| Autor: |
Akira Sato, Norio Watanabe, Kazushi Maruo, Toshihiro Moriyama, Toshi A. Furukawa |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
|
| Zdroj: |
Diagnostic and Prognostic Research, Vol 6, Iss 1, Pp 1-9 (2022) |
| Druh dokumentu: |
article |
| ISSN: |
2397-7523 |
| DOI: |
10.1186/s41512-022-00134-w |
| Popis: |
Abstract Background Schizophrenia is a severe mental illness characterized by recurrent psychoses that typically waxes and wanes through its prodromal, acute, and chronic phases. A large amount of research on individual prognostic factors for relapse in people with schizophrenia has been published, and a few logistic models exist to predict psychotic prognosis for people in the prodromal phase or after the first episode of psychosis. However, research on prediction models for people with schizophrenia, including those in the chronic phase and after multiple recurrences, is scarce. We aim to develop and validate a prediction model for this population. Methods This is a retrospective cohort study to be undertaken in Japan. We will include participants aged 18 years or above, diagnosed with schizophrenia or related disorders, and discharged between January 2014 and December 2018 from one of the acute inpatient care wards of three geographically distinct psychiatric hospitals. We will collect pre-specified nine predictors at the time of recruitment, follow up the participants for 12 months after discharge, and observe whether our primary outcome of a relapse occurs. Relapse will be considered to have occurred in one of the following circumstances: (1) hospitalization; (2) psychiatrist’s judgment that the person needs hospitalization; (3) increasing doses of antipsychotics; or (4) suicidal or homicidal ideation or behavior resulting from such ideation. We will develop a Cox regression model and avoid overfitting by penalizing coefficients using the elastic net. The model will be validated both internally and externally by bootstrapping and “leave-one-hospital-out” cross-validation, respectively. We will evaluate the model’s performance in terms of discrimination and calibration. Decision curve analysis will be presented to aid decision-making. We will present a web application to visualize the model for ease of use in daily practice. Discussion This will be the first prediction modeling study of relapse after discharge among people with both first and multiple episodes of schizophrenia using routinely collected data. Trial registration This study was registered in the UMIN-CTR (UMIN000043345) on February 20, 2021. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
|
Full text from SpringerLink