Anti–Blood Clotting Protein May Help Predict ICU Mortality

Key Point

Plasma protein C concentration, although associated with organ dysfunction, may be a better predictor of ICU mortality than is organ failure assessment score.

A simple laboratory test to measure protein C may offer a useful new indicator of the severity of illness and risk of death among critically ill patients.

The July issue of Anesthesiology features the new study by Frank Brunkhorst, MD, and colleagues of Friedrich Schiller University in Jena, Germany. “Protein C may be a new target for therapy for patients with non-infectious-induced organ failure/dysfunction in the intensive care unit,” said Dr. Brunkhorst in a released statement. “The possibility to measure protein C levels at the bedside in critically ill patients—without time delay by the central lab—would be a great step forward in assessing prognosis, and may influence clinical decision making at an early stage of the evolution of organ dysfunction.”

The researchers analyzed the relationship between protein C and indicators of organ failure in 312 patients admitted to the surgical ICU with an estimated length of stay of more than 48 hours. Changes in plasma protein C levels were measured daily until patient discharge or death, and analyzed for their ability to predict mortality risk.

About half the patients had protein C levels below the lower limit of normal of 50.6%—reflecting an increased risk of abnormal blood clotting—upon ICU admission. Protein C decreased further over the next three to four days before returning to normal by about two weeks, regardless of patient sex, source and type of admission, type of surgery, or the presence of sepsis.

Lower protein C concentrations were correlated with increased severity of sepsis and greater organ dysfunction. In contrast, patients with less-severe illness—based on Sequential Organ Failure Assessment scores—had higher protein C levels.

Overall, 15% of patients died. Particularly during their first four days in the ICU, patients who died had lower protein C levels than did patients who survived. After adjustment for other factors, the risk of death was four times higher for patients whose minimum protein C level was below 45%. Low protein C levels were the strongest predictor of risk of death—even stronger than Sequential Organ Failure Assessment scores.

Previous studies have noted low protein C levels in critically ill patients, but most have focused on patients with sepsis. Gaining a better understanding of the factors associated with protein C might help ICU specialists to identify patients at high risk of severe illness and death—and possibly provide an opportunity for treatments to lower those risks.

The new study—the largest so far to look at protein C levels in critically ill patients—suggests that protein C may be a valuable indicator of severity of illness and risk of death in the ICU. “Severe sepsis is responsible for 750,000 deaths a year in the US,” commented Michael A. Gropper, MD, PhD, of the University of California, San Francisco, author of an accompanying editorial. “The ability to identify these patients and treat them early will significantly improve their chance of survival. This study is important because it identifies a strategy to easily identify patients with severe sepsis and multisystem organ failure.”

The results add to previous studies suggesting that treatments targeting the protein C pathway might benefit critically ill patients. Although much more research will be needed, treatment with recombinant protein C could offer a new way of interrupting the progression to sepsis and organ failure in high-risk patients. In his editorial, Dr. Gropper concludes, “We await further studies of the coagulation pathway in the hopes of new therapies for this devastating syndrome.” 

Reference
Brunkhorst F, Sakr Y, Hagel S, Reinhart K. Protein C concentrations correlate with organ dysfunction and predict outcome independent of the presence of sepsis. Anesthesiology. 2007;107(1):15-23.
Gropper MA. Multisystem organ failure: predicting the future. Anesthesiology. 2007;107(1):6-7.

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