Immanuel Sarah A, Schrader Geoff, Bidargaddi Niranjan
College of Medicine and Public Health, Flinders University, Adelaide, SA, Australia.
Flinders Digital Health Research Centre, Flinders University, Adelaide, SA, Australia.
Front Psychiatry. 2021 Feb 22;12:558056. doi: 10.3389/fpsyt.2021.558056. eCollection 2021.
Multiple relapses over time are common in both affective and non-affective psychotic disorders. Characterizing the temporal nature of these relapses may be crucial to understanding the underlying neurobiology of relapse. Anonymized records of patients with affective and non-affective psychotic disorders were collected from SA Mental Health Data Universe and retrospectively analyzed. To characterize the temporal characteristic of their relapses, a relapse trend score was computed using a symbolic series-based approach. A higher score suggests that relapse follows a trend and a lower score suggests relapses are random. Regression models were built to investigate if this score was significantly different between affective and non-affective psychotic disorders. Logistic regression models showed a significant group difference in relapse trend score between the patient groups. For example, in patients who were hospitalized six or more times, relapse score in affective disorders were 2.6 times higher than non-affective psychotic disorders [OR 2.6, 95% CI (1.8-3.7), < 0.001]. The results imply that the odds of a patient with affective disorder exhibiting a predictable trend in time to relapse were much higher than a patient with recurrent non-affective psychotic disorder. In other words, within recurrent non-affective psychosis group, time to relapse is random. This study is an initial attempt to develop a longitudinal trajectory-based approach to investigate relapse trend differences in mental health patients. Further investigations using this approach may reflect differences in underlying biological processes between illnesses.
随着时间的推移,情感性和非情感性精神障碍多次复发都很常见。了解这些复发的时间特性对于理解复发潜在的神经生物学机制可能至关重要。从南澳大利亚州精神卫生数据大全中收集情感性和非情感性精神障碍患者的匿名记录并进行回顾性分析。为了描述其复发的时间特征,使用基于符号序列的方法计算复发趋势评分。评分越高表明复发呈某种趋势,评分越低表明复发是随机的。构建回归模型以研究情感性和非情感性精神障碍之间该评分是否存在显著差异。逻辑回归模型显示患者组之间在复发趋势评分上存在显著的组间差异。例如,在住院六次或更多次的患者中,情感性障碍的复发评分比非情感性精神障碍高2.6倍[比值比2.6,95%置信区间(1.8 - 3.7),P < 0.001]。结果表明,情感性障碍患者在复发时间上呈现可预测趋势的几率远高于复发性非情感性精神障碍患者。换句话说,在复发性非情感性精神病组中,复发时间是随机的。本研究是开发一种基于纵向轨迹的方法来研究精神卫生患者复发趋势差异的初步尝试。使用这种方法的进一步研究可能会反映不同疾病之间潜在生物学过程的差异。