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Early Determinants of Death Due to Multiple Organ Failure After Noncardiac Surgery in High-Risk Patients

Lobo, Suzana M. MD, PhD*; Rezende, Ederlon MD; Knibel, Marcos F. MD, PhD; Silva, Nilton B. MD, PhD§; Páramo, José A. MD; Nácul, Flávio E. MD; Mendes, Ciro L. MD#; Assunção, Murilo MD**; Costa, Rubens C. MD††; Grion, Cíntia C. MD, PhD‡‡; Pinto, Sérgio F. MD§§; Mello, Patricia M. MD∥∥; Maia, Marcelo O. MD¶¶; Duarte, Péricles A. MD##; Gutierrez, Fernando MD, PhD††; Silva, João M. Junior MD***; Lopes, Marcel R. MD†††; Cordeiro, José A. PhD‡‡‡; Mellot, Charles MD, PhD§§§

doi: 10.1213/ANE.0b013e3181e2bf8e
Critical Care, Trauma, and Resuscitation: Research Reports

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.

Published ahead of print June 8, 2010 Supplemental Digital Content is available in the text.

Author affiliations are provided at the end of the article.

Supported by Centro de Estudos e Pesquisa em Medicina Intensiva, Hospital de Base, São José do Rio Preto, Brazil.

The authors report no conflicts of interest.

Address correspondence and reprint requests to Dr. Suzana Margareth Lobo, Faculdade de Medicina de São José do Rio Preto, Serviço de Terapia Intensiva do Hospital de Base e Laboratório de Sepse, Avenida Brigadeiro Faria Lima, 5544 CEP 15090-000 São Jose do Rio Preto, SP, Brazil. Address e-mail to

Accepted February 25, 2010

Published ahead of print June 8, 2010

Although millions of operations are performed annually worldwide, relatively few patients undergoing major surgery are deemed high risk and at an increased risk of postoperative complications and death.1 A large observational study reported that this population accounts for only 12.5% of all surgical procedures, but for >80% of related deaths.1 Despite the high mortality rates, fewer than 15% of these patients were admitted to the intensive care unit (ICU),1 showing that individual risk can easily be underestimated and high-risk patients not recognized.

In patients with major operative trauma, multiple organ failure (MOF) may be induced by various mechanisms including an aggressive inflammatory response, although the mechanisms by which this occurs are not clear.2 Increasing evidence suggests that oxygen requirements increase significantly as a result of the injury and metabolic response to trauma. However, very frequently, high-risk patients are unable to spontaneously increase their cardiac output to match this increased oxygen demand.3 Such patients are therefore more likely to develop oxygen debt and, as a consequence, severe systemic inflammation with death due to ongoing organ dysfunction and nosocomial sepsis.4 In addition, not infrequently, these patients undergo surgery for peritonitis and therefore already have sepsis when submitted to surgery.

Several attempts have been made to help identify patients at risk of complications and death after surgery. Studies have identified predictors of morbidity and mortality after colon, esophageal, and gastric surgery, and after pulmonary resection.57 Other studies have evaluated predictors of postoperative cardiac complications in noncardiac surgical patients.811 High-risk surgical patients admitted to the ICU frequently die as a consequence of primary or secondary MOF, the latter of which is frequently a result of sepsis.12,13 Predictors of death due to MOF have never been investigated in high-risk surgical patients. Therefore, we investigated the early perioperative risk factors for in-hospital death due to MOF in a population of surgical patients admitted to the ICU.

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Data were extracted from a prospective multicenter observational cohort study, the SCORIS study, performed from April 1 to June 31, 2006, to which 21 Brazilian ICUs from 18 institutions (8 public and 10 private hospitals) contributed. The SCORIS study was designed to evaluate the epidemiology and clinical outcomes of surgical ICU patients and to develop a model to predict the outcome of such patients in Brazilian ICUs. The IRB from the coordinator center waived the need for informed consent because of the observational nature of the study. Institutional recruitment for participation was by open invitation from the study steering committee.

Adult patients (834 cases) undergoing noncardiac surgery and admitted to a participating ICU within 24 hours after operation were evaluated for inclusion. Patients undergoing trauma, neurological, gynecologic, obstetric, or palliative surgery were excluded.

Data were collected on age, gender, smoking habits, alcohol abuse, nutritional status, diabetes, renal function, chronic obstructive pulmonary disease, and presence of malignant disease.

Patients taking oral antidiabetic medications or insulin were considered to have a diagnosis of diabetes. Cardiopathy was defined as the presence of moderate or severe cardiomegaly, turgescent jugular veins, and use of digital, diuretics, antiangina, and antihypertensive drugs. Low functional capacity was defined as inability to climb 2 flights of stairs on subjective evaluation. Electrocardiographic abnormalities included nonsinus rhythms, frequent ventricular extrasystoles (>5/min), Q waves, or ST-T segment abnormalities. For the diagnosis of angina, the Canadian Cardiovascular Society classification system was used. A diagnosis of acute myocardial infarction required the presence of typical electrocardiographic alterations together with elevated cardiac enzymes and/or segmental wall motion abnormalities on echocardiography. Other clinical predictors of increased perioperative cardiovascular risk were defined according to the American College of Cardiology/American Heart Association guidelines. All data were entered on an electronic case report file (Comunicare®) and the variables were cross-checked by 2 of the authors.

The following procedures were considered major surgery: laparotomy, enterectomy, cholecystectomy with choledochostomy, major amputation, vascular and aortic procedures, rectal abdominoperineal resection, pancreatectomy, esophagectomy, and hepatectomy. Unplanned surgery comprised admissions after urgent (within 48 hours of referral) or emergent (immediately after referral/consultation) surgery. The Physiological and Operative Severity Score for the Enumeration of Mortality and Morbidity (POSSUM), the Acute Physiology and Chronic Health Disease Classification System II (APACHE II) score, the Multiple Organ Dysfunction System score, and the Sequential Organ Failure Assessment score were calculated.1417 Peritonitis was classified according to the findings noted at laparotomy as either serum fluid associated with an infection site or the presence of collected or diffuse purulent discharge in the abdominal cavity.14 Severe bleeding was defined as an estimated blood loss >500 mL during surgery. For vital signs, laboratory tests, and central venous pressure (CVP) measurements, the most abnormal values collected over the first 24 hours of ICU stay were registered.

Sepsis syndromes were defined according to the consensus conference definitions.18 Early- and late-onset sepsis were defined as a diagnosis of sepsis made within 72 hours of ICU admission or thereafter, respectively.

Causes of death were classified as follows: MOF, characterized by the presence of at least 2 organ failures contributing to death; refractory cardiovascular failure, characterized as uncontrollable hypotension despite high-dose vasopressors determining death; coagulation failure, characterized as need for massive transfusion, and hemorrhagic shock after surgery; sudden death (unexpected cardiac arrest); and unknown cause.

Data were analyzed using SPSS 13.0 for Windows (SPSS, Inc., Chicago, IL). Continuous variables are presented as mean ± SD and/or median (range), and categorical variables are reported as absolute numbers (percentages). Nonparametric tests of comparison were used for variables evaluated as not normally distributed. Difference testing between groups was performed using the 2-tailed t test, χ2 test, Wilcoxon test, analysis of variance, and Fisher exact test as appropriate. Bonferroni adjustment was used for multiple comparisons. We considered P < 0.05 as statistically significant.

We performed a logistic regression multivariate analysis with in-hospital death due to MOF as the dependent factor. Variables considered for the regression analysis included age, gender, comorbid diseases, the type of admission (planned or unplanned), the type of surgery (nonmajor or major), malnutrition, alcoholism, maximal heart rate (HR), lowest hemoglobin concentration and highest urea concentration before operation, severe bleeding during surgery (estimated blood loss >500 mL), arrhythmia during operation, peritonitis, postoperative measurements of minimal and maximal CVP, minimal axillary temperature, total leukocyte count, hemoglobin concentration, serum lactate concentration, pH, and total platelet count. Colinearity between variables was excluded before modeling. Covariates were selected and entered in the model if they attained a P < 0.2 on a univariate basis.

POSSUM scores with respective estimated mortality rates were calculated. Discrimination for the severity scores was assessed by area under receiver operating characteristic (ROC) curves.

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Characteristics of the Study Groups

A total of 587 consecutive patients were admitted to the participating ICUs during the study period (55% male; mean age = 62.4 ± 17 years). A total of 247 patients were excluded (127 for neurosurgery; 35 palliative surgery; 6 gynecologic surgery; 32 trauma; 34 lost to follow-up; 8 were younger than 18 years; and 5 had no indication for ICU admission).

The characteristics of the study groups are shown in Table 1. Cardiopathy (35.4%), cancer (32%), and diabetes (20%) were the most prevalent comorbid conditions. Sixty-six percent of the patients were admitted after major surgery and 32% after unplanned surgery. The most common type of surgery was gastrointestinal surgery (44%) followed by vascular procedures (23%).

Table 1

Table 1

A total of 135 patients (23%) had sepsis during their ICU stay; 64% of these died in the hospital. One hundred forty-one patients (24.0%) had peritonitis of whom 66 (46.8%) developed sepsis, with 50 cases of early-onset sepsis (37%).

The ICU mortality rate was 15%. Overall hospital mortality rates were 16.7% at 30 days, 20.6% at 60 days, and 20.6% at 90 days. The causes of death in the ICU were MOF (53%), sudden death (14.9%), refractory shock (6.8%), bleeding (2.5%), and unknown (22.8%).

Of the patients who died, 94% had significant medical comorbidities at the time of surgery (3.4 ± 2.2), 66% had undergone urgent surgery, 70% were older than 60 years, and 46% older than 70 years. In addition, 35% had low functional capacity, 28% malnutrition, and 26% hemodynamic instability before surgery. Serum lactate concentrations, HR, and CVP values were higher and pH lower on the first day of ICU admission in nonsurvivors (Table 2).

Table 2

Table 2

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Characteristics and Outcomes of the Patients Who Died Due to MOF

Death was due to MOF in 64 patients (53%) (Table 1). Patients who died due to MOF were more severely ill on ICU admission (APACHE II, 19.9 ± 6.9 vs 17.1 ± 6.0, P < 0.05) and more frequently died in the ICU (98.4% vs 43.8%, P < 0.05) than patients who died due to other causes. Low functional capacity (41% vs 21%) and gastrointestinal surgery (25% vs 3.5%) were significantly more frequent in patients who died due to MOF than in patients who died due to other causes (P < 0.05 for both). In contrast, alcoholism and other types of surgery were more frequently associated with deaths due to other causes (Table 1). Early onset sepsis was more prevalent in patients who died due to MOF (34.3%) compared with patients who died of other causes (19.3%) but the difference was not statistically significant (P = 0.09).

On the day of ICU admission, the maximal CVP was significantly higher (18.2 ± 7.7 vs 14.5 ± 8.2 mm Hg, P < 0.01) and the pH significantly lower (7.20 ± 0.13 vs 7.27 ± 0.09, P < 0.05) in patients who died due to MOF than in patients who died of other causes (Table 2).

The variables identified as independent predictors of death due to MOF were age, unplanned surgery, diabetes, peritonitis, and, on the first day of ICU admission, high CVP (mm Hg), increased HR, increased serum lactate concentrations (mEq/L), and pH (Fig. 1).

Figure 1

Figure 1

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Comparison Between the Outcomes of the Patients to That Predicted by the Severity Scores

The POSSUM score gave a standardized mortality ratio of 1.2 (degrees of freedom = 0.02, P = 0.001). The area under the ROC curve for hospital mortality was 0.80 (95% confidence interval 0.775–0.840) for the POSSUM score. The areas under the ROC curves for hospital mortality for APACHE II, Multiple Organ Dysfunction System, and Sequential Organ Failure Assessment scores were 0.808, 0.802, and 0.805, respectively (Fig. 2).

Figure 2

Figure 2

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Despite the large amount of resources directed at evaluating the risk of perioperative cardiovascular complications, our results indicate that MOF is the main cause of death in high-risk surgical patients, deemed to be the cause of death in 53% of our patients. MOF has recently been shown to be the main cause of morbidity and mortality in patients admitted to ICUs, and has been calculated to account for up to 80% of ICU deaths.19

In an Australasian study, MOF was the cause of death in 20.3% of patients admitted to the ICU with severe noninfectious systemic inflammatory response syndrome and in 69% of patients with severe sepsis.20 In a large prospective study performed in a population of mainly surgical critically ill patients, acute or chronic MOF prevailed as the cause of death in the ICU.13 In a study on macroscopic postmortem findings in surgical intensive care patients with sepsis, the main causes of death as reported in the patient history were refractory MOF in 51.5%.21

The multivariable analysis confirmed that tachycardia, high CVP and serum lactate levels, and pH on the day of admission to the ICU are early predictors of death due to MOF. Moreover, we found that unplanned surgery, peritonitis, older age, and the presence of diabetes significantly increased the risk of death due to MOF.

Tachycardia, lactic acidosis, or acidosis due to other causes, such as hyperchloremic acidosis, are common occurrences after major surgery. These factors are undoubtedly related to traumatic and long operations, with an enhanced systemic inflammatory response, inadequate resuscitation, and tissue hypoperfusion. Our findings are consistent with numerous studies that have demonstrated an association between organ hypoperfusion and indices of tissue trauma and organ dysfunction.22,23 Likewise, studies in surgical ICU patients, and in patients with infection, sepsis, and shock have reported worse outcomes related to higher serum lactate concentrations.2428 Prolonged lactate clearance is related to increased mortality after surgery, and lactate nonclearance during resuscitation was a strong independent predictor of in-hospital death in patients with severe sepsis.2931

Importantly, we found a 12% increase in the risk of death due to MOF for each unit increase in CVP. Traditionally, cardiac filling pressures have been used to assess volume status in critically ill patients. The observational design of our study does not allow us to conclude whether elevated CVP levels represented excessive intravascular volume, poor cardiovascular reserve, or both. Moreover, in more complex cases, the presence of external or intrinsic positive end-expiratory pressure, abdominal hypertension, compromised left ventricular compliance, which is frequently decreased in ICU patients with sepsis, ischemic or hypertrophic cardiopathy, can increase CVP measurements even in the presence of hypovolemia. Nevertheless, several studies have associated a positive fluid balance with complications and death in ICU patients.32

MOF development in patients imposes a heavy burden on staff and resources, and patients have long ICU lengths of stay and high costs. Awareness of early risk factors for MOF would be valuable if changes in clinical management could be prompted by potentially avoidable predictors of poor outcome. Several important clinical trials have documented that early aggressive resuscitation using well-defined protocols, such as goal-directed therapy (GDT), improves outcomes and is cost effective.3340 These studies have used therapeutic strategies aimed at boosting cardiorespiratory function and maintaining end-organ perfusion through a more individualized and targeted fluid therapy and reported reductions in the length of ICU and hospital stay, a faster recovery of gastrointestinal function, and a reduction in mortality when GDT was performed in higher risk surgical patients.41

The mortality rate in our study was higher than that predicted by the POSSUM score. All scoring systems that we evaluated had the same capacity of predicting hospital mortality in this population of surgical patients admitted to the ICU postoperatively. Unfortunately, in our country, early GDT, best known in this set of patients as optimization of oxygen delivery, is still not widely used in clinical practice despite the growing body of evidence. As a consequence of our findings and the high mortality observed in this population of surgical patients, we recommend sequential measurements of serum lactate, pH, and CVP to be used in the context of well-defined protocols of optimization of oxygen delivery to guide adjustments of IV fluid administration and use of dobutamine to maintain a maximal stroke volume in the perioperative period.3439

Age has been reported to be independently associated with MOF in medical patients and in heterogeneous populations of critically ill patients, with death in patients with systemic inflammatory response syndrome and MOF, and with post-ICU mortality in surgical ICU patients.12,20,42,43 Serum glucose levels were tested in the logistic regression model but were not retained; however, a history of diabetes was a strong predictor increasing the odds of MOF by 3.63. Diabetes mellitus is a chronic, systemic debilitating condition that affects many organ functions, increases the likelihood and extent of coronary artery disease, and increases the likelihood of infections. Other studies have shown that glucose levels and glucose variability, rather than diabetes, were important factors associated with organ dysfunction.44,45 Hyperglycemia was independently associated with organ failure and death in critically ill children.46

Unplanned surgery increased the odds of death due to MOF by almost 4-fold. Indeed, in a prospective, observational, Australian study, performed in 1125 subjects undergoing surgery in a tertiary teaching hospital, unplanned ICU admission increased the risk of death by 4-fold.47 Other studies have shown emergency surgery to be an important predictor of mortality in older patients.48

Peritonitis was an independent predictor of death due to MOF. A total of 141 patients (24.0%) had peritonitis, of whom 18.4% developed sepsis within 48 hours of ICU admission. When sepsis progresses to sepsis-associated organ failure and hypotension, mortality increases from 27% to >50% in patients with septic shock.49 Severe sepsis occurred in 23% of the patients in our cohort of high-risk surgical patients, with a hospital mortality rate of 64%. The nosocomial sepsis that is so typical of the later course of such patients in the ICU can occur as a consequence of organ dysfunction, prolonging their stay and increasing the risk of infection.

This study is limited by the relatively small number of patients and ICUs. However, although the size of the study was relatively modest, its selected study group is more likely to represent real surgical practice. Despite the large size of our country, all regions were represented. Our cohort was a population of high-risk surgical patients as demonstrated by the frequent prevalence of comorbid diseases and unplanned surgery, high degrees of physiologic derangement as shown by the high POSSUM and APACHE II scores, and the correspondingly high mortality rates. Bed shortages in Brazilian hospital ICUs may be the cause of the admission of higher risk cases than in some other countries.

In conclusion, the vast majority of deaths in this high-risk population of surgical patients were due to MOF. We identified several routinely available variables as strong predictors of the development of a fatal outcome due to MOF in our high-risk surgical ICU patients.

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From the *Intensive care Unit, Hospital de Base and São José do Rio Preto Medical School; †Intensive Care Unit, Hospital do Servidor Público Estadual Francisco Morato de Oliveira, São Paulo; ‡Intensive Care Unit, Hospital São Lucas and Hospital Cardiotrauma Ipanema, Rio de Janeiro; §Intensive Care Unit, Hospital Moinhos de Vento, Porto Alegre; ∥Intensive Care Unit, Clínica Sorocaba, Rio de Janeiro; ¶Intensive Care Unit, Clínica São Vicente, Rio de Janeiro; #Adult Intensive Care Unit, Hospital Universitário da Universidade Federal da Paraíba, João Pessoa; **Department of Anesthesiology, Pain and Intensive Care, Universidade Federal de São Paulo, São Paulo; ††Intensive Care Unit, Hospital Pró-Cardíaco, Rio de Janeiro; ‡‡Intensive Care Department, Universidade Estadual de Londrina, Londrina; §§Intensive Care Unit, Hospital Universitário da Universidade Federal do Mato Grosso do Sul, Campo Grande; ∥∥Universidade Estadual do Piauí, Teresina; ¶¶Intensive Care Unit, Hospital Santa Luzia, Brasília; ##Medical School, Universidade Estadual do Oeste do Paraná, Cascavel; ***Hospital do Servidor Público Estadual Francisco Morato de Oliveira, São Paulo; †††Intensive Care Unit, Santa Casa de Misericórdia, Passos; ‡‡‡Medical School of São José do Rio Preto, São José do Rio Preto, Brazil; and §§§Department of Intensive Care, Erasme Hospital, Free University of Brussels, Brussels, Belgium.

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SML and ER helped in study design and manuscript preparation; MFK, NBS, JAP, CLM, FEN, MA, RCC, CCG, SFP, PMM, MOM, PAD, FG, and MRL helped in conduct of study; JMS helped in data analysis and conduct of study; and JAC and CM helped in data analysis.

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