title: A clinical deterioration prediction tool for internal medicine patients.
abstract: Many early warning models for hospitalized patients use variables measured on admission to the hospital ward; few have been rigorously derived and validated. The objective was to create and validate a clinical deterioration prediction tool using routinely collected clinical and nursing measurements. Multivariate regression analysis was used to determine clinical variables statistically associated with clinical deterioration; subsequently, the model tool was retrospectively validated using a different cohort of medical inpatients. The Braden Scale (P = .01; odds ratio [OR] = 0.91; confidence interval [CI] = 0.84-0.98), respiratory rate (P < .01; OR = 1.08; CI = 1.04-1.13), oxygen saturation (P < .01; OR = 0.97; CI = 0.96-0.99), and shock index (P < .01; OR = 2.37; CI = 1.14-3.98) were predictive of clinical deterioration 2-12 hours in the future. When applied to the validation cohort, the tool demonstrated fair concordance with actual outcomes. This tool created using routinely collected clinical measurements can serve as a very early warning system for hospitalized medical patients.
authors: Mayo Clinic Rochester, 200 First Street SW, Rochester, MN 55905, USA. Kirkland.lisa@mayo.edu
authors: Lisa L
authors: LL
authors: Kirkland
authors: Michael
authors: M
authors: Malinchoc
authors: Megan
authors: M
authors: O'Byrne
authors: Joanne T
authors: JT
authors: Benson
authors: Deanne T
authors: DT
authors: Kashiwagi
authors: M Caroline
authors: MC
authors: Burton
authors: Prathibha
authors: P
authors: Varkey
authors: Timothy I
authors: TI
authors: Morgenthaler
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D001794:Blood Pressure; D005260:Female; D006339:Heart Rate; D057209:Hospital Rapid Response Team / Q000706:statistics & numerical data; D006801:Humans; D007362:Intensive Care Units / Q000706:statistics & numerical data; D007388:Internal Medicine / Q000706:statistics & numerical data*; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D010343:Patient Admission / Q000706:statistics & numerical data*; D011379:Prognosis; D012189:Retrospective Studies; D018570:Risk Assessment / Q000706:statistics & numerical data*; D012720:Severity of Illness Index