Correlation between pulsatility index of medial cerebri artery and cognitive function in patients with diabetes mellitus type 2
Bibliographic record
Abstract
Background: Cognitive impairment is prevalent among cerebrovascular disease (CVD). Diabetes mellitus type 2 (DMT2) is a major risk factor of CVD. Gold standard used for diagnosing vascular cognitive impairment (VCI) required a combination of neurophysiological approach and magnetic resonance imaging (MRI). The Neurosonological approach, involving measuring the pulsatility index (PI) of the middle cerebral artery (MCA) using Trans Cranial Doppler (TCD) could be applied as an affordable alternative to predict VCI. The objective of this study was to revealed the correlation between PI MCS and cognitive function among DMT2 patients.Methods: This study was a cross-sectional survey in patients with DMT2 visiting Neurology and Endocrine Outpatient Clinics at Prof. Dr. R. D. Kandou Manado General Hospital, who meet the inclusion and exclusion criteria. Sixty (60) subjects were examined by TCD with 2 MHz to assess the hypo-perfusion level. Their cognitive were assessed with the Indonesian version of Montreal Cognitive Assessment (MoCa-Ina).Results: Right and left MCA median PI was 1.1 (IQR 0.9-1.4) and 1.0 (IQR 0.9-1.2) consecutively. MoCa-Ina median score was approximately 25 (IQR 22-26). Boxplot graph showed left PI MCA median score was higher in patients with normal cognitive function compared with cognitive impairment. Authors could not reach any significant statistical difference between PI MCA score and its correlation with cognitive function (p>0.05).Conclusions: Majority of patients with DMT2 have PI MCA score within normal range. Cognitive function among patient with DMT2 was mostly impaired. There is no correlation between PI MCA with cognitive function of patients with DMT2.
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 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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".