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使用 Rasch 运动 FIM 个体增长曲线为截瘫患者的临床决策提供信息。

Using Rasch motor FIM individual growth curves to inform clinical decisions for persons with paraplegia.

机构信息

1] Research Department, Craig Hospital, Englewood, CO, USA [2] Traumatic Brain Injury National Data and Statistical Center, Englewood, CO, USA.

Icahn School of Medicine at Mount Sinai, New York, NY, USA.

出版信息

Spinal Cord. 2014 Sep;52(9):671-6. doi: 10.1038/sc.2014.94. Epub 2014 Jun 17.

Abstract

STUDY DESIGN

A longitudinal retrospective study.

OBJECTIVE

To better understand individual-level temporal change in functional status for participants with paraplegia in the National Spinal Cord Injury Database (NSCID), as measured by Rasch Transformed Motor Functional Indepedence Measure (FIM) scores.

SETTING

Multicenter/Multistate longitudinal study across the United States.

METHODS

Non-linear random effects modeling, that is, individual growth curve analysis of retrospective data obtained from the National Institute on Disability and Rehabilitation Research (NIDRR) NSCID.

RESULTS

We generated non-linear individual level trajectories of recovery for Rasch Transformed Motor FIM scores that rise rapidly from inpatient rehabilitation admission to a plateau. Trajectories are based on relationships between growth parameters and patient and injury factors: race, gender, level of education at admission, age at injury, neurological level at discharge, American Spinal Injury Association Impairment Scale (AIS) at discharge, days from injury to first system inpatient rehabilitation admission, rehabilitation length of stay, marital status and etiology. On the basis of study results, an interactive tool was developed to represent individual level longitudinal outcomes as trajectories based upon an individual's given baseline characteristics, that is, information supplied by the covariates and provides a robust description of temporal change for those with paraplegia within the NSCID.

CONCLUSIONS

This methodology allows researchers and clinicians to generate and better understand patient-specific trajectories through the use of an automated interactive tool where a nearly countless number of longitudinal paths of recovery can be explored. Projected trajectories holds promise in facilitating planning for inpatient and outpatient services, which could positively impact long term outcomes.

摘要

研究设计

一项纵向回顾性研究。

目的

通过使用经拉斯变换后的运动功能独立性测量(FIM)评分,更好地了解国家脊髓损伤数据库(NSCID)中截瘫患者个体水平功能状态的时间变化。

设置

美国多中心/多州的纵向研究。

方法

对从美国国立残疾与康复研究所(NIDRR)NSCID 获得的回顾性数据进行非线性随机效应建模,即个体增长曲线分析。

结果

我们生成了经拉斯变换后的运动 FIM 评分的非线性个体水平恢复轨迹,这些轨迹从住院康复入院时迅速上升到一个平台。轨迹基于生长参数与患者和损伤因素之间的关系:种族、性别、入院时的教育程度、受伤年龄、出院时的神经水平、出院时的美国脊髓损伤协会损伤分级(AIS)、受伤至首次系统住院康复入院的天数、康复住院时间、婚姻状况和病因。基于研究结果,开发了一个交互式工具,根据个体的基线特征(即协变量提供的信息)代表个体水平的纵向结果作为轨迹,并为 NSCID 中的截瘫患者提供了时间变化的强大描述。

结论

该方法允许研究人员和临床医生通过使用自动交互式工具生成和更好地理解患者特定的轨迹,其中可以探索几乎无数的恢复纵向路径。预测轨迹有望促进住院和门诊服务的规划,从而对长期结果产生积极影响。

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