A systematic database-derived approach to improve indexation of transpulmonary thermodilution-derived global end-diastolic volume.

Global end-diastolic volume (GEDV) has been indexed to body surface area (BSA). However, data validating this indexation of GEDV are scarce. Furthermore, it has been suggested to index GEDV to "predicted BSA" based on predicted body weight. Therefore, we aimed to identify biometric parameters independently associated with GEDV. We analyzed a database including 3812 TPTD measurements in 234 patients treated in the ICU of a German university hospital. GEDVI indexed to actual BSA was significantly lower than GEDVI indexed to predicted BSA (748 ± 179 vs. 804 ± 190 mL/m2; p < 0.001). GEDV was independently associated with older age, male sex, height, and actual body weight. In a regression model for the estimation of GEDV, age and height were the most important parameters: Each year in age and each cm in height increased GEDV by 9 and 15 mL, respectively. In addition to height and weight also age and sex should be considered for indexation of GEDV.

Indexation of cardiac output to biometric parameters in critically ill patients: A systematic analysis of a transpulmonary thermodilution-derived database.

PURPOSE: Cardiac output (CO) (liters per minute) is usually normalized (ie, indexed) to the patient's body surface area (BSA) resulting in the hemodynamic variable cardiac index (CI) (liters per minute per square meter). We aimed (1) to evaluate the impact of different body weight-based CO indexations on the resulting CI values and (2) to identify biometric parameters independently associated with CO in critically ill patients. MATERIALS AND METHODS: The study is an analysis of a database containing transpulmonary thermodilution-derived hemodynamic variables of 234 medical intensive care unit patients. RESULTS: Cardiac index indexed to actual BSA was statistically significantly lower compared with CI indexed to predicted BSA in the totality of patients and in the subgroups of patients with body mass index greater than or equal to 25 kg/m(2) but less than 30 kg/m(2) and body mass index greater than or equal to 30 kg/m(2) (with a statistically significant difference in the proportion of low and high CI measurements). Multivariate analysis of the first CO measurement of each patient demonstrated that CO was independently associated with age (P < .001), height (P = .001), and actual body weight (BWact) (P = .030). Multivariate analysis of the mean of the patients' CO measurements confirmed age (P < .001), height (P = .001), and BWact (P < .001) as biometric factors independently associated with CO. Age was identified as the most important factor with each year of age decreasing CO by 66 mL/min (95% confidence interval, 47-86 mL/min). CONCLUSIONS: The indexation of CO to BSA is highly dependent on the body weight estimation formula used to calculate BSA. Cardiac output is independently associated with the biometric factors age, height, and BWact. These factors might be considered for indexation of CO.

Extravascular lung water and its association with weight, height, age, and gender: a study in intensive care unit patients.

PURPOSE: With regard to large inter-individual variability of height, body weight (BW), and age, several hemodynamic parameters are adjusted for biometric data. This also applies to extravascular lung water (EVLW), which traditionally was indexed to actual BW (BW-act) resulting in EVLW-index (EVLWI; i.e., EVLWI-act). Since indexation to BW-act might inappropriately diminish EVLWI-act in obese patients, the indexation has been changed to predicted BW (BW-pred) resulting in EVLWI-pred. BW-pred is a weight estimation formula calculated from height and gender that has not been derived from population-based data. The aim of the study was to investigate the independent association of biometric data with EVLW. METHODS: We analyzed a hemodynamic monitoring database including 3,691 transpulmonary thermodilution-derived EVLW measurements (234 consecutive patients; intensive care unit of a university hospital). We performed univariate and multivariate analyses regarding the association of biometric data with the first EVLW measurement and the mean EVLW value of each patient. RESULTS: In univariate analysis, the first EVLW significantly correlated with height (r = 0.254; p < 0.001), but neither with age nor BW-act. Similar findings were made in the analysis of the patients' EVLW means of all measurements ("one point per patient"). In multivariate analysis (primary endpoint), including BW-act, height, age, and gender, only height was independently associated with EVLW, with each centimeter of height increasing the first measurement of EVLW by 6.882 mL (p < 0.001) and mean EVLW by 6.727 mL (p < 0.001). CONCLUSIONS: Height is the only biometric parameter independently associated with the first and mean EVLW. In adult patients, EVLW should be indexed to height.