Clinical Study about Cerebral Blood Perfusion of Vascular Cognitive Impairment
Bibliographic record
Abstract
Objective To investigate the significance of diagnose in vascular cognitive impairment(VCI) with single photon emission computed tomography.To analyze the relationship with decrease of regional cerebral blood perfusion and the specified domain of cognitive impairment. Methods The patients were collected from either the ward or clinic in Tianjin general hospital from April 2009 till April 2010.We divided all the patients into 3 groups according to the level of their cognition.The 3 groups are the control group,the vascular cognitive impairment not dementia(VCIND) group and the vascular dementia(VaD) group.We compared the change of regional cerebral blood flow(rCBF) in each area of cerebrum within 3 groups and analyzed the relationship with decrease of regional cerebral blood perfusion and score of the Montreal cognitive assessment(MoCA).We compared the difference of perfusion image and morphological image and analyzed the relationship with decrease of regional cerebral blood flow and the specified domain of cognitive impairment. Results The rCBF of the left temporal lobe,thalamus and hippocampus of VaD and VC1ND is lower than the control group.There is difference in statistics among these 3 groups(F=8.232,6.237, 6.136;P=0.002,0.006,0.000).The rCBF of the left temporal lobe,thalamus and hippocampus has positive collection with the score of MoCA through the spearman analysis(r=0.421,0.355, 0.323;P=0.011,0.023,0.029).The rCBF of the left temporal lobe has the positive relationship in the domain of calculation(Beta=0.445,P=0.020),and the rCBF of the right temporal lobe and hippocampus have the positive relationship in the domain of orientation(Beta=0.626,0.740, P=0.035,0.023). Conclusion The low rCBF in the temporal lobe,thalamus and hippocampus supply the evidence to the conclusion that the performance in pathology of VCI is low perfusion of the temporal lobe, thalamus and hippocampus.The change in perfusion may have the tendency of performing earlier than the change in morphology.
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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 | 0.002 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".