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Dr. Dubaybo is Professor of Medicine, and Director, Fellowship Training Program, Pulmonary, Critical Care and Sleep Medicine, Wayne State University School of Medicine. Corresondence to: Basim A. Dubaybo, MD, FCCP, 3-Hudson, Harper Hospital, 3990 John R, Detroit, MI 48201; e-mail: bdubaybo@intmed.wayne.edu
Predicting patient outcome is an important component of patient care in critical care units. Physicians are frequently faced with a number of challenging questions posed by patients, relatives, referring physicians, and other health-care providers. Will the patient make a full recovery? What functional status will the patient have following recovery? How soon will the patient be discharged? How aggressively should this patient be resuscitated in the case of cardiopulmonary arrest? Hospital administrators pose a different set of challenging questions. Are our limited resources properly allocated? Can we justify the cost?
Faced with these challenges, intensivists have developed a number of prognostication tools for patients admitted to the ICU. Though useful, these tools are complex. The widely used APACHE (acute physiology and chronic health evaluation) II score,1 for example, requires input of a large number of variables derived from the patient’s history, physical examination, and initial laboratory data. This is also true of the APACHE III score, sequential organ failure assessment score, simplified acute physiology score, and others.2 3 4 In addition, scoring systems rely mainly on data obtained early in the course of the illness. It is well-known that the physiologic responses of patients to insults and interventions vary. The strength of initial predications, therefore, may be influenced by numerous factors during the course of hospitalization. These factors may not be accounted for in the initial assessment. That this is the case is supported by studies5 6 that show that multiple severity-of-illness scores, including APACHE III, frequently underestimate hospital mortality in several conditions.
In this edition of CHEST (see page 1984), Abid et al propose microalbuminuria as a simple, inexpensive, and dynamic prognostic tool in a medical ICU. In a pilot study, they evaluated its prognostic value for the development of acute respiratory failure and/or multiple organ failure. There are theoretical reasons why this parameter should be a useful prognostic index in critically ill patients admitted to the ICU. First, it makes intuitive sense to look at one or more kidney functions as surrogate markers for systemic illness. Kidney involvement is a recognized complication of several systemic diseases. Furthermore, the kidney receives a generous portion of the cardiac output. Exogenous as well as endogenous agents precipitating or contributing to the patient’s critical illness have a high probability of traversing the kidney circulation and causing glomerular injury. Second, microalbuminuria is a reflection of capillary leak, which is observed in multiple organ dysfunction syndrome.7 In this syndrome, diffuse systemic inflammation results in systemic capillary leak in most vascular beds, including the kidney, where it manifests as albuminuria. Gossling8 observed peak albuminuria in patients with systemic inflammation up to 2 days before a detectable rise in other markers of inflammation.
Microalbuminuria, defined as urinary albumin levels in the range of 30 to 200 mg/L, can be detected by the use of a simple semiquantitative dipstick technique. The prognostic usefulness of microalbuminuria has been demonstrated in a number of conditions. In lung cancer patients, for example, Pedersen and Milman9 observed that the presence of microalbuminuria was associated with advanced disease and poor survival. A similar observation was made in patients with non-Hodgkin’s lymphoma.10 In addition, microalbuminuria was found to be a useful tool in predicting cardiovascular mortality in treated hypertensive men with or without diabetes mellitus.11 Borch-Johnsen et al12 concluded that microalbuminuria is an independent predictor of ischemic heart disease and its presence substantially increases cardiovascular risk. Microalbuminuria measured 6 h after ICU admission demonstrated a significant difference between survivors and nonsurvivors.13 In another study,14 an increase in glomerular permeability during the first 24 h after trauma correlated with the extent of injury, although it did not appear to have a positive predictive value with respect to severity of illness or outcome. It is interesting that these latter two studies attempted to evaluate microalbuminuria after some (albeit short) period of time had elapsed since hospital admission. This lends more credence to the notion that parameters measured during the course of hospitalization are important in predicting outcome.
In this context, the work of Abid et al on the prognostic value of microalbuminuria is very significant. The investigators measured this index of inflammation as early as 8 h after hospital admission, and repeated this measurement on a daily basis for 5 days. This allowed the investigators to follow changes in the magnitude of microalbuminuria with time. They found that patients with increasing microalbuminuria, suggesting progressive inflammation, had a worse outcome and higher mortality than those who had a decreasing trend. As expected, APACHE II and sequential organ failure assessment scores were higher in the former group. Interestingly, progressively decreasing microalbuminuria had a negative predictive value of 100% for the development of acute respiratory failure and 96% for multiple organ failure. This was superior to the positive predictive value of increasing microalbuminuria, which was 57% and 50% for these two parameters, respectively. Because of the limited number of patients in every diagnostic category, it was not possible to do subgroup analysis. Larger cohorts of patients may prove this tool to be even more useful in specific patient populations such as sepsis or respiratory tract infections. As the authors indicate, this is a pilot study that needs to be confirmed in larger studies encompassing multiple conditions. However, this study emphasizes the need to look for simple and inexpensive tools to predict outcome. Furthermore, this study confirms what intensivists have known for a long time: the predictive value of severity-of-illness scores can be substantially improved by utilizing data collected serially during the course of hospitalization in the ICU. The notion that severity-of-illness scores should incorporate data collected on an ongoing basis is here to stay.
References
This article has been cited by other articles:
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  M. Gai, V. Cantaluppi, C. Fenocchio, D. Motta, S. Masini, A. Pacitti, and G. Lanfranco Presence of Protein Fragments in Urine of Critically Ill Patients with Acute Renal Failure: A Nephrologic Enigma Clin. Chem., October 1, 2004; 50(10): 1822 - 1824. [Full Text] [PDF]
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