Diagnosis and Treatment of Comorbid Borderline Personality Disorder and Substance Use Disorder
Bibliographic record
Abstract
Environ 1% de la population générale répond aux critères du diagnostic de trouble de personnalité limite (TPL). Chez ces personnes, la prévalence du trouble lié à l’usage de substance(s) (TLU) au cours de la vie est très élevée. Les patients souffrant à la fois de TPL et de TLU semblent être une sous-population plus handicapée. Ils se présentent avec un début précoce de TLU, une augmentation de la gravité de l’addiction, et une plus grande altération du fonctionnement. Il existe seulement une petite quantité de données disponibles sur les approches de traitement pour TLU et TPL. Par conséquent, nous avons décidé de présenter un cas typique d’un patient présentant une TPL et un TLU concomitants et d’examiner la littérature sur les différentes approches thérapeutiques disponibles pour ces patients. À la lumière des données limitées disponibles, il semble que le traitement pharmacologique du trouble lié à l’usage d’alcool (TLUA) chez les patients souffrant de TPL et d’TLUA concomitants, devrait être considéré précocement dans le processus thérapeutique car les preuves ne montrent aucunement qu’il soit moins efficace dans ce sous-groupe. Nous pouvons également affirmer que ces patients sont susceptibles de répondre aux soins intégratifs structurés, y compris la thérapie comportementale dialectique adaptée pour TLU, la pharmacothérapie de prévention des rechutes basée sur des preuves pour la dépendance et les programmes 12 étapes. La psychothérapie dynamique reconstructive pourrait également être bénéfique, mais les résultats des études devraient être reproduits. La thérapie à schéma à double-focus semblait offrir des avantages limités et inconsistants. Dans cet article, nous voulions exprimer la nécessité d’approches intégratives, en particulier chez les patients souffrant de TPL et de TLU, qui ont tendance à être marginalisés. ABSTRACT Approximately 1% of the general population meets criteria for borderline personality disorder (BPD) diagnosis. In these individuals, the lifetime prevalence of substance use disorder (SUD) is very high. The patients suffering from both BPD and SUD seem to be a more impaired subpopulation. They present with an earlier onset of SUD, an increased addiction severity, and greater impairment in functioning. There is only a small amount of data available on treatment approaches for co-occurring SUD and BPD. Therefore, we decided to present a typical case of a patient presenting with concurrent BPD and SUD and to review the literature of the different treatment approaches available for these patients. In light of the limited data available, it seems that the pharmacological treatment of alcohol use disorder (AUD), in patients suffering from concurrent BPD and AUD, should be considered early in the therapeutic process as the evidence does not show that it less efficacious in this subgroup. We can also affirm that these patients are likely to respond to structured integrative care, including Dialectical Behavioral Therapy for SUD, evidence-based relapse prevention pharmacotherapy for addiction and 12 steps programs. Deconstructive Dynamic Psychotherapy could also be beneficial, but the results of the studies would need to be replicated. Dual-Focus Schema Therapy appeared to offer limited and inconsistent benefits. In this article, we wanted to convey the need for comprehensive approaches, specifically with patients suffering from BPD and SUD, who tend to be marginalized.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".