Frontal Lobe Hypometabolism Predicts Cognitive Decline in Patients With Lacunar Infarcts
Bibliographic record
Abstract
BACKGROUND: A proportion of patients with subcortical lacunes will suffer progressive cognitive dysfunction, but the basis for this decline is controversial and little is known about predicting cognitive decline in these patients. Studies of Alzheimer disease have shown that imaging measures of temporal and parietal metabolism and blood flow predict disease course. OBJECTIVE: To determine whether regional cerebral glucose metabolism predicts cognitive decline by testing 2 opposing hypotheses: (1) temporoparietal activity predicts decline (based on the idea that concomitant Alzheimer disease causes decline) vs (2) frontal hypometabolism predicts decline (based on evidence that subcortical frontal circuits are especially vulnerable to small vessel ischemia). DESIGN: Prospective cohort study. SETTING: University outpatient dementia center. PATIENTS: A convenience sample of 26 patients with radiologically defined lacunes and baseline cognitive function ranging from normal to moderately demented. MAIN OUTCOME MEASURES: Regional cerebral metabolism was quantitated in the form of atrophy-corrected positron emission tomographic activity ratios in cortical regions that were defined a priori. Patients were followed up at a mean of 1.8 years, and the dependent variable was rate of change in the Mini-Mental State Examination score. RESULTS: Bilateral and right hemisphere dorsolateral frontal metabolism significantly predicted cognitive decline, with right dorsolateral frontal metabolism explaining 19% of the variance. No other positron emission tomographic region was a significant predictor, nor were demographic variables or baseline Mini-Mental State Examination scores significant predictors. CONCLUSION: Cognitive decline in patients with lacunes may result in part from progressive vascular compromise in subcortical frontal circuits.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".