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Clinical Diagnosis and Treatment of Schizophrenia
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Clinical Diagnosis and Treatment of Schizophrenia

A special issue of Journal of Clinical Medicine (ISSN 2077-0383). This special issue belongs to the section "Mental Health".

Deadline for manuscript submissions: closed (20 September 2024) | Viewed by 8396

Special Issue Editor

Dr. Nathalie Coulon

E-Mail
Guest Editor
1. Laboratoire de Psychologie de la Perception, Université Paris Descartes, 8158 Paris, France
2. Fondation Fondamental, Créteil, France
3. Schizophrenia and Autism Expert Centers, Alpes Isere Hospital, Grenoble, France
Interests: childhood schizophrenia; autism; stress response; neurodevelopmental disorders; anorexia nervosa

Special Issue Information

Dear Colleagues,

Complex and chronic schizophrenia and schizophrenia spectrum disorders are present worldwide in all cultures. According to the WHO, it is one of the 10 most disabling diseases. However, giving a diagnosis is never easy for the subject, the families and sometimes even the teams, particularly with early-onset schizophrenia. Moreover, many unknows remain in this pathological spectrum regarding its limits and borders. Finding new markers and more precise clues to make progress in diagnosis and care, has been one of the challenges of recent years in terms of research. In this Special Issue, we welcome authors to submit their papers on the clinical and paraclinical (biological, imaging) advances that will help us to better understand schizophrenia spectrum disorders and early-onset schizophrenia in order to improve care.

Dr. Nathalie Coulon
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Clinical Medicine is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • schizophrenia
  • early-onset schizophrenia
  • very early-onset schizophrenia
  • diagnosis
  • care

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (4 papers)

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Research

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19 pages, 2476 KiB  
Article
Cognitive Impairments Related to COMT and Neuregulin 1 Phenotypes as Transdiagnostic Markers in Schizophrenia Spectrum Patients
by Mariana Bondrescu, Liana Dehelean, Simona Sorina Farcas, Ion Papava, Vlad Nicoras, Carla Andreea Podaru, Madalina Sava, Elena Sabina Bilavu, Sandra Putnoky and Nicoleta Ioana Andreescu
J. Clin. Med. 2024, 13(21), 6405; https://doi.org/10.3390/jcm13216405 - 25 Oct 2024
Viewed by 1019
Abstract
Background: Research on the interaction between antipsychotic treatment and cognitive dysfunction in schizophrenia spectrum disorders (SSDs) is extensive, yet the role of genetic polymorphisms in catechol-O-methyltransferase (COMT) and neuregulin 1 (NRG1) remains underexplored. Methods: This study evaluates the impact of COMT (rs4680) [...] Read more.
Background: Research on the interaction between antipsychotic treatment and cognitive dysfunction in schizophrenia spectrum disorders (SSDs) is extensive, yet the role of genetic polymorphisms in catechol-O-methyltransferase (COMT) and neuregulin 1 (NRG1) remains underexplored. Methods: This study evaluates the impact of COMT (rs4680) and NRG1 (rs3924999 and rs35753505) polymorphisms on cognitive functions in SSD patients. A cross-sectional study was conducted with fifty-four patients, assessed using the Positive and Negative Syndrome Scale (PANSS) and the CNS Vital Signs battery. Results: Significant cognitive function differences were observed across SSD diagnostic categories (p < 0.001). The NRG1 rs35753505 TT genotype was significantly associated with better verbal memory performance compared to the CC genotype (p = 0.03), while no significant differences were observed for other genotypes. The NRG1 rs3924999 AA genotype showed superior reasoning performance compared to AG and GG genotypes (p = 0.01), with AG and GG associated with lower scores (p = 0.01 and p = 0.02, respectively). Additionally, the COMT Val158Met genotype significantly influenced processing speed, with patients at the first episode of psychosis showing higher scores than chronic patients (p = 0.01). Conclusions: These findings suggest that NRG1 and COMT polymorphisms may influence cognitive domains in schizophrenia spectrum disorders, potentially informing personalized treatment and cognitive rehabilitation strategies. Full article
(This article belongs to the Special Issue Clinical Diagnosis and Treatment of Schizophrenia)
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7 pages, 202 KiB  
Communication
External Validation of a Machine Learning Model for Schizophrenia Classification
by Yupeng He, Kenji Sakuma, Taro Kishi, Yuanying Li, Masaaki Matsunaga, Shinichi Tanihara, Nakao Iwata and Atsuhiko Ota
J. Clin. Med. 2024, 13(10), 2970; https://doi.org/10.3390/jcm13102970 - 17 May 2024
Cited by 2 | Viewed by 1549
Abstract
Background and Objective: Excellent generalizability is the precondition for the widespread practical implementation of machine learning models. In our previous study, we developed the schizophrenia classification model (SZ classifier) to identify potential schizophrenia patients in the Japanese population. The SZ classifier has exhibited [...] Read more.
Background and Objective: Excellent generalizability is the precondition for the widespread practical implementation of machine learning models. In our previous study, we developed the schizophrenia classification model (SZ classifier) to identify potential schizophrenia patients in the Japanese population. The SZ classifier has exhibited impressive performance during internal validation. However, ensuring the robustness and generalizability of the SZ classifier requires external validation across independent sample sets. In this study, we aimed to present an external validation of the SZ classifier using outpatient data. Methods: The SZ classifier was trained by using online survey data, which incorporate demographic, health-related, and social comorbidity features. External validation was conducted using an outpatient sample set which is independent from the sample set during the model development phase. The model performance was assessed based on the sensitivity and misclassification rates for schizophrenia, bipolar disorder, and major depression patients. Results: The SZ classifier demonstrated a sensitivity of 0.75 when applied to schizophrenia patients. The misclassification rates were 59% and 55% for bipolar disorder and major depression patients, respectively. Conclusions: The SZ classifier currently encounters challenges in accurately determining the presence or absence of schizophrenia at the individual level. Prior to widespread practical implementation, enhancements are necessary to bolster the accuracy and diminish the misclassification rates. Despite the current limitations of the model, such as poor specificity for certain psychiatric disorders, there is potential for improvement if including multiple types of psychiatric disorders during model development. Full article
(This article belongs to the Special Issue Clinical Diagnosis and Treatment of Schizophrenia)
10 pages, 551 KiB  
Article
Cognitive Effects of Reducing First-Generation Antipsychotic Dose Compared to Switching to Ziprasidone in Long-Stay Patients with Schizophrenia
by Jan P. A. M. Bogers, Jasper A. Blömer and Lieuwe de Haan
J. Clin. Med. 2024, 13(7), 2112; https://doi.org/10.3390/jcm13072112 - 4 Apr 2024
Cited by 3 | Viewed by 1681
Abstract
Background: Cognitive impairment is a core symptom of schizophrenia and is associated with functional outcomes. Improving cognitive function is an important treatment goal. Studies have reported beneficial cognitive effects of the second-generation antipsychotic (SGA) ziprasidone. Reducing the dose of first-generation antipsychotics (FGA) might [...] Read more.
Background: Cognitive impairment is a core symptom of schizophrenia and is associated with functional outcomes. Improving cognitive function is an important treatment goal. Studies have reported beneficial cognitive effects of the second-generation antipsychotic (SGA) ziprasidone. Reducing the dose of first-generation antipsychotics (FGA) might also improve cognitive function. This study compared the cognitive effects in long-stay patients who were randomized to groups who underwent FGA dose reduction or switched to ziprasidone. Methods: High-dose FGA was reduced to an equivalent of 5 mg of haloperidol in 10 patients (FGA-DR-condition), and 13 patients switched to ziprasidone 80 mg b.i.d. (ZIPRA condition). Five domains of cognitive function were assessed before dose reduction or switching (T0) and after 1 year (T1). This study was approved by the ethics committee of the Open Ankh (CCMO number 338) and registered at the Netherlands Trial Register (code 5864). Results: Non-significant deterioration was seen in all cognitive domains studied in the FGA-DR condition, whereas there was a non-significant improvement in all cognitive domains in the ZIPRA condition. The most robust difference between conditions, in favor of ziprasidone, was in executive function. Conclusions: In patients with severe chronic schizophrenia, ziprasidone had a non-significant and very modest beneficial effect on cognitive function compared with FGA dose reduction. Larger trials are needed to further investigate this effect. Full article
(This article belongs to the Special Issue Clinical Diagnosis and Treatment of Schizophrenia)
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Review

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12 pages, 286 KiB  
Review
Unraveling the Boundaries, Overlaps, and Connections between Schizophrenia and Obsessive–Compulsive Disorder (OCD)
by Simone Pardossi, Alessandro Cuomo and Andrea Fagiolini
J. Clin. Med. 2024, 13(16), 4739; https://doi.org/10.3390/jcm13164739 - 12 Aug 2024
Cited by 2 | Viewed by 3472
Abstract
Schizophrenia (SCZ) and obsessive–compulsive disorder (OCD) typically have distinct diagnostic criteria and treatment approaches. SCZ is characterized by delusions, hallucinations, disorganized speech, and cognitive impairments, while OCD involves persistent, intrusive thoughts (obsessions) and repetitive behaviors (compulsions). The co-occurrence of these disorders increases clinical [...] Read more.
Schizophrenia (SCZ) and obsessive–compulsive disorder (OCD) typically have distinct diagnostic criteria and treatment approaches. SCZ is characterized by delusions, hallucinations, disorganized speech, and cognitive impairments, while OCD involves persistent, intrusive thoughts (obsessions) and repetitive behaviors (compulsions). The co-occurrence of these disorders increases clinical complexity and poses significant challenges for diagnosis and treatment. Epidemiological studies indicate a significant overlap, with prevalence rates of comorbid OCD in SCZ patients ranging from 12% to 25%, which is higher than in the general population. Etiological hypotheses suggest shared genetic, neurobiological, and environmental factors, with genetic studies identifying common loci and pathways, such as glutamatergic and dopaminergic systems. Neuroimaging studies reveal both overlapping and distinct neural abnormalities, indicating shared and unique neurobiological substrates. Environmental factors, like early life stressors and urbanicity, also contribute to the comorbidity. The overlapping clinical features of both disorders complicate diagnosis. Treatment approaches include combining SSRIs with antipsychotics and cognitive behavioral therapy (CBT). The complexity of SCZ and OCD comorbidity underscores the need for a dimensional, spectrum-based perspective on psychiatric disorders, alongside traditional categorical approaches, to improve diagnosis and treatment outcomes. Full article
(This article belongs to the Special Issue Clinical Diagnosis and Treatment of Schizophrenia)
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