Poor olfaction prior to cardiac surgery: Association with cognition, plasma neurofilament light, and post‐operative delirium
Bibliographic record
Abstract
OBJECTIVES: Post-operative delirium (POD) affects up to 50% of cardiac surgery patients, with higher incidence in older adults. There is increasing need for screening tools that identify individuals most vulnerable to POD. Here, we examined the relationship between pre-operative olfaction and both incident POD and POD severity in patients undergoing cardiac surgery. We also examined cross-sectional relationships between baseline olfaction, cognition, and plasma neurofilament light (NfL). METHODS: Individuals undergoing cardiac surgery (n = 189; mean age = 70 years; 75% men) were enrolled in a clinical trial of cerebral autoregulation monitoring. At baseline, odor identification performance (Brief Smell Identification Test), cognitive performance, and plasma concentrations of NfL levels (Simoa™ NF-Light Assay) were measured. Delirium was assessed with the Confusion Assessment Method (CAM) or CAM-ICU, and delirium severity was assessed using the Delirium Rating Scale-Revised-98. The association of baseline olfaction, delirium incidence, and delirium severity was examined in regression models adjusting for age, duration of cardiopulmonary bypass, logistic European System for Cardiac Operative Risk Evaluation (EuroSCORE), and baseline cognition. RESULTS: Olfactory dysfunction was present in 30% of patients, and POD incidence was 44%. Pre-operative olfactory dysfunction was associated with both incident POD (OR = 3.17, p = 0.001) and greater severity of POD after cardiac surgery (OR = 3.94 p < 0.001) in models adjusted for age, duration of bypass, and a surgical risk score. The addition of baseline cognition attenuated the strength of the association, but it remained significant for incident POD (OR = 2.25, p = 0.04) and POD severity (OR 2.10, p = 0.04). Poor baseline olfaction was associated with greater baseline cognitive dysfunction (p < 0.001) and increased baseline plasma NfL concentrations (p = 0.04). Neither age, cognition, nor baseline NFL concentration modified the association of impaired olfaction and delirium outcomes. CONCLUSIONS: Olfactory assessment may be a useful pre-surgical screening tool for the identification of patients undergoing cardiac surgery at increased risk of POD. Identifying those at highest risk for severe delirium and poor cognitive outcomes following surgery would allow for earlier intervention and pre-operative rehabilitation strategies, which could ultimately impact the functional disability and morbidity associated with POD.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".