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Abstract：
UNASSIGNED: This study aims to utilize latent growth model (LGM) to explore the developmental trajectory of motor dysfunction in Parkinson\'s disease (PD) patients and investigate the relationship between depression and motor dysfunction.
UNASSIGNED: Four-year follow-up data from 389 PD patients were collected through the Parkinson\'s Progression Marker Initiative (PPMI). Firstly, a univariate LGM was employed to examine the developmental trajectory of motor dysfunction in PD patients. Subsequently, depression levels were introduced as covariates into the model, and depression was further treated as a parallel growth latent variable to study the longitudinal relationship between motor dysfunction and depression.
UNASSIGNED: In the trajectory analysis of motor dysfunction, the fit indices for the quadratic growth LGM model were χ2 = 7.419, df = 6, CFI = 0.998, TLI = 0.997, SRMR = 0.019, and RMSEA = 0.025, indicating that the growth trend of motor dysfunction follows a quadratic curve rather than a simple linear pattern. Introducing depression symptoms as time-varying covariates to explore their effect on motor dysfunction revealed significant positive correlations (β = 0.383, p = 0.026; β = 0.675, p < 0.001; β = 0.385, p = 0.019; β = 0.415, p = 0.014; β = 0.614, p = 0.003), suggesting that as depression levels increase, motor dysfunction scores also increase. Treating depression as a parallel developmental process in the LGM, the regression coefficients for depression intercept on motor dysfunction intercept, depression slope on motor dysfunction slope, and depression quadratic factor on motor dysfunction quadratic factor were 0.448 (p = 0.046), 1.316 (p = 0.003), and 1.496 (p = 0.038), respectively. These significant regression coefficients indicate a complex relationship between depression and motor dysfunction, involving not only initial level associations but also growth trends over time and possible quadratic effects.
UNASSIGNED: This study indicates a quadratic growth trajectory for motor dysfunction in PD, suggesting a continuous increase in severity with a gradual deceleration in growth rate. The relationship between depression and motor dysfunction is complex, involving initial associations, evolving trends over time, and potential quadratic effects. Exacerbation of depressive symptoms may coincide with motor function deterioration.
UNASSIGNED: Four-year follow-up data from 389 PD patients were collected through the Parkinson\'s Progression Marker Initiative (PPMI). Firstly, a univariate LGM was employed to examine the developmental trajectory of motor dysfunction in PD patients. Subsequently, depression levels were introduced as covariates into the model, and depression was further treated as a parallel growth latent variable to study the longitudinal relationship between motor dysfunction and depression.
UNASSIGNED: In the trajectory analysis of motor dysfunction, the fit indices for the quadratic growth LGM model were χ2 = 7.419, df = 6, CFI = 0.998, TLI = 0.997, SRMR = 0.019, and RMSEA = 0.025, indicating that the growth trend of motor dysfunction follows a quadratic curve rather than a simple linear pattern. Introducing depression symptoms as time-varying covariates to explore their effect on motor dysfunction revealed significant positive correlations (β = 0.383, p = 0.026; β = 0.675, p < 0.001; β = 0.385, p = 0.019; β = 0.415, p = 0.014; β = 0.614, p = 0.003), suggesting that as depression levels increase, motor dysfunction scores also increase. Treating depression as a parallel developmental process in the LGM, the regression coefficients for depression intercept on motor dysfunction intercept, depression slope on motor dysfunction slope, and depression quadratic factor on motor dysfunction quadratic factor were 0.448 (p = 0.046), 1.316 (p = 0.003), and 1.496 (p = 0.038), respectively. These significant regression coefficients indicate a complex relationship between depression and motor dysfunction, involving not only initial level associations but also growth trends over time and possible quadratic effects.
UNASSIGNED: This study indicates a quadratic growth trajectory for motor dysfunction in PD, suggesting a continuous increase in severity with a gradual deceleration in growth rate. The relationship between depression and motor dysfunction is complex, involving initial associations, evolving trends over time, and potential quadratic effects. Exacerbation of depressive symptoms may coincide with motor function deterioration.
摘要：
■本研究旨在利用潜在生长模型（LGM）探索帕金森病（PD）患者运动功能障碍的发展轨迹，并探讨抑郁症与运动功能障碍之间的关系。
■通过帕金森进展标志物倡议（PPMI）收集了389名PD患者的四年随访数据。首先,采用单变量LGM检查PD患者运动功能障碍的发展轨迹.随后，抑郁水平作为协变量引入模型，并进一步将抑郁症作为平行生长潜在变量来研究运动功能障碍与抑郁症之间的纵向关系。
■在运动功能障碍的轨迹分析中，二次增长LGM模型的拟合指数为χ2=7.419，df=6，CFI=0.998，TLI=0.997，SRMR=0.019，RMSEA=0.025，表明运动功能障碍的增长趋势遵循二次曲线而不是简单的线性模式。将抑郁症状引入时变协变量以探讨其对运动功能障碍的影响显示出显着正相关（β=0.383，p=0.026；β=0.675，p<0.001；β=0.385，p=0.019；β=0.415，p=0.014；β=0.614，p=0.003），这表明随着抑郁水平的增加，运动功能障碍评分也增加。将抑郁症视为LGM中的平行发育过程，抑郁症截距对运动功能障碍截距的回归系数，运动功能障碍斜率上的抑郁斜率，抑郁二次因子对运动功能障碍二次因子的影响为0.448（p=0.046），1.316（p=0.003），和1.496(p=0.038)，分别。这些显著的回归系数表明抑郁症和运动功能障碍之间的复杂关系，不仅涉及初始水平关联，还涉及随时间的增长趋势和可能的二次效应。
■这项研究表明PD运动功能障碍的二次增长轨迹，表明严重程度持续增加，增长率逐渐减速。抑郁症和运动功能障碍之间的关系是复杂的，涉及最初的协会，随着时间的推移不断演变的趋势，和潜在的二次效应。抑郁症状的加重可能与运动功能恶化有关。
■通过帕金森进展标志物倡议（PPMI）收集了389名PD患者的四年随访数据。首先,采用单变量LGM检查PD患者运动功能障碍的发展轨迹.随后，抑郁水平作为协变量引入模型，并进一步将抑郁症作为平行生长潜在变量来研究运动功能障碍与抑郁症之间的纵向关系。
■在运动功能障碍的轨迹分析中，二次增长LGM模型的拟合指数为χ2=7.419，df=6，CFI=0.998，TLI=0.997，SRMR=0.019，RMSEA=0.025，表明运动功能障碍的增长趋势遵循二次曲线而不是简单的线性模式。将抑郁症状引入时变协变量以探讨其对运动功能障碍的影响显示出显着正相关（β=0.383，p=0.026；β=0.675，p<0.001；β=0.385，p=0.019；β=0.415，p=0.014；β=0.614，p=0.003），这表明随着抑郁水平的增加，运动功能障碍评分也增加。将抑郁症视为LGM中的平行发育过程，抑郁症截距对运动功能障碍截距的回归系数，运动功能障碍斜率上的抑郁斜率，抑郁二次因子对运动功能障碍二次因子的影响为0.448（p=0.046），1.316（p=0.003），和1.496(p=0.038)，分别。这些显著的回归系数表明抑郁症和运动功能障碍之间的复杂关系，不仅涉及初始水平关联，还涉及随时间的增长趋势和可能的二次效应。
■这项研究表明PD运动功能障碍的二次增长轨迹，表明严重程度持续增加，增长率逐渐减速。抑郁症和运动功能障碍之间的关系是复杂的，涉及最初的协会，随着时间的推移不断演变的趋势，和潜在的二次效应。抑郁症状的加重可能与运动功能恶化有关。
