Blesa Malpica A L, Cubells Romeral M, Morales Sorribas E, Tejero Redondo A, Martínez Sagasti F, Martín Benítez J C, Garitacelaya Gorrochategui M, Ortuño Anderiz F
Servicio de Medicina Intensiva, Hospital Clínico San Carlos, Madrid, España.
Nutr Hosp. 2011 May-Jun;26(3):622-35. doi: 10.1590/S0212-16112011000300028.
Glycemic alterations are known as a risk condition of death in several diseases, such as ischemic cardiovascular and neurological disorders. The fact that its tight control under narrow normality levels decreases mortality and morbidity have led to further studies seeking to confirm the results and expand them to other disease areas.
To determine whether glycemic changes by themselves are a mortality risk factor in a sample of patients within an Intensive Care Unit (ICU), among which predominates traumatic-surgical patients.
Demographic and analytical characteristics were revised, as well as common monitoring variables in an ICU, among a sample of 2,554 patients from admissions between 1st January 2004 and 31 December 2008. Data were obtained from a database which endorsed records compiled with the monitoring ICU patients program "Carevue". They were processed with dynamics sheets included in the Excel software with the following variables: initial glycemia, mean glycemia during the first 24 hours and number of determinations performed. We used the mean value in the admission day of the remaining analytical and monitoring variables and the number of test performed on this first day. The sample was stratified in two groups for the statistical analysis: a) General Sample (MG) and b) sample excluding patients admitted after a programmed surgery (EQP). In both cases the effect of initial and averaged glycemia was checked. Group b was divided in two, according to the number of determinations b1) a single blood glucose determination group (EQP1) and b2) a multiple determination group (EQPM). From this group of non-programmed surgical patients the study was repeated in those patients who stayed at the ICU 3 or more days (EQP3D). Chi-square and Mantel-Haenzel test for the ODD ratio determination were performed for qualitative variables; quantitative variables were examined with the Mann-Whitney test. At each analysis level, logistic regression was performed using mortality as the dependent variable, including those variables with p-values < 0.05 which represented more than 60% of the data. An initially saturated model with backward till the final equation was used. A p-value of 0.05 (i.e. p < 0.05) was set as the significant threshold for all statistical analysis. They were performed with SPSS and GSTAT 2 statistical software.
A total of 2,165 of the 2,554 admitted patients during the study period were included (96.5%). Exclusion criteria were absence of plasma glucose determinations. In the bivariate analysis, first and mean glucose blood levels showed significant differences in mortality rates in absolute figures and also when data were classified stratified in three levels (< 60 mg/dl; 60-110 mg/dl or > 110 mg/dl) or in two (normal values 60 to 110 mg/dl and unusual figures < 60 mg/dl or > 110 mg/dl). These significant differences were lost when a logistic model was applied. From the remaining variables, renal function and NEMS showed to be mortality risks factors in this sample.
Hyperglycemia is a predominant phenomenon in critically ill patients. Hypoglycemia is less frequent and is associated with higher mortality rates. Initial glucose blood level, by itself, was not a mortality risk factor in the multivariate study and at none of the studied levels. Average glycemia did not add any prediction power. The changes in glucose blood levels seemed to be an adaptation process, which determined by itself a risk for the patient's discharge, at least in the first 24 hours period after ICU admission.
血糖改变在多种疾病中被认为是死亡的风险因素,如缺血性心血管疾病和神经系统疾病。在狭窄的正常水平下严格控制血糖可降低死亡率和发病率,这一事实促使进一步研究以证实结果并将其扩展到其他疾病领域。
确定在重症监护病房(ICU)的患者样本中,血糖变化本身是否为死亡风险因素,其中创伤手术患者占主导。
回顾了2004年1月1日至2008年12月31日期间收治的2554例患者样本的人口统计学和分析特征,以及ICU中的常见监测变量。数据来自一个数据库,该数据库认可了通过“Carevue”ICU患者监测程序汇编的记录。使用Excel软件中的动态工作表对以下变量进行处理:初始血糖、最初24小时内的平均血糖以及进行的测定次数。我们使用入院当天其余分析和监测变量的平均值以及第一天进行的检测次数。为进行统计分析,样本分为两组:a)一般样本(MG)和b)排除计划性手术后入院患者的样本(EQP)。在这两种情况下,均检查了初始血糖和平均血糖的影响。根据测定次数,b组又分为两组:b1)单次血糖测定组(EQP1)和b2)多次测定组(EQPM)。在这些非计划性手术患者中,对在ICU停留3天或更长时间的患者(EQP3D)重复进行该研究。对定性变量进行卡方检验和用于确定比值比的Mantel-Haenzel检验;对定量变量进行Mann-Whitney检验。在每个分析层面,以死亡率作为因变量进行逻辑回归,纳入p值<0.05且占数据60%以上的变量。使用最初的饱和模型并向后推导直至最终方程。将p值0.05(即p<0.05)设定为所有统计分析的显著阈值。使用SPSS和GSTAT 2统计软件进行分析。
在研究期间收治的2554例患者中,共有2165例被纳入(96.5%)。排除标准为未进行血浆葡萄糖测定。在双变量分析中,首次和平均血糖水平在绝对死亡率方面以及在按三个水平(<60mg/dl;60 - 110mg/dl或>110mg/dl)或两个水平(正常范围60至110mg/dl以及异常值<60mg/dl或>110mg/dl)分层分类数据时,死亡率存在显著差异。应用逻辑模型后,这些显著差异消失。在其余变量中,肾功能和NEMS在该样本中显示为死亡风险因素。
高血糖在危重症患者中是主要现象。低血糖较少见且与较高死亡率相关。在多变量研究中,初始血糖水平本身在任何研究层面均不是死亡风险因素。平均血糖并未增加任何预测能力。血糖水平的变化似乎是一个适应过程,其本身决定了患者出院的风险,至少在ICU入院后的最初24小时内如此。