Assessing the links between childhood trauma, C-reactive protein and response to antidepressant treatment in patients with affective disorders
Bibliographic record
Abstract
Adverse Childhood Experiences (ACE) are a well-known risk-factor for depression. Additionally, (high-sensitive) C-reactive Protein (hsCRP) is elevated in subgroups of depressed patients and high following ACE. In this context the literature considers hsCRP and ACE to be associated with treatment resistant depression. With the data being heterogenous, this study aimed to explore the associations of ACE, hsCRP levels and response to antidepressant treatment in uni- and bipolar depression. N = 76 patients diagnosed with uni- or bipolar depression and N = 53 healthy controls were included. Treatment was over 6 weeks in an inpatient psychiatric setting within an observatory study design. Depressive symptoms were assessed by the Montgomery-Asberg Depression Rating Scale (MADRS), ACE were assessed by the Childhood Trauma Questionnaire (CTQ); the body-mass-index (BMI) and hsCRP were measured. HsCRP levels did not differ between the study population and the healthy controls. While the depressive symptoms decreased, the hsCRP levels increased. Sexual abuse was associated with significant higher and emotional abuse with lower levels of hsCRP after 6 weeks. The baseline hsCRP levels and the ACE subgroups did not show significant associations with the treatment response in unipolar depressed patients. The long-lasting effects of specific forms of ACE may have relevant impact on inflammation, supporting hsCRP to be a suitable biomarker. With ACE and hsCRP not showing any significant associations with treatment response in the unipolar depressed subgroup, a more differentiate research concerning biomarkers and treatment regimens is needed when talking about treatment response.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 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 | 0.001 |
| 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 teacher head, 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".