We prospectively studied perioperative changes of renal function in 12 previously normal patients (plasma creatinine < 1.5 mg/dL) scheduled for elective coronary surgery. Glomerular filtration rate (GFR) and effective renal plasma flow (ERPF) were measured with inulin and 125I-hippuran clearances before induction of anesthesia, before cardiopulmonary bypass (CPB), during hypo- and normothermic CPB, after sternal closure, and 1 h postoperatively. Renal and systemic vascular resistances were calculated. Urinary N-acetyl-beta-D-glucosaminidase (NAG) and plasma and urine electrolytes were measured, and free water, osmolal, and creatinine clearances, and fractional excretion of sodium and potassium were calculated before and after surgery. 125I-hippuran clearance was lower than normal in all patients before surgery. During hypothermic CPB, ERPF increased significantly (from 261 +/- 107 to 413 +/- 261 mL/min) and returned toward baseline values during normothermia. GFR was normal before and after surgery and decreased nonsignificantly during CPB. Filtration fraction was above normal before surgery and decreased significantly during CPB (0.38 +/- 0.09 to 0.18 +/- 0.06). Renal vascular resistance (RVR) was high before surgery and further increased after sternotomy (from 18,086 +/- 6849 to 30,070 +/- 24,427 dynes.s.cm-5), decreasing during CPB to 13,9647 +/- 14,662 dynes.s.cm-5. Urine NAG, creatinine, and free water clearances were normal in all patients both pre- and postoperatively. Osmolal clearance and fractional excretion of sodium increased postoperatively from 1.54 +/- 0.06 to 12.47 4/- 11.37 mL/min, and from 0.44 +/- 0.3 to 6.07 +/- 6.27, respectively. We conclude that renal function does not seem to be adversely affected by CPB.(ABSTRACT TRUNCATED AT 250 WORDS)
This paper presents a method for estimating parameters of a cardiovascular model, including the left-ventricular function, using the sequential quadratic programming (SQP) and the least minimum square (LMS) algorithms. In a first stage, a radial arterial-pressure waveform with corresponding cardiac output are used to automatically seek the set of parameters of the diastolic model. Computer simulation of the model using these parameters generate a pressure waveform and a cardiac output very close to those used for the estimation. In a second stage, the estimated arterial load parameters are used to select the best left-ventricular model function, from four different possibilities, and to estimate its optimum parameter values. The method has been tested numerically and applied to real cases, using data obtained from cardiovascular patients. It has also been subjected to preliminary validation using data obtained from laboratory dogs, in which cardiovascular function was artificially altered.
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