Patterns of brain structural alteration in COPD with different levels of pulmonary function impairment and its association with cognitive deficits
Bibliographic record
Abstract
Abstract Background To explore patterns of brain structural alteration in chronic obstructive pulmonary disease (COPD) patients with different levels of lung function impairment and the associations of those patterns with cognitive functional deficits using voxel-based morphometry (VBM) and tract-based spatial statistics (TBSS) analyses based on high-resolution structural MRI and diffusion tensor imaging (DTI). Methods A total of 115 right-handed participants (26 severe, 29 moderate, and 29 mild COPD patients and a comparison group of 31 individuals without COPD) completed tests of cognitive (Montreal Cognitive Assessment [MoCA]) and pulmonary function (forced expiratory volume in 1 s [FEV1]) and underwent MRI scanning. VBM and TBSS analyses were used to identify changes in grey matter density (GMD) and white matter (WM) integrity in COPD patients. In addition, correlation analyses between these imaging parameter changes and cognitive and pulmonary functional impairments were performed. Results There was no significant difference in brain structure between the comparison groups and the mild COPD patients. Patients with moderate COPD had atrophy of the left middle frontal gyrus and right opercular part/triangular part of the inferior frontal gyrus, and WM changes were present mainly in the superior and posterior corona radiata, corpus callosum and cingulum. Patients with severe COPD exhibited the most extensive changes in GMD and WM. Some grey matter (GM) and WM changes were correlated with MoCA scores and FEV1. Conclusions These findings suggest that patients with COPD exhibit progressive structural impairments in both the GM and the WM, along with impaired levels of lung function, highlighting the importance of early clinical interventions.
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".