Carboxyhemoglobin, Methemoglobin and Lactate Levels in Patients with Systemic Inflammatory Response Syndrome

Abstract

Background: Systemic inflammatory response syndrome (SIRS) is a common, severe inflammatory condition. This condition forms the basis of the definitions of sepsis, severe sepsis, septic shock, and multiple organ failure syndromes. The diagnosis can be made earlier with arterial blood gas analysis, which can provide a lot of information within minutes. This study aimed to determine the value of carboxyhemoglobin (COHb), methemoglobin (metHb), and lactate levels in the prognosis and mortality of patients with SIRS. Methods:Patients who met the SIRS criteria with the first vital signs and laboratory values and who had arterial blood gas analysis according to the clinician's decision were included in the study. The demographic characteristics, prognosis and correlation of 1-month mortality rates of patients with baseline COHb, metHb and lactate levels were investigated.Results: Among non-smoker patients, no significant difference was found between fCOHb values and age, gender, presence of infection, blood pressure, department of hospitalization, and 1-month mortality rates (p>0.05). Also, the relationship between fCOHb values and length of stay in the hospital was not statistically significant (r = -0.013, p = 0.883). Among the patients included in the study; there was no significant difference in metHb values between age groups (p = 0.9941), gender (p = 0.6422), presence of infection (p = 0.1311), blood pressure (p = 0.7711), length of stay in hospital (p = 0.737), inpatient clinics (p = 0.6722) and 1-month mortality (p = 0.8752). Lactate values were found to be correlated with the 1-month mortality of the patients (p = 0.005). Lactate levels were significantly higher in patients who died within 1-month compared to those who survived. Conclusions:In patients with SIRS, initial COHb and metHb values cannot be considered a predictor for prognosis and mortality. However, lactate values may be useful to predict SIRS mortality even during hospital admission.