Preoperative mild cognitive impairment as a risk factor of postoperative cognitive dysfunction in elderly patients undergoing spine surgery
Bibliographic record
Abstract
Introduction Any persistent degree of cognitive impairment in older adults is a concern as it can progress to dementia. This study aimed to determine the incidence and risk factors for early postoperative cognitive dysfunction (POCD) in elderly patients undergoing spine surgery. Methods Patients were enrolled from a previous prospective observational study after screening for normal cognitive function using the Mini Mental State Examination (MMSE). Cognitive function was evaluated before surgery and at 1 week, month, and year post-surgery using MMSE and Montreal Cognitive Assessment scores (MoCA). Mild cognitive impairment (MCI) was determined using the MoCA scores adjusted for age. POCD was defined as a drop of three or more points on the MMSE 1 week post-surgery. Multivariate logistic analysis was performed to identify POCD risk factors. Results A total of 427 patients were included. Eighty-five (20%) had pre-existing MCI. The MCI group showed lower MoCA scores at each time point (baseline, 1 week after surgery, 1 month after surgery, 1 year after surgery) compared to the non-MCI group. Those in the MCI group had a higher rate of admission to intensive care unit after surgery, postoperative delirium, and POCD 1 week post-surgery, than those in the non-MCI group (16.5% vs. 6.7%, p = 0.008; 27.1% vs. 15.8%, p = 0.024; and 18.8% vs. 8.2%, p < 0.001, respectively). Among them, 10.3% were assessed for POCD on postoperative day 7 and self-reported poor social roles and physical functioning 1 week postoperatively. Conclusion Preoperative MCI was seen in ~20% of surgical patients aged >70 years. POCD was seen in ~20% of patients with pre-existing MCI, and ~ 10% of those without. Benzodiazepine use, significant comorbidities, pre-existing MCI, and depressive tendencies were risk factors for POCD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".