Short-term cognitive and functional decline in older patients undergoing elective cardiac surgery: preliminary results of a longitudinal study
Bibliographic record
Abstract
Aim: The implementation of new techniques has significantly reduced mortality and morbidity in older cardiovascular patients undergoing cardiac surgery. However, few studies have assessed post-surgery functional and cognitive outcomes in this demographic. This study aims to characterize baseline cognitive and functional status of patients undergoing elective cardiothoracic surgery (CS) and to evaluate their modifications over a 3-month follow-up. Methods: Data were extracted from a prospective study starting May 2023. Patients aged 65+ undergoing elective CS received pre-operative geriatric assessments. Postoperative complications and delirium were monitored, with a 3-month follow-up assessing functional and cognitive status. Kruskal-Wallis and Fisher's tests analyzed clinical and demographic features, and linear regression examined the relationship between follow-up functional autonomy and preoperative cognitive status. Results: Seventy-seven patients (median age: 72 [IQR, 68.00-75.25], 53% males) were included in the study, showing a median Instrumental Activities of Daily Living (IADL) of 8 [5.00-8.00]. The median pre-operative Montreal Cognitive Assessment (MoCA) was 22.88 [19.96-24.80]. 21.4% of patients with impaired cognitive performance at baseline experienced delirium, compared to 2.3% of those without impairment (p=0.052). At follow-up, 58 patients were re-assessed, showing a median IADL of 7.5 [5.00, 8.00] and an almost 64.3% prevalence of impaired cognitive performance on Telephone MoCA testing. At the linear regression analysis, pre-operative MoCA was correlated with three-month IADL decline [β = 0.144; 95% CI 0.044-0.243; p=0.005]. Conclusions: Routine cognitive assessments reveal significant cognitive deficits in older CS patients. Preliminary findings suggest a link between preoperative cognitive impairment and functional decline.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".