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Objective: Amphetamine prescribing has increased in the United States in recent years. Previous research identified an increased risk of incident psychosis with prescription amphetamines. The purpose of this study was to examine the impact of dose levels of prescription amphetamines on the risk of this rare but serious adverse outcome. Methods: A case-control study using electronic health records was conducted to compare the odds of incident psychosis or mania with past-month exposure to prescription amphetamines. Case subjects were patients ages 16–35 hospitalized at McLean Hospital for incident psychosis or mania between 2005 and 2019. Control subjects were patients with an initial psychiatric hospitalization for other reasons, most commonly depression and/or anxiety. Amphetamine doses were converted to dextroamphetamine equivalents and divided into terciles. Secondary analyses evaluated the odds of psychosis or mania with methylphenidate use. Results: Among 1,374 case subjects and 2,748 control subjects, the odds of psychosis and mania were increased for individuals with past-month prescription amphetamine use compared with no use (adjusted odds ratio=2.68, 95% CI=1.90–3.77). A dose-response relationship was observed; high doses of amphetamines (>30 mg dextroamphetamine equivalents) were associated with 5.28-fold increased odds of psychosis or mania. Past-month methylphenidate use was not associated with increased odds of psychosis or mania compared with no use (adjusted odds ratio=0.91, 95% CI=0.54–1.55). Conclusions: Although use of hospitalized control subjects excludes individuals with less severe disease, leading to selection bias, the study results suggest that caution should be exercised when prescribing high doses of amphetamines, with regular screening for symptoms of psychosis or mania. [ABSTRACT FROM AUTHOR]

COVID‐19 can affect physical and mental health long after acute infection. In this descriptive study, 48 individuals hospitalized for COVID‐19 between April and May 2020 were interviewed regarding their experience with COVID‐19 after hospitalization. The mean age of participants was 51.1 (±11.91) years (range 25–65 years) and 26 (54.2%) were men. Individuals had a mean of 1.2 (±0.94) comorbidities associated with more severe COVID‐19, with hypertension (37.5%) being most common. Nineteen (39.6%) individuals required treatment in the intensive care unit. Participants were interviewed a median time of 553 days (IQR, 405.5−589.0) after discharge from the hospital. Thirty‐seven (77.1%) individuals had 5 or more persistent symptoms at time of interview with only 3 (6.3%) experiencing none. The most reported persistent symptoms were fatigue (79.2%), difficulty breathing (68.8%), and muscle weakness (60.4%). Poor quality of life was experienced by 39 (81.3%) participants and 8 (16.7%) had a posttraumatic stress disorder (PTSD) score within the clinical range for diagnosis. For multivariable analyses, persistent fatigue was significantly predicted by number of symptoms during acute COVID‐19 (t = 4.4, p < 0.001). Number of symptoms during acute COVID‐19 was also significantly associated with persistent dyspnea (t = 3.4, p = 0.002). Higher scores on the Chalder fatigue scale after COVID‐19 was significantly associated with poor quality of life (t = 2.6, p = 0.01) and PTSD symptomatology (t = 2.9, p = 0.008). More research is needed to highlight the wide range of resources those suffering from Long COVID require long after discharge. [ABSTRACT FROM AUTHOR]

Objective: The authors used a large clinical data set to determine which index diagnoses of schizophrenia spectrum disorder were new diagnoses.Methods: Using the Massachusetts All-Payer Claims Database (2012–2016), the authors identified patients with a schizophrenia spectrum disorder diagnosis in 2016 (index diagnosis) and then reviewed patients’ care histories for the previous 12, 24, 36, and 48 months to identify previous diagnoses. Logistic regression was used to examine patient characteristics associated with the index diagnosis being a new diagnosis.Results: Overall, 7,217 individuals ages 15–35 years had a 2016 diagnosis of schizophrenia spectrum disorder; 67.7% had at least 48 months of historical data. Among those with at least 48 months of care history, 23% had no previous diagnoses. Diagnoses from inpatient psychiatric admissions or among female or younger patients were more likely to represent new diagnoses, compared with diagnoses from most other diagnosis locations or among males or older age groups, and outpatient diagnoses were less likely to represent new diagnoses than were most other diagnosis settings. Reviewing 48 instead of 12 months of data reduced estimated rates of new diagnoses from 112 to 66 per 100,000 persons; historical diagnoses were detected for 61% and 77% of patients with 12 or 48 months of care history, respectively.Conclusions: Examining multiple years of patient history spanning all payers and providers is critical to identifying new schizophrenia spectrum disorder diagnoses in large data sets. Review of 48 months of care history resulted in lower rates of new schizophrenia spectrum disorder diagnoses than previously reported. [ABSTRACT FROM AUTHOR]

Tobacco use is the top preventable cause of early mortality in schizophrenia. Over 60% of people with schizophrenia smoke, three times the general prevalence. The biological basis of this increased risk is not understood, and existing interventions do not target schizophrenia-specific pathology. We therefore used a connectome-wide analysis to identify schizophrenia-specific circuits of nicotine addiction. We reanalyzed data from two studies: In Cohort 1, 35 smokers (18 schizophrenia, 17 control) underwent resting-state fMRI and clinical characterization. A multivariate pattern analysis of whole-connectome data was used to identify the strongest links between cigarette use and functional connectivity. In Cohort 2, 12 schizophrenia participants and 12 controls were enrolled in a randomized, controlled crossover study of nicotine patch with resting-state fMRI. We correlated change in network functional connectivity with nicotine dose. In Cohort 1, the strongest (p < 0.001) correlate between connectivity and cigarette use was driven by individual variation in default mode network (DMN) topography. In individuals with greater daily cigarette consumption, we observed a pathological expansion of the DMN territory into the identified parieto-occipital region, while in individuals with lower daily cigarette consumption, this region was external to the DMN. This effect was entirely driven by schizophrenia participants. Given the relationship between DMN topography and nicotine use we observed in Cohort 1, we sought to directly test the impact of nicotine on this network using an independent second cohort. In Cohort 2, nicotine reduced DMN connectivity in a dose-dependent manner (R = −0.50; 95% CI −0.75 to −0.12, p < 0.05). In the placebo condition, schizophrenia subjects had hyperconnectivity compared to controls (p < 0.05). Nicotine administration normalized DMN hyperconnectivity in schizophrenia. We here provide direct evidence that the biological basis of nicotine dependence is different in schizophrenia and in non-schizophrenia populations. Our results suggest the high prevalence of nicotine use in schizophrenia may be an attempt to correct a network deficit known to interfere with cognition. [ABSTRACT FROM AUTHOR]

Background: The prescription use of the stimulants methylphenidate and amphetamine for the treatment of attention deficit-hyperactivity disorder (ADHD) has been increasing. In 2007, the Food and Drug Administration mandated changes to drug labels for stimulants on the basis of findings of new-onset psychosis. Whether the risk of psychosis in adolescents and young adults with ADHD differs among various stimulants has not been extensively studied.Methods: We used data from two commercial insurance claims databases to assess patients 13 to 25 years of age who had received a diagnosis of ADHD and who started taking methylphenidate or amphetamine between January 1, 2004, and September 30, 2015. The outcome was a new diagnosis of psychosis for which an antipsychotic medication was prescribed during the first 60 days after the date of the onset of psychosis. To estimate hazard ratios for psychosis, we used propensity scores to match patients who received methylphenidate with patients who received amphetamine in each database, compared the incidence of psychosis between the two stimulant groups, and then pooled the results across the two databases.Results: We assessed 337,919 adolescents and young adults who received a prescription for a stimulant for ADHD. The study population consisted of 221,846 patients with 143,286 person-years of follow up; 110,923 patients taking methylphenidate were matched with 110,923 patients taking amphetamines. There were 343 episodes of psychosis (with an episode defined as a new diagnosis code for psychosis and a prescription for an antipsychotic medication) in the matched populations (2.4 per 1000 person-years): 106 episodes (0.10%) in the methylphenidate group and 237 episodes (0.21%) in the amphetamine group (hazard ratio with amphetamine use, 1.65; 95% confidence interval, 1.31 to 2.09).Conclusions: Among adolescents and young adults with ADHD who were receiving prescription stimulants, new-onset psychosis occurred in approximately 1 in 660 patients. Amphetamine use was associated with a greater risk of psychosis than methylphenidate. (Funded by the National Institute of Mental Health and others.). [ABSTRACT FROM AUTHOR]

The high prevalence of nicotine dependence contributes to excess mortality in schizophrenia. Cue reactivity, or the encounter of drug-related cues or contexts, triggers craving, drug-seeking, and relapse. Prior functional magnetic resonance imaging (fMRI) research indicates that individuals with schizophrenia have blunted neural responses to rewarding stimuli in association with more severe negative symptoms. The objectives of this study are to determine if smokers with schizophrenia have altered neural reactivity to smoking cues compared with non-psychiatrically ill smokers and to evaluate the influence of negative symptoms on cue reactivity. Twenty smokers with schizophrenia and 19 control smokers underwent fMRI while viewing smoking-related and neutral cues. The primary analysis was group comparison of Smoking-Neutral contrast using whole-brain analysis (Pcorrected < .05). Smokers with schizophrenia had significantly greater baseline carbon monoxide levels and longer duration of smoking, suggesting more nicotine use. While both groups had greater brain reactivity to smoking vs neutral cues, smokers with schizophrenia had significantly decreased cue reactivity (Smoking-Neutral) compared to controls in bilateral frontal midline regions. There were significant negative correlations between negative symptoms and frontal midline reactivity. Despite greater nicotine use, smokers with schizophrenia exhibited decreased smoking cue-induced neural reactivity in frontal midline regions, suggesting that increased smoking and low cessation rates in schizophrenia are not primarily driven by responses to smoking- related cues. The finding of negative correlations between cue reactivity and negative symptoms is consistent with previous research demonstrating decreased neural responses to rewarding cues, particularly in patients with negative symptoms. [ABSTRACT FROM AUTHOR]

In the context of these evolving definitions of bipolar disorder, differentiating that diagnosis from attention-deficit/hyperactivity disorder (ADHD) in pediatric patients is a challenging task. This work supports previous findings of shared genetic influence between ADHD and bipolar disorder and extends these findings to ADHD and hypomania in youth. Therefore, as the authors note, it is possible that the proportion of shared genetic variance between ADHD and hypomania may be inflated by overlap in mood-related symptoms between ADHD and hypomania that was not accounted for. [Extracted from the article]

Background: Women experience greater difficulty quitting smoking than men, which may be explained by sex differences in brain circuitry underlying cognitive control. Prior work has linked reduced interhemispheric executive control network (ECN) coupling with poor executive function, shorter time to relapse, and greater substance use. Lower structural connectivity between a key ECN hub, the dorsolateral prefrontal cortex (DLPFC), and the dorsal striatum (DS) also contributes to less efficient cognitive control recruitment, and reduced intrahemispheric connectivity between these regions has been associated with smoking relapse. Therefore, sex differences were probed by evaluating interhemispheric ECN and intrahemispheric DLPFC-DS connectivity. To assess the potential sex by nicotine interaction, a pilot sample of non-smokers was evaluated following acute nicotine and placebo administration.Methods: Thirty-five smokers (19 women) completed one resting state functional magnetic resonance imaging scan. Seventeen non-smokers (8 women) were scanned twice using a repeated measures design where they received 2 and 0 mg nicotine.Results: In smokers, women had less interhemispheric ECN and DLPFC-DS coupling than men. In non-smokers, there was a drug x sex interaction where women, relative to men, had weaker ECN coupling following nicotine but not placebo administration.Conclusions: The current work indicates that nicotine-dependent women, versus men, have weaker connectivity in brain networks critically implicated in cognitive control. How these connectivity differences contribute to the behavioral aspects of smoking requires more testing. However, building on the literature, it is likely these deficits in functional connectivity contribute to the lower abstinence rates noted in women relative to men. [ABSTRACT FROM AUTHOR]

Background: Nicotine-dependent individuals have altered activity in neurocognitive networks such as the default mode (DMN), salience (SN) and central executive networks (CEN). One theory suggests that, among chronic tobacco smokers, nicotine abstinence drives more DMN-related internal processing while nicotine replacement suppresses DMN and enhances SN and CEN. Whether acute nicotine impacts network dynamics in non-smokers is, however, unknown.Methods: In a randomized double-blind crossover study, 17 healthy non-smokers (8 females) were administered placebo and nicotine (2-mg lozenge) on two different days prior to collecting resting-state functional magnetic resonance imaging (fMRI). Previously defined brain states in 462 individuals that spatially overlap with well-characterized resting-state networks including the DMN, SN, and CEN were applied to compute state-specific dynamics at rest: total time spent in state, persistence in each state after entry, and frequency of state transitions. We examined whether nicotine acutely alters these resting-state dynamics.Results: A significant drug-by-state interaction emerged; post-hoc analyses clarified that, relative to placebo, nicotine suppressed time spent in a frontoinsular-DMN state (posterior cingulate cortex, medial prefrontal cortex, anterior insula, striatum and orbitofrontal cortex) and enhanced time spent in a SN state (anterior cingulate cortex and insula). No significant findings were observed for persistence and frequency.Conclusions: In non-smokers, nicotine biases resting-state brain function away from the frontoinsular-DMN and toward the SN, which may reduce internally focused cognition and enhance salience processing. While past work suggests nicotine impacts DMN activity, the current work shows nicotinic influences on a specific DMN-like network that has been linked with rumination and depression. [ABSTRACT FROM AUTHOR]

Objective: The authors utilized patient-reported outcomes from a large U.S. behavioral health care system to evaluate the strength of improvements in patients' self-perceived recovery during mental health treatment., Methods: This was a cohort study conducted with electronic health records from 2021-2022 Discovery Behavioral Health patients. Patients were grouped according to their 41-item Recovery Assessment Scale (RAS) scores at admission. Linear regression models accounting for patient characteristics were used to estimate RAS score changes from admission to discharge and RAS score at discharge., Results: Of 9,441 patients, those belonging to groups with lower RAS scores at admission showed substantial score improvements, although their scores at discharge were still much lower compared with those of patients with higher admission scores. Results were consistent across secondary analyses., Conclusions: Substantial improvements in recovery were evident during treatment, especially for patients with lower RAS scores at admission. The findings underline the importance of research into enhanced personalized treatment approaches to optimize recovery., Competing Interests: Dr. Moran reports being currently employed by Sage Therapeutics. The other authors report no financial relationships with commercial interests.

Background and Hypothesis: The onset of schizophrenia occurs after the age of 40 in up to 20% of cases. We aim to depict risk factors for first-episode psychosis after the age of 40 by comparing late-onset psychosis (LOP) patients to healthy age-matched controls., Study Design: In this case-control study using electronic health records, 142 individuals aged 40-65 years with an encounter for a first episode of psychosis between 2013 and 2021 were included. Four controls (N = 568) were matched to each case on age, sex, race, and year of encounter. Potential risk factors for the primary analysis were captured via structured data and text-mining of medical notes. Conditional logistic regression models were used to assess the odds of LOP with potential risk factors., Study Results: After adjusting for all variables in the main analysis, odds for LOP were increased by immigration (OR 3.30, 95% CI, 1.56-6.98), depression (OR 3.58, 95% CI, 2.01-6.38), anxiety (OR 2.12, 95% CI, 1.20-3.75), cannabis use (OR 3.00, 95% CI, 1.36-6.61), alcohol use disorder (OR 5.46, 95% CI, 2.41-12.36), polysubstance use (OR 4.22, 95% CI, 1.30-13.7), severe trauma (OR 2.29, 95% CI, 1.08-4.48), and caregiver burden (OR 15.26, 95% CI, 3.85-60.48)., Conclusions: Life stressors along with the effects of substance use and other psychiatric conditions may confer some risk to the development of LOP. Replication is required in independent prospective studies. Further research is necessary to truly parse out which of these factors belong on the causal pathway., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Early and accurate diagnosis is crucial for effective treatment and improved outcomes, yet identifying psychotic episodes presents significant challenges due to its complex nature and the varied presentation of symptoms among individuals. One of the primary difficulties lies in the underreporting and underdiagnosis of psychosis, compounded by the stigma surrounding mental health and the individuals' often diminished insight into their condition. Existing efforts leveraging Electronic Health Records (EHRs) to retrospectively identify psychosis typically rely on structured data, such as medical codes and patient demographics, which frequently lack essential information. Addressing these challenges, our study leverages Natural Language Processing (NLP) algorithms to analyze psychiatric admission notes for the diagnosis of psychosis, providing a detailed evaluation of rule-based algorithms, machine learning models, and pre-trained language models. Additionally, the study investigates the effectiveness of employing keywords to streamline extensive note data before training and evaluating the models. Analyzing 4,617 initial psychiatric admission notes (1,196 cases of psychosis versus 3,433 controls) from 2005 to 2019, we discovered that the XGBoost classifier employing Term Frequency-Inverse Document Frequency (TF-IDF) features derived from notes pre-selected by expert-curated keywords, attained the highest performance with an F1 score of 0.8881 (AUROC [95% CI]: 0.9725 [0.9717, 0.9733]). BlueBERT demonstrated comparable efficacy an F1 score of 0.8841 (AUROC [95% CI]: 0.97 [0.9580, 0.9820]) on the same set of notes. Both models markedly outperformed traditional International Classification of Diseases (ICD) code-based detection methods from discharge summaries, which had an F1 score of 0.7608, thus improving the margin by 0.12. Furthermore, our findings indicate that keyword pre-selection markedly enhances the performance of both machine learning and pre-trained language models. This study illustrates the potential of NLP techniques to improve psychosis detection within admission notes and aims to serve as a foundational reference for future research on applying NLP for psychosis identification in EHR notes., Competing Interests: CONFLICT OF INTEREST N/A

Introduction: Nicotinic acetylcholine receptors are present in the cerebral white matter (WM). We hypothesized that WM response to nicotine can be detected by diffusion tensor imaging (DTI); and that such responses may be associated with nicotine-led cognitive enhancement in sustained attention., Methods: A randomized, nicotine-placebo patch, crossover, double-blind clinical trial in two non-overlapping cohorts of smokers was used to test the hypothesis. The discovery cohort consisted of 39 subjects (N = 20/19 controls/schizophrenic patients, age = 36.8 ± 10.1 years) and the replication cohorts consisted of 38 healthy smokers (31.7 ± 10.5 years). WM integrity was measured by fractional anisotropy (FA) values for the whole brain and nine preselected WM tracts using tract-based-spatial-statistics., Results: Nicotine significantly enhanced FA values for the genu of corpus callosum compared with placebo (ΔFAgenu) (p = 0.01) in smokers with low recent smoking exposure as measured by low average cotinine level. This finding was replicated in the second cohort (p = 0.02). ΔFAgenu values explained 22% of variance in performance of a sustained attention task during the nicotine session (p = 0.006). However, this effect was limited to schizophrenia patients (r = 0.62 and 0.09; p = 0.003 and 0.7 for patients and controls, respectively)., Conclusion: Acute pharmacological influence of nicotine patch on WM integrity appeared present, but was dependent on nicotine intake from recent smoking. Change in the WM integrity in the genu of corpus callosum was associated with a significant proportion of variability of nicotine-led changes in sustained attention/working memory of the smokers. Further studies will be necessary to understand biophysical underpinning of the nicotine-related changes in FA.