1. New clinical prediction model for early recognition of sepsis in adult primary care patients: a prospective diagnostic cohort study of development and external validation
- Author
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Loots, Feike J, Smits, Marleen, Hopstaken, Rogier M, Jenniskens, Kevin, Schroeten, Fleur H, van den Bruel, Ann, van de Pol, Alma C, Oosterheert, Jan Jelrik, Bouma, Hjalmar, Little, Paul, Moore, Michael, van Delft, Sanne, Rijpsma, Douwe, Holkenborg, Joris, van Bussel, Bas CT, Laven, Ralph, Bergmans, Dennis CJJ, Hoogerwerf, Jacobien J, Latten, Gideon HP, de Bont, Eefje GPM, Giesen, Paul, den Harder, Annemarie, Kusters, Ron, van Zanten, Arthur RH, Verheij, Theo JM, Critical care, Anesthesiology, Peri-operative and Emergency medicine (CAPE), MUMC+: MA Medische Staf IC (9), RS: CAPHRI - R5 - Optimising Patient Care, Intensive Care, MUMC+: MA Arts Assistenten IC (9), RS: NUTRIM - R2 - Liver and digestive health, and Family Medicine
- Subjects
general practice ,Aquacultuur en Visserij ,diagnosis ,INTERNATIONAL CONSENSUS DEFINITIONS ,PERFORMANCE ,GUIDELINES ,clinical decision rule ,Nutritional Biology ,Healthcare improvement science Radboud Institute for Health Sciences [Radboudumc 18] ,vital signs ,sepsis ,lnfectious Diseases and Global Health Radboud Institute for Health Sciences [Radboudumc 4] ,Aquaculture and Fisheries ,after-hours care ,SCORE ,Life Science ,CAMPAIGN ,ORGAN FAILURE - Abstract
BACKGROUND: Recognising patients who need immediate hospital treatment for sepsis while simultaneously limiting unnecessary referrals is challenging for GPs. AIM: To develop and validate a sepsis prediction model for adult patients in primary care. DESIGN AND SETTING: This was a prospective cohort study in four out-of-hours primary care services in the Netherlands, conducted between June 2018 and March 2020. METHOD: Adult 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. RESULTS: A 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. CONCLUSION: Based 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. ispartof: BRITISH JOURNAL OF GENERAL PRACTICE vol:72 issue:719 pages:E437-E445 ispartof: location:England status: published
- Published
- 2022