Low hedonic tone and attention-deficit hyperactivity disorder: risk factors for treatment resistance in depressed adults
Bibliographic record
Abstract
Background: The burdens imposed by treatment-resistant depression (TRD) necessitate the identification of predictive factors that may improve patient treatment and outcomes. Because depression and attention-deficit hyperactivity disorder (ADHD) are frequently comorbid and share a complex relationship, we hypothesized that ADHD may be a predictive factor for the diagnosis of TRD. This exploratory study aimed to determine the percentage of undetected ADHD in those with TRD and evaluate factors associated with treatment resistance and undetected ADHD in depressed patients. Subjects and methods: Adults referred (n=160) for psychiatric consultation completed a structured interview (MINI Plus, Mini International Neuropsychiatric Interview Plus) to assess the presence of psychiatric disorders. Results: TRD was significantly associated with the number of diagnoses ( P <0.001), past ( P <0.001) and present medications ( P <0.001), chronic anhedonia ( P =0.013), and suicide ideation ( P =0.008). Undetected ADHD was present in 34% of TRD patients. The number of referral diagnoses ( P <0.001), failed medications ( P =0.002), and past selective serotonin reuptake inhibitor failures ( P =0.035) were predictive of undetected ADHD in TRD. Conclusion: Undetected ADHD may be more prevalent among TRD patients than previously thought. In addition, TRD patients are more likely to present with psychiatric comorbidity than non-TRD patients. Screening patients with depression for the presence of ADHD and chronic anhedonia/low hedonic tone may help identify patients with TRD and undetected ADHD and improve treatment outcomes. Keywords: anhedonia, catecholamine, suicide, dopamine, attention, drug response
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".