Preexisting Cognitive Impairment in Women Before Cardiac Surgery and Its Relationship with C-Reactive Protein Concentrations
Bibliographic record
Abstract
In Brief Preoperative cognitive state is seldom considered when investigating the effects of cardiac surgery on cognition. In this study we sought to determine the prevalence of cognitive impairment in women scheduled for cardiac surgery using nonhospitalized volunteers as a reference group and to examine the relationship between C-reactive protein levels and cognitive impairment. Psychometric testing was performed in 108 postmenopausal women scheduled for cardiac surgery and in 58 nonhospitalized control women. High sensitivity C-reactive protein levels were measured in the surgical patients. Preoperative cognitive impairment was defined as >2 sd lower scores on ≥2 tests compared with the controls. Cognitive impairment was present in 49 of 108 (45%) patients. C-reactive protein levels were higher for patients with compared with those without cognitive impairment (median, 8.1 mg/L versus 4.7 mg/L; P = 0.04). Based on multivariate logistic regression analysis, patient age, lower attained level of education, type 2 diabetes mellitus, and prior myocardial infarction identified risk for cognitive impairment (P < 0.05) but C-reactive protein levels did not (P = 0.09). In conclusion, cognitive impairment is prevalent in women before cardiac surgery. C-reactive protein levels are increased in women with this condition but the relationship between this inflammatory marker and preexisting cognitive impairment is likely secondary to the acute phase reactant serving as a marker for other predisposing conditions. IMPLICATIONS: Cognitive impairment was found in 45% of women before cardiac surgery. C-reactive protein levels are increased in women with preexisting cognitive impairment, but the relationship between this inflammatory marker and preexisting cognitive impairment is likely secondary to the acute phase reactant serving as a marker for other predisposing conditions.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".