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Timeframe for Conversion to Psychosis From Individuals at Clinical High-Risk: A Quantile Regression
Schizophrenia Bulletin ( IF 5.3 ) Pub Date : 2024-07-26 , DOI: 10.1093/schbul/sbae129 TianHong Zhang 1 , YanYan Wei 1 , XiaoChen Tang 1 , LiHua Xu 1 , YeGang Hu 1 , HaiChun Liu 2 , ZiXuan Wang 3 , Tao Chen 4, 5 , ChunBo Li 1 , JiJun Wang 1, 6, 7
Schizophrenia Bulletin ( IF 5.3 ) Pub Date : 2024-07-26 , DOI: 10.1093/schbul/sbae129 TianHong Zhang 1 , YanYan Wei 1 , XiaoChen Tang 1 , LiHua Xu 1 , YeGang Hu 1 , HaiChun Liu 2 , ZiXuan Wang 3 , Tao Chen 4, 5 , ChunBo Li 1 , JiJun Wang 1, 6, 7
Affiliation
Background and Hypothesis The time taken for an individual who is at the clinical high-risk (CHR) stage to transition to full-blown psychosis may vary from months to years. This temporal aspect, known as the timeframe for conversion to psychosis (TCP), is a crucial but relatively underexplored dimension of psychosis development. Study Design The sample consisted of 145 individuals with CHR who completed a 5-year follow-up with a confirmed transition to psychosis within this period. Clinical variables along with functional variables such as the Global Assessment of Function (GAF) score at baseline (GAF baseline) and GAF-drop from the highest score in the past year. The TCP was defined as the duration from CHR identification to psychosis conversion. Participants were categorized into 3 groups based on TCP: “short” (≤6 months, ≤33.3%), “median” (7–17 months, 33.3%–66.6%), and “long” (≥18 months, ≥66.6%). The quantile regression analysis was applied. Study Results The overall sample had a median TCP of 11 months. Significant differences among the three TCP groups were observed, particularly in GAF-drop (χ2 = 8.806, P = .012), disorganized symptoms (χ2 = 7.071, P = .029), and general symptoms (χ2 = 6.586, P = .037). Greater disorganized symptoms (odds ratio [OR] = 0.824, P = .009) and GAF-drop (OR = 0.867, P = .011) were significantly associated with a shorter TCP, whereas greater general symptoms (OR = 1.198, P = .012) predicted a longer TCP. Quantile regression analysis demonstrated a positive association between TCP and GAF baseline above the 0.7 quantile and a negative association between TCP rank and GAF drop below the 0.5 quantile. Conclusions This study underscores the pivotal role of functional characteristics in shaping TCP among individuals with CHR, emphasizing the necessity for a comprehensive consideration of temporal aspects in early prevention efforts.
中文翻译:
临床高风险个体转变为精神病的时间范围:分位数回归
背景和假设 处于临床高危(CHR)阶段的个体过渡到全面精神病所需的时间可能从数月到数年不等。这个时间方面,称为转化为精神病的时间范围(TCP),是精神病发展的一个重要但相对而言尚未得到充分探索的维度。研究设计 样本由 145 名患有 CHR 的个体组成,他们完成了 5 年的随访,并确认在此期间转变为精神病。临床变量以及功能变量,例如基线时的总体功能评估 (GAF) 评分(GAF 基线)和 GAF 从过去一年最高评分的下降。 TCP 被定义为从 CHR 识别到精神病转变的持续时间。根据 TCP,参与者被分为 3 组:“短”(≤6 个月,≤33.3%)、“中值”(7-17 个月,33.3%-66.6%)和“长”(≥18 个月,≥66.6%) %)。应用分位数回归分析。研究结果 总体样本的 TCP 中位数为 11 个月。三个 TCP 组之间观察到显着差异,特别是在 GAF 下降(χ2 = 8.806,P = .012)、紊乱症状(χ2 = 7.071,P = .029)和一般症状(χ2 = 6.586,P = .029)方面。 037)。更大的紊乱症状(比值比 [OR] = 0.824,P = .009)和 GAF 下降(OR = 0.867,P = .011)与较短的 TCP 显着相关,而更大的一般症状(OR = 1.198,P = .011)与较短的 TCP 显着相关。 .012) 预测 TCP 更长。分位数回归分析表明,TCP 和 GAF 基线在 0.7 分位数之上呈正相关,而 TCP 排名和 GAF 下降在 0.5 分位数以下之间呈负相关。 结论 本研究强调了功能特征在 CHR 个体 TCP 塑造中的关键作用,强调了在早期预防工作中全面考虑时间方面的必要性。
更新日期:2024-07-26
中文翻译:
临床高风险个体转变为精神病的时间范围:分位数回归
背景和假设 处于临床高危(CHR)阶段的个体过渡到全面精神病所需的时间可能从数月到数年不等。这个时间方面,称为转化为精神病的时间范围(TCP),是精神病发展的一个重要但相对而言尚未得到充分探索的维度。研究设计 样本由 145 名患有 CHR 的个体组成,他们完成了 5 年的随访,并确认在此期间转变为精神病。临床变量以及功能变量,例如基线时的总体功能评估 (GAF) 评分(GAF 基线)和 GAF 从过去一年最高评分的下降。 TCP 被定义为从 CHR 识别到精神病转变的持续时间。根据 TCP,参与者被分为 3 组:“短”(≤6 个月,≤33.3%)、“中值”(7-17 个月,33.3%-66.6%)和“长”(≥18 个月,≥66.6%) %)。应用分位数回归分析。研究结果 总体样本的 TCP 中位数为 11 个月。三个 TCP 组之间观察到显着差异,特别是在 GAF 下降(χ2 = 8.806,P = .012)、紊乱症状(χ2 = 7.071,P = .029)和一般症状(χ2 = 6.586,P = .029)方面。 037)。更大的紊乱症状(比值比 [OR] = 0.824,P = .009)和 GAF 下降(OR = 0.867,P = .011)与较短的 TCP 显着相关,而更大的一般症状(OR = 1.198,P = .011)与较短的 TCP 显着相关。 .012) 预测 TCP 更长。分位数回归分析表明,TCP 和 GAF 基线在 0.7 分位数之上呈正相关,而 TCP 排名和 GAF 下降在 0.5 分位数以下之间呈负相关。 结论 本研究强调了功能特征在 CHR 个体 TCP 塑造中的关键作用,强调了在早期预防工作中全面考虑时间方面的必要性。