de la Fuente Jesús, García-Torrecillas Juan Manuel, Solinas Giulliana, Iglesias-Espinosa María Mar, Garzón-Umerenkova Angélica, Fiz-Pérez Javier
Educational Psychology, School of Education and Psychology, University of Navarra, Pamplona, Spain.
Educational Psychology, School of Psychology, University of Almería, Almería, Spain.
Front Neurol. 2019 May 17;10:498. doi: 10.3389/fneur.2019.00498. eCollection 2019.
Traditionally, predictive models of in-hospital mortality in ischemic stroke have focused on individual patient variables, to the neglect of in-hospital contextual variables. In addition, frequently used scores are betters predictors of risk of sequelae than mortality, and, to date, the use of structural equations in elaborating such measures has only been anecdotal. The aim of this paper was to analyze the joint predictive weight of the following: (1) individual factors (age, gender, obesity, and epilepsy) on the mediating factors (arrhythmias, dyslipidemia, hypertension), and ultimately death (exitus); (2) contextual in-hospital factors (year and existence of a stroke unit) on the mediating factors (number of diagnoses, procedures and length of stay, and re-admission), as determinants of death; and (3) certain factors in predicting others. Retrospective cohort study through observational analysis of all hospital stays of Diagnosis Related Group (DRG) 14, non-lysed ischemic stroke, during the time period 2008-2012. The sample consisted of a total of 186,245 hospital stays, taken from the Minimum Basic Data Set (MBDS) upon discharge from Spanish hospitals. MANOVAs were carried out to establish the linear effect of certain variables on others. These formed the basis for building the Structural Equation Model (SEM), with the corresponding parameters and restrictive indicators. A consistent model of causal predictive relationships between the postulated variables was obtained. One of the most interesting effects was the predictive value of contextual variables on individual variables, especially the indirect effect of the existence of stroke units on reducing number of procedures, readmission and in-hospital mortality. Contextual variables, and specifically the availability of stroke units, made a positive impact on individual variables that affect prognosis and mortality in ischemic stroke. Moreover, it is feasible to determine this impact through the use of structural equation methodology. We analyze the methodological and clinical implications of this type of study for hospital policies.
传统上，缺血性中风院内死亡率的预测模型一直侧重于个体患者变量，而忽视了院内环境变量。此外，常用评分在预测后遗症风险方面比死亡率更有效，而且迄今为止，在阐述此类指标时使用结构方程也只是个别情况。本文的目的是分析以下因素的联合预测权重：（1）个体因素（年龄、性别、肥胖和癫痫）对中介因素（心律失常、血脂异常、高血压）以及最终死亡的影响；（2）院内环境因素（年份和卒中单元的存在）对中介因素（诊断数量、手术和住院时间以及再次入院情况）作为死亡决定因素的影响；（3）某些因素对其他因素的预测作用。通过对2008 - 2012年期间诊断相关组（DRG）14（非溶栓缺血性中风）的所有住院病例进行观察分析，开展回顾性队列研究。样本包括从西班牙医院出院时取自最低基本数据集（MBDS）的总共186,245例住院病例。进行多变量方差分析以确定某些变量对其他变量的线性影响。这些分析结果构成了构建结构方程模型（SEM）的基础，并给出了相应参数和限制指标。获得了假定变量之间一致的因果预测关系模型。其中一个最有趣的效应是环境变量对个体变量的预测价值，特别是卒中单元的存在对减少手术数量、再次入院率和院内死亡率的间接影响。环境变量，特别是卒中单元的可用性，对影响缺血性中风预后和死亡率的个体变量产生了积极影响。此外，通过使用结构方程方法来确定这种影响是可行的。我们分析了这类研究对医院政策的方法学和临床意义。
