Objective:To examine the prevalence and effect of cognitive impairment on treatment outcomes in elderly patients undergoing arthroplasty and to describe the feasibility of cognitive tests.Materials and Methods:The participants were 52 patients with a mean age of 78 years 11 months (SD: 3.3), waiting for primary arthroplasty. We translated Montreal Cognitive Assessment (MoCA) into Finnish and compared it with Mini-Mental State Examination (MMSE), Mini-Cog, and clock-drawing tests prior to and 3 months after the surgery. The ability to perform activities of daily living, depression, quality of life, and years of education were evaluated.Results:The mean MoCA score on the first visit was 20.7 (SD: 4.1). The pre- and postoperative cognitive tests implied there were no changes in cognitive functioning. Unambiguous delirium was detected in 6 patients. Delirium was not systematically assessed and consequently hypoactive delirium cases were possibly missed. Both MMSE and Mini-Cog found 3/6 of those and clock drawing and MoCA 6/6. Low preoperative MoCA, MMSE, and Mini-Cog scores predicted follow-up treatment in health-care center hospitals (P = .02, .011, and .044, respectively). During the 5-year follow-up period, 11/52 patients died. Higher education was the only variable associated with survival. The survivors had attained the median of 8 (range: 4-19) years of education compared with 6 (range: 4-8) years among the deceased.Conclusion:The prevalence of cognitive impairment among older patients presenting for arthroplasty is high and mostly undiagnosed. It is feasible to use the MoCA to identify cognitive impairment preoperatively in this group. The clock-drawing test was abnormal in all patients with postoperative delirium, which could be used as a screening test. Higher education predicted survival on a 5-year follow-up period.

The aim of this study was to determine the clinical utility of the Finnish version of the MoCA test for screening Alzheimer’s disease and MCI. The purpose was to examine the ability (sensitivity and specificity) of the MoCA to distinguish patients with AD and MCI from cognitively normal controls. The study population consists of three participant groups: patients with AD (n=25), patients meeting the criteria for MCI (n=18), and cognitively normal controls (NC) (n=39). The AD group consists of subjects with very mild (CDR= 0.5, n=12), mild (CDR=1, n=12), and moderate (CDR=2, n=1) dementia, and they were given a diagnosis of dementia by using the revised NINCDS-ARDRA criteria. The normal control group (NC) consists of 39 cognitively normal volunteer participants. The three study groups differed from each other in terms of sex, age, and level of education. The NCs were younger than the subjects with AD (t [37,374] = 3.265, p = 0.002) and MCI (t [30,800] = 4.306, p = < 0.001). The NCs were also better-educated than the patients with AD (t [54,975] = -3.419, p = 0.001) and MCI (t [40,782] = -3.008, p = 0.004). The sensitivity and specificity of the MoCA in detecting AD and MCI was done according to various cutoff points. With a cutoff score of 26, the MoCA had a sensitivity of 100% to detect subjects with AD and a sensitivity of 100% to detect subjects with MCI. The specificity was 79.5%. With a cutoff score of 24, which was the best threshold in the present study, the MoCA not only had a high sensitivity to detect subjects with AD (96%) and MCI (89%) but also delivered a high specificity (97%). The MoCA has a high sensitivity and specificity to detect subjects with AD and MCI with a cutoff score of 24/30. The Finnish version of the MoCA is a feasible screening instrument for assessing cognitive decline. According to our study, the optimal cutoff score of the MoCA is 24/30.

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