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Derivation of Novel Risk Prediction Scores for Community-Acquired Sepsis and Severe Sepsis*

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Objective:

We sought to derive and internally validate a Sepsis Risk Score and a Severe Sepsis Risk Score predicting future sepsis and severe sepsis events among community-dwelling adults.

Design:

National population-based cohort.

Setting:

United States.

Subjects:

A total of 30,239 community-dwelling adults 45 years old or older in the national REasons for Geographic And Racial Differences in Stroke cohort.

Interventions:

None.

Measurements and Main Results:

Over a median of 6.6 years (interquartile range, 5.1–8.1 yr) of follow-up, there were 1,532 first sepsis (prevalence 8.3 per 1,000 person-years) and 1,151 first severe sepsis (6.2 per 1,000 person-years) events. Risk factors in the best derived Sepsis Risk Score and Severe Sepsis Risk Score included chronic lung disease, age 75 years or older, peripheral artery disease, diabetes, tobacco use, white race, stroke, atrial fibrillation, coronary artery disease, obesity, hypertension, deep vein thrombosis, male sex, high-sensitivity C-reactive protein greater than 3.0 mg/dL, cystatin C ≥1.11 mg/dL, estimated glomerular filtration rate less than 60 mL/min/1.73 m2, and albumin-to-creatinine ratio protein greater than 30 μg/mg. Sepsis Risk Score risk categories were very low (0–3 points; 2.3 events per 1,000 person-years), low (4–6; 4.1), medium (7–9; 6.5), high (10–12; 9.7), and very high (13–38; 21.1). Severe Sepsis Risk Score risk categories were very low (0–5 points; 1.5 events per 1,000 person-years), low (6–9; 3.4), medium (10–13; 6.7), high (14–17; 9.9), and very high (18–45; 22.1). The Sepsis Risk Score and Severe Sepsis Risk Score exhibited good discrimination (bootstrapped C index, 0.703 and 0.742) and calibration (p = 0.65 and 0.06).

Conclusions:

The Sepsis Risk Score and Severe Sepsis Risk Score predict 10-year sepsis and severe sepsis risk among community-dwelling adults and may aid in sepsis prevention or mitigation efforts.
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Keywords: epidemiology; infections; risk prediction; sepsis

Document Type: Research Article

Publication date: 2016-07-01

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