Krause James S, Devivo Michael J, Jackson Amie B
Medical University of South Carolina, Charleston 29425, USA.
Arch Phys Med Rehabil. 2004 Nov;85(11):1764-73. doi: 10.1016/j.apmr.2004.06.062.
To examine the association of health, community integration, and economic status with subsequent mortality and life expectancy among persons with spinal cord injury.
Cohort study.
Model Spinal Cord Injury Systems (MSCIS) hospitals.
A total of 5947 persons injured since 1973 who were enrolled in the National Spinal Cord Injury Database and who were still alive and received an annual evaluation from November 1995 through March 2002.
Not applicable.
Mortality was determined by routine follow-up supplemented by information from the Social Security Death Index. A logistic regression model based on the full set of predictor variables was developed to estimate the chance of dying in any given year.
After adjusting for demographic characteristics and injury severity, health status indicators, measures of community integration, and economic status indicators all had relatively small but statistically significant effects (20%-70% increases) on the likelihood of dying during the next year. Inclusion of these factors may result in higher life expectancy estimates under highly favorable conditions.
Whereas previous reports of the MSCIS data have identified the life expectancies associated with a particular set of demographic (eg, age, gender) and injury-related characteristics (level and completeness of injury; ventilator dependence), the current analysis suggests that consideration of health, economic, and psychosocial factors may make computations of life expectancy more accurate.
研究脊髓损伤患者的健康状况、社区融入情况和经济状况与随后的死亡率及预期寿命之间的关联。
队列研究。
脊髓损伤示范系统(MSCIS)医院。
共有5947名自1973年起受伤的患者,他们被纳入国家脊髓损伤数据库,在1995年11月至2002年3月期间仍存活且接受年度评估。
不适用。
死亡率通过常规随访确定,并辅以社会保障死亡指数的信息。基于全套预测变量建立逻辑回归模型,以估计在任何给定年份死亡的几率。
在调整人口统计学特征和损伤严重程度后,健康状况指标、社区融入指标和经济状况指标对次年死亡可能性均有相对较小但具有统计学意义的影响(增加20%-70%)。纳入这些因素可能会在极为有利的条件下得出更高的预期寿命估计值。
虽然之前关于MSCIS数据的报告已经确定了与特定人口统计学特征(如年龄、性别)和损伤相关特征(损伤水平和完整性;呼吸机依赖)相关的预期寿命,但当前分析表明,考虑健康、经济和心理社会因素可能会使预期寿命的计算更加准确。