The International Mood Network (IMN) Nosology Project: differentiating borderline personality from bipolar illness

OBJECTIVE

The differential diagnosis of bipolar illness vs. borderline personality is controversial. Both conditions manifest impulsive behavior, unstable interpersonal relationships, and mood symptoms. This study examines whether and which mood clinical features can differentiate between both conditions.

METHOD

A total of 260 patients (mean ± standard deviation age 41 ± 13 years, 68% female) attending to a mood clinic were examined for diagnosis of bipolar illness and borderline personality disorder using SCID-I, SCID-II, and clinical mood criteria extracted from Mood Disorder Questionnaire (MDQ). They were analyzed using diagnoses as dependent variables. Predictors of bipolar and borderline diagnoses were identified by multivariable logistic regressions, and predictive validity of models was assessed using ROC curve analysis.

RESULTS

Bipolar illness was strongly predicted by elevated mood (OR = 4.02, 95% CI: 1.80-9.15), increased goal-directed activities (OR = 3.90, 95% CI: 1.73-8.96), and episodicity of mood symptoms (OR = 3.48, 95% CI 1.49-8.39). This triad model predicted bipolar illness with 88.7% sensitivity, 81.4% specificity, and obtained an auROC of 0.91 (95% CI: 0.76-0.96) and a positive predictive value of 85.1%. For borderline personality disorder, only female gender was a statistically significant predictor (OR = 3.41, 95% CI: 1.29-13.7), and the predictive model obtained an auROC of 0.67 (95% CI: 0.53-0.74).

CONCLUSION

In a mood disorder clinic setting, manic criteria and episodic mood course distinguished bipolar illness from borderline personality disorder.

High sodium intake is associated with increased glucocorticoid production, insulin resistance and metabolic syndrome

OBJECTIVE

High sodium (HS) diet is associated with hypertension (HT) and insulin resistance (IR). We evaluated whether HS diet was associated with a dysregulation of cortisol production and metabolic syndrome (MetS).

PATIENTS AND MEASUREMENTS

We recruited 370 adults (18-85 years, BMI 29·3 ± 4·4 kg/m(2) , 70% women, 72% HT, 61% MetS). HS diet (urinary sodium >150 mEq/day) was observed in 70% of subjects. We measured plasma hormones, lipid profile, urinary free cortisol (UFC) and cortisol tetrahydrometabolites (THM).

RESULTS

Urinary sodium was correlated with UFC (r = +0·45, P < 0·001), cortisol THM (r = +0·41, P < 0·001) and inversely with adiponectin, HDL and aldosterone, after adjusting by age, gender and BMI. Subjects with high, compared with adequate sodium intake (50-149 mEq/day) had higher UFC (P < 0·001), THM (P < 0·001), HOMA-IR (P = 0·04), HT (81% vs 50%, P < 0·001), MetS (69% vs 41%, P < 0·001) and lower adiponectin (P = 0·003). A multivariate predictive model adjusted by confounders showed a high discriminative capacity for MetS (ROC curve 0·878) using four clinical variables: HS intake [OR = 5·6 (CI 2·3-15·3)], HOMA-IR [OR 1·7 (1·3-2·2)] cortisol THM [OR 1·2 (1·1-1·4)] and adiponectin [OR = 0·9 (0·8-0·9)], the latter had a protective effect.

CONCLUSIONS

High sodium diet was associated with increased urinary cortisol and its metabolites. Also, HS diet was associated with HT, insulin resistance, dyslipidaemia and hypoadiponectinaemia, even when adjusting by confounding variables. Further, we observed that high salt intake, IR and higher cortisol metabolites, alone or combined in a clinical simple model, accurately predicted MetS status, suggesting an additive mechanism in obesity-related metabolic disorders.

A clinical predictive score for mood disorder risk in low-income primary care settings

BACKGROUND

Despite availability of validated screening tests for mood disorders, busy general practitioners (GPs) often lack the time to use them routinely. This study aimed to develop a simplified clinical predictive score to help screen for presence of current mood disorder in low-income primary care settings.

METHODS

In a cross-sectional study, 197 patients seen at 10 primary care centers in Santiago, Chile completed self-administered screening tools for mood disorders: the Patient Health questionnaire (PHQ-9) and the Mood Disorder Questionnaire (MDQ). To determine participants' current-point mood disorder status, trained clinicians applied a gold-standard diagnostic interview (SCID-I). A simplified clinical predictive model (CM) was developed based on clinical features and selected questions from the screening tools. Using CM, a clinical predictive score (PS) was developed. Full PHQ-9 and GP assessment were compared with PS.

RESULTS

Using multivariate logistic regression, clinical and demographic variables predictive of current mood disorder were identified for a simplified 8-point predictive score (PS). PS had better discrimination than GP assessment (auROC-statistic=0.80 [95% CI 0.72, 0.85] vs. 0.58 [95% CI 0.52, 0.62] p-value <0.0001), but not as good as the full PHQ-9 (0.89 [95% CI 0.85, 0.93], p-value=0.03). Compared with GP assessment, PS increased sensitivity by 50% at a fixed specificity of 90%. Administered in a typical primary care clinical population, it correctly predicted almost 80% of cases.

LIMITATIONS

Further research must verify external validity of the PS.

CONCLUSION

An easily administered clinical predictive score determined, with reasonable accuracy, the current risk of mood disorders in low-income primary care settings.

Affective temperaments in clinical practice: a validation study in mood disorders

BACKGROUND

We sought to examine correlations between clinical validators and temperaments in clinical practice.

METHODS

We provided the self-report TEMPS-A (50 item long) to 123 consecutive patients seen in the Mood Disorders Program of Tufts Medical Center. Temperament was assessed as cyclothymia, dysthymia, irritable or hyperthymia. Cut-offs were tested using (50%) and (75%) thresholds of affirmative responses, as well as highest percent for dominant temperament. We reported no dominant temperament at 75% cut-off . Multivariate regression modeling was conducted to assess confounding bias.

RESULTS

Using clinical and demographic validators, cyclothymia was the most strongly validated temperament, followed by dysthymia and hyperthymia. Irritable temperament did not appear to be valid in this sample. A 75% item endorsement cut-off appeared to identify clinically important temperaments in slightly less than half of this sample. Those without any temperament at 75% cut-off had better prognostic features. 50% cut-off was highly nonspecific, and poorly correlated with diagnostic validators.

CONCLUSIONS

Affective temperaments correlate with clinical validators, most robustly for cyclothymia. 75% cut-off on the TEMPS may provide a useful categorical definition of abnormal affective temperaments in mood disorders. With that definition, slightly less than one-half of patients with mood disorders have affective temperaments. Those without abnormal affective temperaments have better prognostic features.