The early identification of disease progression in patients with suspected infection presenting to the emergency department: a multi-centre derivation and validation study
Kordo Saeed,
Darius Cameron Wilson,
Frank Bloos,
Philipp Schuetz,
Yuri van der Does,
Olle Melander,
Pierre Hausfater,
Jacopo M. Legramante,
Yann-Erick Claessens,
Deveendra Amin,
Mari Rosenqvist,
Graham White,
Beat Mueller,
Maarten Limper,
Carlota Clemente Callejo,
Antonella Brandi,
Marc-Alexis Macchi,
Nicholas Cortes,
Alexander Kutz,
Peter Patka,
María Cecilia Yañez,
Sergio Bernardini,
Nathalie Beau,
Matthew Dryden,
Eric C. M. van Gorp,
Marilena Minieri,
Louisa Chan,
Pleunie P. M. Rood,
Juan Gonzalez del Castillo
Affiliations
Kordo Saeed
Department of Microbiology, Hampshire Hospitals NHS Foundation Trust
Darius Cameron Wilson
B·R·A·H·M·S GmbH
Frank Bloos
Department of Anesthesiology and Intensive Care Medicine, Jena University Hospital
Philipp Schuetz
Division of General and Emergency Medicine, University Department of Medicine
Yuri van der Does
Department of Emergency Medicine, Erasmus University Medical Center
Olle Melander
Department of Internal Medicine, Skåne University Hospital
Pierre Hausfater
Emergency Department hôpital Pitié-Salpêtrière, Assistance Publique - Hôpitaux de Paris and Sorbonne Universités GRC-14 BIOSFAST and INSERM UMR-S 1166
Jacopo M. Legramante
Emergency Department, Policlinico Tor Vergata
Yann-Erick Claessens
Department of Emergency Medicine, Monaco Princess Grace Hospital
Deveendra Amin
Department of Critical Care, Morton Plant Hospital
Mari Rosenqvist
Department of Clinical Sciences Malmö, Lund University
Graham White
Department of Blood Sciences, Hampshire Hospitals NHS Foundation Trust
Beat Mueller
Division of General and Emergency Medicine, University Department of Medicine
Maarten Limper
Department of Rheumatology and Clinical Immunology, University Medical Center, Utrecht University
Carlota Clemente Callejo
Emergency Department, Hospital Clínico San Carlos
Antonella Brandi
Emergency Department, Policlinico Tor Vergata
Marc-Alexis Macchi
Department of Emergency Medicine, Monaco Princess Grace Hospital
Nicholas Cortes
Department of Microbiology, Hampshire Hospitals NHS Foundation Trust
Alexander Kutz
Division of General and Emergency Medicine, University Department of Medicine
Peter Patka
Department of Emergency Medicine, Erasmus University Medical Center
María Cecilia Yañez
Emergency Department, Hospital Clínico San Carlos
Sergio Bernardini
Department of Laboratory Medicine, Policlinico Tor Vergata
Nathalie Beau
Department of Emergency Medicine, Monaco Princess Grace Hospital
Matthew Dryden
Department of Microbiology, Hampshire Hospitals NHS Foundation Trust
Eric C. M. van Gorp
Department of Internal Medicine, Erasmus University Medical Center
Marilena Minieri
Department of Laboratory Medicine, Policlinico Tor Vergata
Louisa Chan
Department of accident and emergency, Hampshire Hospitals NHS Foundation Trust
Pleunie P. M. Rood
Department of Emergency Medicine, Erasmus University Medical Center
Juan Gonzalez del Castillo
Emergency Department, Instituto de Investigación Sanitaria (IdISSC), Hospital Clínico San Carlos
Abstract Background There is a lack of validated tools to assess potential disease progression and hospitalisation decisions in patients presenting to the emergency department (ED) with a suspected infection. This study aimed to identify suitable blood biomarkers (MR-proADM, PCT, lactate and CRP) or clinical scores (SIRS, SOFA, qSOFA, NEWS and CRB-65) to fulfil this unmet clinical need. Methods An observational derivation patient cohort validated by an independent secondary analysis across nine EDs. Logistic and Cox regression, area under the receiver operating characteristic (AUROC) and Kaplan-Meier curves were used to assess performance. Disease progression was identified using a composite endpoint of 28-day mortality, ICU admission and hospitalisation > 10 days. Results One thousand one hundred seventy-five derivation and 896 validation patients were analysed with respective 28-day mortality rates of 7.1% and 5.0%, and hospitalisation rates of 77.9% and 76.2%. MR-proADM showed greatest accuracy in predicting 28-day mortality and hospitalisation requirement across both cohorts. Patient subgroups with high MR-proADM concentrations (≥ 1.54 nmol/L) and low biomarker (PCT < 0.25 ng/mL, lactate < 2.0 mmol/L or CRP < 67 mg/L) or clinical score (SOFA < 2 points, qSOFA < 2 points, NEWS < 4 points or CRB-65 < 2 points) values were characterised by a significantly longer length of hospitalisation (p < 0.001), rate of ICU admission (p < 0.001), elevated mortality risk (e.g. SOFA, qSOFA and NEWS HR [95%CI], 45.5 [10.0–207.6], 23.4 [11.1–49.3] and 32.6 [9.4–113.6], respectively) and a greater number of disease progression events (p < 0.001), compared to similar subgroups with low MR-proADM concentrations (< 1.54 nmol/L). Increased out-patient treatment across both cohorts could be facilitated using a derivation-derived MR-proADM cut-off of < 0.87 nmol/L (15.0% and 16.6%), with decreased readmission rates and no mortalities. Conclusions In patients presenting to the ED with a suspected infection, the blood biomarker MR-proADM could most accurately identify the likelihood of further disease progression. Incorporation into an early sepsis management protocol may therefore aid rapid decision-making in order to either initiate, escalate or intensify early treatment strategies, or identify patients suitable for safe out-patient treatment.