Cystatin C as an early marker of acute kidney injury in septic shock. / Cistatina C como marcador precoz de lesión renal aguda en el shock séptico.

OBJECTIVE: To describe the utility of determining plasma cystatinC concentrations in the diagnosis of acute incident kidney injury in septic shock. PATIENTS AND METHODS: Prospective series of 50 patients with septic shock and plasma creatinine levels <2mg/dL hospitalized in an intensive care unit. Clinical and laboratory follow-ups were conducted, with measurements of cystatinC, urea and plasma creatinine levels from the diagnosis of septic shock to 5days later. The severity of the septic shock was assessed with the RIFLE scale. RESULTS: Twenty patients (40%) developed acute kidney injury: 8 (16%) were categorized as RIFLE-R, 5 (10%) as RIFLE-I and 7 (14%) as RIFLE-F. All patients categorized as RIFLE-F required extracorporeal renal clearance. Eighteen (36%) patients died, 8 (20%) of whom had developed acute kidney injury in their evolution. There was poor correlation between plasma creatinine and cystatin C levels (r=.501; P=.001), which disappeared upon reaching any degree of renal impairment on the RIFLE scale. CystatinC levels increased earlier and were better able to identify patients who would develop serious renal function impairment (RIFLE-F) than creatinine and urea levels. The initial cystatinC levels were related to mortality at 30days (OR=1.16; 95%CI: 03-.85). CONCLUSIONS: For patients who developed acute septic kidney injury, the plasma cystatinC levels increased before the classical markers of renal function. CystatinC also constitutes a severity biomarker that correlates with progression to RIFLE-F, the need for extrarenal clearance and, ultimately, mortality. This precocity could be useful for starting measures that prevent the progression of renal dysfunction.

[NEMS: a new predictor of mortality in the critical patient?]. / NEMS: ¿nuevo predictor de mortalidad en el paciente crítico?

Numerical scales are commonly used in intensive care units to predict hospital mortality and to assess the therapeutic effort and care that critically ill patients require. The aim of this work was to study whether the NEMS value can be used as a predictor of mortality, comparing it with the APACHE II. A prospective study in a 24 intensive care unit beds was conducted. The APACHE II and NEMS values were stratified into three levels. Demographic data and the first 24 hours values of APACHE II and NEMS scales were collected. A total of 1257 patients were included, 16.4% of whom died. 69.6% were surgical; median stay was 2 days (1-4). Median age was 66 years (50-77), 59.3% were men. The median APACHE II and NEMS for the living and the dead in the subsequent course was 10 (6-20) versus 22.5 (17.25 to 29) (p <0.001) and 24 (18-29) versus 34 (25 to 39.7) (p<0.001) respectively. The correlation between both scales was rho=0.457 (p<0.01). Logistic regression controlled for age, sex and APACHE II showed an OR of 3.1 (95% CI: 1.5-6.6) only for high NEMS, compared to the lowest level. According to the results NEMS should not be used as a predictor of mortality, although the risk of death increases by three times with high NEMS.

[Blood glucose levels in the first 24 hours of admission is not a risk factor for mortality in critical care patients]. / La glucemia de las primeras 24 horas no es un factor pronóstico de mortalidad en pacientes críticos.

INTRODUCTION: 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. OBJECTIVES: 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. METHODS: 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. RESULTS AND DISCUSSION: 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. CONCLUSIONS: 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.

[Hypokalemia-induced paraplegia secondary to acute diarrhea]. / Paraplejia por hipopotasemia secundaria a diarrea aguda.

Hypokalemia can give a variety of syntomatology but more often courses without it or with inespecific clinical manifestations. In our enviroment the etiology of hypokalemia is wide but one of the most common causes in third world countries are diarrheas. We describe a case of severe hypokalemia due to acute diarrhea which was manifested with severe neurologic symtoms but improves with conventional treatment.