Health status, community integration, and economic risk factors for mortality after spinal cord injury
Health status, community integration, and economic risk factors for mortality after spinal cord injury
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DOI：
10.1016/j.apmr.2004.06.062
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发表时间：
2004-11-01
影响因子：
4.3
通讯作者：
Jackson, AB
中科院分区：
文献类型：
--
作者：
Krause, JS;DeVivo, MJ;Jackson, AB
目的：研究脊髓损伤患者的健康、社区融合和经济状况与随后的死亡率和预期寿命之间的关系。设计：队列研究。设置：脊髓损伤模型系统 (MSCIS) 医院。参与者：自 1973 年以来总共 5947 名受伤者被登记在国家脊髓损伤数据库中，他们仍然活着，并从 1995 年 11 月到 3 月接受了年度评估2002.干预措施：不适用。主要结果指标：通过常规随访并辅以社会保障死亡指数信息来确定死亡率。基于全套预测变量的逻辑回归模型被开发出来，用于估计任何给定年份的死亡几率。结果：在调整人口特征和伤害严重程度后，健康状况指标、社区融合措施和经济状况指标对下一年的死亡可能性都有相对较小但具有统计显着性的影响（增加 20%-70%）。在非常有利的条件下，纳入这些因素可能会导致更高的预期寿命估计。 结论：虽然之前的 MSCIS 数据报告已经确定了与特定人口统计（例如年龄、性别）和伤害相关特征（伤害的程度和完整性；呼吸机依赖）相关的预期寿命，但当前的分析表明，考虑健康、经济和社会心理因素可能会使预期寿命的计算更加准确。
Objective: To examine the association of health, community integration, and economic status with subsequent mortality and life expectancy among persons with spinal cord injury.Design: Cohort study.Setting: Model Spinal Cord Injury Systems (MSCIS) hospitals.Participants: 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.Interventions: Not applicable.Main Outcome Measure: 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.Results: 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.Conclusions: 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.