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OALib Journal期刊

ISSN: 2333-9721

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Simulation-Based Natural Language Processing of Synthetic Clinical Notes to Detect Early Linguistic Markers of Antidepressant-Induced Hypomania in Bipolar Disorder: A Proof-of-Concept Study  [PDF]
Rocco de Filippis, Abdullah Al Foysal
Open Access Library Journal (OALib Journal) , 2026, DOI: 10.4236/oalib.1115676
Abstract: Antidepressant-induced hypomania in bipolar disorder (BD) is a clinically consequential pharmacological safety event that may be preceded by changes in patient and clinician language. This proof-of-concept simulation study evaluates whether natural language processing (NLP) can recover such signals from fully synthetic outpatient clinical notes and simulated hypomania labels; it does not establish clinical validity. We generated one synthetic note for each of N = 700 simulated antidepressant-exposed BD patients (hypomania prevalence 25.1%). A three-tier feature architecture encoded: i) 18 psycholinguistic and syntactic features; ii) 30 latent semantic analysis components derived from TF-IDF representations; and iii) 12 simulated clinical meta-features. A four-layer multilayer perceptron, termed ClinicalBERT-sim to distinguish it from an actually fine-tuned ClinicalBERT model, was trained on the combined feature matrix. An out-of-fold stacking ensemble fused ClinicalBERT-sim, LightGBM, and Random Forest outputs. The proposed ensemble achieved AUC = 0.912 (95% CI: 0.842 - 0.969), F1 = 0.708, sensitivity = 0.595, and specificity = 0.974 on the held-out synthetic test set. SHAP analysis identified hypomanic term score, word count, energy word score, physician concern score, and positive affect ratio as the dominant simulated predictors. Longitudinal illustrative trajectories showed rising hypomanic term score and word count across simulated weekly notes before simulated onset. These findings demonstrate technical feasibility within the designed simulator, but performance may partly reflect the rules used to generate notes and labels. Validation on independently annotated, real outpatient BD notes is required before any clinical screening or workflow use.
Machine Learning Models for Predicting Antidepressant-Induced Mania in Bipolar Disorder: A Synthetic Proof-of-Concept Simulation Study  [PDF]
Rocco de Filippis, Abdullah Al Foysal
Open Access Library Journal (OALibJ) , 2026, DOI: 10.4236/oalib.1115140
Abstract: Antidepressant-induced mania represents a significant clinical challenge in the management of bipolar depression, with incidence rates ranging from 5% - 20% in clinical populations. Despite the widespread use of antidepressants in bipolar disorder, reliable methods for predicting individual susceptibility to manic switches remain elusive. This study presents a synthetic proof-of-concept simulation to evaluate machine learning models to predict antidepressant-induced mania using comprehensive clinical, genetic, and pharmacological data. We generated a synthetic clinical dataset of 2000 patients with bipolar disorder based on established clinical risk factors and epidemiological parameters. Five machine learning algorithms Logistic Regression, Random Forest, Gradient Boosting, Support Vector Machine (SVM), and Neural Network were trained and validated using 5-fold cross-validation. Model performance was evaluated using AUC-ROC, precision-recall metrics, and calibration analyses. Feature importance analysis identified key predictive variables. The Gradient Boosting model achieved the highest predictive performance (AUC-ROC = 0.926, 95% CI: 0.901 ± 0.011), followed by Random Forest (AUC-ROC = 0.909). The model successfully stratified patients into four risk quartiles with observed mania rates ranging from 0% in the lowest risk group to 61% in the highest risk group. Key predictive features included bipolar disorder subtype (Type I), absence of concurrent mood stabilizer treatment, rapid cycling history, polygenic risk scores for mania vulnerability, and antidepressant class (tricyclic antidepressants and MAOIs). Machine learning models demonstrate excellent predictive accuracy for antidepressant-induced mania and enable clinically actionable risk stratification. These findings demonstrate methodological feasibility within a simulated environment and establish a principled framework for future validation in real-world clinical cohorts. No clinical deployment conclusions can be drawn from synthetic data alone.
Pre-Initiation Prediction of Antidepressant-Associated Cycle Acceleration in Bipolar Disorder: A Synthetic Proof-of-Concept Study  [PDF]
Rocco De Filippis, Abdullah Al Foysal
Open Access Library Journal (OALib Journal) , 2026, DOI: 10.4236/oalib.1115670
Abstract: Antidepressant-associated cycle acceleration (AICA), encompassing antidepressant-related switching, rapid-cycling induction or acceleration, and mixed-state emergence, is an important treatment-safety concern in bipolar disorder (BD). Because these outcomes may be difficult to distinguish from spontaneous illness progression, pre-initiation risk stratification is clinically relevant. This proof-of-concept simulation study evaluates whether a multivariate machine-learning framework can recover prespecified AICA-risk structure from synthetic data; it does not test clinical effectiveness or establish a validated prediction tool. We developed an interpretable stacked ensemble using an entirely synthetic cohort of N = 850 simulated antidepressant-exposed patients with BD. No hospital records, registry observations, individual patient data, or hybrid clinical-synthetic records were used. The feature architecture integrated pharmacological history, episode chronology, and circadian digital biomarkers. Random Forest, XGBoost, and LightGBM were combined through a five-fold out-of-fold logistic-regression meta-learner and compared with five baseline models. Evaluation included held-out discrimination, calibration, decision-curve analysis, SHAP attribution, and exploratory model-fit summaries. On the held-out synthetic test set, the ensemble achieved AUC = 0.939 (95% CI: 0.889 - 0.976), F1 = 0.850 (95% CI: 0.754 - 0.929), sensitivity = 0.839 (95% CI: 0.704 - 0.949), and specificity = 0.946 (95% CI: 0.894 - 0.989). XGBoost had the lowest Brier score (0.077), followed closely by the ensemble (0.079). The ensemble showed the highest estimated net benefit across the reported threshold range in this synthetic test set. SHAP attribution ranked prior AICA history, interdaily stability, mood stabiliser adequacy, antidepressant-class risk, and mixed-episode fraction as the leading predictors, reflecting relationships embedded in the simulation design. The results demonstrate internal recovery of a synthetic risk-generating structure rather than prospective clinical validity. The model should therefore be regarded as a methodological and hypothesis-generating framework. Full disclosure of the simulator, robustness analyses under alternative label-generating assumptions, and validation in independently collected real-world cohorts are required before any prescribing recommendation, contraindication threshold, or clinical decision-support use can be considered.
Dosage-related nature of escitalopram treatment-emergent mania/hypomania: a case series
Sohei Kimoto,Takeshi Nagahama,Toshifumi Kishimoto,Yasunari Yamaguchi
- , 2018, DOI: 10.2147/NDT.S168078
Abstract: Several studies have documented that treatment with various antidepressant agents can result in mood switching during major depressive episodes. Escitalopram, one of the newer selective serotonin reuptake inhibitors (SSRIs), is considered preferable due to its relatively high efficacy and acceptability. Although a few cases of escitalopram treatment-emergent mania have been reported, it remains unknown whether this effect is dose-related
Women’s sexual dysfunction associated with psychiatric disorders and their treatment
Rosemary Basson,Thea Gilks
- , 2018, DOI: 10.1177/1745506518762664
Abstract: Impairment of mental health is the most important risk factor for female sexual dysfunction. Women living with psychiatric illness, despite their frequent sexual difficulties, consider sexuality to be an important aspect of their quality of life. Antidepressant and antipsychotic medication, the neurobiology and symptoms of the illness, past trauma, difficulties in establishing relationships and stigmatization can all contribute to sexual dysfunction. Low sexual desire is strongly linked to depression. Lack of subjective arousal and pleasure are linked to trait anxiety: the sensations of physical sexual arousal may lead to fear rather than to pleasure. The most common type of sexual pain is 10 times more common in women with previous diagnoses of anxiety disorder. Clinicians often do not routinely inquire about their patients’ sexual concerns, particularly in the context of psychotic illness but careful assessment, diagnosis and explanation of their situation is necessary and in keeping with patients’ wishes. Evidence-based pharmacological and non-pharmacological interventions are available but poorly researched in the context of psychotic illness
Associations between the Use of Antidepressants and Other Medications  [PDF]
Ray M. Merrill, Arielle A. Sloan
Open Journal of Depression (OJD) , 2014, DOI: 10.4236/ojd.2014.31007
Abstract: Purpose: The purpose of this study was to use a pharmacy claims database to identify associations between？and the timing of antidepressant and other medication use by age and sex. Material/Methods: A retrospective？cohort study was conducted of the 70,519 members of the Deseret Mutual Benefit Administrators？(DMBA) insurance company who were continuously covered from the years 2001-2011. Results:？During 2009-2011, 13.3% of males and 21.6% of females had at least one pharmacy claim for antidepressants.？Those prescribed one of 25 different drug classifications were more likely than the general？population to have used antidepressants the previous year. For all of the drug classifications, the use of？antidepressants was significantly more common the same year and the year after the drug was first prescribed.？The positive association between antidepressant use and other selected drug classifications generally？depended on age rather than sex, with the positive association more pronounced in the youngest age？group. Conclusion: The positive association between antidepressant use and other selected drug classifications？suggests that depression may both lead to and result from many chronic diseases. This association？is the strongest among younger individuals, so this age group proves a valuable target for public health？interventions.
Hypomania as an aura in migraine
Datta Soumitra,Kumar Sudhir
Neurology India , 2006,
Abstract: We report a 19-year-old man presenting to the department of Psychiatry for the evaluation of prominent behavioral symptoms associated with episodic headaches, with normal inter-episodic periods. A diagnosis of classic migraine with hypomanic aura was made. Other possible co-morbid or causative illnesses were excluded and preventive therapy with valproate was started due to the prominent affective symptoms as a part of the migranous aura. With this the frequency of headaches gradually decreased over the next four months. He was followed up for 2 years when he was found to be symptom-free. Recent research into the mechanisms of migraine has identified that the cortical hyperexcitability and an imbalance between neuronal inhibition and excitement mediated by gamma-aminobutyric acid and excitatory amino acids respectively may be the underlying mechanism. The high rate of affective disorders in patients with migraine, association of migraine with an aura comprising of mood symptoms and good response to treatment with mood-stabilisers might give newer insights into the pathophysiology of mood disorder as well.
Diagnóstico, tratamento e preven？？o da mania e da hipomania no transtorno bipolar
Moreno, Ricardo Alberto;Moreno, Doris Hupfeld;Ratzke, Roberto;
Revista de Psiquiatria Clínica , 2005, DOI: 10.1590/S0101-60832005000700007
Abstract: at least 5% (moreno, 2004 e angst et al., 2003) of the general population have presented mania or hypomania. irritability and depressive symptoms during brief hyperactivity episodes and the heterogeneity of symptoms complicate the diagnosis. neurological, metabolic, endocrine, inflammatory diseases, besides drugs intoxication and abstinence can cause a manic syndrome. sometimes hypomania or mania are misdiagnosed as normality, major depression, schizophrenia, personality, anxiety and impulse control disorders. lithium is the first treatment choice for episodes of mania. valproic acid, carbamazepine and atypical antipsychotics are frequently used as well. electroconvulsive therapy should be used in severe, psychotic or gestational mania. for the prophylaxy of manic episodes, lithium is the medication with most controlled studies. more studies are needed to investigate the prophylactic efficacy of valproate, olanzapine and other medications. the treatment and prophylaxis of hypomania remains understudied, and usually follows the guidelines used for mania.
Self Reported Hypomanic and Psychotic Symptoms are Positively Correlated in an International Sample of Undergraduate Students
T. Richardson,H. Garavan
Asian Journal of Epidemiology , 2009,
Abstract: This study aimed to examine whether self-reported hypomanic and psychotic symptoms are correlated in a non-clinical population. A sample of 303 undergraduates from the UK, Ireland, the US, Australia, New Zealand and Canada (14.7% male, 84.2% female, age 18-65) completed an online battery consisting of the 32-item Hypomania Checklist (HCL-32) and psychosis questions from the Diagnostic Interview Schedule (DIS-P). The HLC-32 total score correlated significantly with the DIS-P total score; rho = 0.16, p<0.01, DIS-P Delusional beliefs subscale; rho = 0.15, p<0.01 and DIS-P Hallucinatory experiences subscale; rho = 0.11, p<0.05. The HCL-32 Risk-Taking or Irritable subscale correlated with the DIS-P total score; rho = 0.26, p<0.001, Delusional beliefs subscale; rho = 0.26, p<0.001 and Hallucinatory experiences subscale; rho = 0.20, p<0.001. In conclusion, hypomanic symptoms appear to be related to psychotic symptoms in non-clinical populations, going against previous research suggesting that this is not the case.
Screening of the unrecognised bipolar disorders among outpatients with recurrent depressive disorder: a cross-sectional study in psychiatric hospital in Morocco
- , 2017, DOI: 10.11604/pamj.2017.27.247.8792
Abstract: The bipolar disorder is often misdiagnosed in particular among outpatients with recurrent depression. Indeed, this work confirmed that the unrecognised bipolar disorder is common among depressed outpatients, which were younger, unemployed, single or divorced with a low socio-economic level. These socio-demographics data gives us an idea about the disability experienced by the unknown bipolar patients. Also, we demonstrate that the under-diagnosis bipolar disorder was associated with the earliest onset age of a depressive episode and it was more prevalent in depressed patients with suicidal ideation and suicide attempts. These factors should be taken into account when we screen for the unknowm bipolar disorder, especially type II to improve the early diagnosis and the quality of life of these patients
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