Gama de Abreu M, Kirschfink M, Quintel M, Albrecht D M
Clinic of Anesthesiology and Intensive Care Medicine, University Clinic Carl Gustav Carus, Technical University Dresden, Germany.
Crit Care Med. 1998 Jun;26(6):1040-8. doi: 10.1097/00003246-199806000-00025.
To investigate and select nonassociated variables with predictive value for acute respiratory distress syndrome (ARDS) in patients at risk.
Prospective, observational study.
A university hospital intensive care unit.
Twenty-four critically ill patients with different risk factors for ARDS.
Arterial and mixed venous blood, as well as urine samples, were collected. Invasive hemodynamic measurements were performed.
Fifty-nine variables pertaining to the cardiorespiratory, hepatic, immunologic, and renal systems and including plasma complement activation products C3a and SC5b-9 and polymorphonuclear elastase, were determined every 6 hrs for 3 days in patients at risk for ARDS. Associations among variables were investigated and the predictive value of nonassociated variables for ARDS was determined. Patients who developed ARDS (n=8) had lower white blood cell counts at the time they entered the study (p=.006) and during the first 24 hrs thereafter (p=.032). Also, plasma C3a concentrations were markedly higher during the first 24 hrs in patients who developed ARDS (p=.006). Plasma C3a had better predictive value than did white blood cell counts for cutoff points set by discriminant analysis at 1075 ng/mL (1.075 x 10(-3) g/L) and 5700 cells/mL, respectively. The combination of both variables in a discriminant function improved the predictive value for ARDS.
The most notable and nonassociated alterations observed in patients who developed ARDS were lower white blood cell counts and higher plasma C3a concentrations compared with counts and concentrations in patients who did not develop ARDS. Plasma C3a concentrations showed better predictive value than white blood cell counts. The combination of white blood cell counts with plasma C3a concentrations synergistically improved the predictive value for ARDS. This combination may prove useful for identifying subpopulations at highest risk for ARDS and may contribute to make treatment at an early stage of the syndrome possible.
