Cognitive and gait effects of repetitive transcranial magnetic stimulation in middle aged and older persons with depression: A systematic review
Bibliographic record
Abstract
Background Late-life depression (LLD) is a growing public health concern with distinct cognitive and somatic symptom profiles compared to early-onset major depressive disorder (MDD). Repetitive transcranial magnetic stimulation (rTMS) has emerged as a non-invasive intervention for treatment-resistant depression (TRD), with increasing attention to its cognitive and motor effects. Methods This systematic review assessed the impact of rTMS on cognitive and gait outcomes in patients aged ≥50 with MDD or TRD. Literature searches were conducted in MEDLINE, CENTRAL, PsychINFO, and Embase. Seventeen trials involving rTMS and any comparator were included. Study characteristics, stimulation protocols, outcome domains, and adverse events were extracted and synthesized qualitatively. Results Global cognitive screening scores (e.g., MMSE, MoCA) largely remained stable, but more sensitive, domain-specific assessments revealed isolated improvements in memory and executive function. A subset of studies demonstrated clinically meaningful gains in gait speed, particularly among participants with baseline mobility limitations. While changes in gait variability were not consistently detected, these findings may nonetheless reflect emerging effects within motor domains. Across all trials, rTMS was well tolerated, with most adverse events being mild and transient; serious events were rare. Conclusions rTMS is a well-tolerated intervention with growing evidence for domain-specific cognitive enhancement and functional mobility gains in middle aged and older patients with MDD. Although heterogeneity and small sample sizes limit generalizability, the consistency of improvements in targeted domains signals real therapeutic potential. Future trials that adopt standardized protocols, longer follow-up, and refined outcome measures are poised to further establish rTMS as a valuable component of late-life depression management.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".