Capacity of cognitive control in patients with cerebral small vessel disease
Bibliographic record
Abstract
Objective To evaluate the capacity of cognitive control(CCC) in patients with cerebral small vessel disease(CSVD) and explore the relationship between CCC and cognitive function in CSVD, and to assess the predict value of CCC on the occurrence of CSVD. Methods Twenty-two patients with CSVD and twenty-three healthy controls were enrolled.All of them completed the majority function task-masked (MFT-M) and a set of neuropsychological tests.Neuropsychological test was performed by Montreal cognitive assessment (MoCA), verbal fluency test (VFT), Chinese auditory learning test (CAVLT), symbol digit modalities test (SDMT), digital span (DS), Stroop color word test (SCWT), color trail test (CTT) and Modified Boston naming test (Modified BNT). The predict value of CCC for the occurrence of CSVD was assessed with logistic regression analysis. Results CCC of patients with CSVD was lower than that of healthy control ((2.97±0.72)bps vs (3.53±0.62)bps, t=-2.704, P=0.01). Between patients with CSVD and healthy control, there were significant differences in MoCA ((22.24±4.58 vs (24.86±2.42), t=-2.334, P=0.026), VFT-animal (12(6) vs 15(6), Z=-2.965, P=0.003), VFT-vegetables and fruits ((13.79±3.81) vs (18.27±4.13), t=-3.592, P=0.001), CAVLT-immediate ((7.45±2.18) vs (9.11±2.08), t=-2.502, P=0.017), CAVLT-short term delay ((7.20±3.32) vs (10.76±3.08), t=-3.564, P=0.001), CAVLT-long term delay ((7.30±3.16) vs (10.29±3.18), t=-3.012, P=0.005), SDMT ((15.95±5.49) vs (23.41±12.73), t=-2.513, P=0.018), CTT-A (85.17(42.60) vs 55.50(52.65), Z=-2.965, P=0.003), CTT-B ((200.69±71.35) vs (132.44±53.66), t=3.556, P=0.001), and CTT-B-A ((104.13±53.31) vs (65.20±35.98), t=2.819, P=0.007). But there was no significant difference in VFT-word begin with Chinese characterwater((3.68±2.63) vs (5.44±2.71), t=-1.940, P=0.061), CAVLT-recognition (14(3) vs 14(4), Z=-0.524, P=0.601), DS-forward (7.0(3.0) vs 5.5(2.0), Z=-0.152, P=0.880), DS-backward (4(1) vs 4(2), Z=-1.044, P=0.297), SCWT ((9.50±9.28) vs (5.94±10.47), t=1.123, P=0.268), Modified BNT (14.0(3.0) vs 13.5(3.0), Z=-0.727, P=0.467) between CSVD patients and healthy controls.In patients with CSVD, CCC was positively correlated with scores of MoCA (r=0.551, P=0.010) and also with DS-forward (r=0.532, P=0.013) and SCWT (r=-0.487, P=0.040). Logistic regression analysis showed that CCC was an important variable in predicting the possibility of CSVD (B=-1.318, P=0.019, OR=0.268, 95%CI (0.089-0.808)). Conclusion Compared with the healthy control, CCC in patients with CSVD decreases significantly and CCC is related to the cognitive impairment.CCC can predict the possibility of CSVD. Key words: Cognitive control capacity; Cerebral small vessel disease; Cognitive function
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".