[IC‐P‐073]: CEREBRAL 18F‐FLUORODEOXYGLUCOSE‐POSITRON EMISSION TOMOGRAPHY IN PROLONGED DELIRIUM
Bibliographic record
Abstract
Delirium, an acute neuropsychiatric disorder frequently seen in hospitalized elderly patients, is associated with increased risk of cognitive decline. It remains unclear if that risk is linked to acceleration by delirium of pre-existing disease, possibly increasing in itself the risk of delirium under physiological stress, and if so whether certain specific conditions are more likely to be involved. To begin clarifying this, we analyzed the cerebral FDG PET (CPET) patterns reported in patients with prolonged delirium. We retrospectively reviewed cerebral CPET studies in hospitalized patients who presented prolonged (>7 days) delirium according to the Confusion Assessment Method criteria between 01/2012 and 12/2015 at CHUM. Subjects had to be > 65 years old and without a history of dementia, idiopathic Parkinson's disease, or significant psychiatric disorder. They were age and sex matched with randomly selected outpatient controls imaged with CPET for evaluation of cognitive impairment. Imaging studies were re-interpreted by 2 Nuclear Medicine physicians trained in neuroimaging, blinded to clinical diagnosis. We reviewed 1604 files, with 28 meeting inclusion criteria (mean age: 81 ± 8, 64% male). Although not statistically significant, patients with delirium were more likely to show a scintigraphic pattern of neurodegenerative disease than controls (89 % vs. 68%, p = 0.101). Alzheimer's was the most frequent diagnosis for both groups (17 in the delirium group, 10 controls; p = 0,108). The scintigraphic pattern was compatible with Lewy body pathology in 9 patients with prolonged delirium compared to only 1 in controls (32% vs. 4%, p = 0.012). Moreover, the scintigraphic pattern was suggestive of co-occurring neural pathologies in 18 cases of patients with prolonged delirium while only 8 controls were so classified (64% vs. 29%, p = 0.015). The frequency of a PET-defined neurodegenerative condition in patients with an episode of prolonged delirium is high but similar to that of outpatients with cognitive deterioration. However, the repartition across neurodegenerative processes encountered in the prolonged delirium group differs from that of controls, with Lewy body disease and mixed pathologies being over-represented in the delirium group; AD remains the most frequent diagnosis in both groups.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".