利用电子健康记录开发和内部验证一种预后模型（P 风险），以改善初级保健人群中精神分裂症的预测：MAPPED 研究。

Developing and internally validating a prognostic model (P Risk) to improve the prediction of psychosis in a primary care population using electronic health records: The MAPPED study.

机构信息

Centre for Academic Mental Health, Bristol Medical School, Population Health Sciences, University of Bristol, Bristol, UK; National Institute for Health Research, Bristol Biomedical Research Centre, University Hospitals Bristol NHS Foundation Trust, University of Bristol, Bristol, UK.

National Institute for Health Research, Bristol Biomedical Research Centre, University Hospitals Bristol NHS Foundation Trust, University of Bristol, Bristol, UK; Centre for Academic Primary Care, Bristol Medical School, Population Health Sciences, University of Bristol, Bristol, UK.

出版信息

Schizophr Res. 2022 Aug;246:241-249. doi: 10.1016/j.schres.2022.06.031. Epub 2022 Jul 14.

DOI:10.1016/j.schres.2022.06.031

PMID:35843156

Abstract

BACKGROUND

An accurate risk prediction algorithm could improve psychosis outcomes by reducing duration of untreated psychosis.

OBJECTIVE

To develop and validate a risk prediction model for psychosis, for use by family doctors, using linked electronic health records.

METHODS

A prospective prediction study. Records from family practices were used between 1/1/2010 to 31/12/2017 of 300,000 patients who had consulted their family doctor for any nonpsychotic mental health problem. Records were selected from Clinical Practice Research Datalink Gold, a routine database of UK family doctor records linked to Hospital Episode Statistics, a routine database of UK secondary care records. Each patient had 5-8 years of follow up data. Study predictors were consultations, diagnoses and/or prescribed medications, during the study period or historically, for 13 nonpsychotic mental health problems and behaviours, age, gender, number of mental health consultations, social deprivation, geographical location, and ethnicity. The outcome was time to an ICD10 psychosis diagnosis.

FINDINGS

830 diagnoses of psychosis were made. Patients were from 216 family practices; mean age was 45.3 years and 43.5 % were male. Median follow-up was 6.5 years (IQR 5.6, 7.8). Overall 8-year psychosis incidence was 45.8 (95 % CI 42.8, 49.0)/100,000 person years at risk. A risk prediction model including age, sex, ethnicity, social deprivation, consultations for suicidal behaviour, depression/anxiety, substance abuse, history of consultations for suicidal behaviour, smoking history and prescribed medications for depression/anxiety/PTSD/OCD and total number of consultations had good discrimination (Harrell's C = 0.774). Identifying patients aged 17-100 years with predicted risk exceeding 1.0 % over 6 years had sensitivity of 71 % and specificity of 84 %.

FUNDING

NIHR, School for Primary Care Research, Biomedical Research Centre.

摘要

背景

准确的风险预测算法可以通过减少未治疗的精神病持续时间来改善精神病的预后。

目的

使用电子健康记录，为家庭医生开发和验证一种精神病风险预测模型。

方法

这是一项前瞻性预测研究。从 2010 年 1 月 1 日至 2017 年 12 月 31 日，使用来自 300000 名因任何非精神病心理健康问题而向家庭医生就诊的患者的家庭医生记录。记录来自临床实践研究数据链接黄金，这是一个英国家庭医生记录的常规数据库，与英国二级保健记录的常规数据库医院发病统计数据链接。每位患者有 5-8 年的随访数据。研究预测因子为研究期间或历史上，为 13 种非精神病心理健康问题和行为、年龄、性别、心理健康咨询次数、社会贫困、地理位置和种族而进行的咨询、诊断和/或开处方。结果是 ICD10 精神病诊断的时间。

结果

共诊断出 830 例精神病。患者来自 216 个家庭实践；平均年龄为 45.3 岁，43.5%为男性。中位随访时间为 6.5 年（IQR 5.6，7.8）。总体而言，8 年精神病发病率为 45.8（95%CI 42.8，49.0）/100000 人年。一个包含年龄、性别、种族、社会贫困、自杀行为咨询、抑郁/焦虑、物质滥用、自杀行为咨询史、吸烟史和开处方治疗抑郁/焦虑/创伤后应激障碍/强迫症以及咨询总数的风险预测模型具有良好的区分能力（哈雷尔 C=0.774）。在 6 年内预测风险超过 1.0%的 17-100 岁患者中，敏感性为 71%，特异性为 84%。