The Use of MoCA and Other Cognitive Tests in Evaluation of Cognitive Impairment in Elderly Patients Undergoing Arthroplasty
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.100 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".