Study on the correlation between cerebral hemodynamics and cognitive function in patients with mild cognitive impairment
Bibliographic record
Abstract
Objective To study the characteristics of cerebral hemodynamics and the correlation with cognitive function in patients with mild cognitive impairment (MCI). Methods A total of 80 cases were divided into MCI group (N = 40) and control group (N = 40). Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) were used to evaluate the cognitive function of 2 groups. Bilateral middle cerebral artery (MCA) and basilar artery (BA) were examined by means of transcranial Doppler (TCD) ultrasound to obtain mean flow velocity (MFV), pulsatility index (PI), resistance index (RI) and the ratio of peak systolic velocity to end-diastolic velocity (S/D) in all subjects. Results Compared with control group, PI (P = 0.023) and RI (P = 0.035) of MCA were significantly increased in MCI group. The differences in MFV, S/D and hemodynamic indexes of BA had no significance between 2 groups (P > 0.05, for all). The rate of abnormal PI of MCA in MCI group was higher than that in control group [45% (18/40) vs. 20% (8/40); χ2 = 4.615, P = 0.032]. Pearson correlation analysis showed that PI of MCA had negative correlation with MoCA score in MCI group (r = -0.382, P = 0.036), and no correlation with MMSE score (P > 0.05). MFV, RI and S/D of MCA and MFV, PI, RI and S/D of BA had no correlation with MoCA and MMSE scores (P > 0.05, for all). MCI group was further divided into subgroups according to PI, and MoCA score was significantly lower in abnormal PI subgroup than that in normal PI subgroup [(18.57 ± 3.02) score vs. (23.41 ± 2.78) score; t = 3.914, P = 0.015]. Conclusions Cerebral hemodynamics in MCI patients was changed. The cognitive impairment was closely related to the increase of PI in MCA. DOI: 10.3969/j.issn.1672-6731.2017.01.011
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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) | 0.001 | 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".