早期精神病代谢风险计算器(PsyMetRiC):芬兰外部验证研究。

IF 5.3 2区 医学 Q1 PSYCHIATRY Acta Psychiatrica Scandinavica Pub Date : 2024-08-29 DOI:10.1111/acps.13752
Jaakko Keinänen, Saana Eskelinen, Tiina From, Heikki Laurikainen, Jarmo Hietala, Graham K Murray, Jaana Suvisaari, Benjamin I Perry
{"title":"早期精神病代谢风险计算器(PsyMetRiC):芬兰外部验证研究。","authors":"Jaakko Keinänen, Saana Eskelinen, Tiina From, Heikki Laurikainen, Jarmo Hietala, Graham K Murray, Jaana Suvisaari, Benjamin I Perry","doi":"10.1111/acps.13752","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>Accurate detection of cardiometabolic risk in early psychosis is crucial to reducing somatic morbidity and mortality in people with psychotic disorders. We conducted an external validation of the psychosis metabolic risk calculator (PsyMetRiC), a cardiometabolic risk prediction tool developed in the UK and tailored for young people with psychosis. We compared the predictive accuracy and clinical usefulness of PsyMetRiC and a general population-based risk prediction tool for type 2 diabetes, the Finnish Diabetes Risk Score (FINDRISC).</p><p><strong>Methods: </strong>We included first-episode psychosis and ultra-high-risk for psychosis patients without metabolic syndrome aged 18-35 years from the Helsinki Early Psychosis and Turku Early Psychosis Study cohorts. We tested two versions of PsyMetRiC: the full model including age, sex, ethnicity, body-mass index, smoking status, prescription of metabolically-active antipsychotic medication, high-density lipoprotein, and triglyceride concentrations, and the partial-model excluding biochemical predictors, and the simplified FINDRISC including BMI, sex, systolic blood pressure, and fasting glucose. Discrimination, calibration, and decision curve analyses were used to assess the predictive performance and clinical usefulness of both PsyMetRiC and FINDRISC. We performed a site-specific re-calibration of PsyMetRiC (PsyMetRiC-Fi).</p><p><strong>Results: </strong>The study sample consisted of 278 individuals (all White European ethnicity, 58.6% male, mean age 24.8 years, 37.8% smoking, mean BMI 23.5). Discrimination was marginally better in the PsyMetRiC full model (C = 0.72, 95% CI, 0.59-0.82) compared with partial model (C = 0.70, 95% CI 0.59-0.80) or FINDRISC (C = 0.63, 95% CI 0.54-0.71). Calibration plots displayed evidence of minor miscalibration for PsyMetRiC, which corrected following recalibration. Miscalibration was more pronounced for FINDRISC. Decision curve analysis showed that PsyMetRiC offers likely clinical usefulness in improving cardiometabolic risk management in early psychosis compared with giving everyone or no one an intervention.</p><p><strong>Conclusion: </strong>PsyMetRiC has utility in predicting cardiometabolic risk in Finnish patients with early psychosis. It has better discriminatory accuracy and offers more accurate risk prediction compared to other available strategies.</p>","PeriodicalId":108,"journal":{"name":"Acta Psychiatrica Scandinavica","volume":null,"pages":null},"PeriodicalIF":5.3000,"publicationDate":"2024-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Psychosis metabolic risk calculator (PsyMetRiC) in early psychosis: External validation study in Finland.\",\"authors\":\"Jaakko Keinänen, Saana Eskelinen, Tiina From, Heikki Laurikainen, Jarmo Hietala, Graham K Murray, Jaana Suvisaari, Benjamin I Perry\",\"doi\":\"10.1111/acps.13752\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Introduction: </strong>Accurate detection of cardiometabolic risk in early psychosis is crucial to reducing somatic morbidity and mortality in people with psychotic disorders. We conducted an external validation of the psychosis metabolic risk calculator (PsyMetRiC), a cardiometabolic risk prediction tool developed in the UK and tailored for young people with psychosis. We compared the predictive accuracy and clinical usefulness of PsyMetRiC and a general population-based risk prediction tool for type 2 diabetes, the Finnish Diabetes Risk Score (FINDRISC).</p><p><strong>Methods: </strong>We included first-episode psychosis and ultra-high-risk for psychosis patients without metabolic syndrome aged 18-35 years from the Helsinki Early Psychosis and Turku Early Psychosis Study cohorts. We tested two versions of PsyMetRiC: the full model including age, sex, ethnicity, body-mass index, smoking status, prescription of metabolically-active antipsychotic medication, high-density lipoprotein, and triglyceride concentrations, and the partial-model excluding biochemical predictors, and the simplified FINDRISC including BMI, sex, systolic blood pressure, and fasting glucose. Discrimination, calibration, and decision curve analyses were used to assess the predictive performance and clinical usefulness of both PsyMetRiC and FINDRISC. We performed a site-specific re-calibration of PsyMetRiC (PsyMetRiC-Fi).</p><p><strong>Results: </strong>The study sample consisted of 278 individuals (all White European ethnicity, 58.6% male, mean age 24.8 years, 37.8% smoking, mean BMI 23.5). Discrimination was marginally better in the PsyMetRiC full model (C = 0.72, 95% CI, 0.59-0.82) compared with partial model (C = 0.70, 95% CI 0.59-0.80) or FINDRISC (C = 0.63, 95% CI 0.54-0.71). Calibration plots displayed evidence of minor miscalibration for PsyMetRiC, which corrected following recalibration. Miscalibration was more pronounced for FINDRISC. Decision curve analysis showed that PsyMetRiC offers likely clinical usefulness in improving cardiometabolic risk management in early psychosis compared with giving everyone or no one an intervention.</p><p><strong>Conclusion: </strong>PsyMetRiC has utility in predicting cardiometabolic risk in Finnish patients with early psychosis. It has better discriminatory accuracy and offers more accurate risk prediction compared to other available strategies.</p>\",\"PeriodicalId\":108,\"journal\":{\"name\":\"Acta Psychiatrica Scandinavica\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":5.3000,\"publicationDate\":\"2024-08-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Acta Psychiatrica Scandinavica\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1111/acps.13752\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"PSYCHIATRY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Acta Psychiatrica Scandinavica","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1111/acps.13752","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PSYCHIATRY","Score":null,"Total":0}
引用次数: 0

摘要

导言:准确检测早期精神病患者的心脏代谢风险对于降低精神病患者的躯体发病率和死亡率至关重要。我们对精神病代谢风险计算器(PsyMetRiC)进行了外部验证,该计算器是英国开发的一种心脏代谢风险预测工具,专为患有精神病的年轻人量身定制。我们比较了 PsyMetRiC 和基于普通人群的 2 型糖尿病风险预测工具芬兰糖尿病风险评分(FINDRISC)的预测准确性和临床实用性:我们的研究对象包括赫尔辛基早期精神病研究队列和图尔库早期精神病研究队列中年龄在18-35岁之间、无代谢综合征的首发精神病患者和超高危精神病患者。我们测试了两个版本的 PsyMetRiC:包括年龄、性别、种族、体重指数、吸烟状况、代谢活性抗精神病药物处方、高密度脂蛋白和甘油三酯浓度在内的完整模型和排除生化预测因子的部分模型,以及包括体重指数、性别、收缩压和空腹血糖在内的简化 FINDRISC。我们使用辨别、校准和决策曲线分析来评估 PsyMetRiC 和 FINDRISC 的预测性能和临床实用性。我们对 PsyMetRiC(PsyMetRiC-Fi)进行了特定地点的重新校准:研究样本包括 278 人(均为欧洲白人,58.6% 为男性,平均年龄 24.8 岁,37.8% 吸烟,平均体重指数 23.5)。与部分模型(C = 0.70,95% CI 0.59-0.80)或 FINDRISC(C = 0.63,95% CI 0.54-0.71)相比,PsyMetRiC 完全模型(C = 0.72,95% CI,0.59-0.82)的识别率略高。校准图显示 PsyMetRiC 存在轻微的校准误差,在重新校准后得到纠正。FINDRISC 的误校正更为明显。决策曲线分析表明,与对所有人进行干预或不进行干预相比,PsyMetRiC 在改善早期精神病患者的心脏代谢风险管理方面可能具有临床实用性:结论:PsyMetRiC可用于预测芬兰早期精神病患者的心脏代谢风险。结论:PsyMetRiC可用于预测芬兰早期精神病患者的心脏代谢风险,与其他现有策略相比,它具有更好的鉴别准确性,并能提供更准确的风险预测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Psychosis metabolic risk calculator (PsyMetRiC) in early psychosis: External validation study in Finland.

Introduction: Accurate detection of cardiometabolic risk in early psychosis is crucial to reducing somatic morbidity and mortality in people with psychotic disorders. We conducted an external validation of the psychosis metabolic risk calculator (PsyMetRiC), a cardiometabolic risk prediction tool developed in the UK and tailored for young people with psychosis. We compared the predictive accuracy and clinical usefulness of PsyMetRiC and a general population-based risk prediction tool for type 2 diabetes, the Finnish Diabetes Risk Score (FINDRISC).

Methods: We included first-episode psychosis and ultra-high-risk for psychosis patients without metabolic syndrome aged 18-35 years from the Helsinki Early Psychosis and Turku Early Psychosis Study cohorts. We tested two versions of PsyMetRiC: the full model including age, sex, ethnicity, body-mass index, smoking status, prescription of metabolically-active antipsychotic medication, high-density lipoprotein, and triglyceride concentrations, and the partial-model excluding biochemical predictors, and the simplified FINDRISC including BMI, sex, systolic blood pressure, and fasting glucose. Discrimination, calibration, and decision curve analyses were used to assess the predictive performance and clinical usefulness of both PsyMetRiC and FINDRISC. We performed a site-specific re-calibration of PsyMetRiC (PsyMetRiC-Fi).

Results: The study sample consisted of 278 individuals (all White European ethnicity, 58.6% male, mean age 24.8 years, 37.8% smoking, mean BMI 23.5). Discrimination was marginally better in the PsyMetRiC full model (C = 0.72, 95% CI, 0.59-0.82) compared with partial model (C = 0.70, 95% CI 0.59-0.80) or FINDRISC (C = 0.63, 95% CI 0.54-0.71). Calibration plots displayed evidence of minor miscalibration for PsyMetRiC, which corrected following recalibration. Miscalibration was more pronounced for FINDRISC. Decision curve analysis showed that PsyMetRiC offers likely clinical usefulness in improving cardiometabolic risk management in early psychosis compared with giving everyone or no one an intervention.

Conclusion: PsyMetRiC has utility in predicting cardiometabolic risk in Finnish patients with early psychosis. It has better discriminatory accuracy and offers more accurate risk prediction compared to other available strategies.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Acta Psychiatrica Scandinavica
Acta Psychiatrica Scandinavica 医学-精神病学
CiteScore
11.20
自引率
3.00%
发文量
135
审稿时长
6-12 weeks
期刊介绍: Acta Psychiatrica Scandinavica acts as an international forum for the dissemination of information advancing the science and practice of psychiatry. In particular we focus on communicating frontline research to clinical psychiatrists and psychiatric researchers. Acta Psychiatrica Scandinavica has traditionally been and remains a journal focusing predominantly on clinical psychiatry, but translational psychiatry is a topic of growing importance to our readers. Therefore, the journal welcomes submission of manuscripts based on both clinical- and more translational (e.g. preclinical and epidemiological) research. When preparing manuscripts based on translational studies for submission to Acta Psychiatrica Scandinavica, the authors should place emphasis on the clinical significance of the research question and the findings. Manuscripts based solely on preclinical research (e.g. animal models) are normally not considered for publication in the Journal.
期刊最新文献
Issue Information Variation of subclinical psychosis as a function of population density across different European settings: Findings from the multi-national EU-GEI study. Risk and timing of postpartum depression in parents of twins compared to parents of singletons. Digital phenotyping in bipolar disorder: Using longitudinal Fitbit data and personalized machine learning to predict mood symptomatology. The risk of diabetes and HbA1c deterioration during antipsychotic drug treatment: A Danish two-cohort study among patients with first-episode schizophrenia.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1