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J Crit Care. 2017 Apr;38:237-244. doi: 10.1016/j.jcrc.2016.11.037. Epub 2016 Dec 3.

Sepsis as 2 problems: Identifying sepsis at admission and predicting onset in the hospital using an electronic medical record-based acuity score.

Author information

1
PeraHealth, Inc, 6302 Fairview Rd, Suite 310, Charlotte, NC, 28203. Electronic address: mrothman@perahealth.com.
2
Alpert Medical School at Brown University, Providence, RI. Electronic address: mitchell_levy@brown.edu.
3
Cooper Medical School of Rowan University, Cooper University Health, Camden, NJ. Electronic address: dellinger-phil@cooperhealth.edu.
4
Houston Methodist Hospital, Weill Cornell Medical College, Houston, TX. Electronic address: sljones2@houstonmethodist.org.
5
Yale School of Medicine, New Haven, CT. Electronic address: robert.fogerty@yale.edu.
6
Sarasota Memorial Hospital, Sarasota, FL. Electronic address: kirk-voelker@smh.com.
7
Riverside Regional Medical Center, Newport News, VA. Electronic address: barry.gross@rivhs.com.
8
Rutgers New Jersey Medical School, MedERA, Inc., Newark, NJ. Electronic address: albertmarchetti@yahoo.com.
9
PeraHealth, Inc, 6302 Fairview Rd, Suite 310, Charlotte, NC, 28203. Electronic address: jbeals@perahealth.com.

Abstract

PURPOSE:

Early identification and treatment improve outcomes for patients with sepsis. Current screening tools are limited. We present a new approach, recognizing that sepsis patients comprise 2 distinct and unequal populations: patients with sepsis present on admission (85%) and patients who develop sepsis in the hospital (15%) with mortality rates of 12% and 35%, respectively.

METHODS:

Models are developed and tested based on 258 836 adult inpatient records from 4 hospitals. A "present on admission" model identifies patients admitted to a hospital with sepsis, and a "not present on admission" model predicts postadmission onset. Inputs include common clinical measurements and the Rothman Index. Sepsis was determined using International Classification of Diseases, Ninth Revision, codes.

RESULTS:

For sepsis present on admission, area under the curves ranged from 0.87 to 0.91. Operating points chosen to yield 75% and 50% sensitivity achieve positive predictive values of 17% to 25% and 29% to 40%, respectively. For sepsis not present on admission, at 65% sensitivity, positive predictive values ranged from 10% to 20% across hospitals.

CONCLUSIONS:

This approach yields good to excellent discriminatory performance among adult inpatients for predicting sepsis present on admission or developed within the hospital and may aid in the timely delivery of care.

KEYWORDS:

Rothman Index; Sepsis, predicting sepsis; qSOFA

PMID:
27992851
DOI:
10.1016/j.jcrc.2016.11.037
[Indexed for MEDLINE]
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