A proposal for virtual, telephone-based preoperative cognitive assessment in older adults undergoing elective surgery
Bibliographic record
Abstract
OBJECTIVE: To assess the feasibility of administering the MoCA 5-minute test/Telephone (T-MoCA), an abbreviated version of the Montreal Cognitive Assessment to older adults perioperatively DESIGN: A feasibility study including patients aged ≥ 70 years scheduled for surgery from December 2020 to March 2021 SETTING: Preoperative virtual clinic PATIENTS: Patients ≥70 years undergoing major elective surgery INTERVENTION: A study investigator called eligible patients prior to surgery, obtained consent, and completed the preoperative cognitive assessment. Follow-up assessment was completed 1-month postoperatively, and participating clinicians were surveyed at the completion of the study. MEASUREMENTS: An attention test, T-MoCA, Activities of Daily Living (ADL), Instrumental Activities of Daily Living (IADL), and Generalized Anxiety Disorder 2-item (GAD-2) MAIN RESULTS: Overall, 37/40 (92.5%) patients completed the pre- and post-operative assessments. The cohort was 50% female, white (97.5%), with a median age of 76 years (interquartile range (IQR) 73-79), and education level was higher than high school in 82.5% of patients. Preoperatively, the median number of medications was 8 (IQR 7-11), 27/40 (67.5%) had medications with anticholinergic effects, and 6/40 (15%) had benzodiazepines. Median completion time of the phone assessment was 10 min (IQR 8.25-12) and 4 min (IQR 3-5) for the T-MoCA with a median T-MoCA score of 13 (IQR 12-14). Most patients (37/40) completed the post-operative assessment, and 6/37 (16.2%) reported they had experienced a change in memory or attention post-operatively. Clinician's survey reported ease and feasibility in performing T-MoCA as a preoperative cognitive evaluation. CONCLUSION: Preoperative cognitive assessment of older adults using T-MoCA over the phone is easy to perform by clinicians and had a high completion rate by patients. This test is feasible for virtual assessments. Further research is needed to better define validity and correlation with postoperative outcomes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.043 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.025 | 0.015 |
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 source (direct Gemma or distilled Codex), 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".