Diego Librenza-Garcia

Diego Librenza-Garcia
McMaster University | McMaster · Department of Psychiatry and Behavioural Neurosciences

MD

About

36
Publications
3,629
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350
Citations

Publications

Publications (36)
Article
Full-text available
The placebo effect across psychiatric disorders is still not well understood. In the present study, we conducted meta-analyses including meta-regression, and machine learning analyses to investigate whether the power of placebo effect depends on the types of psychiatric disorders. We included 108 clinical trials (32,035 participants) investigating...
Article
Schizophrenia (SZ) is a chronic debilitating disease. Subjects with SZ have significant shorter life expectancy. Growing evidence suggests that a process of pathological accelerated aging occurs in SZ, leading to early development of severe clinical diseases and worse morbimortality. Furthermore, unaffected relatives can share certain endophenotype...
Article
Full-text available
Importance: Large population-based data on the trajectory to disability after the first diagnosis of a mood disorder are lacking. Objective: To assess the time between an incident mood disorder diagnosis and the receipt of disability services during a follow-up period of as long as 20 years. Design, setting, and participants: This cohort study...
Chapter
Neuroprogression is associated with structural and functional brain changes that occur in parallel with cognitive and functioning impairments. There is substantial evidence showing early white matter changes, as well as trajectory-related gray matter alterations. Several structures, including prefrontal, parietal, temporal cortex, and limbic struct...
Article
Background Depression is highly prevalent and marked by a chronic and recurrent course. Despite being a major cause of disability worldwide, little is known regarding the determinants of its heterogeneous course. Machine learning techniques present an opportunity to develop tools to predict diagnosis and prognosis at an individual level. Methods W...
Article
Objective This study used machine learning techniques combined with peripheral biomarker measurements to build signatures to help differentiating (1) patients with bipolar depression from patients with unipolar depression, and (2) patients with bipolar depression or unipolar depression from healthy controls. Methods We assessed serum levels of int...
Article
Background: Childhood trauma is associated with psychosis in adults with bipolar disorder (BD). Although bullying represents a widespread form of childhood trauma, no studies thus far have investigated the association of bullying and psychosis in pediatric bipolar disorder (PBD). We aim to examine the association between psychosis in PBD with bull...
Article
Objectives: The International Society for Bipolar Disorders (ISBD) Big Data Task Force assembled leading researchers in the field of bipolar disorder (BD), machine learning, and big data with extensive experience to evaluate the rationale of machine learning and big data analytics strategies for BD. Method: A task force was convened to examine a...
Article
Pediatric Bipolar Disorder (PBD) is a highly heritable condition responsible for 18% of all pediatric mental health hospitalizations. Despite the heritability of this disorder, few studies have assessed potential differences in the clinical manifestation of PBD among patients with a clear parental history of BD. Additionally, while recent studies s...
Article
Background: Subjects with panic disorder are nearly 4 times as likely to attempt suicide as compared to subjects without this condition. Methods: We searched the literature from Jan 1, 1960 to May, 4, 2019. Articles that reported a dichotomous sample of patients with panic disorder with and without suicidal behavior were included. Outcomes: Tw...
Chapter
Data science is reshaping our world in ways we never experienced before. This transformation carries an enormous potential to improve mental health care and patient assessment. However, it is not only data gathering that is increasing at a high velocity, but also relevant ethical issues derived from its ownership, analysis, and impact in our lives....
Article
Full-text available
Background The present study analyzes the feasibility of text classification to predict individual suicidal behavior. Entries from Virginia Woolf’s diaries and letters were used to assess whether a text classification algorithm could identify written patterns associated with suicide. Methods This is a text classification study. We compared 46 text...
Data
Receiver Operating Characteristic curve of the text classification model with the criteria of at least 3 appearances. Results with the criteria of at least 3 appearances. Balanced Accuracy: 0.80. Sensitivity: 0.69. Specificity: 0.91. P-Value: 0.003. Kappa: 0.6. AUC: 0.80. (TIF)
Data
Common words written in the last 60 days before Virginia Woolf’s suicide. (PDF)
Data
Receiver Operating Characteristic curve of the text classification model with the criteria of at least 4 appearances. Results with the criteria of at least 4 appearances. Balanced Accuracy: 0.80. Sensitivity: 0.76. Specificity: 0.83. P-Value: 0.003. Kappa: 0.6. AUC: 0.80. (TIF)
Data
Words written in the last 60 days before Virginia Woolf’s suicide. (PDF)
Data
Words written outside the 60 days prior to Virginia Woolf’s suicide. (PDF)
Data
Word cloud of words written in randomly selected periods, outside the two months prior to Virginia Woolf’s suicide with the criteria of at least 3 appearances. (TIF)
Data
Receiver Operating Characteristic curve of the text classification model without words "and,” “one,” “the,” “but”. Results without words "and,” “one,” “the,” “but”. Balanced Accuracy: 0.59. Sensitivity: 0.94. Specificity: 0.25. P-Value: 0.42. Kappa: 0.22. AUC: 0.59. (TIF)
Data
Different words written in the last 60 days before Virginia Woolf’s suicide compared to outside the 60 days prior to Virginia Woolf’s suicide. (PDF)
Data
Word cloud of words written in the last 60 days before Virginia Woolf’s suicide with the criteria of at least 3 appearances. (TIF)
Data
Word cloud of words written in the last 60 days before Virginia Woolf’s suicide with the criteria of at least 4 appearances. (TIF)
Data
Word cloud of words written in randomly selected periods, outside the two months prior to Virginia Woolf’s suicide with the criteria of at least 3 appearances. (TIF)
Data
Word cloud of words written in the last 60 days before Virginia Woolf’s suicide without words "and,” “one,” “the,” “but”. (TIF)
Data
Word cloud of words written in randomly selected periods, outside the two months prior to Virginia Woolf’s suicide without words "and,” “one,” “the,” “but”. (TIF)
Poster
Cognitive functioning impairment prediction in patients with bipolar disorder: a pilot study using machine learning techniques. In: 20th Annual Conference of the International Society for Bipolar Disorders, 2018, Mexico City. Bipolar disorders, 2018. v. 20. p. 63-141.
Poster
Predicting functional impairment in bipolar disorder: a pilot study with a machine learning approach. In: 30th European College of Neuropsychopharmacology Congress, 2017, Paris.
Article
Full-text available
Accumulating evidence has shown the importance of glial cells in the neurobiology of bipolar disorder. Activated microglia and inflammatory cytokines have been pointed out as potential biomarkers of bipolar disorder. Indeed, recent studies have shown that bipolar disorder involves microglial activation in the hippocampus and alterations in peripher...
Article
Machine learning techniques provide new methods to predict diagnosis and clinical outcomes at an individual level. We aim to review the existing literature on the use of machine learning techniques in the assessment of subjects with bipolar disorder. We systematically searched PubMed, Embase and Web of Science for articles published in any language...
Article
Full-text available
Introduction: The longitudinal course of bipolar disorder is highly variable, and a subset of patients seems to present a progressive course associated with brain changes and functional impairment. Areas covered: We discuss the theory of neuroprogression in bipolar disorder. This concept considers the systemic stress response that occurs within mo...