Aims: To develop and validate a conversion table between the MMSE and the MoCA using Rasch analysis in older adults undergoing selective surgery and examine its diagnostic accuracy in detecting cognitive impairment.
Design: Cross-sectional study.
Methods: Older patients [N = 129; age 66.0 (4.6) years, education 7.7 (3.5) years] undergoing elective surgery were recruited from December 2017 to June 2018. All participants completed the MMSE and MoCA and 113 of them completed a battery of neuropsychological tests. Common person linking based on Rasch analysis was performed to develop the conversion table. The conversions were validated by calculating the intraclass correlation coefficient (ICC), score differences between actual and converted scores, and root mean squared error of the difference (RMSE). The diagnostic accuracy of the conversions for detecting cognitive impairment was also tested.
Results: The MoCA [person measure: 1.3 (1.1) logits] was better targeted to the patients than the MMSE [person measure: 3.2 (1.3) logits]. Conversion from MoCA to MMSE scores (ICC 0.84, 95% CI 0.77-0.88; RMSE 1.36) was more precise than conversion from MMSE to MoCA (ICC 0.82, 95% CI 0.75-0.87; RMSE 2.56). Conversion from MoCA to MMSE demonstrated better diagnostic accuracy in detecting cognitive impairment than the actual MMSE, whereas conversion from MMSE to MoCA exhibited the opposite pattern.
Conclusion: Conversion from MoCA to MMSE was more precise and had better diagnostic accuracy in detecting pre-operative cognitive impairment in older patients undergoing selective surgery than conversion from MMSE into MoCA.
Impact: The finding is useful for interpreting, comparing, and integrating cognitive measurements in surgical settings and clinical research. Statistically sound conversion between MoCA and MMSE based on Rasch analysis is now possible for surgical setting and clinical research.
目的: 通过对进行择期手术的老年人采用Rasch分析法,制定并验证简易精神状态检查表和蒙特利尔认知量表之间的换算表,并检查其检测认知障碍的诊断准确性。 设计: 横向研究。 方法: 自2017年12月至2018年6月,招募了进行择期手术的老年患者【N = 129; 年龄 66.0 (4.6) 岁, 教育年限7.7 (3.5)】。所有患者均完成了简易精神状态检查表和蒙特利尔认知量表,其中113人完成了一系列神经心理学测试。根据Rash分析法,进行正常的人员关联,制定换算表。通过计算组内相关系数(ICC)、实际和转化后的评分之间的差异、均方根误差(RMSE),换算验证为有效。同样对检测认知障碍换算的诊断准确性进行了测试。 结果: 与简易精神状态检查表【测量人员:3.2(1.3)分对数】相比,蒙特利尔认知量表【测量人员:1.3(1.1)分对数】更吻合患者情况。从蒙特利尔认知量表换算成简易精神状态检查表评分(组内相关系数0.84、95% CI 0.77-0.88;均方根误差1.36)比从简易精神状态检查表换算成蒙特利尔认知量表的评分(组内相关系数0.82、95% CI 0.75-0.87; 均方根误差2.56)更为精确。经证明,从蒙特利尔认知量表换算成简易精神状态检查表,在检测进行择期手术的老年人的术前认知障碍方面,与现行的简易精神状态检查表相比,诊断准确性更高,而从简易精神状态检查表换算成蒙特利尔认知量表则表现出相反的模数。 结论: 与从简易精神状态检查表换算成蒙特利尔认知量表相比,从蒙特利尔认知量表换算成简易精神状态检查表,更为精确,且在检测进行择期手术的老年人的术前认知障碍方面,诊断准确性更高。 影响: 研究结果有助于解释、比较及融合手术场景及临床研究中的认知测量。如今,在手术场景和临床研究中,蒙在特利尔认知量表和简易精神状态检查表之间进行合理换算,从统计学上讲可行。.
Keywords: Rasch analysis; cognitive impairment; elderly; selective surgery; the Mini-Mental State Examination; the Montreal Cognitive Assessment.
© 2020 John Wiley & Sons Ltd.