Relationship between heart rate variability and cognitive function in patients with enlarged perivascular space
Bibliographic record
Abstract
Objective To explore the relationship between heart rate variability (HRV), the brain distribution of enlarged perivascular space (EPVS), and cognitive impairment in patients with EPVS. Materials and methods The clinical and imaging data of 199 patients with EPVS were retrospectively analyzed. EPVS load in the basal ganglia (BG) and centrum semiovale (CS) regions were assessed using the Potter’s method. Cognitive function was evaluated using the Montreal Cognitive Assessment Scale. A logistic regression model was used to analyze the relationship between HRV, the brain distribution of EPVS and cognitive function in patients with EPVS. A receiver operating characteristic curve was used to assess the predictive value of HRV for cognitive function in patients with EPVS. Results Of the 199 patients, 27 and 42 presented with severe BG-EPVS and cognitive impairment, respectively. Significant differences were observed in the root mean square of successive differences of normal-normal (NN) intervals for period of interest (rMSSD), the percentage of adjacent NN intervals greater than 50 ms (PNN50), and the ratio of low-frequency power (LF) to high-frequency power (HF) between the mild and severe BG-EPVS groups (P < 0.05). Patients who presented with and without cognitive impairment differed significantly in the standard deviation of NN intervals (SDNN), rMSSD, PNN50, total power, LF, and LF/HF (P < 0.05). rMSSD (odds ratio [OR] 0.871, 95% confidence interval [CI] 0.768–0.988) and LF/HF (OR 3.854, 95% CI 1.196–12.419) were independent influencing factors of BG-EPVS, and rMSSD (OR 0.936, 95% CI 0.898–0.976) was an independent influencing factor of cognitive impairment in patients with EPVS. The optimal cut-off point was 0.312, with an area under the curve of 0.795 (95% CI 0.719–0.872) for predicting cognitive impairment in patients with EPVS by rMSSD. Conclusion Reduced HRV is involved in the pathophysiological mechanisms of the formation and development of BG-EPVS and is associated with cognitive impairment in patients with EPVS, independent of CS-EPVS. For patients with HRV changes but without autonomic nervous system symptoms, positive intervention may slow the occurrence or progression of EPVS and cognitive impairment in patients with EPVS.
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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 | 0.000 |
| 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".