0
Original Research |

Epidemiology of Critical Care Syndromes, Organ Failures, and Life-Support Interventions in a Suburban US CommunityEpidemiology of Critical Care Syndromes FREE TO VIEW

Rodrigo Cartin-Ceba, MD; Marija Kojicic, MD; Guangxi Li, MD; Daryl J. Kor, MD; Jaise Poulose, MD; Vitaly Herasevich, MD; Rahul Kashyap, MBBS, MD; Cesar Trillo-Alvarez, MD; Javier Cabello-Garza, MD; Rolf Hubmayr, MD, FCCP; Edward G. Seferian, MD; Ognjen Gajic, MD
Author and Funding Information

From the Multidisciplinary Epidemiology and Translational Research in Intensive Care (M.E.T.R.I.C) (Drs Cartin-Ceba, Kojicic, Li, Kor, Poulose, Herasevich, Kashyap, Trillo-Alvarez, Cabello-Garza, Hubmayr, Seferian, and Gajic); Department of Medicine (Drs Cartin-Ceba, Li, Poulose, Herasevich, Trillo-Alvarez, Cabello-Garza, Hubmayr, Seferian, and Gajic), Division of Pulmonary and Critical Care Medicine; and Department of Anesthesiology (Dr Kor), Mayo Clinic, Rochester, MN; and Institute for Pulmonary Diseases of Vojvodina (Dr Kojicic), Sremska Kamenica, Serbia.Dr Seferian is currently at Cedars-Sinai Medical Center (Los Angeles, California).

Correspondence to: Rodrigo Cartin-Ceba, MD, Mayo Clinic, 200 First St SW, Rochester, MN 55905; e-mail: cartinceba.rodrigo@mayo.edu

Data are presented as mean ± SD, No. (%), and median (interquartile range). APACHE = Acute Physiologic and Chronic Health Evaluation; DNR = do not resuscitate; PACU = postanesthesia care unit.

AKI = acute kidney injury; ALI = acute lung injury; CCS = critical care syndrome; DIC = disseminated intravascular coagulation; IABP = intraaortic balloon counterpulsation; LVAD = left ventricular assist device; MV = mechanical ventilation; RRT = renal replacement therapy.

a

Per 100,000 population.

b

According to the Sequential Organ Failure Assessment.

See Table 2 legend for expansion of abbreviation.

Funding/Support: The authors have reported to CHEST that no funding was received for this study.

Reproduction of this article is prohibited without written permission from the American College of Chest Physicians (http://www.chestpubs.org/site/misc/reprints.xhtml).


Funding/Support: The authors have reported to CHEST that no funding was received for this study.

Funding/Support: The authors have reported to CHEST that no funding was received for this study.

Reproduction of this article is prohibited without written permission from the American College of Chest Physicians (http://www.chestpubs.org/site/misc/reprints.xhtml).

Reproduction of this article is prohibited without written permission from the American College of Chest Physicians (http://www.chestpubs.org/site/misc/reprints.xhtml).


Chest. 2011;140(6):1447-1455. doi:10.1378/chest.11-1197
Text Size: A A A
Published online

Background:  ICU services represent a significant and increasing proportion of medical care. Population-based epidemiologic studies are essential to inform physicians and policymakers about current and future ICU demands. We aimed to determine the incidence of critical care syndromes, organ failures, and life-support interventions in a defined US suburban community with unrestricted access to critical care services.

Methods:  This population-based observational cohort from January 1 to December 31, 2006, in Olmsted County, Minnesota, included all consecutive critically ill adult residents admitted to the ICU. Main outcomes were incidence of critical care syndromes, life-support interventions, and organ failures as defined by standard criteria. Incidences are reported per 100,000 population (95% CIs) and were age adjusted to the 2006 US population.

Results:  A total of 1,707 ICU admissions were identified from 1,461 patients. Incidences of critical care syndromes were respiratory failure, 430 (390-470); acute kidney injury, 290 (257-323); severe sepsis, 286 (253-319); all-cause shock, 194 (167-221); acute lung injury, 86 (68-105); all-cause coma, 43 (30-55); and overt disseminated intravascular coagulation, 18 (10-26). Incidence of mechanical ventilation was invasive, 310 (276-344); noninvasive, 180 (154-206); vasopressors and inotropes, 183(155-208). Renal replacement therapy incidence was 96 (77-116). Of the cohort, 1,330 patients (91%) survived to hospital discharge. Short- and long-term survival decreased by the number of failing organs.

Conclusions:  In a suburban US community with high access to critical care services, cumulative incidences of critical care syndromes and life-support interventions were higher than previously reported. The results of this study have important implications for future planning of critical care delivery.

Figures in this Article

In the United States, millions of patients are admitted to the ICU each year. The resulting health-care costs are substantial, having been recently estimated at 0.7% of the annual gross domestic product.1 One in five Americans dies while receiving critical care services,2 and it is expected that this proportion will increase as the population’s life expectancy continues to rise.3 The comorbidities associated with aging are also increasing, and both the demand for intensive care and the complexity of critically ill patients are on the rise.4

Describing the epidemiology of critical care syndromes (CCSs) is challenging for a number of reasons, including practice variation, lack of standardized and reliable definitions for some of the main CCSs,5 and the complexity of critical illness with syndrome overlap. Moreover, the reported incidences of CCS characteristically rely on the “treated” incidence, which often is quite different from the true incidence, particularly when access to ICU services is limited.6 In addition, some of the limitations of incidence studies of CCS include reliance on administrative (billing) data, lack of a population-based approach (most studies reported incidence as the number of cases per 100 ICU admissions and not per 100,000 inhabitants), nonstandardized clinical definitions, sampling over a short period of time (seasonal limitation), and underestimation by excluding less severe forms of disease. In addition, epidemiologic information for many important syndromes, such as all-cause shock, nontraumatic coma, and hypovolemic shock, are lacking.

The epidemiologic success of population-based studies, such as the Framingham study7,8 and the Rochester Epidemiology Project,9 have broadened our knowledge of the risk factors of important diseases and have helped immensely in the planning of prevention strategies as well as in the early identification and treatment of diseases. In order to provide a comprehensive epidemiologic description, we aimed to describe the incidence of CCS, organ failures, and life-support interventions in the community by conducting an observational cohort study of adult Olmsted County, Minnesota, residents admitted to the ICU during the year 2006.

After receiving Mayo Clinic Institutional Review Board approval (number 07-005248), we performed a population-based, retrospective cohort study of Olmsted County residents (aged ≥ 18 years); admitted to the ICUs at two Mayo Clinic hospitals in Rochester, Minnesota, from January 1 to December 31, 2006. The demographics of Olmsted County residents are typical of a suburban community in the midwestern United States. The total population was 124,277 and largely comprised middle-class whites, with minorities representing 13% of the population according to 2000 US census reports.

Olmsted County acute care hospitals are the Mayo Clinic-affiliated hospitals (private, not-for-profit academic institutions) Rochester Methodist (342 inpatient beds) and Saint Marys (946 inpatient beds) and Olmsted Medical Center (64 inpatient beds). These hospitals provide > 95% of medical care for Olmsted County.3 Because of its geographic isolation, critical care services are provided exclusively by the two Mayo Clinic hospitals in Rochester. The closest competing medical centers are located in Minneapolis, Minnesota (139.2 km to the north); LaCrosse, Wisconsin (113.6 km to the east); Iowa City and Des Moines, Iowa (316.8 and 332.8 km to the south, respectively); and Sioux Falls, South Dakota (376 km to the west). The eight Mayo Clinic adult ICUs have a total of 164 beds and include medical, surgical, and cardiac care units.3 Patients are managed or comanaged by specialists in critical care medicine. Olmsted County residents were identified based on the nine-digit zip code of their primary residence and verified with the Rochester Epidemiology Project database.9 We excluded patients who denied authorization for the use of their medical information for research (< 5% of the population).

The main outcomes assessed were the cumulative incidences of CCS, organ failures, and life-support interventions. Secondary outcomes included hospital mortality and long-term survival. For survival analysis, patients were followed until June 20, 2009, which is the last date of available data for the study.

Data Abstraction and Management

The study used a protocol to identify patients who met the standardized criteria for CCS, organ failures, or life-support interventions. Abstraction of data was performed by eight critical care fellows who had been trained in the reliable identification of the main outcomes (initially by simulated cases and then by real cases under direct supervision and auditing by critical care specialists). Data were obtained from institutional databases and electronic medical records. Hemodynamic, fluid, drug infusion, and respiratory information were available with a 15-min time resolution. Nursing observations, including Glasgow Coma Scale, were charted at 4-h intervals. In patients who required respiratory support, digital portable chest radiographs were independently reviewed according to standardized criteria.

Identification of Cases

We defined CCS, organ failures, and life-support interventions based on standardized criteria (e-Appendix 1). Given that a significant number of patients presented with multiple admissions and in order to prevent introduction of bias by inclusion of multiple episodes in the same patient, only the first episode where any of the CCS, organ failures, and life-support interventions occurred was included in the analysis.

Data Quality Assessment

Extensive efforts were made to ensure the quality of the data. At the end of the data collection, the cases were reviewed by a critical care specialist to assess whether criteria definitions were met. We used a standardized electronic data collection form in order to secure the quality of the information entered. To increase interobserver reliability, assessors were trained on simulated cases before the initiation of the data collection and, therefore, were evaluated on the quality of the data entered. For adequate interpretation of radiological studies in the diagnosis of acute lung injury (ALI), the abstractors reviewed a structured ALI tutorial prior to study onset. Interrater reliability was performed for ALI, acute kidney injury (AKI), and shock ascertainment in all incident cases, with a κ of 0.8, 0.88, and 0.84, respectively.

Statistical Analysis

All continuous data are summarized as mean ± SD for normally distributed data and median and interquartile range (IQR) for skewed data. Categorical data are summarized as counts and percentages. Cumulative incidence (95% CI) of CCS, organ failures, and life-support interventions were calculated, assuming the entire 2006 population of Olmsted County (aged ≥ 18 years) was at risk. Rates were calculated using the incident cases as the numerator, and the denominator was the age-adjusted Olmsted County (≥ 18 years) population derived from the projected 2006 US population (using the data from the 2000 US population census and calculating an expected 1.9% population growth per year). Survival analysis was performed and reported with a Kaplan-Meier curve and the log-rank test. Standardized mortality ratio was calculated by dividing actual by mean predicted death rate at hospital discharge.10 JMP, version 8.0, and SAS, version 9.1 (SAS Institute Inc; Cary, North Carolina) statistical software programs were used for all data analyses.

During 2006, we identified 1,707 ICU admissions from 1,461 adult Olmsted County residents (Fig 1). Table 1 presents the baseline characteristics of the patients included in the study. The mean ± SD age of this group of critically ill patients was 62 ± 19 years, with 52% men and 89% white. A total of 551 patients (37.7%) were postoperative (394 patients postelective surgery). Patients with do-not-resuscitate orders on ICU admission comprised 9.5% of the cohort. Nine percent of the patients were nursing home residents, and the majority of the patients (48.8%) were admitted from the ED. The most common reason for ICU admission was a cardiovascular disorder (15.6%), and the mean APACHE (Acute Physiology and Chronic Health Evaluation) III score was 48 ± 24. The hospital mortality of the cohort was 9%, with a standardized mortality ratio of 0.86. The ICU mortality was 4% (95% CI, 3.1%-5%). ICU and hospital length of stay were 1.2 days (IQR, 0.85-2.2 days) and 4.9 days (IQR, 2.6-8.7 days), respectively.

Figure Jump LinkFigure 1. Study cohort of Olmsted County ICU admissions in 2006.Grahic Jump Location
Table Graphic Jump Location
Table 1 —Baseline Characteristics of Olmsted County Patients Admitted to the ICU in 2006

Data are presented as mean ± SD, No. (%), and median (interquartile range). APACHE = Acute Physiologic and Chronic Health Evaluation; DNR = do not resuscitate; PACU = postanesthesia care unit.

Table 2 presents the cumulative incidence and hospital mortality of CCS, organ failures, and life-support interventions in the population. The incidences reported are not exclusive of one another. Although cardiovascular disorders were the most common reason for ICU admission, respiratory failure had the highest incidence of all CCS (430 episodes per 100,000 population; 95% CI, 390-470 episodes). AKI had the second highest incidence, followed by severe sepsis. Mechanical ventilation (MV) using an artificial airway (invasive) was the most common life-support intervention (310 episodes per 100,000 population; 95% CI, 276-344 episodes). Acute respiratory failure represented the main reason for initiation of MV (70.3% of all cases), followed by acute on chronic respiratory failure (19%) and coma (7%). Septic shock was the most common type of shock (112 episodes per 100,000 population; 95% CI, 92-133 episodes). Cardiogenic shock was the second most common type of shock. Cardiogenic shock was secondary to non-ST-elevation myocardial infarction in 60% of the episodes, to ST-elevation myocardial infarction in 20%, and to other causes (arrhythmias, valvular disease, and myocarditis) in the remaining 20%. The incidence of vasopressors and inotrope use was 183 episodes per 100,000 population (95% CI, 155-208 episodes). After excluding 48 patients with baseline end-stage renal disease, failure-AKI accounted for the highest incidence of the different classes of AKI defined by risk, injury, failure, loss, and end-stage kidney disease (RIFLE) criteria (109 episodes per 100,000 population; 95% CI, 89-130 episodes). Thirty-three percent of all AKI episodes were defined using the urine output criterion, whereas the remainder was done with the creatinine criterion. Continuous renal replacement therapy (RRT) was used in 45% of patients that required dialysis, and no patient in this cohort used peritoneal dialysis. All-cause coma incidence was 43 episodes per 100,000 population (95% CI, 30-55 episodes); most of the cases were secondary to cerebrovascular ischemic and hypoxic events.

Table Graphic Jump Location
Table 2 —Age-Adjusted Incidence of CCSs, Organ Failures, and Life-Support Interventions in Olmsted County During 2006

AKI = acute kidney injury; ALI = acute lung injury; CCS = critical care syndrome; DIC = disseminated intravascular coagulation; IABP = intraaortic balloon counterpulsation; LVAD = left ventricular assist device; MV = mechanical ventilation; RRT = renal replacement therapy.

a 

Per 100,000 population.

b 

According to the Sequential Organ Failure Assessment.

Hospital mortality exhibited a marked incremental rise, depending on the number of organ failures present during the ICU course and reaching almost 100% mortality when four or more organs failed (Fig 2). Long-term survival evidenced a significant decline in the first 100 days after the ICU admission in all groups of organ failure (Fig 3). The probability of survival after ICU admission was significantly worse, with an increasing number of organ failures as outlined in Figure 3.

Figure Jump LinkFigure 2. Episodes of organ failure and hospital mortality according to number of organs failing in Olmsted County residents in 2006.Grahic Jump Location
Figure Jump LinkFigure 3. Survival of Olmsted County residents after ICU admission according to number of organ failures (one failure, 281 episodes; two failures, 97 episodes; three or more failures, 46 episodes).Grahic Jump Location

In this population-based study, we present a detailed epidemiologic description of CCS, organ failures, and life-support interventions in residents of Olmsted County, Minnesota. To our knowledge, the cumulative incidence has not been described before for all-cause shock, overt disseminated intravascular coagulation (DIC), nontraumatic coma, or hypovolemic shock. In this suburban US community with unrestricted access to critical care services (164 adult ICU beds per 100,000 population), the incidence of CCS and life-support interventions were higher than previously described. Furthermore, the 2006 Olmsted County population had higher severity of illness and a larger number of chronic comorbidities in 2006 compared with previous population-based data of this community from 1998.3,4

The published studies on the incidence of some CCS are presented in Table 3. When comparing the incidence of respiratory failure from the present cohort (430 episodes per 100,000 population) to previous population-based studies,11,12 the present cohort’s incidence is significantly higher. Although our definition of respiratory failure included both invasive and noninvasive MV, exclusion of the noninvasive MV patients did not reduce the incidence to the level seen in the aforementioned studies. One possible explanation stems from our definition of respiratory failure that included the need for mechanical respiratory support for > 12 h; in contrast, both studies previously mentioned11,12 required mechanical respiratory support for ≥ 24 h and were done during a 2-month period, which can introduce seasonal bias.

Table Graphic Jump Location
Table 3 —Published Studies on the Incidence of CCS

See Table 2 legend for expansion of abbreviation.

The incidence of severe sepsis in the present study is similar to the incidence found in the study by Angus and collaborators13 but is much higher than that reported in other countries1417 (Table 3). Variability in demographics, ICU access,21 and health systems in general make comparing the incidence of severe sepsis difficult.

The incidence of all-cause shock has not been described previously to our knowledge, and we provide important data regarding the incidence of this syndrome in a community with full access to critical care services. For cardiogenic shock, the incidence has been well described only in patients experiencing an ST-elevation myocardial infarction.2227 We were able to provide the incidence of cardiogenic shock from all causes, and interestingly, most of the cases were secondary to non-ST-elevation myocardial infarction. Until this study, hypovolemic shock had only been described in trauma patients.28,29 The present study is also among the first to describe the incidence of this important type of shock with a standardized definition. The results confirmed the magnitude of hypovolemic shock in a diverse population that included a significant proportion of surgical patients. Septic shock has been the most commonly described type of shock, with multiple epidemiology studies of sepsis in the United States and other countries reporting an estimated incidence ranging from 6.1% to 29.9% of ICU admissions.15,17,3034 Only two of these studies reported the incidence of septic shock from a population-based perspective,15,17 the incidence of which significantly differs from the estimated incidence of 112 cases of septic shock per 100,000 population in the present study. The reported mortality in the present study, although still high, is lower than that reported by Esteban et al17 (45.7%) and lower than nonpopulation-based studies where the hospital mortality in septic shock has ranged from 52% to 61%.31,33,35

Because of the lack of a uniform definition, the reported incidence of AKI in critically ill patients has varied from 1% to 25%.3638 Studies using the accepted RIFLE classification39 have led to more standardized epidemiologic studies; however, the incidence of AKI in ICU admissions ranges from 10.8%40 to as high as 67%.41 This discrepancy likely reflects different ICU populations and practices. Only one study has published the population-based AKI incidence using the RIFLE classification.18 In the present study, we found a higher AKI incidence of 290 cases per 100,000 population, which is likely explained by the fact that we used both the urine and the creatinine criteria for the diagnosis of AKI, whereas in the latter study, the urine criterion was not used. Interestingly, despite the high incidence of AKI, the use of RRT (5.7% of all ICU admissions) was similar to the incidence of RRT use in the ICU described in prior studies.18,41,42 The mortality of patients with AKI was lower in the present cohort (22%) than in previous studies, including the population-based study by Ali and colleagues18 (32.7%-39.8%). The reported higher mortality has been mainly from nonpopulation-based reports where severity of disease could be higher and explain the differences. The differences in practice (eg, intermittent vs continuous RRT) and processes of care also might affect the observed outcome.

Overt DIC incidence in the ICU has been reported in the range of 9.2% to 19% of ICU admissions.4345 However, no population-based assessment of this important syndrome has been described. Using a standardized definition,46 we provide novel information regarding the incidence of overt DIC in the community. Its incidence is relatively low compared with other CCS and differs from the higher incidence of coagulation failure as measured by the Sequential Organ Failure Assessment (SOFA) score. The definition proposed by the International Society on Thrombosis and Hemostasis is more specific for the diagnosis of DIC46 as opposed to the coagulation SOFA, which takes into account only the platelet count.

The epidemiology of coma has been well described in the trauma literature.19,20,47 However, to the best of our knowledge, no epidemiologic studies regarding all-cause coma have been performed. Nontraumatic coma in the ICU was previously described in a cohort of 169 patients,48 but the study did not mention the denominator, and, therefore, the incidence of nontraumatic coma is unknown. The incidence of all-cause coma in the present study may differ from studies of coma in larger urban communities, where higher numbers of coma may represent a higher incidence of traumatic brain injury. However, we observed the incidence of traumatic coma in the current cohort as similar to previous descriptions.19,20 It is important to mention the limitations of the Glasgow Coma Scale system, which include low sensitivity to subtle changes in arousal; failure to assess brainstem function; and difficulty with obtaining a verbal score in patients who are intubated, sedated, or aphasic.49

We have also presented an unprecedented description of the incidence of organ failure in the community. Previous studies have described higher ICU incidence of organ failures defined by maximum SOFA scores than described in the present study34,50,51; however, none of these studies took a population-based approach. In the present population, mortality is significantly lower for patients with one or two organ failures compared with previous reports. The better outcomes could be explained by the availability of critical care services for the residents of Olmsted County as well as improvements in critical care over the past decade. However, the mortality for patients with three and four or more organ failures is very similar across studies, with a range of 60% to 100%.

The main limitation of this study is the generalizability of the results. Although strengthened by its population-based nature, unique aspects of either Olmsted County residents or care delivered at Mayo Clinic Rochester may limit generalizability. In addition, we could have missed a small number of patients who required ICU care in the Veterans Administration hospitals because Olmsted County does not have a Veterans Administration hospital, but this is unlikely to have affected the findings significantly. We cannot exclude the possibility of overuse of critical care beds in Olmsted County given the availability compared with other states.

Another limitation of our study stems from its retrospective observational design. However, electronic medical records provide easier access and more accurate information with high-resolution data needed for ascertainment of organ failures and syndromes. We did not collect information regarding processes of care for this study, but the study was performed after several major quality improvements in critically ill patients were done throughout the world, including lung protective ventilation, early goal-directed resuscitation, improvement in sedation practices, restrictive transfusion policy, better prophylaxis practice for ventilator-associated pneumonia and thromboembolic disease, and use of checklists to prevent catheter-associated line infections.

The differences in access to the health-care system and practice variations make the results difficult to compare with other centers, especially those from outside the United States. In addition, lack of standardized definitions for CCS might explain the observed differences. On the other hand, the higher incidence of organ failures and life-support interventions in a community with practically unrestricted to critical care services (compared with US average of 20 ICU beds per 100,000 population)21 and overall good outcome of critical illness has important implications for future planning of critical care in other regions.

It is well known that critical care is becoming the core competency for many acute care hospitals that will have to satisfy an exploding demand for intensive services with fewer resources (declining reimbursement, shortage of work force, and increasing demand) than they have today. This situation requires a fundamental redesign in critical care planning in order to provide optimum care. The first step in this process is to describe and quantify the CCS and interventions for future planning, as performed in the present study. Further, as described in this study, critical care patients are sicker; better informed; and more demanding, especially when it comes to involvement in care planning and decision making. Future planning of critical care services necessitates system-level change in the organization of the services that are now provided. Alternative organizational models that may expand access to high-quality critical care, increase survival, and reduce costs have been proposed by others, including tiered regionalization, ICU telemedicine, and quality improvement through regional outreach.52

In conclusion, in this population-based study of Olmsted County, Minnesota, cumulative incidences of CCS and life-support interventions were higher than previously reported, although the outcomes appeared favorable compared to those previously reported. In addition, the demand for ICU services in this community markedly increased during the past decade. Because of an aging population and the increasing prevalence of chronic medical illnesses, demands for ICU services in the United States are expected to increase further. The results of this study can help with future planning of ICU health-care delivery.

Author contributions: Drs Cartin-Ceba and Gajic had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Dr Cartin-Ceba: contributed to the study concept and design, data analysis and interpretation, statistical analysis, and drafting of the manuscript.

Dr Kojicic: contributed to the data acquisition and revision of the manuscript for important intellectual content.

Dr Li: contributed to the data acquisition and revision of the manuscript for important intellectual content.

Dr Kor: contributed to the critical revision of the manuscript for important intellectual content.

Dr Poulose: contributed to the data acquisition and revision of the manuscript for important intellectual content.

Dr Herasevich: contributed to the data acquisition and revision of the manuscript for important intellectual content.

Dr Kashyap: contributed to the data acquisition and revision of the manuscript for important intellectual content.

Dr Trillo-Alvarez: contributed to the data acquisition and revision of the manuscript for important intellectual content.

Dr Cabello-Garza: contributed to the data acquisition and revision of the manuscript for important intellectual content.

Dr Hubmayr: contributed to the critical revision of the manuscript for important intellectual content.

Dr Seferian: contributed to the critical revision of the manuscript for important intellectual content.

Dr Gajic: contributed to the study concept and design, data analysis and interpretation, statistical analysis, and drafting of the manuscript.

Financial/nonfinancial disclosures: The authors have reported to CHEST that no potential conflicts of interest exist with any companies/organizations whose products or services may be discussed in this article.

Other contributions: The study was performed at Mayo Clinic, Rochester, Minnesota. We thank Mohammed Ahmed, MD; Giath Shari, MD; Girish Mour, MD; Alexander Ivaskovic, MD; and Sweta Thakur, MD, for their collaboration in this study.

Additional information: The e-Appendix can be found in the Online Supplement at http://chestjournal.chestpubs.org/content/140/6/1447/suppl/DC1

Author contributions: Drs Cartin-Ceba and Gajic had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Dr Cartin-Ceba: contributed to the study concept and design, data analysis and interpretation, statistical analysis, and drafting of the manuscript.

Dr Kojicic: contributed to the data acquisition and revision of the manuscript for important intellectual content.

Dr Li: contributed to the data acquisition and revision of the manuscript for important intellectual content.

Dr Kor: contributed to the critical revision of the manuscript for important intellectual content.

Dr Poulose: contributed to the data acquisition and revision of the manuscript for important intellectual content.

Dr Herasevich: contributed to the data acquisition and revision of the manuscript for important intellectual content.

Dr Kashyap: contributed to the data acquisition and revision of the manuscript for important intellectual content.

Dr Trillo-Alvarez: contributed to the data acquisition and revision of the manuscript for important intellectual content.

Dr Cabello-Garza: contributed to the data acquisition and revision of the manuscript for important intellectual content.

Dr Hubmayr: contributed to the critical revision of the manuscript for important intellectual content.

Dr Seferian: contributed to the critical revision of the manuscript for important intellectual content.

Dr Gajic: contributed to the study concept and design, data analysis and interpretation, statistical analysis, and drafting of the manuscript.

Financial/nonfinancial disclosures: The authors have reported to CHEST that no potential conflicts of interest exist with any companies/organizations whose products or services may be discussed in this article.

Other contributions: The study was performed at Mayo Clinic, Rochester, Minnesota. We thank Mohammed Ahmed, MD; Giath Shari, MD; Girish Mour, MD; Alexander Ivaskovic, MD; and Sweta Thakur, MD, for their collaboration in this study.

Additional information: The e-Appendix can be found in the Online Supplement at http://chestjournal.chestpubs.org/content/140/6/1447/suppl/DC1

AKI

acute kidney injury

ALI

acute lung injury

CCS

critical care syndrome

DIC

disseminated intravascular coagulation

IQR

interquartile range

MV

mechanical ventilation

RIFLE

risk, injury, failure, loss, and end-stage kidney disease

RRT

renal replacement therapy

SOFA

Sequential Organ Failure Assessment

Barnato AE, Kahn JM, Rubenfeld GD, et al. Prioritizing the organization and management of intensive care services in the United States: the PrOMIS Conference. Crit Care Med. 2007;354:1003-1011 [CrossRef] [PubMed]
 
Angus DC, Barnato AE, Linde-Zwirble WT, et al; Robert Wood Johnson Foundation ICU End-Of-Life Peer Group Robert Wood Johnson Foundation ICU End-Of-Life Peer Group Use of intensive care at the end of life in the United States: an epidemiologic study. Crit Care Med. 2004;323:638-643 [CrossRef]
 
Seferian EG, Afessa B. Demographic and clinical variation of adult intensive care unit utilization from a geographically defined population. Crit Care Med. 2006;348:2113-2119 [CrossRef]
 
Seferian EG, Afessa B. Adult intensive care unit use at the end of life: a population-based study. Mayo Clin Proc. 2006;817:896-901 [CrossRef]
 
Rubenfeld GD, Christie JD. The epidemiologist in the intensive care unit. Intensive Care Med. 2004;301:4-6 [CrossRef]
 
Linde-Zwirble WT, Angus DC. Severe sepsis epidemiology: sampling, selection, and society. Crit Care. 2004;84:222-226 [CrossRef]
 
Oppenheimer GM. Becoming the Framingham Study 1947-1950. Am J Public Health. 2005;954:602-610 [CrossRef]
 
Dawber TR, Meadors GF, Moore FE Jr. Epidemiological approaches to heart disease: the Framingham Study. Am J Public Health Nations Health. 1951;413:279-281 [CrossRef]
 
Melton LJ III. History of the Rochester Epidemiology Project. Mayo Clin Proc. 1996;713:266-274 [CrossRef]
 
Knaus WA, Wagner DP, Zimmerman JE, Draper EA. Variations in mortality and length of stay in intensive care units. Ann Intern Med. 1993;11810:753-761
 
Lewandowski K, Metz J, Deutschmann C, et al. Incidence, severity, and mortality of acute respiratory failure in Berlin, Germany. Am J Respir Crit Care Med. 1995;1514:1121-1125
 
Antonsen K, Wetterslev J, Bonde J. Incidence, severity and mortality of acute respiratory failure in Denmark [in Danish]. Ugeskr Laeger. 2000;16220:2876-2881
 
Angus DC, Linde-Zwirble WT, Lidicker J, Clermont G, Carcillo J, Pinsky MR. Epidemiology of severe sepsis in the United States: analysis of incidence, outcome, and associated costs of care. Crit Care Med. 2001;297:1303-1310 [CrossRef]
 
Flaatten H. Epidemiology of sepsis in Norway in 1999. Crit Care. 2004;84:R180-R184 [CrossRef]
 
van Gestel A, Bakker J, Veraart CP, van Hout BA. Prevalence and incidence of severe sepsis in Dutch intensive care units. Crit Care. 2004;84:R153-R162 [CrossRef]
 
Finfer S, Bellomo R, Lipman J, French C, Dobb G, Myburgh J. Adult-population incidence of severe sepsis in Australian and New Zealand intensive care units. Intensive Care Med. 2004;304:589-596 [CrossRef]
 
Esteban A, Frutos-Vivar F, Ferguson ND, et al. Sepsis incidence and outcome: contrasting the intensive care unit with the hospital ward. Crit Care Med. 2007;355:1284-1289 [CrossRef]
 
Ali T, Khan I, Simpson W, et al. Incidence and outcomes in acute kidney injury: a comprehensive population-based study. J Am Soc Nephrol. 2007;184:1292-1298 [CrossRef]
 
Masson F, Thicoipe M, Mokni T, Aye P, Erny P, Dabadie P. Aquaitaine Group for Severe Brain Injury Study Aquaitaine Group for Severe Brain Injury Study Epidemiology of traumatic comas: a prospective population-based study. Brain Inj. 2003;174:279-293 [CrossRef]
 
von Elm E, Osterwalder JJ, Graber C, et al. Severe traumatic brain injury in Switzerland - feasibility and first results of a cohort study. Swiss Med Wkly. 2008;13823-24:327-334
 
Wunsch H, Angus DC, Harrison DA, et al. Variation in critical care services across North America and Western Europe. Crit Care Med. 2008;3610:2787-2793 [CrossRef]
 
Goldberg RJ, Gore JM, Alpert JS, et al. Cardiogenic shock after acute myocardial infarction. Incidence and mortality from a community-wide perspective, 1975 to 1988. N Engl J Med. 1991;32516:1117-1122 [CrossRef]
 
Goldberg RJ, Gore JM, Thompson CA, Gurwitz JH. Recent magnitude of and temporal trends (1994-1997) in the incidence and hospital death rates of cardiogenic shock complicating acute myocardial infarction: the second national registry of myocardial infarction. Am Heart J. 2001;1411:65-72 [CrossRef]
 
Goldberg RJ, Samad NA, Yarzebski J, Gurwitz J, Bigelow C, Gore JM. Temporal trends in cardiogenic shock complicating acute myocardial infarction. N Engl J Med. 1999;34015:1162-1168 [CrossRef]
 
Hochman JS, Sleeper LA, Webb JG, et al. Early revascularization in acute myocardial infarction complicated by cardiogenic shock. SHOCK Investigators. Should We Emergently Revascularize Occluded Coronaries for Cardiogenic Shock. N Engl J Med. 1999;3419:625-634 [CrossRef]
 
Babaev A, Frederick PD, Pasta DJ, Every N, Sichrovsky T, Hochman JS. NRMI Investigators NRMI Investigators Trends in management and outcomes of patients with acute myocardial infarction complicated by cardiogenic shock. JAMA. 2005;2944:448-454 [CrossRef]
 
Holmes DR Jr, Bates ER, Kleiman NS, et al. Contemporary reperfusion therapy for cardiogenic shock: the GUSTO-I trial experience. The GUSTO-I Investigators. Global Utilization of Streptokinase and Tissue Plasminogen Activator for Occluded Coronary Arteries. J Am Coll Cardiol. 1995;263:668-674 [CrossRef]
 
Gutierrez G, Reines HD, Wulf-Gutierrez ME. Clinical review: hemorrhagic shock. Crit Care. 2004;85:373-381 [CrossRef]
 
Schulman AM, Claridge JA, Carr G, Diesen DL, Young JS. Predictors of patients who will develop prolonged occult hypoperfusion following blunt trauma. J Trauma. 2004;574:795-800 [CrossRef]
 
Alberti C, Brun-Buisson C, Burchardi H, et al. Epidemiology of sepsis and infection in ICU patients from an international multicentre cohort study. Intensive Care Med. 2002;282:108-121 [CrossRef]
 
Annane D, Aegerter P, Jars-Guincestre MC, Guidet B. CUB-Réa Network CUB-Réa Network Current epidemiology of septic shock: the CUB-Réa Network. Am J Respir Crit Care Med. 2003;1682:165-172 [CrossRef]
 
Salvo I, de Cian W, Musicco M, et al. The Italian SEPSIS study: preliminary results on the incidence and evolution of SIRS, sepsis, severe sepsis and septic shock. Intensive Care Med. 1995;21suppl 2:S244-S249 [CrossRef]
 
Silva E, Pedro MdeA, Sogayar AC, et al; Brazilian Sepsis Epidemiological Study Brazilian Sepsis Epidemiological Study Brazilian Sepsis Epidemiological Study (BASES study). Crit Care. 2004;84:R251-R260 [CrossRef]
 
Vincent JL, Sakr Y, Sprung CL, et al; Sepsis Occurrence in Acutely Ill Patients Investigators Sepsis Occurrence in Acutely Ill Patients Investigators Sepsis in European intensive care units: results of the SOAP study. Crit Care Med. 2006;342:344-353 [CrossRef]
 
Brun-Buisson C, Doyon F, Carlet J, et al; French ICU Group for Severe Sepsis French ICU Group for Severe Sepsis Incidence, risk factors, and outcome of severe sepsis and septic shock in adults. A multicenter prospective study in intensive care units. JAMA. 1995;27412:968-974 [CrossRef]
 
Uchino S, Bellomo R, Goldsmith D, Bates S, Ronco C. An assessment of the RIFLE criteria for acute renal failure in hospitalized patients. Crit Care Med. 2006;347:1913-1917 [CrossRef]
 
Kellum JA, Leblanc M, Gibney RT, Tumlin J, Lieberthal W, Ronco C. Primary prevention of acute renal failure in the critically ill. Curr Opin Crit Care. 2005;116:537-541
 
Kellum JA, Ronco C, Mehta R, Bellomo R. Consensus development in acute renal failure: The Acute Dialysis Quality Initiative. Curr Opin Crit Care. 2005;116:527-532 [CrossRef]
 
Bellomo R, Ronco C, Kellum JA, Mehta RL, Palevsky P. Acute Dialysis Quality Initiative workgroup Acute Dialysis Quality Initiative workgroup Acute renal failure—definition, outcome measures, animal models, fluid therapy and information technology needs: the Second International Consensus Conference of the Acute Dialysis Quality Initiative (ADQI) Group. Crit Care. 2004;84:R204-R212 [CrossRef]
 
Cruz DN, Bolgan I, Perazella MA, et al; North East Italian Prospective Hospital Renal Outcome Survey on Acute Kidney Injury (NEiPHROS-AKI) Investigators North East Italian Prospective Hospital Renal Outcome Survey on Acute Kidney Injury (NEiPHROS-AKI) Investigators North East Italian Prospective Hospital Renal Outcome Survey on Acute Kidney Injury (NEiPHROS-AKI): targeting the problem with the RIFLE Criteria. Clin J Am Soc Nephrol. 2007;23:418-425 [CrossRef]
 
Hoste EA, Clermont G, Kersten A, et al. RIFLE criteria for acute kidney injury are associated with hospital mortality in critically ill patients: a cohort analysis. Crit Care. 2006;103:R73 [CrossRef]
 
Ostermann M, Chang RW. Acute kidney injury in the intensive care unit according to RIFLE. Crit Care Med. 2007;358:1837-1843 [CrossRef]
 
Sivula M, Tallgren M, Pettilä V. Modified score for disseminated intravascular coagulation in the critically ill. Intensive Care Med. 2005;319:1209-1214 [CrossRef]
 
Angstwurm MW, Dempfle CE, Spannagl M. New disseminated intravascular coagulation score: a useful tool to predict mortality in comparison with Acute Physiology and Chronic Health Evaluation II and Logistic Organ Dysfunction scores. Crit Care Med. 2006;342:314-320 [CrossRef]
 
Toh CH, Downey C. Performance and prognostic importance of a new clinical and laboratory scoring system for identifying non-overt disseminated intravascular coagulation. Blood Coagul Fibrinolysis. 2005;161:69-74 [CrossRef]
 
Taylor FB Jr, Toh CH, Hoots WK, Wada H, Levi M. Scientific Subcommittee on Disseminated Intravascular Coagulation (DIC) of the International Society on Thrombosis and Haemostasis (ISTH) Scientific Subcommittee on Disseminated Intravascular Coagulation (DIC) of the International Society on Thrombosis and Haemostasis (ISTH) Towards definition, clinical and laboratory criteria, and a scoring system for disseminated intravascular coagulation. Thromb Haemost. 2001;865:1327-1330
 
Masson F, Thicoipe M, Aye P, et al; Aquitaine Group for Severe Brain Injuries Study Aquitaine Group for Severe Brain Injuries Study Epidemiology of severe brain injuries: a prospective population-based study. J Trauma. 2001;513:481-489 [CrossRef]
 
Sacco RL, VanGool R, Mohr JP, Hauser WA. Nontraumatic coma. Glasgow coma score and coma etiology as predictors of 2-week outcome. Arch Neurol. 1990;4711:1181-1184 [CrossRef]
 
Stevens RD, Nyquist PA. Types of brain dysfunction in critical illness. Neurol Clin. 2008;262:469-486 [CrossRef]
 
Vincent JL, de Mendonça A, Cantraine F, et al. Use of the SOFA score to assess the incidence of organ dysfunction/failure in intensive care units: results of a multicenter, prospective study. Working group on “sepsis-related problems” of the European Society of Intensive Care Medicine. Crit Care Med. 1998;2611:1793-1800 [CrossRef]
 
Moreno R, Vincent JL, Matos R, et al. The use of maximum SOFA score to quantify organ dysfunction/failure in intensive care. Results of a prospective, multicentre study. Working Group on Sepsis related Problems of the ESICM. Intensive Care Med. 1999;257:686-696 [CrossRef]
 
Nguyen YL, Kahn JM, Angus DC. Reorganizing adult critical care delivery: the role of regionalization, telemedicine, and community outreach. Am J Respir Crit Care Med. 2010;18111:1164-1169 [CrossRef]
 

Figures

Figure Jump LinkFigure 1. Study cohort of Olmsted County ICU admissions in 2006.Grahic Jump Location
Figure Jump LinkFigure 2. Episodes of organ failure and hospital mortality according to number of organs failing in Olmsted County residents in 2006.Grahic Jump Location
Figure Jump LinkFigure 3. Survival of Olmsted County residents after ICU admission according to number of organ failures (one failure, 281 episodes; two failures, 97 episodes; three or more failures, 46 episodes).Grahic Jump Location

Tables

Table Graphic Jump Location
Table 1 —Baseline Characteristics of Olmsted County Patients Admitted to the ICU in 2006

Data are presented as mean ± SD, No. (%), and median (interquartile range). APACHE = Acute Physiologic and Chronic Health Evaluation; DNR = do not resuscitate; PACU = postanesthesia care unit.

Table Graphic Jump Location
Table 2 —Age-Adjusted Incidence of CCSs, Organ Failures, and Life-Support Interventions in Olmsted County During 2006

AKI = acute kidney injury; ALI = acute lung injury; CCS = critical care syndrome; DIC = disseminated intravascular coagulation; IABP = intraaortic balloon counterpulsation; LVAD = left ventricular assist device; MV = mechanical ventilation; RRT = renal replacement therapy.

a 

Per 100,000 population.

b 

According to the Sequential Organ Failure Assessment.

Table Graphic Jump Location
Table 3 —Published Studies on the Incidence of CCS

See Table 2 legend for expansion of abbreviation.

References

Barnato AE, Kahn JM, Rubenfeld GD, et al. Prioritizing the organization and management of intensive care services in the United States: the PrOMIS Conference. Crit Care Med. 2007;354:1003-1011 [CrossRef] [PubMed]
 
Angus DC, Barnato AE, Linde-Zwirble WT, et al; Robert Wood Johnson Foundation ICU End-Of-Life Peer Group Robert Wood Johnson Foundation ICU End-Of-Life Peer Group Use of intensive care at the end of life in the United States: an epidemiologic study. Crit Care Med. 2004;323:638-643 [CrossRef]
 
Seferian EG, Afessa B. Demographic and clinical variation of adult intensive care unit utilization from a geographically defined population. Crit Care Med. 2006;348:2113-2119 [CrossRef]
 
Seferian EG, Afessa B. Adult intensive care unit use at the end of life: a population-based study. Mayo Clin Proc. 2006;817:896-901 [CrossRef]
 
Rubenfeld GD, Christie JD. The epidemiologist in the intensive care unit. Intensive Care Med. 2004;301:4-6 [CrossRef]
 
Linde-Zwirble WT, Angus DC. Severe sepsis epidemiology: sampling, selection, and society. Crit Care. 2004;84:222-226 [CrossRef]
 
Oppenheimer GM. Becoming the Framingham Study 1947-1950. Am J Public Health. 2005;954:602-610 [CrossRef]
 
Dawber TR, Meadors GF, Moore FE Jr. Epidemiological approaches to heart disease: the Framingham Study. Am J Public Health Nations Health. 1951;413:279-281 [CrossRef]
 
Melton LJ III. History of the Rochester Epidemiology Project. Mayo Clin Proc. 1996;713:266-274 [CrossRef]
 
Knaus WA, Wagner DP, Zimmerman JE, Draper EA. Variations in mortality and length of stay in intensive care units. Ann Intern Med. 1993;11810:753-761
 
Lewandowski K, Metz J, Deutschmann C, et al. Incidence, severity, and mortality of acute respiratory failure in Berlin, Germany. Am J Respir Crit Care Med. 1995;1514:1121-1125
 
Antonsen K, Wetterslev J, Bonde J. Incidence, severity and mortality of acute respiratory failure in Denmark [in Danish]. Ugeskr Laeger. 2000;16220:2876-2881
 
Angus DC, Linde-Zwirble WT, Lidicker J, Clermont G, Carcillo J, Pinsky MR. Epidemiology of severe sepsis in the United States: analysis of incidence, outcome, and associated costs of care. Crit Care Med. 2001;297:1303-1310 [CrossRef]
 
Flaatten H. Epidemiology of sepsis in Norway in 1999. Crit Care. 2004;84:R180-R184 [CrossRef]
 
van Gestel A, Bakker J, Veraart CP, van Hout BA. Prevalence and incidence of severe sepsis in Dutch intensive care units. Crit Care. 2004;84:R153-R162 [CrossRef]
 
Finfer S, Bellomo R, Lipman J, French C, Dobb G, Myburgh J. Adult-population incidence of severe sepsis in Australian and New Zealand intensive care units. Intensive Care Med. 2004;304:589-596 [CrossRef]
 
Esteban A, Frutos-Vivar F, Ferguson ND, et al. Sepsis incidence and outcome: contrasting the intensive care unit with the hospital ward. Crit Care Med. 2007;355:1284-1289 [CrossRef]
 
Ali T, Khan I, Simpson W, et al. Incidence and outcomes in acute kidney injury: a comprehensive population-based study. J Am Soc Nephrol. 2007;184:1292-1298 [CrossRef]
 
Masson F, Thicoipe M, Mokni T, Aye P, Erny P, Dabadie P. Aquaitaine Group for Severe Brain Injury Study Aquaitaine Group for Severe Brain Injury Study Epidemiology of traumatic comas: a prospective population-based study. Brain Inj. 2003;174:279-293 [CrossRef]
 
von Elm E, Osterwalder JJ, Graber C, et al. Severe traumatic brain injury in Switzerland - feasibility and first results of a cohort study. Swiss Med Wkly. 2008;13823-24:327-334
 
Wunsch H, Angus DC, Harrison DA, et al. Variation in critical care services across North America and Western Europe. Crit Care Med. 2008;3610:2787-2793 [CrossRef]
 
Goldberg RJ, Gore JM, Alpert JS, et al. Cardiogenic shock after acute myocardial infarction. Incidence and mortality from a community-wide perspective, 1975 to 1988. N Engl J Med. 1991;32516:1117-1122 [CrossRef]
 
Goldberg RJ, Gore JM, Thompson CA, Gurwitz JH. Recent magnitude of and temporal trends (1994-1997) in the incidence and hospital death rates of cardiogenic shock complicating acute myocardial infarction: the second national registry of myocardial infarction. Am Heart J. 2001;1411:65-72 [CrossRef]
 
Goldberg RJ, Samad NA, Yarzebski J, Gurwitz J, Bigelow C, Gore JM. Temporal trends in cardiogenic shock complicating acute myocardial infarction. N Engl J Med. 1999;34015:1162-1168 [CrossRef]
 
Hochman JS, Sleeper LA, Webb JG, et al. Early revascularization in acute myocardial infarction complicated by cardiogenic shock. SHOCK Investigators. Should We Emergently Revascularize Occluded Coronaries for Cardiogenic Shock. N Engl J Med. 1999;3419:625-634 [CrossRef]
 
Babaev A, Frederick PD, Pasta DJ, Every N, Sichrovsky T, Hochman JS. NRMI Investigators NRMI Investigators Trends in management and outcomes of patients with acute myocardial infarction complicated by cardiogenic shock. JAMA. 2005;2944:448-454 [CrossRef]
 
Holmes DR Jr, Bates ER, Kleiman NS, et al. Contemporary reperfusion therapy for cardiogenic shock: the GUSTO-I trial experience. The GUSTO-I Investigators. Global Utilization of Streptokinase and Tissue Plasminogen Activator for Occluded Coronary Arteries. J Am Coll Cardiol. 1995;263:668-674 [CrossRef]
 
Gutierrez G, Reines HD, Wulf-Gutierrez ME. Clinical review: hemorrhagic shock. Crit Care. 2004;85:373-381 [CrossRef]
 
Schulman AM, Claridge JA, Carr G, Diesen DL, Young JS. Predictors of patients who will develop prolonged occult hypoperfusion following blunt trauma. J Trauma. 2004;574:795-800 [CrossRef]
 
Alberti C, Brun-Buisson C, Burchardi H, et al. Epidemiology of sepsis and infection in ICU patients from an international multicentre cohort study. Intensive Care Med. 2002;282:108-121 [CrossRef]
 
Annane D, Aegerter P, Jars-Guincestre MC, Guidet B. CUB-Réa Network CUB-Réa Network Current epidemiology of septic shock: the CUB-Réa Network. Am J Respir Crit Care Med. 2003;1682:165-172 [CrossRef]
 
Salvo I, de Cian W, Musicco M, et al. The Italian SEPSIS study: preliminary results on the incidence and evolution of SIRS, sepsis, severe sepsis and septic shock. Intensive Care Med. 1995;21suppl 2:S244-S249 [CrossRef]
 
Silva E, Pedro MdeA, Sogayar AC, et al; Brazilian Sepsis Epidemiological Study Brazilian Sepsis Epidemiological Study Brazilian Sepsis Epidemiological Study (BASES study). Crit Care. 2004;84:R251-R260 [CrossRef]
 
Vincent JL, Sakr Y, Sprung CL, et al; Sepsis Occurrence in Acutely Ill Patients Investigators Sepsis Occurrence in Acutely Ill Patients Investigators Sepsis in European intensive care units: results of the SOAP study. Crit Care Med. 2006;342:344-353 [CrossRef]
 
Brun-Buisson C, Doyon F, Carlet J, et al; French ICU Group for Severe Sepsis French ICU Group for Severe Sepsis Incidence, risk factors, and outcome of severe sepsis and septic shock in adults. A multicenter prospective study in intensive care units. JAMA. 1995;27412:968-974 [CrossRef]
 
Uchino S, Bellomo R, Goldsmith D, Bates S, Ronco C. An assessment of the RIFLE criteria for acute renal failure in hospitalized patients. Crit Care Med. 2006;347:1913-1917 [CrossRef]
 
Kellum JA, Leblanc M, Gibney RT, Tumlin J, Lieberthal W, Ronco C. Primary prevention of acute renal failure in the critically ill. Curr Opin Crit Care. 2005;116:537-541
 
Kellum JA, Ronco C, Mehta R, Bellomo R. Consensus development in acute renal failure: The Acute Dialysis Quality Initiative. Curr Opin Crit Care. 2005;116:527-532 [CrossRef]
 
Bellomo R, Ronco C, Kellum JA, Mehta RL, Palevsky P. Acute Dialysis Quality Initiative workgroup Acute Dialysis Quality Initiative workgroup Acute renal failure—definition, outcome measures, animal models, fluid therapy and information technology needs: the Second International Consensus Conference of the Acute Dialysis Quality Initiative (ADQI) Group. Crit Care. 2004;84:R204-R212 [CrossRef]
 
Cruz DN, Bolgan I, Perazella MA, et al; North East Italian Prospective Hospital Renal Outcome Survey on Acute Kidney Injury (NEiPHROS-AKI) Investigators North East Italian Prospective Hospital Renal Outcome Survey on Acute Kidney Injury (NEiPHROS-AKI) Investigators North East Italian Prospective Hospital Renal Outcome Survey on Acute Kidney Injury (NEiPHROS-AKI): targeting the problem with the RIFLE Criteria. Clin J Am Soc Nephrol. 2007;23:418-425 [CrossRef]
 
Hoste EA, Clermont G, Kersten A, et al. RIFLE criteria for acute kidney injury are associated with hospital mortality in critically ill patients: a cohort analysis. Crit Care. 2006;103:R73 [CrossRef]
 
Ostermann M, Chang RW. Acute kidney injury in the intensive care unit according to RIFLE. Crit Care Med. 2007;358:1837-1843 [CrossRef]
 
Sivula M, Tallgren M, Pettilä V. Modified score for disseminated intravascular coagulation in the critically ill. Intensive Care Med. 2005;319:1209-1214 [CrossRef]
 
Angstwurm MW, Dempfle CE, Spannagl M. New disseminated intravascular coagulation score: a useful tool to predict mortality in comparison with Acute Physiology and Chronic Health Evaluation II and Logistic Organ Dysfunction scores. Crit Care Med. 2006;342:314-320 [CrossRef]
 
Toh CH, Downey C. Performance and prognostic importance of a new clinical and laboratory scoring system for identifying non-overt disseminated intravascular coagulation. Blood Coagul Fibrinolysis. 2005;161:69-74 [CrossRef]
 
Taylor FB Jr, Toh CH, Hoots WK, Wada H, Levi M. Scientific Subcommittee on Disseminated Intravascular Coagulation (DIC) of the International Society on Thrombosis and Haemostasis (ISTH) Scientific Subcommittee on Disseminated Intravascular Coagulation (DIC) of the International Society on Thrombosis and Haemostasis (ISTH) Towards definition, clinical and laboratory criteria, and a scoring system for disseminated intravascular coagulation. Thromb Haemost. 2001;865:1327-1330
 
Masson F, Thicoipe M, Aye P, et al; Aquitaine Group for Severe Brain Injuries Study Aquitaine Group for Severe Brain Injuries Study Epidemiology of severe brain injuries: a prospective population-based study. J Trauma. 2001;513:481-489 [CrossRef]
 
Sacco RL, VanGool R, Mohr JP, Hauser WA. Nontraumatic coma. Glasgow coma score and coma etiology as predictors of 2-week outcome. Arch Neurol. 1990;4711:1181-1184 [CrossRef]
 
Stevens RD, Nyquist PA. Types of brain dysfunction in critical illness. Neurol Clin. 2008;262:469-486 [CrossRef]
 
Vincent JL, de Mendonça A, Cantraine F, et al. Use of the SOFA score to assess the incidence of organ dysfunction/failure in intensive care units: results of a multicenter, prospective study. Working group on “sepsis-related problems” of the European Society of Intensive Care Medicine. Crit Care Med. 1998;2611:1793-1800 [CrossRef]
 
Moreno R, Vincent JL, Matos R, et al. The use of maximum SOFA score to quantify organ dysfunction/failure in intensive care. Results of a prospective, multicentre study. Working Group on Sepsis related Problems of the ESICM. Intensive Care Med. 1999;257:686-696 [CrossRef]
 
Nguyen YL, Kahn JM, Angus DC. Reorganizing adult critical care delivery: the role of regionalization, telemedicine, and community outreach. Am J Respir Crit Care Med. 2010;18111:1164-1169 [CrossRef]
 
NOTE:
Citing articles are presented as examples only. In non-demo SCM6 implementation, integration with CrossRef’s "Cited By" API will populate this tab (http://www.crossref.org/citedby.html).
Supporting Data
Data Supplement

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging & repositioning the boxes below.

CHEST Journal Articles
PubMed Articles
Guidelines
Critical care in pregnancy.
American College of Obstetricians and Gynecologists | 7/10/2009
  • CHEST Journal
    Print ISSN: 0012-3692
    Online ISSN: 1931-3543