Cognitive Profiles in Treatment-Resistant Late-Life Depression and Their Impact on Treatment Outcomes
Bibliographic record
Abstract
BACKGROUND: Late-life depression (LLD) is associated with cognitive impairment, but substantial heterogeneity exists among patients. Data on the extent of cognitive impairments are inconclusive, particularly in patients with treatment-resistant depression (TRD). We investigated the cognitive profiles of patients with treatment-resistant versus nonresistant LLD and aimed to identify distinct cognitive subgroups. We also examined whether cognitive subgroups responded differentially to treatment with bilateral repetitive transcranial magnetic stimulation (rTMS). METHODS: A total of 165 patients with LLD were divided into treatment-resistant and nonresistant groups and compared with healthy control participants on measures of executive function, information processing speed, verbal learning, and memory. Cluster analysis identified subgroups based on cognitive scores. Demographic and clinical variables, as well as outcomes with bilateral rTMS, were compared between cognitive subgroups. RESULTS: Patients with LLD, particularly TRD, exhibited significantly worse cognitive performance than healthy controls. A 3-cluster solution was found, including cognitively intact (n = 89), cognitively diminished (n = 29), and impaired memory (n = 47) subgroups. Both the cognitively diminished and impaired memory subgroups had more anxiety symptoms and a higher proportion of patients with TRD than the cognitively intact group, although the latter difference did not survive multiple comparison correction. No significant differences were observed in outcomes to rTMS treatment. CONCLUSIONS: Patients with LLD exhibited impairments across cognitive domains, which were more pronounced in TRD. Three cognitive subgroups responded similarly to rTMS treatment, indicating its effectiveness across cognitive profiles, especially when medications are not tolerated. Future research should examine the relationships among cognitive subgroups, cognitive decline, and neurodegeneration.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".