Mentalizing abilities and serum lipid levels in adult MDD patients with childhood maltreatment – preliminary results
Bibliographic record
Abstract
Introduction Childhood maltreatment (CM) contributes to negative mental and physical health outcomes including major depressive disorder (MDD), and an elevated risk for cardiovascular disease (CDV) in adults. Also, childhood maltreatment can be related to mentalizing deficits in MDD. Cardio-metabolic diseases often coincide with MDD and worsen its course and outcome. Little is known on the interplay of these factors. Objectives We examined MDD patients with and without CM to explore the effects of CM on serum lipid and lipoprotein levels and assessed their mentalizing abilities. Self-oriented mentalizing was operationalized as emotional self-awareness/alexithymia, other-oriented mentalizing was defined as theory of mind (ToM). Methods MDD patients (N=42) and healthy controls (n=20) matched in age, sex, and lifestyle were investigated. Total cholesterol, triglycerides, high- and low-density lipoproteins (HDL-C and LDL-C), body mass index, and exercise in a typical week were measured. Beck Depression Inventory, Childhood Trauma Questionnaire, Toronto Alexithymia scale, and the Reading the mind in the Eyes Test were used to assess clinical symptoms, mentalizing abilities and CM. Results After controlling for depressive symptom severity, demographic and lifestyle variables, CM was found to be a strong predictor of serum lipid alterations. Mentalizing deficits correlated with CM. Serum triglycerides, HDL-C were significant predictors of ToM performance (P<0.05, and P=0.005) and alexithymia (P< 0.05, and P< 0.05) in the MDD group. Conclusions Several, inter-correlated pathways may mediate the undesirable effects of CM on the course and outcome of MDD. According to our preliminary results, diminished self-awareness and ToM can be possible mediating factors. Disclosure This work was financially supported by the Hungarian Brain Research Program (2017-1.2.1-NKP-2017-00002)
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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) | 0.000 | 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".