Publications by authors named "Michelle Worthington"

11 Publications

  • Page 1 of 1

Effect of citalopram on hippocampal volume in first-episode schizophrenia: Structural MRI results from the DECIFER trial.

Psychiatry Res Neuroimaging 2021 Apr 7;312:111286. Epub 2021 Apr 7.

Department of Psychiatry, NYU Langone Health, 1 Park Avenue, New York, NY 10016, United States of America; Nathan Kline Institute for Psychiatric Research, 140 Old Orangeburg Road, Orangeburg, NY 10962, United States of America. Electronic address:

Hippocampal volume loss is prominent in first episode schizophrenia (FES) and has been associated with poor clinical outcomes and with BDNF genotype; antidepressants are believed to reverse hippocampal volume loss via release of BDNF. In a 12-month, placebo-controlled add-on trial of the antidepressant, citalopram, during the maintenance phase of FES, negative symptoms were improved with citalopram. We now report results of structural brain imaging at baseline and 6 months in 63 FES patients (34 in citalopram group) from the trial to assess whether protection against hippocampal volume loss contributed to improved negative symptoms with citalopram. Hippocampal volumetric integrity (HVI) did not change significantly in the citalopram or placebo group and did not differ between treatment groups, whereas citalopram was associated with greater volume loss of the right CA1 subfield. Change in cortical thickness was associated with SANS change in 4 regions (left rostral anterior cingulate, right frontal pole, right cuneus, and right transverse temporal) but none differed between treatment groups. Our findings suggest that minimal hippocampal volume loss occurs after stabilization on antipsychotic treatment and that citalopram's potential benefit for negative symptoms is unlikely to result from protection against hippocampal volume loss or cortical thinning.
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http://dx.doi.org/10.1016/j.pscychresns.2021.111286DOI Listing
April 2021

Association of Aripiprazole With Reduced Hippocampal Atrophy During Maintenance Treatment of First-Episode Schizophrenia.

J Clin Psychopharmacol 2021 May-Jun 01;41(3):244-249

Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai.

Purpose/background: Hippocampal volume loss in early schizophrenia has been linked with markers of inflammation and oxidative stress, and with less response of negative symptoms. Aripiprazole has been reported to preserve hippocampal volume and to reduce inflammation.

Methods/procedures: Study 1 was a 12-month multicenter randomized placebo-controlled trial of citalopram added to clinician-determined second-generation antipsychotic medication in 95 patients with first-episode schizophrenia (FES), 19 of whom received aripiprazole. We compared participants taking aripiprazole with those on other antipsychotics to determine whether those on aripiprazole had less hippocampal volume loss. We also examined peripheral biomarker data from medication-naive patients with schizophrenia receiving 8 weeks of antipsychotic treatment (n = 24) to see whether markers of inflammation and oxidative stress that previously predicted hippocampal volume differed between aripiprazole (n = 9) and other antipsychotics (study 2).

Findings/results: Aripiprazole was associated with a mean increase in hippocampal volume of 0.35% (SD, 0.80%) compared with a 0.53% decrease (SD, 1.2%) with other antipsychotics during the first year of maintenance treatment in patients with FES. This difference was significant after adjusting for age, sex, citalopram treatment, and baseline Brief Psychiatric Rating Scale score (B = 0.0079, P = 0.03). Aripiprazole was also associated with reduced concentrations of the inflammatory cytokines interleukin-8 and tumor necrosis factor (P < 0.01) during the first 8 weeks of treatment in medication-naive patients with FES.

Implications/conclusions: These results suggest that aripiprazole may protect against hippocampal atrophy via an anti-inflammatory mechanism, but these results require replication in larger, randomized trials, and the clinical relevance of hippocampal volume loss is not established.
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http://dx.doi.org/10.1097/JCP.0000000000001391DOI Listing
April 2021

Prospective prediction of PTSD diagnosis in a nationally representative sample using machine learning.

BMC Psychiatry 2020 11 10;20(1):532. Epub 2020 Nov 10.

Department of Counseling and Clinical Psychology, Teachers College, Columbia University, New York, USA.

Background: Recent research has identified a number of pre-traumatic, peri-traumatic and post-traumatic psychological and ecological factors that put an individual at increased risk for developing PTSD following a life-threatening event. While these factors have been found to be associated with PTSD in univariate analyses, the complex interactions of these risk factors and how they contribute to individual trajectories of the illness are not yet well understood. In this study, we examine the impact of prior trauma, psychopathology, sociodemographic characteristics, community and environmental information, on PTSD onset in a nationally representative sample of adults in the United States, using machine learning methods to establish the relative contributions of each variable.

Methods: Individual risk factors identified in Waves 1 of the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) were combined with community-level data for the years concurrent to the NESARC Wave 1 (n = 43,093) and 2 (n = 34,653) surveys. Machine learning feature selection and classification analyses were used at the national level to create models using individual- and community-level variables that would best predict the new onset of PTSD at Wave 2.

Results: Our classification algorithms yielded 89.7 to 95.6% accuracy for predicting new onset of PTSD at Wave 2. A prior diagnosis of DSM-IV-TR Borderline Personality Disorder, Major Depressive Disorder or Anxiety Disorder conferred the greatest relative influence in new diagnosis of PTSD. Distal risk factors such as prior psychiatric diagnosis accounted for significantly greater relative risk than proximal factors (such as adverse event exposure).

Conclusions: Our findings show that a machine learning classification approach can successfully integrate large numbers of known risk factors for PTSD into stronger models that account for high-dimensional interactions and collinearity between variables. We discuss the implications of these findings as pertaining to the targeted mobilization emergency mental health resources. These findings also inform the creation of a more comprehensive risk assessment profile to the likelihood of developing PTSD following an extremely adverse event.
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http://dx.doi.org/10.1186/s12888-020-02933-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7653804PMC
November 2020

Incorporating cortisol into the NAPLS2 individualized risk calculator for prediction of psychosis.

Schizophr Res 2021 Jan 9;227:95-100. Epub 2020 Oct 9.

Department of Psychology, Yale University, New Haven, CT, United States of America; Department of Psychiatry, Yale University, New Haven, CT, United States of America. Electronic address:

Background: Risk calculators are useful tools that can help clinicians and researchers better understand an individual's risk of conversion to psychosis. The North American Prodrome Longitudinal Study (NAPLS2) Individualized Risk Calculator has good predictive accuracy but could be potentially improved by the inclusion of a biomarker. Baseline cortisol, a measure of hypothalamic-pituitary-adrenal (HPA) axis functioning that is impacted by biological vulnerability to stress and exposure to environmental stressors, has been shown to be higher among individuals at clinical high-risk for psychosis (CHRP) who eventually convert to psychosis than those who do not. We sought to determine whether the addition of baseline cortisol to the NAPLS2 risk calculator improved the performance of the risk calculator.

Methods: Participants were drawn from the NAPLS2 study. A subset of NAPLS2 participants provided salivary cortisol samples. A multivariate Cox proportional hazards regression evaluated the likelihood of an individual's eventual conversion to psychosis based on demographic and clinical variables in addition to baseline cortisol levels.

Results: A total of 417 NAPLS2 participants provided salivary cortisol and were included in the analysis. Higher levels of cortisol were predictive of conversion to psychosis in a univariate model (C-index = 0.59, HR = 21.5, p-value = 0.004). The inclusion of cortisol in the risk calculator model resulted in a statistically significant improvement in performance from the original risk calculator model (C-index = 0.78, SE = 0.028).

Conclusions: Salivary cortisol is an inexpensive and non-invasive biomarker that could improve individual predictions about conversion to psychosis and treatment decisions for CHR-P individuals.
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http://dx.doi.org/10.1016/j.schres.2020.09.022DOI Listing
January 2021

Air pollution and hippocampal atrophy in first episode schizophrenia.

Schizophr Res 2020 04 10;218:63-69. Epub 2020 Mar 10.

NYU Langone Health Department of Psychiatry, New York, NY, United States of America; Nathan Kline Institute for Psychiatric Research, Orangeburg, NY, United States of America. Electronic address:

Air pollution has recently been linked to central nervous system (CNS) diseases, possibly mediated by inflammation and oxidative stress. Hippocampal atrophy in individuals with first episode schizophrenia (FES) has also been associated with biomarkers of inflammation and oxidative stress, whereas hippocampal atrophy was not observed in matched healthy controls with similar biomarker levels of inflammation and oxidative stress. Fine particulate matter (PM2.5), one component of air pollution, is most strongly implicated in CNS disease. The present study examined the association between PM2.5 and hippocampal volume in individuals with FES who participated in a 52-week placebo-controlled clinical trial of citalopram added to clinician-determined antipsychotic treatment at four sites in the US and China. Left hippocampal volumetric integrity (LHVI; inversely related to atrophy) was measured at baseline and week 52 using an automated highly-reliable algorithm. Mean annual PM2.5 concentrations were obtained from records compiled by the World Health Organization. The relationships between baseline LHVI and PM2.5 and change in LHVI and PM2.5 were evaluated using regression analyses. 89 participants completed imaging at baseline and 46 participants completed imaging at week 52. Mean annual PM2.5 was significantly associated with both baseline LHVI and change in LHVI after controlling for age, sex, baseline LHVI, duration of untreated psychosis and baseline antipsychotic medication dose. Air pollution may contribute to the progression of hippocampal atrophy after a first episode of illness, but these findings should be considered preliminary since other unmeasured factors may have differed between cities and contributed to the observed effect.
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http://dx.doi.org/10.1016/j.schres.2020.03.001DOI Listing
April 2020

Selection for psychosocial treatment for youth at clinical high risk for psychosis based on the North American Prodrome Longitudinal Study individualized risk calculator.

Early Interv Psychiatry 2021 Feb 14;15(1):96-103. Epub 2020 Jan 14.

Department of Psychology, Yale University, New Haven, Connecticut.

Aim: Recent findings suggest that family-focused therapy (FFT) is effective for individuals at clinical high-risk for psychosis (CHR-P). As outcomes of CHR-P individuals are quite varied, certain psychosocial interventions may be differentially effective in subgroups. The present study examined change in positive symptoms for CHR-P individuals at different levels of predicted risk for conversion to psychosis who received either FFT, a brief form of family education termed enhanced care (EC) or treatment as usual.

Methods: Participants were drawn from the North American Prodromal Longitudinal Study (NAPLS2). A subset of NAPLS2 participants completed a randomized study involving FFT or EC. The present study includes participants from the FFT-CHR sub-study and non-randomized NAPLS2 participants. Predicted risk of conversion was calculated using the Individualized Risk Calculator for Psychosis. Robust linear regressions evaluated whether the association between predicted risk of conversion and positive symptom change differed across intervention groups.

Results: A total of 94 participants from the FFT-CHR sub-study (FFT-CHR n = 50, EC n = 44) and 401 non-randomized NAPLS2 participants were included in this study. There was a treatment group by predicted risk of conversion interaction that predicted positive symptom improvement: higher risk individuals improved more with FFT-CHR than EC or the non-randomized NAPLS group, whereas lower-risk individuals did not differ in positive symptom improvement across treatment groups (FFT-CHR vs EC: P = .03, β = 20.27; FFT-CHR vs NAPLS2: P < .001, β = 28.40).

Conclusions: Intensive treatments such as FFT-CHR may be most appropriate for individuals at the highest levels of clinical risk for psychosis.
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http://dx.doi.org/10.1111/eip.12914DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7358123PMC
February 2021

Optical coherence tomography of the retina in schizophrenia: Inter-device agreement and relations with perceptual function.

Schizophr Res 2020 05 11;219:13-18. Epub 2020 Jan 11.

Department of Psychiatry, New York University School of Medicine, New York, NY, USA; Nathan Kline Institute for Psychiatric Research, Orangeburg, NY, USA. Electronic address:

Background: Optical coherence tomography (OCT) studies have demonstrated differences between people with schizophrenia and controls. Many questions remain including the agreement between scanners. The current study seeks to determine inter-device agreement of OCT data in schizophrenia compared to controls and to explore the relations between OCT and visual function measures.

Methods: Participants in this pilot study were 12 individuals with schizophrenia spectrum disorders and 12 age- and sex-matched controls. Spectralis and Cirrus OCT machines were used to obtain retinal nerve fiber layer (RNFL) thickness and macular volume. Cirrus was used to obtain ganglion cell layer + inner plexiform layer (GCL + IPL) thickness. Visual function was assessed with low-contrast visual acuity and the King-Devick test of rapid number naming.

Results: There was excellent relative agreement in OCT measurements between the two machines, but poor absolute agreement, for both patients and controls. On both machines, people with schizophrenia showed decreased macular volume but no difference in RNFL thickness compared to controls. No between-group difference in GCL + IPL thickness was found on Cirrus. Controls showed significant associations between King-Devick performance and RNFL thickness and macular volume, and between low-contrast visual acuity and GCL + IPL thickness. Patients did not show significant associations between OCT measurements and visual function.

Conclusions: Good relative agreement suggests that the offset between machines remains constant and should not affect comparisons between groups. Decreased macular volume in individuals with schizophrenia on both machines supports findings of prior studies and provides further evidence that similar results may be found irrespective of OCT device.
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http://dx.doi.org/10.1016/j.schres.2019.10.046DOI Listing
May 2020

Discovery and Validation of Prediction Algorithms for Psychosis in Youths at Clinical High Risk.

Biol Psychiatry Cogn Neurosci Neuroimaging 2020 08 4;5(8):738-747. Epub 2019 Nov 4.

Department of Psychology, Yale University, New Haven, Connecticut. Electronic address:

In the past 2 to 3 decades, clinicians have used the clinical high risk for psychosis (CHR-P) paradigm to better understand factors that contribute to the onset of psychotic disorders. While this paradigm is useful to identify individuals at risk, the CHR-P criteria are not sufficient to predict outcomes from the CHR-P population. Because approximately 25% of the CHR-P population will ultimately convert to psychosis, more precise methods of prediction are needed to account for heterogeneity in both risk factors and outcomes in the CHR-P population. To this end, several groups in recent years have used data-driven approaches to refine predictive algorithms to predict both conversion to psychosis and functional outcomes. These models have generally used either clinical and behavioral data, including demographics and measures of symptom severity, neurocognitive functioning, and social functioning, or neuroimaging data, including structural and functional measures, to predict conversion to psychosis in CHR-P samples. This review focuses on the empirical models that have been derived within each of these lines of research and evaluates the performance and methodology of these models. This review also serves to inform best practices for data-driven approaches and directions moving forward to improve our prediction of psychotic disorders and associated outcomes. Because sample size is still the most critical consideration in the current models, we urge that algorithms to predict conversion be conducted using multisite data in order to obtain the power necessary to conclusively determine predictive accuracy without overfitting.
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http://dx.doi.org/10.1016/j.bpsc.2019.10.006DOI Listing
August 2020

Citalopram in first episode schizophrenia: The DECIFER trial.

Schizophr Res 2019 06 30;208:331-337. Epub 2019 Jan 30.

National Clinical Research Center for Mental Disorders, Mental Health Institute, The Second Xiangya Hospital of Central South University, 139 Renmin Middle Road, Changsha, Hunan, China.

Antidepressants are frequently prescribed in first episode schizophrenia (FES) patients for negative symptoms or for subsyndromal depressive symptoms, but therapeutic benefit has not been established, despite evidence of efficacy in later-stage schizophrenia. We conducted a 52 week, placebo-controlled add-on trial of citalopram in patients with FES who did not meet criteria for major depression to determine whether maintenance therapy with citalopram would improve outcomes by preventing or improving negative and depressive symptoms. Primary outcomes were negative symptoms measured by the Scale for Assessment of Negative Symptoms and depressive symptoms measured by the Calgary Depression Scale for Schizophrenia; both were analyzed by an intent-to-treat, mixed effects, area-under-the-curve analysis to assess the cumulative effects of symptom improvement and symptom prevention over a one-year period. Ninety-five patients were randomized and 52 (54%) completed the trial. Negative symptoms were reduced with citalopram compared to placebo (p = .04); the effect size of citalopram versus placebo was 0.32 for participants with a duration of untreated psychosis (DUP) of <18 weeks (median split) and 0.52 with a DUP >18 weeks. Rates of new-onset depression did not differ between groups; improvement in depressive symptoms was greater with placebo than citalopram (p = .02). Sexual side effects were more common with citalopram, but overall treatment-emergent side effects were not increased compared to placebo. In conclusion, citalopram may reduce levels of negative symptoms, particularly in patients with longer DUP, but we found no evidence of benefit for subsyndromal depressive symptoms.
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http://dx.doi.org/10.1016/j.schres.2019.01.028DOI Listing
June 2019

A naturalistic retrospective review of weight gain in bipolar patients treated with second generation antipsychotics.

J Clin Psychopharmacol 2015 Apr;35(2):192-3

Department of Psychology, Columbia University, New York, NY Mood Disorders Research Program, Depression Center, Department of Psychiatry and Behavioral Sciences, University of Louisville, School of Medicine, Louisville, KY

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http://dx.doi.org/10.1097/JCP.0000000000000271DOI Listing
April 2015

Immune-modulating formulas: who wins the meta-analysis race?

Nutr Clin Pract 2011 Dec;26(6):650-5

NorthShore University Health System, 2650 Ridge Ave, Evanston, IL 60201, USA.

Most agree that enteral nutrition is the ideal way to feed critically ill patients who have a functional gastrointestinal tract, but selecting the appropriate enteral formula can be difficult. Specifically, the use of immune-modulating diets has brought much excitement as well as debate. Literature to date presents both positive and potential adverse effects. To aid the clinician in the decision-making process, this article reviews the current research and recommendations regarding the use of immune-modulating diets.
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http://dx.doi.org/10.1177/0884533611425799DOI Listing
December 2011