Early determinants of death due to multiple organ failure after noncardiac surgery in high-risk patients.

BACKGROUND: Prediction of perioperative cardiac complications is important in the medical management of patients undergoing noncardiac surgery. However, these patients frequently die as a consequence of primary or secondary multiple organ failure (MOF), often as a result of sepsis. We investigated the early perioperative risk factors for in-hospital death due to MOF in surgical patients. METHODS: This was a prospective, multicenter, observational cohort study performed in 21 Brazilian intensive care units (ICUs). Adult patients undergoing noncardiac surgery who were admitted to the ICU within 24 hours after operation were evaluated. MOF was characterized by the presence of at least 2 organ failures. To determine the relative risk (RR) of in-hospital death due to MOF, we performed a logistic regression multivariate analysis. RESULTS: A total of 587 patients were included (mean age, 62.4 ± 17 years). ICU and hospital mortality rates were 15% and 20.6%, respectively. The main cause of death was MOF (53%). Peritonitis (RR 4.17, 95% confidence interval [CI] 1.38-12.6), diabetes (RR 3.63, 95% CI 1.17-11.2), unplanned surgery (RR 3.62, 95% CI 1.18-11.0), age (RR 1.04, 95% CI 1 0.01-1.08), and elevated serum lactate concentrations (RR 1.52, 95% CI 1.14-2.02), a high central venous pressure (RR 1.12, 95% CI 1.04-1.22), a fast heart rate (RR 3.63, 95% CI 1.17-11.2) and pH (RR 0.04, 95% CI 0.0005-0.38) on the day of admission were independent predictors of death due to MOF. CONCLUSIONS: MOF is the main cause of death after surgery in high-risk patients. Awareness of the risk factors for death due to MOF may be important in risk stratification and can suggest routes for therapy.

Pulse pressure variation: beyond the fluid management of patients with shock.

In anesthetized patients without cardiac arrhythmia the arterial pulse pressure variation (PPV) induced by mechanical ventilation has been shown the most accurate predictor of fluid responsiveness. In this respect, PPV has so far been used mainly in the decision-making process regarding volume expansion in patients with shock. As an indicator of the position on the Frank-Starling curve, PPV may actually be useful in many other clinical situations. In patients with acute lung injury or with acute respiratory distress syndrome, PPV can predict hemodynamic instability induced by positive end-expiratory pressure and recruitment maneuvers. PPV may also be useful to prevent excessive fluid restriction/depletion in patients with pulmonary edema, and to prevent excessive ultrafiltration in critically ill patients undergoing hemodialysis or hemofiltration. In the operating room, a goal-directed fluid therapy based on PPV monitoring has the potential to improve the outcome of patients undergoing high-risk surgery.

Goal-directed fluid management based on pulse pressure variation monitoring during high-risk surgery: a pilot randomized controlled trial.

INTRODUCTION: Several studies have shown that maximizing stroke volume (or increasing it until a plateau is reached) by volume loading during high-risk surgery may improve post-operative outcome. This goal could be achieved simply by minimizing the variation in arterial pulse pressure (deltaPP) induced by mechanical ventilation. We tested this hypothesis in a prospective, randomized, single-centre study. The primary endpoint was the length of postoperative stay in hospital. METHODS: Thirty-three patients undergoing high-risk surgery were randomized either to a control group (group C, n = 16) or to an intervention group (group I, n = 17). In group I, deltaPP was continuously monitored during surgery by a multiparameter bedside monitor and minimized to 10% or less by volume loading. RESULTS: Both groups were comparable in terms of demographic data, American Society of Anesthesiology score, type, and duration of surgery. During surgery, group I received more fluid than group C (4,618 +/- 1,557 versus 1,694 +/- 705 ml (mean +/- SD), P < 0.0001), and deltaPP decreased from 22 +/- 75 to 9 +/- 1% (P < 0.05) in group I. The median duration of postoperative stay in hospital (7 versus 17 days, P < 0.01) was lower in group I than in group C. The number of postoperative complications per patient (1.4 +/- 2.1 versus 3.9 +/- 2.8, P < 0.05), as well as the median duration of mechanical ventilation (1 versus 5 days, P < 0.05) and stay in the intensive care unit (3 versus 9 days, P < 0.01) was also lower in group I. CONCLUSION: Monitoring and minimizing deltaPP by volume loading during high-risk surgery improves postoperative outcome and decreases the length of stay in hospital. TRIAL REGISTRATION: NCT00479011.