RESUMEN
Both the high-frequency component of systolic arterial pressure variability and systolic pressure variation (SPV) have been indicated to be strongly affected by respiratory effect and sensitively reflect circulating blood volume (CBV). We attempted to determine the best means reflecting CBV from various parameters using power spectrum analyses of systolic arterial pressure variability (PSSAPV) and heart rate variability (PSHRV), SPV, and pulse pressure variation during graded hemorrhaging and fluid resuscitation. Under isoflurane anesthesia and mechanical ventilation, rabbits in group S (n = 6) had hemorrhaging induced, whereas those in group H (n = 10) had hemorrhaging induced followed by fluid resuscitation. After collecting baseline data, blood was withdrawn at a rate of 1 mL.kg.min for 25 min in both groups, and data were collected at 5 min after bleeding was stopped. Furthermore, in group H, hydroxyethyl starch was continuously infused at a rate of 1 mL.kg.min for 25 min; data were collected at 5 and 60 min after fluid resuscitation. The correlations between CBV and total power (TP, 0.04-2.00 Hz), high-frequency component (0.75-1.40 Hz), and low-frequency component (0.04-0.40 Hz) of PSSAPV were more significant as compared with SPV and pulse pressure variation, whereas no correlations were noted between CBV and PSHRV. To evaluate the regression models appropriately, Akaike information criterion was used, and TP of PSSAPV showed the lowest value. We concluded that TP of PSSAPV most sensitively reflected changes of CBV and that PSSAPV was the most useful parameter for evaluation of volume status as compared with conventional circulatory parameters.
Asunto(s)
Presión Sanguínea/fisiología , Volumen Sanguíneo/fisiología , Frecuencia Cardíaca/fisiología , Choque Hemorrágico/fisiopatología , Animales , Fluidoterapia , Masculino , Conejos , Distribución Aleatoria , Solución Salina Hipertónica/uso terapéutico , Choque Hemorrágico/terapiaRESUMEN
BACKGROUND: Creatinine clearance (Ccr) is an efficient index of renal function. However, measurement of Ccr is not routinely performed for preoperative patients. To predict preoperative renal impairment, we estimated the preoperative Ccr by using serum creatinine (sCr) and other laboratory findings. METHODS: 702 patients served as the training samples and other 128 patients as the validation samples. (1) Values of sCr and BUN to predict lower Ccr levels were developed from the training samples. In the combination of sCr and BUN, we selected the optimal combination in receiver operating characteristics curve. This value was applied to the validation samples. (2) The predictive equation was derived from the training samples by multiple regression analysis, and it was compared with the equations previously reported. RESULTS: (1) The optimal sensitivity and specificity for predicting Ccr less than 30 ml x min(-1) x 1.48 m(-2) were 60% and 84%, respectively. (2) Among the equations to predict Ccr, our equation showed the highest correlation coefficient (r), and the smallest differences between predicted and measured Ccr. CONCLUSIONS: We determined the values of sCr and BUN to predict renal impairment and derived predictive equation. Our equation was the best to assess the preoperative renal function.