Extending international sepsis epidemiology: the impact of organ dysfunction

In the previous issue of Critical Care, Blanco and colleagues contributed to a growing body of literature on the international epidemiology of severe sepsis. Taken together, these studies confirm that the sepsis incidence is high, that the development of organ dysfunction is a major determinant of mortality and that the occurrence of organ dysfunction is influenced by chronic comorbid medical conditions. It is clear that early detection of organ dysfunction and serial sequential organ dysfunction scoring provides us with the best chance to optimize clinical care. Identifying factors that contribute to the development of organ dysfunction in sepsis will lead to the development of new treatment modalities that will reduce mortality. Future studies must therefore focus on the impact of new treatment modalities for preventing progression to multiple organ dysfunction syndrome and consequent mortality in sepsis

The role of infection and comorbidity: Factors that influence disparities in sepsis

OBJECTIVE:Large healthcare disparities exist in the incidence of sepsis based on both race and gender. We sought to determine factors that may influence the occurrence of these healthcare disparities, with respect to the source of infection, causal organisms, and chronic comorbid medical conditions. DESIGN: Historical cohort study. SETTING: U.S. acute care hospitals from 1979 to 2003. PATIENTS: Hospitalized patients with a diagnosis of sepsis were identified from the National Hospital Discharge Survey per codes of the International Statistical Classification of Diseases, Ninth Revision (ICD-9CM). Chronic comorbid medical conditions and the source and type of infection were characterized by corresponding ICD-9CM diagnoses. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Sepsis incidence rates are mean cases per 100,000 after age adjustment to the 2000 U.S. Census. Males and nonwhite races were confirmed at increased risk for sepsis. Both proportional source distribution and incidence rates favored respiratory sources of sepsis in males (36% vs. 29%, p \u3c .01) and genitourinary sources in females (35% vs. 27%, p \u3c .01). Incidence rates for all common sources of sepsis were greater in nonwhite races, but proportional source distribution was approximately equal. After stratification by the source of infection, males (proportionate ratio 1.16, 95% confidence interval 1.04-1.29) and black persons (proportionate ratio 1.25, 95% confidence interval 1.18-1.32) remained more likely to have Gram-positive infections. Chronic comorbid conditions that alter immune function (chronic renal failure, diabetes mellitus, HIV, alcohol abuse) were more common in nonwhite sepsis patients, and cumulative comorbidities were associated with greater acute organ dysfunction. Compared with white sepsis patients, nonwhite sepsis patients had longer hospital length of stay (2.0 days, 95% confidence interval 1.9-2.1) and were less likely to be discharged to another medical facility (30% whites, 25% blacks, 18% other races). Case-fatality rates were not significantly different across racial and gender groups. CONCLUSIONS: Healthcare disparities exist in the incidence of sepsis within all major sources of infection, and males and blacks have greater frequency of Gram-positive infections independent of the infection source. The differential distribution of specific chronic comorbid medical conditions may contribute to these disparities. Large cohort and administrative studies are required to confirm discrete root causes of sepsis disparities

Systematized and efficient: organization of critical care in the future

Since the advent of critical care in the twentieth century, the core elements that are the foundation for critical care systems, namely to care for critically ill and injured patients and to save lives, have evolved enormously. The past half-century has seen dramatic advancements in diagnostic, organ support, and treatment modalities in critical care, with further improvements now needed to achieve personalized critical care of the highest quality. For critical care to be even higher quality in the future, advancements in the following areas are key: the physical ICU space; the people that care for critically ill patients; the equipment and technologies; the information systems and data; and the research systems that impact critically ill patients and families. With acutely and critically ill patients and their families as the absolute focal point, advancements across these areas will hopefully transform care and outcomes over the coming years

Early Identification of Patients at Risk of Acute Lung Injury

Rationale: Accurate, early identification of patients at risk for developing acute lung injury (ALI) provides the opportunity to test and implement secondary prevention strategies. Objectives: To determine the frequency and outcome of ALI development in patients at risk and validate a lung injury prediction score (LIPS). Methods: In this prospective multicenter observational cohort study, predisposing conditions and risk modifiers predictive of ALI development were identified from routine clinical data available during initial evaluation. The discrimination of the model was assessed with area under receiver operating curve (AUC). The risk of death from ALI was determined after adjustment for severity of illness and predisposing conditions. Measurements and Main Results: Twenty-two hospitals enrolled 5,584 patients at risk. ALI developed a median of 2 (interquartile range 1–4) days after initial evaluation in 377 (6.8%; 148 ALI-only, 229 adult respiratory distress syndrome) patients. The frequency of ALI varied according to predisposing conditions (from 3% in pancreatitis to 26% after smoke inhalation). LIPS discriminated patients who developed ALI from those who did not with an AUC of 0.80 (95% confidence interval, 0.78–0.82). When adjusted for severity of illness and predisposing conditions, development of ALI increased the risk of in-hospital death (odds ratio, 4.1; 95% confidence interval, 2.9–5.7). Conclusions: ALI occurrence varies according to predisposing conditions and carries an independently poor prognosis. Using routinely available clinical data, LIPS identifies patients at high risk for ALI early in the course of their illness. This model will alert clinicians about the risk of ALI and facilitate testing and implementation of ALI prevention strategies. Clinical trial registered with www.clinicaltrials.gov (NCT00889772)

Early Identification of Patients at Risk of Acute Lung Injury: Evaluation of Lung Injury Prediction Score in a Multicenter Cohort Study

Rationale: Accurate, early identification of patients at risk for developing acute lung injury (ALI) provides the opportunity to test and implement secondary prevention strategies

Physician agreement on the diagnosis of sepsis in the intensive care unit: estimation of concordance and analysis of underlying factors in a multicenter cohort

Abstract Background Differentiating sepsis from the systemic inflammatory response syndrome (SIRS) in critical care patients is challenging, especially before serious organ damage is evident, and with variable clinical presentations of patients and variable training and experience of attending physicians. Our objective was to describe and quantify physician agreement in diagnosing SIRS or sepsis in critical care patients as a function of available clinical information, infection site, and hospital setting. Methods We conducted a post hoc analysis of previously collected data from a prospective, observational trial (N = 249 subjects) in intensive care units at seven US hospitals, in which physicians at different stages of patient care were asked to make diagnostic calls of either SIRS, sepsis, or indeterminate, based on varying amounts of available clinical information (clinicaltrials.gov identifier: NCT02127502). The overall percent agreement and the free-marginal, inter-observer agreement statistic kappa (κ free) were used to quantify agreement between evaluators (attending physicians, site investigators, external expert panelists). Logistic regression and machine learning techniques were used to search for significant variables that could explain heterogeneity within the indeterminate and SIRS patient subgroups. Results Free-marginal kappa decreased between the initial impression of the attending physician and (1) the initial impression of the site investigator (κ free 0.68), (2) the consensus discharge diagnosis of the site investigators (κ free 0.62), and (3) the consensus diagnosis of the external expert panel (κ free 0.58). In contrast, agreement was greatest between the consensus discharge impression of site investigators and the consensus diagnosis of the external expert panel (κ free 0.79). When stratified by infection site, κ free for agreement between initial and later diagnoses had a mean value + 0.24 (range − 0.29 to + 0.39) for respiratory infections, compared to + 0.70 (range + 0.42 to + 0.88) for abdominal + urinary + other infections. Bioinformatics analysis failed to clearly resolve the indeterminate diagnoses and also failed to explain why 60% of SIRS patients were treated with antibiotics. Conclusions Considerable uncertainty surrounds the differential clinical diagnosis of sepsis vs. SIRS, especially before organ damage has become highly evident, and for patients presenting with respiratory clinical signs. Our findings underscore the need to provide physicians with accurate, timely diagnostic information in evaluating possible sepsis