghua University Yuquan Hospital, Beijing, 100040, People's Republic of China.

Cuiping Yu (C)

Department of Anesthesiology, Tsinghua University Yuquan Hospital, Beijing, 100040, People's Republic of China.

Yao Chen (Y)

Department of Anesthesiology, Tsinghua University Yuquan Hospital, Beijing, 100040, People's Republic of China.

Jian Ding (J)

Department of Anesthesiology, Tsinghua University Yuquan Hospital, Beijing, 100040, People's Republic of China.

Jianfeng Yu (J)

Department of Anesthesiology, Tsinghua University Yuquan Hospital, Beijing, 100040, People's Republic of China.

Rongsong Zhou (R)

Department of Neurosurgery, Tsinghua University Yuquan Hospital, Beijing, 100040, People's Republic of China.

Ning Yang (N)

Department of Anesthesiology, Peking University Third Hospital, Beijing, 100191, People's Republic of China.
Beijing Center of Quality Control and Improvement on Clinical Anesthesia, Beijing, 100191, People's Republic of China.

Taotao Liu (T)

Department of Anesthesiology, Peking University Third Hospital, Beijing, 100191, People's Republic of China.
Beijing Center of Quality Control and Improvement on Clinical Anesthesia, Beijing, 100191, People's Republic of China.

Xiangyang Guo (X)

Department of Anesthesiology, Peking University Third Hospital, Beijing, 100191, People's Republic of China.
Beijing Center of Quality Control and Improvement on Clinical Anesthesia, Beijing, 100191, People's Republic of China.

Ting Fan (T)

Department of Anesthesiology, Tsinghua University Yuquan Hospital, Beijing, 100040, People's Republic of China.

Chengmei Shi (C)

Department of Anesthesiology, Peking University Third Hospital, Beijing, 100191, People's Republic of China.
Beijing Center of Quality Control and Improvement on Clinical Anesthesia, Beijing, 100191, People's Republic of China.

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Classifications MeSH