• Feike J Loots, Marleen Smits, Rogier M Hopstaken, Kevin Jenniskens, Fleur H Schroeten, Ann van den Bruel, Alma C van de Pol, Jan Jelrik Oosterheert, Hjalmar Bouma, Paul Little, Michael Moore, Sanne van Delft, Douwe Rijpsma, Joris Holkenborg, Bas Ct van Bussel, Ralph Laven, Dennis Cjj Bergmans, Jacobien J Hoogerwerf, Gideon Hp Latten, Eefje Gpm de Bont, Paul Giesen, Annemarie den Harder, Ron Kusters, Arthur Rh van Zanten, and Theo Jm Verheij.
• Julius Center for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht University, Utrecht, the Netherlands.
• Br J Gen Pract. 2022 Jun 1; 72 (719): e437e445e437-e445.

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 four 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°C; systolic blood pressure ≤110 mmHg; heart rate >110/min; saturation ≤95%; and altered mental status) had good discrimination and calibration (C-statistic of 0.80 [95% confidence interval = 0.75 to 0.84]; Brier score 0.175). Biomarkers did not improve the performance of the model and were therefore not included. The model was robust during external validation.ConclusionBased 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.© The Authors.

18 keywords...

hide…