The ability of PiCCO versus LiDCO variables to detect changes in cardiac index: a prospective clinical study.

BACKGROUND: Both PiCCO and LiDCO can provide dynamic preload parameters, pulse pressure variation (PPV) and stroke volume variation (SVV). The PiCCO device also provides a measure of intrathoracic blood volume index (ITBVI). We investigated the agreement between SVV and PPV, as well as the reliability of LiDCO- and PiCCO-measured SVV, PPV and ITBVI, in detecting fluid responsiveness before and after fluid challenge (FC). METHODS: We performed a prospective clinical study in University Hospital ICU. Nine adult ICU patients with cardiovascular instability were enrolled in the study. All patients were sedated and mechanically ventilated with intermittent positive pressure ventilation. The PiCCO and LiDCO systems were both connected to each patient. The PiCCO pulse waveform system was joined by a 5-French (Fr) thermistor-tipped arterial catheter inserted into the femoral artery. LiDCO measurements were performed through radial artery pulse contour analysis. Fluid challenge was performed using a rapid infusion of 7 mL/kg of 6% hydroxyethylstarch over 30 min. RESULTS: Measurements of CI, ITBVI, SVV, and PVV were made using both techniques before and after FC. Pre-FC cardiac index (CI) measurements were similar with both devices, although the reading was higher after FC with the PiCCO device (P<0.001). The correlation coefficient between PiCCO-CI and LiDCO-CI was 0.85 (95% CI: 0.69 to 0.93; P<0.001); for P-PPV and L-PPV, it was 0.74 (95% CI: 0.49 to 0.88; P<0.001). Only ITBV had a significant correlation with LiDCO-CI or PiCCO-CI. CONCLUSION: We found a narrow bias but less accurate precision in cardiac index values measured by a radial artery-site LiDCO catheter and a femoral artery-site PiCCO catheter, with poor agreement between radial and femoral-derived SVV and PPV measurements. ITBVI proved to be the best predictor of fluid responsiveness. The SVV does not seem to be reliable for preload optimization in ICU patients.

Successful early voriconazole treatment of Aspergillus infection in two non immunocompromised patients in Intensive Care Unit.

We report two cases of respiratory Aspergillus infection that occurred in patients admitted to the Intensive Care Unit of a teaching hospital during renovation works and treated with new triazole voriconazole (Vfend). The first patient was affected with cerebral hemorrhage, the second with polytrauma and both developed Aspergillus Pneumonia during their ICU stay. Bronchoalveolar lavage, dosage with anti-Aspergillus antibodies, antigen measurements and galactomannan research with Sanofi Platelia were performed. Therapy was carried out with voriconazole for 12 days. Chest X-ray and laboratory tests showed complete resolution after 12 days of therapy; clinical symptoms were negative after 4 days. Aspergillus infection can be observed frequently in non-immunocompromised patients during ward renovation or in hospitals near building areas. Since treatment is often unsuccessful, we preferred to immediately employ new agents to reduce the impact of this disease.

Correlation between hyperglycemia and mortality in a medical and surgical intensive care unit.

AIM: The aim of this study was to assess the correlation between hyperglycemia and mortality in a group of patients admitted to a medical and surgical ICU and to evaluate if the association between hyperglycemia and reason of ICU admission significantly worsens patients' outcomes. METHODS: A retrospective clinical study was conducted in the ICU of a University Hospital. Four-hundred and twelve adult patients admitted to our ICU were enrolled. The blood glucose level was measured at the time of admission and daily at 2-4 h intervals. When the glucose level exceeded 180 mg/dL, an insulin bolus or a continuous infusion were performed to maintain the glucose level at or below 180-200 mg/dL. RESULTS: Analysing the mean blood glucose levels of patients with the receiver operating characteristic (ROC) curve, it resulted that the blood glucose level of 141.7 mg/dL had higher sensitivity (76%) and specificity (56.5%) to discriminate the probability of death. In other words, in patients in whom the mean blood glucose levels were greater than 141.7 mg/dL, the probability of death was higher (26.62%) than in the group of patients in whom a strict blood glucose control was maintained (13.55%) (P = 0.0017). CONCLUSIONS: A strict blood glucose control seems to be crucial, even in a medical and surgical ICU. The need for intensive insulin therapy, even by means of continuous infusion of insulin, to obtain the normalization of blood glucose levels, appears essential.

To verify four 5-year-old mathematical models to predict the outcome of ICU patients.

AIM: The aim of this study is to verify calibration and discrimination after 5 years in the case mix of patients admitted to the Intensive Care Unit (ICU) during the year 2000. In this way we want to perform a quality control of our ICU in order to justify the increased amount of money spent for intensive care. METHODS: A prospective study has been made on the 357 patients admitted to the ICU during the year 2000. The Apache II score was calculated within the first 24 hours and, depending on the length of stay in the ICU, on the 5(th), 10(th) and 15(th) day after ICU admission. On the basis of the 4 mathematical models death risk has been calculated for each of the 4 times. The Hosmer-Lemeshow test was performed for calibration and ROC curves for discrimination, always for each of the 4 mathematical models. RESULTS: The 1(st) model, at 24 hours from ICU admission, showed a bad calibration (p=0.000088), while the ROC curve was 0.744+/-0.32. Also the 2(nd) model, at the 5(th) day from admission, showed a bad calibration (p=0.000588), with ROC curve of 0.827+/-0.04. The 3(rd) model (10(th) day), was well calibrated (p=0.112247) and discriminating (ROC=0.888 +/-0.04). Finally the models at 15 days showed again a bad calibration (p=0.001422) but a very good discrimination (area=0.906+/-0.06). CONCLUSION: Developing mathematical models to predict mortality within ICUs can be useful to assess quality of care, even if these models should not be the only ICU quality controls, but must be accompanied by other indicators, looking at quality of life of the patients after ICU discharge.