New clinical prediction model for early recognition of sepsis in adult primary care patients:a prospective diagnostic cohort study of development and external validation

BackgroundRecognising patients who need immediate hospital treatment for sepsis while simultaneously limiting unnecessary referrals is challenging for GPs.AimTo Develop and validate a sepsis prediction model for adult patients in primary care.Design and settingThis was a prospective cohort study in tour out-of-hours primary care services in the Netherlands, conducted between June 2018 and March 2020.MethodAdult patients who were acutely ill and received home visits were included. A total of nine clinical variables were selected as candidate predictors, next to the biomarkers C-reactive protein, procalcitonin, and lactate. The primary endpoint was sepsis within 72 hours of inclusion, as established by an expert panel. Multivariable logistic regression with backwards selection was used to design an optimal model with continuous clinical variables. The added value of the biomarkers was evaluated. Subsequently, a simple model using single cut-off points of continuous variables was developed and externally validated in two emergency department populations.ResultsA total of 357 patients were included with a median age of 80 years (interquartile range 71-86), of which 151 (42%) were diagnosed with sepsis. A model based on a simple count of one point for each of six variables (aged >65 years; temperature >38 degrees C; systolic blood pressure 110/min; saturationConclusionBased on this study's GP out-of-hours population, a simple model can accurately predict sepsis in acutely ill adult patients using readily available clinical parameters.