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Observational Study
. 2019 Feb 8;23(1):40.
doi: 10.1186/s13054-019-2329-5.

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  1   2 , Darius Cameron Wilson  3 , Frank Bloos  4   5 , Philipp Schuetz  6   7 , Yuri van der Does  8 , Olle Melander  9   10 , Pierre Hausfater  11 , Jacopo M Legramante  12   13 , Yann-Erick Claessens  14 , Deveendra Amin  15 , Mari Rosenqvist  10   16 , Graham White  17 , Beat Mueller  6   7 , Maarten Limper  18 , Carlota Clemente Callejo  19 , Antonella Brandi  12 , Marc-Alexis Macchi  14 , Nicholas Cortes  20   21   22 , Alexander Kutz  6 , Peter Patka  8 , María Cecilia Yañez  19 , Sergio Bernardini  23   24 , Nathalie Beau  14 , Matthew Dryden  20   21   25 , Eric C M van Gorp  26   27 , Marilena Minieri  23 , Louisa Chan  28 , Pleunie P M Rood  8 , Juan Gonzalez Del Castillo  29
Affiliations
Observational Study

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 et al. Crit Care. .

Erratum in

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.

Keywords: Disease progression; Emergency department; MR-proADM; SOFA; Sepsis; qSOFA.

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Conflict of interest statement

Ethics approval and consent to participate

The study protocol was approved by the ethics board of each hospital where necessary, and written informed consent was obtained from all patients or their legal representatives where appropriate.

Consent for publication

No individual participant data is reported that would require consent to publish from the participant (or legal parent or guardian for children).

Competing interests

All authors have provided information on potential conflicts of interests directly or indirectly related to the work submitted in the journal’s disclosure forms. KS received research grant paid to the insitituion from Thermofisher, as well as educational grants and support to attend meetings. PS and BM received research support paid to the Institution from bioMerieux and Thermofisher. AK received support from BRAHMS to attend meetings and fulfilled speaking engagements. PH received Lecture honorarium (ThermoFisher Scientific, Beckman Coulter), Educational support honorarium (bioMérieux) Clinical research grants (ThermoFisher Scientific, bioMérieux). DCW is an employee of BRAHMS GmbH, which holds patent rights on the procalcitonin and mid-regional proadrenomedullin assay. All other authors reported no conflicts of interest.

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Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Figures

Fig. 1
Fig. 1
Flow chart describing the enrolment of patients. CNS central nervous system, MR-proADM mid-regional proadrenomedullin, N number, SOFA Sequential Organ Failure Assessment
Fig. 2
Fig. 2
ROC curve and AUC analysis for 28-day mortality prediction within the derivation (a) and validation (b) cohorts following presentation to the emergency department. AUC area under the curve, CRB-65 severity score for community-acquired pneumonia, CRP C-reactive protein, LR- negative likelihood ratio, LR+ positive likelihood ratio, MR-proADM mid-regional proadrenomedullin, NEWS National Early Warning Score, OR diagnostic odds ratio, NPV negative predictive value, PCT procalcitonin, PPV positive predictive value, qSOFA quick Sequential Organ Failure Assessment, ROC receiver operating characteristic, SIRS systemic inflammatory response syndrome, SOFA Sequential Organ Failure Assessment
Fig. 3
Fig. 3
Kaplan-Meier analysis to identify disease severity subgroups using biomarkers and clinical scores within the derivation patient population according to MR-proADM (a), lactate (b), SOFA (c), qSOFA (d), NEWS (e) and CRB-65 (f) cut-offs. CRB-65 severity score for community-acquired pneumonia, MR-proADM mid-regional proadrenomedullin, NEWS National Early Warning Score, qSOFA quick Sequential Organ Failure Assessment, SOFA Sequential Organ Failure Assessment
Fig. 4
Fig. 4
Kaplan-Meier analysis to identify patient populations enriched for either uncomplicated infections or further disease progression within the derivation cohort. Patients were stratified according to a combination of MR-proADM and lactate (a), PCT (b), SOFA (c), qSOFA (d), NEWS (e) and CRB-65 (f) cut-offs. CRB-65 severity score for community-acquired pneumonia, MR-proADM mid-regional proadrenomedullin, NEWS National Early Warning Score, PCT procalcitonin, qSOFA quick Sequential Organ Failure Assessment, SOFA Sequential Organ Failure Assessment
Fig. 5
Fig. 5
ROC curve and AUC analysis for hospitalisation decisions within the derivation (a) and validation (b) cohorts following presentation to the Emergency Department. AUC area under the curve, CRB-65 severity score for community-acquired pneumonia, CRP C-reactive protein, LR- negative likelihood ratio, LR+ positive likelihood ratio, MR-proADM mid-regional proadrenomedullin, NEWS National Early Warning Score, NPV negative predictive value, OR diagnostic odds ratio, PCT procalcitonin, PPV positive predictive value, ROC receiver operating characteristic, qSOFA quick Sequential Organ Failure Assessment, SOFA Sequential Organ Failure Assessment
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Comment in

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