Severe sepsis is a leading cause of death in the United States and the most common cause of death among critically ill patients in non-coronary intensive care units (ICU). Respiratory tract infections, particularly pneumonia, are the most common site of infection, and associated with the highest mortality. The type of organism causing severe sepsis is an important determinant of outcome, and gram-positive organisms as a cause of sepsis have increased in frequency over time and are now more common than gram-negative infections. Recent studies suggest that acute infections worsen pre-existing chronic diseases or result in new chronic diseases, leading to poor long-term outcomes in acute illness survivors. People of older age, male gender, black race, and preexisting chronic health conditions are particularly prone to develop severe sepsis; hence prevention strategies should be targeted at these vulnerable populations in future studies.

IMPORTANCE Sepsis is a heterogeneous syndrome. Identification of distinct clinical phenotypes may allow more precise therapy and improve care. OBJECTIVE To derive sepsis phenotypes from clinical data, determine their reproducibility and correlation with host-response biomarkers and clinical outcomes, and assess the potential causal relationship with results from randomized clinical trials (RCTs). DESIGN, SETTINGS, AND PARTICIPANTS Retrospective analysis of data sets using statistical, machine learning, and simulation tools. Phenotypes were derived among 20 189 total patients (16 552 unique patients) who met Sepsis-3 criteria within 6 hours of hospital presentation at 12 Pennsylvania hospitals (2010-2012) using consensus k means clustering applied to 29 variables. Reproducibility and correlation with biological parameters and clinical outcomes were assessed in a second database (2013-2014; n = 43 086 total patients and n = 31 160 unique patients), in a prospective cohort study of sepsis due to pneumonia (n = 583), and in 3 sepsis RCTs (n = 4737). EXPOSURES All clinical and laboratory variables in the electronic health record. MAIN OUTCOMES AND MEASURES Derived phenotype (α, β, γ, and δ) frequency, host-response biomarkers, 28-day and 365-day mortality, and RCT simulation outputs. RESULTS The derivation cohort included 20 189 patients with sepsis (mean age, 64 [SD, 17] years; 10 022 [50%] male; mean maximum 24-hour Sequential Organ Failure Assessment [SOFA] score, 3.9 [SD, 2.4]). The validation cohort included 43 086 patients (mean age, 67 [SD, 17] years; 21 993 [51%] male; mean maximum 24-hour SOFA score, 3.6 [SD, 2.0]). Of the 4 derived phenotypes, the α phenotype was the most common (n = 6625; 33%) and included patients with the lowest administration of a vasopressor; in the β phenotype (n = 5512; 27%), patients were older and had more chronic illness and renal dysfunction; in the γ phenotype (n = 5385; 27%), patients had more inflammation and pulmonary dysfunction; and in the δ phenotype (n = 2667; 13%), patients had more liver dysfunction and septic shock. Phenotype distributions were similar in the validation cohort. There were consistent differences in biomarker patterns by phenotype. In the derivation cohort, cumulative 28-day mortality was 287 deaths of 5691 unique patients (5%) for the α phenotype; 561 of 4420 (13%) for the β phenotype; 1031 of 4318 (24%) for the γ phenotype; and 897 of 2223 (40%) for the δ phenotype. Across all cohorts and trials, 28-day and 365-day mortality were highest among the δ phenotype vs the other 3 phenotypes (P < .001). In simulation models, the proportion of RCTs reporting benefit, harm, or no effect changed considerably (eg, varying the phenotype frequencies within an RCT of early goal-directed therapy changed the results from >33% chance of benefit to >60% chance of harm). CONCLUSIONS AND RELEVANCE In this retrospective analysis of data sets from patients with sepsis, 4 clinical phenotypes were identified that correlated with host-response patterns and clinical outcomes, an...

IMPORTANCE The risk of cardiovascular disease (CVD) after infection is poorly understood. OBJECTIVE To determine whether hospitalization for pneumonia is associated with an increased short-term and long-term risk of CVD. DESIGN, SETTINGS, AND PARTICIPANTS We examined 2 community-based cohorts: the Cardiovascular Health Study (CHS, n = 5888; enrollment age, ≥65 years; enrollment period, 1989–1994) and the Atherosclerosis Risk in Communities study (ARIC, n = 15 792; enrollment age, 45-64 years; enrollment period, 1987–1989). Participants were followed up through December 31, 2010. We matched each participant hospitalized with pneumonia to 2 controls. Pneumonia cases and controls were followed for occurrence of CVD over 10 years after matching. We estimated hazard ratios (HRs) for CVD at different time intervals, adjusting for demographics, CVD risk factors, subclinical CVD, comorbidities, and functional status. EXPOSURES Hospitalization for pneumonia. MAIN OUTCOMES AND MEASURES Incident CVD (myocardial infarction, stroke, and fatal coronary heart disease). RESULTS Of 591 pneumonia cases in CHS, 206 had CVD events over 10 years after pneumonia hospitalization. Compared with controls, CVD risk among pneumonia cases was highest during the first year after hospitalization and remained significantly higher than among controls through 10 years. In ARIC, of 680 pneumonia cases, 112 had CVD events over 10 years after hospitalization. After the second year, CVD risk among pneumonia cases was not significantly higher than among controls. Pneumonia Cases Controls HR (95% CI) CHS No. of participants 591 1182 CVD events  0-30 d 54 6 4.07 (2.86-5.27)  31-90 d 11 9 2.94 (2.18-3.70)  91 d-1 y 22 55 2.10 (1.59-2.60)  9-10 y 4 12 1.86 (1.18-2.55) ARIC No. of participants 680 1360 CVD events  0-30 d 4 3 2.38 (1.12-3.63)  31-90 d 4 0 2.40 (1.23-3.47)  91 d-1 y 11 8 2.19 (1.20-3.19)  1-2 y 8 7 1.88 (1.10-2.66) CONCLUSIONS AND RELEVANCE Hospitalization for pneumonia was associated with increased short-term and long-term risk of CVD, suggesting that pneumonia may be a risk factor for CVD.

While sepsis is a leading cause of acute kidney injury in critically ill patients, the relationship between immune response and acute kidney injury in less severely ill patients with infection is not known. Here we studied the epidemiology, 1-year mortality, and immune response associated with acute kidney injury in 1836 hospitalized patients with community-acquired severe and non-severe pneumonia. Acute kidney injury developed in 631 patients of whom 329 had severe and 302 had non-severe sepsis. Depending on the subgroup classification, 16–25% of the patients with non-severe pneumonia also developed acute kidney injury. In general, patients with acute kidney injury were older, had more comorbidity, and had higher biomarker concentrations (interleukin-6, tumor necrosis factor, D-dimer) even among patients without severe sepsis. The risk of death associated with acute kidney injury varied when assessed by Gray's survival model and after adjusting for differences in age, gender, ethnicity, and comorbidity. This risk was significantly higher immediately after hospitalization but gradually fell over time in the overall cohort and in those with non-severe pneumonia. A significantly higher risk of death (hazard ratio 1.29) was also present in those never admitted to an intensive care unit. Hence acute kidney injury is common even among patients with non-severe pneumonia and is associated with higher immune response and an increased risk of death.