Muscle sympathetic nervous activity in depressed patients before and after treatment with sertraline
Bibliographic record
Abstract
BACKGROUND: Sympathetic hyperactivity is one of the mechanisms involved in the increased cardiovascular risk associated with depression, and there is evidence that antidepressants decrease sympathetic activity. OBJECTIVES: We tested the following two hypotheses: patients with major depressive disorder with high scores of depressive symptoms (HMDD) have augmented muscle sympathetic nervous system activity (MSNA) at rest and during mental stress compared with patients with major depressive disorder with low scores of depressive symptoms (LMDD) and controls; sertraline decreases MSNA in depressed patients. METHODS: Ten HMDD, nine LMDD and 11 body weight-matched controls were studied. MSNA was directly measured from the peroneal nerve using microneurography for 3 min at rest and 4 min during the Stroop color word test. For the LMDD and HMDD groups, the tests were repeated after treatment with sertraline (103.3 +/- 40 mg). RESULTS: Resting MSNA was significantly higher in the HMDD [29.1 bursts/min (SE 2.9)] compared with LMDD [19.9 (1.6)] and controls [22.2 (2.0)] groups (P = 0.026 and 0.046, respectively). There was a significant positive correlation between resting MSNA and severity of depression. MSNA increased significantly and similarly during stress in all the studied groups. Sertraline significantly decreased resting MSNA in the LMDD group and MSNA during mental stress in LMDD and HMDD groups. Sertraline significantly decreased resting heart rate and heart rate response to mental stress in the HMDD group. CONCLUSION: Moderate-to-severe depression is associated with increased MSNA. Sertraline treatment reduces MSNA at rest and during mental challenge in depressed patients, which may have prognostic implications in this group.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".