Analysis of Clinical Efficacy, Negative Emotions and Cognitive Function of Sertraline Combined with Repetitive Transcranial Magnetic Stimulation for Depression and Anxiety
Bibliographic record
Abstract
To explore the effects of sertraline combined with repetitive transcranial magnetic stimulation on clinical efficacy, negative emotions and cognitive function in adolescent patients with depressive disorders and anxious features was the objective of this study. This study selected 119 adolescent individuals with depressive disorders and anxious features who were admitted to The First Affiliated Hospital of Air Force Military Medical University from April 2019 to April 2022 and followed up for 1 y. All the individuals were divided into control (n=55) and research groups (n=64). The control group received sertraline and a research group receiving sertraline with repetitive transcranial magnetic stimulation. The clinical efficacy, negative emotions, cognitive function, adverse event rate and recurrence rate were comparatively analyzed. Among them, negative emotions were mainly assessed by the Hamilton depression and anxiety scales scores. Similarly, cognitive function was evaluated by the Montreal cognitive assessment scale and Wisconsin card sorting test and adverse event rate was statistically analyzed by observing nausea, anorexia, dizziness and drowsiness. Compared with the control group, the total effective rate of the research group was significantly higher; scores of Hamilton depression and anxiety, number of wrong answers and persistent errors were significantly lower after treatment. Montreal cognitive assessment score, total number of replies, number of number of correct answers and number of number of classifications completed were significantly higher after treatment. No notable difference was identified between groups in the adverse event rate. However, the recurrence rate within 12 mo was lower in the research group. Sertraline combined with repetitive transcranial magnetic stimulation has a definite clinical effect on adolescent patients with depressive disorders and anxious features, which can significantly relieve anxiety and depression, and improve cognitive function while not increasing the risk of adverse drug events, with a lower 1 y recurrence risk.
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 | 0.001 | 0.001 |
| 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) | 0.000 | 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".