Sepsis is a common cause of death, but outcomes in individual patients are difficult to predict. Elucidating the molecular processes that differ between sepsis patients who survive and those who die may permit more appropriate treatments to be deployed. We examined the clinical features, and the plasma metabolome and proteome of patients with and without community-acquired sepsis, upon their arrival at hospital emergency departments and 24 hours later. The metabolomes and proteomes of patients at hospital admittance who would die differed markedly from those who would survive. The different profiles of proteins and metabolites clustered into fatty acid transport and β-oxidation, gluconeogenesis and the citric acid cycle. They differed consistently among several sets of patients, and diverged more as death approached. In contrast, the metabolomes and proteomes of surviving patients with mild sepsis did not differ from survivors with severe sepsis or septic shock. An algorithm derived from clinical features together with measurements of seven metabolites predicted patient survival. This algorithm may help to guide the treatment of individual patients with sepsis.

The combination of ascorbic acid, corticosteroids, and thiamine has been identified as a potential therapy for septic shock.OBJECTIVE To determine whether the combination of ascorbic acid, corticosteroids, and thiamine attenuates organ injury in patients with septic shock. DESIGN, SETTING, AND PARTICIPANTS Randomized, blinded, multicenter clinical trial of ascorbic acid, corticosteroids, and thiamine vs placebo for adult patients with septic shock. Two hundred five patients were enrolled between February 9, 2018, and October 27, 2019, at 14 centers in the United States. Follow-up continued until November 26, 2019.INTERVENTIONS Patients were randomly assigned to receive parenteral ascorbic acid (1500 mg), hydrocortisone (50 mg), and thiamine (100 mg) every 6 hours for 4 days (n = 103) or placebo in matching volumes at the same time points (n = 102). MAIN OUTCOMES AND MEASURESThe primary outcome was change in the Sequential Organ Failure Assessment (SOFA) score (range, 0-24; 0 = best) between enrollment and 72 hours. Key secondary outcomes included kidney failure and 30-day mortality. Patients who received at least 1 dose of study drug were included in analyses. RESULTS Among 205 randomized patients (mean age, 68 [SD,15] years; 90 [44%] women), 200 (98%) received at least 1 dose of study drug, completed the trial, and were included in the analyses (101 with intervention and 99 with placebo group). Overall, there was no statistically significant interaction between time and treatment group with regard to SOFA score over the 72 hours after enrollment (mean SOFA score change from 9.1 to 4.4 [−4.7] points with intervention vs 9.2 to 5.1 [−4.1] points with placebo; adjusted mean difference, −0.8; 95% CI, −1.7 to 0.2; P = .12 for interaction). There was no statistically significant difference in the incidence of kidney failure (31.7% with intervention vs 27.3% with placebo; adjusted risk difference, 0.03; 95% CI, −0.1 to 0.2; P = .58) or in 30-day mortality (34.7% vs 29.3%, respectively; hazard ratio, 1.3; 95% CI, 0.8-2.2; P = .26). The most common serious adverse events were hyperglycemia (12 patients with intervention and 7 patients with placebo), hypernatremia (11 and 7 patients, respectively), and new hospital-acquired infection (13 and 12 patients, respectively). CONCLUSIONS AND RELEVANCEIn patients with septic shock, the combination of ascorbic acid, corticosteroids, and thiamine, compared with placebo, did not result in a statistically significant reduction in SOFA score during the first 72 hours after enrollment. These data do not support routine use of this combination therapy for patients with septic shock.

Acute respiratory infections caused by bacterial or viral pathogens are among the most common reasons for seeking medical care. Despite improvements in pathogen-based diagnostics, most patients receive inappropriate antibiotics. Host response biomarkers offer an alternative diagnostic approach to direct antimicrobial use. This observational, cohort study determined whether host gene expression patterns discriminate non-infectious from infectious illness, and bacterial from viral causes of acute respiratory infection in the acute care setting. Peripheral whole blood gene expression from 273 subjects with community-onset acute respiratory infection (ARI) or non-infectious illness as well as 44 healthy controls was measured using microarrays. Sparse logistic regression was used to develop classifiers for bacterial ARI (71 probes), viral ARI (33 probes), or a non-infectious cause of illness (26 probes). Overall accuracy was 87% (238/273 concordant with clinical adjudication), which was more accurate than procalcitonin (78%, p<0.03) and three published classifiers of bacterial vs. viral infection (78-83%). The classifiers developed here externally validated in five publicly available datasets (AUC 0.90-0.99). A sixth publically available dataset included twenty-five patients with co-identification of bacterial and viral pathogens. Applying the ARI classifiers defined four distinct groups: a host response to bacterial ARI; viral ARI; co-infection; and neither a bacterial nor viral response. These findings create an opportunity to develop and utilize host gene expression classifiers as diagnostic platforms to combat inappropriate antibiotic use and emerging antibiotic resistance.

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A biomarker panel of neutrophil gelatinase-associated lipocalin, interleukin-1ra, and Protein C was predictive of severe sepsis, septic shock, and death in ED patients with suspected sepsis. Further study is warranted to prospectively validate the clinical utility of these biomarkers and the sepsis score in risk-stratifying patients with suspected sepsis.

Background Aggressive diagnosis and treatment of patients presenting to the emergency department (ED) with septic shock has been shown to reduce mortality. To enhance the ability to intervene in patients with lesser illness severity, a better understanding of the natural history of the early progression from simple infection to more severe illness is needed. Objectives The objectives were to 1) describe the clinical presentation of ED sepsis, including types of infection and causative microorganisms, and 2) determine the incidence, patient characteristics, and mortality associated with early progression to septic shock among ED patients with infection. Methods This was a multicenter study of adult ED patients with sepsis but no evidence of shock. Multivariable logistic regression was used to identify patient factors for early progression to shock and its association with 30-day mortality. Results Of 472 patients not in shock at ED presentation (systolic blood pressure > 90 mm Hg and lactate < 4 mmol / L), 84 (17.8%) progressed to shock within 72 hours. Independent factors associated with early progression to shock included older age, female sex, hyperthermia, anemia, comorbid lung disease, and vascular access device infection. Early progression to shock (vs. no progression) was associated with higher 30-day mortality (13.1% vs. 3.1%, odds ratio [OR] = 4.72, 95% confidence interval [CI] = 2.01 to 11.1; p ≤ 0.001). Among 379 patients with uncomplicated sepsis (i.e., no evidence of shock or any end-organ dysfunction), 86 (22.7%) progressed to severe sepsis or shock within 72 hours of hospital admission. Conclusions A significant portion of ED patients with less severe sepsis progress to severe sepsis or shock within 72 hours. Additional diagnostic approaches are needed to risk stratify and more effectively treat ED patients with sepsis.

ObjectiveTo identify metabolomic biomarkers predictive of Intensive Care Unit (ICU) mortality in adults.RationaleComprehensive metabolomic profiling of plasma at ICU admission to identify biomarkers associated with mortality has recently become feasible.MethodsWe performed metabolomic profiling of plasma from 90 ICU subjects enrolled in the BWH Registry of Critical Illness (RoCI). We tested individual metabolites and a Bayesian Network of metabolites for association with 28-day mortality, using logistic regression in R, and the CGBayesNets Package in MATLAB. Both individual metabolites and the network were tested for replication in an independent cohort of 149 adults enrolled in the Community Acquired Pneumonia and Sepsis Outcome Diagnostics (CAPSOD) study.ResultsWe tested variable metabolites for association with 28-day mortality. In RoCI, nearly one third of metabolites differed among ICU survivors versus those who died by day 28 (N = 57 metabolites, p<.05). Associations with 28-day mortality replicated for 31 of these metabolites (with p<.05) in the CAPSOD population. Replicating metabolites included lipids (N = 14), amino acids or amino acid breakdown products (N = 12), carbohydrates (N = 1), nucleotides (N = 3), and 1 peptide. Among 31 replicated metabolites, 25 were higher in subjects who progressed to die; all 6 metabolites that are lower in those who die are lipids. We used Bayesian modeling to form a metabolomic network of 7 metabolites associated with death (gamma-glutamylphenylalanine, gamma-glutamyltyrosine, 1-arachidonoylGPC(20:4), taurochenodeoxycholate, 3-(4-hydroxyphenyl) lactate, sucrose, kynurenine). This network achieved a 91% AUC predicting 28-day mortality in RoCI, and 74% of the AUC in CAPSOD (p<.001 in both populations).ConclusionBoth individual metabolites and a metabolomic network were associated with 28-day mortality in two independent cohorts. Metabolomic profiling represents a valuable new approach for identifying novel biomarkers in critically ill patients.

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