Of the many studies describing psychotic symptoms in schizophrenia, few have investigated their direct influence on prognosis.

We aimed to apply natural language-processing (NLP) algorithms in routine healthcare records to identify reported somatic passivity and thought interference symptoms (thought broadcasting, insertion and withdrawal), and determine associations with prognosis by an analysis of routine outcomes.

Four algorithms were thus developed on de-identified mental healthcare data from a large south London provider and were applied to ascertain recorded symptoms over the three months following first presentation to that service in a cohort of patients with a primary schizophreniform disorder (ICD-10 F20-F29) diagnosis. The primary binary dependent variable for logistic regression analyses was any negative outcome (Mental Health Act section, >2 antipsychotics prescribed, >22 days spent in crisis care) over the subsequent 2 years, adjusted for age, gender, ethnic group, neighbourhood deprivation, diagnostic group, and recorded paranoia, persecutory delusions or auditory hallucinations.

In 9,323 patients, final models indicated significant associations of this composite outcome with baseline somatic passivity (prevalence 4.9%; adjusted odds ratio 1.61, 95% CI 1.37-1.88), thought insertion (10.7%; 1.24, 1.15-1.55) and thought withdrawal (4.9%; 1.36, 1.10-1.69), but not independently with thought broadcast (10.3%; 1.05, 0.91-1.22).

Symptoms traditionally central to the diagnosis of schizophrenia, but under-represented in current diagnostic frameworks, were thus identified as important predictors of short- to medium-term prognosis.

No conflict of interest - past support from Janssen; GSK; Takeda; Induction Healthcare; Holmusk; the NIHR; SLaM NHS Trust; the MRC; KCL; the NIHR ARC; KCH NHS Trust; the Academy of Medical Sciences; The Wellcome Trust; BHF; Arthritis Research UK; the Roya

在描述精神分裂症精神病症状的许多研究中，很少有人研究它们对预后的直接影响。

我们旨在在常规医疗记录中应用自然语言处理 (NLP) 算法，以识别报告的躯体被动和思维干扰症状（思维传播、插入和撤回），并通过对常规结果的分析确定与预后的关联。

因此，根据来自伦敦南部一家大型医疗服务提供者的去识别化心理保健数据开发了四种算法，并应用于确定首次就诊后三个月内在一组原发性精神分裂症患者中记录的症状 (ICD-10 F20 -F29) 诊断。逻辑回归分析的主要二元因变量是随后 2 年内的任何负面结果（精神健康法案部分，> 2 种抗精神病药，> 22 天在危机护理中度过），根据年龄、性别、种族群体、邻里剥夺、诊断组，并记录偏执、被害妄想或幻听。

在 9,323 名患者中，最终模型表明该复合结果与基线躯体被动（患病率为 4.9%；调整后的比值比为 1.61，95% CI 1.37-1.88）、思想插入（10.7%；1.24、1.15-1.55）和思想戒断之间存在显着关联(4.9%; 1.36, 1.10-1.69)，但不是独立于思想传播 (10.3%; 1.05, 0.91-1.22)。

症状传统上是精神分裂症诊断的核心，但在当前的诊断框架中代表性不足，因此被确定为中短期预后的重要预测因子。

无利益冲突 - Janssen 过去的支持；葛兰素史克；武田; 感应医疗；霍尔木斯克；国家卫生研究院；SLaM NHS 信托；MRC；氯化钾；NIHR ARC；KCH NHS 信托；医学科学院；威康信托；BHF; 英国关节炎研究；罗亚