An electronic health records study of long-term weight gain following antidepressant use.

IMPORTANCE: Short-term studies suggest antidepressants are associated with modest weight gain but little is known about longer-term effects and differences between individual medications in general clinical populations. OBJECTIVE: To estimate weight gain associated with specific antidepressants over the 12 months following initial prescription in a large and diverse clinical population. DESIGN, SETTING, AND PARTICIPANTS: We identified 22,610 adult patients who began receiving a medication of interest with available weight data in a large New England health care system, including 2 academic medical centers and affiliated outpatient primary and specialty care clinics. We used electronic health records to extract prescribing data and recorded weights for any patient with an index antidepressant prescription including amitriptyline hydrochloride, bupropion hydrochloride, citalopram hydrobromide, duloxetine hydrochloride, escitalopram oxalate, fluoxetine hydrochloride, mirtazapine, nortriptyline hydrochloride, paroxetine hydrochloride, venlafaxine hydrochloride, and sertraline hydrochloride. As measures of assay sensitivity, additional index prescriptions examined included the antiasthma medication albuterol sulfate and the antiobesity medications orlistat, phentermine hydrochloride, and sibutramine hydrochloride. Mixed-effects models were used to estimate rate of weight change over 12 months in comparison with the reference antidepressant, citalopram. MAIN OUTCOME AND MEASURE: Clinician-recorded weight at 3-month intervals up to 12 months. RESULTS: Compared with citalopram, in models adjusted for sociodemographic and clinical features, significantly decreased rate of weight gain was observed among individuals treated with bupropion (ß [SE]: -0.063 [0.027]; P = .02), amitriptyline (ß [SE]: -0.081 [0.025]; P = .001), and nortriptyline (ß [SE]: -0.147 [0.034]; P < .001). As anticipated, differences were less pronounced among individuals discontinuing treatment prior to 12 months. CONCLUSIONS AND RELEVANCE: Antidepressants differ modestly in their propensity to contribute to weight gain. Short-term investigations may be insufficient to characterize and differentiate this risk.

QT interval and antidepressant use: a cross sectional study of electronic health records.

OBJECTIVE: To quantify the impact of citalopram and other selective serotonin reuptake inhibitors on corrected QT interval (QTc), a marker of risk for ventricular arrhythmia, in a large and diverse clinical population. DESIGN: A cross sectional study using electrocardiographic, prescribing, and clinical data from electronic health records to explore the relation between antidepressant dose and QTc. Methadone, an opioid known to prolong QT, was included to demonstrate assay sensitivity. SETTING: A large New England healthcare system comprising two academic medical centres and outpatient clinics. PARTICIPANTS: 38,397 adult patients with an electrocardiogram recorded after prescription of antidepressant or methadone between February 1990 and August 2011. MAIN OUTCOME MEASURES: Relation between antidepressant dose and QTc interval in linear regression, adjusting for potential clinical and demographic confounding variables. For a subset of patients, change in QTc after drug dose was also examined. RESULTS: Dose-response association with QTc prolongation was identified for citalopram (adjusted beta 0.10 (SE 0.04), P<0.01), escitalopram (adjusted beta 0.58 (0.15), P<0.001), and amitriptyline (adjusted beta 0.11 (0.03), P<0.001), but not for other antidepressants examined. An association with QTc shortening was identified for bupropion (adjusted beta 0.02 (0.01) P<0.05). Within-subject paired observations supported the QTc prolonging effect of citalopram (10 mg to 20 mg, mean QTc increase 7.8 (SE 3.6) ms, adjusted P<0.05; and 20 mg to 40 mg, mean QTc increase 10.3 (4.0) ms, adjusted P<0.01). CONCLUSIONS: This study confirmed a modest prolongation of QT interval with citalopram, and identified additional antidepressants with similar observed risk. Pharmacovigilance studies using electronic health record data may be a useful method of identifying potential risk associated with treatments.