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The early identification of disease progression in patients with suspected infection presenting to the emergency department: a multi-centre derivation and validation study.

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

SUBMITTER: Saeed K

PROVIDER: S-EPMC6368690 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature

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The early identification of disease progression in patients with suspected infection presenting to the emergency department: a multi-centre derivation and validation study.

Saeed Kordo K Wilson Darius Cameron DC Bloos Frank F Schuetz Philipp P van der Does Yuri Y Melander Olle O Hausfater Pierre P Legramante Jacopo M JM Claessens Yann-Erick YE Amin Deveendra D Rosenqvist Mari M White Graham G Mueller Beat B Limper Maarten M Callejo Carlota Clemente CC Brandi Antonella A Macchi Marc-Alexis MA Cortes Nicholas N Kutz Alexander A Patka Peter P Yañez María Cecilia MC Bernardini Sergio S Beau Nathalie N Dryden Matthew M van Gorp Eric C M ECM Minieri Marilena M Chan Louisa L Rood Pleunie P M PPM Del Castillo Juan Gonzalez JG

Critical care (London, England) 20190208 1

<h4>Background</h4>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.<h4>Methods</h4>An observational derivation patient cohort validated by an independent secondary analysis across ...[more]

PMID: 30736862

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Project description:OBJECTIVE:To derive and validate a new clinical prediction rule to risk-stratify emergency department (ED) patients admitted with suspected sepsis. DESIGN:Retrospective prognostic study of prospectively collected data. SETTING:ED. PARTICIPANTS:Patients aged ?18 years who met two Systemic Inflammatory Response Syndrome criteria or one Red Flag sepsis criteria on arrival, received intravenous antibiotics for a suspected infection and admitted. PRIMARY OUTCOME MEASURE:In-hospital all-cause mortality. METHOD:The data were divided into derivation and validation cohorts. The simplified-Mortality in Severe Sepsis in the ED score and quick-SOFA scores, refractory hypotension and lactate were collectively termed 'component scores' and cumulatively termed the 'Risk-stratification of ED suspected Sepsis (REDS) score'. Each patient in the derivation cohort received a score (0-3) for each component score. The REDS score ranged from 0 to 12. The component scores were subject to univariate and multivariate logistic regression analyses. The receiver operator characteristic (ROC) curves for the REDS and the components scores were constructed and their cut-off points identified. Scores above the cut-off points were deemed high-risk. The area under the ROC (AUROC) curves and sensitivity for mortality of the high-risk category of the REDS score and component scores were compared. The REDS score was internally validated. RESULTS:2115 patients of whom 282 (13.3%) died in hospital. Derivation cohort: 1078 patients with 140 deaths (13%). The AUROC curve with 95% CI, cut-off point and sensitivity for mortality (95% CI) of the high-risk category of the REDS score were: derivation: 0.78 (0.75 to 0.80); ?3; 85.0 (78 to 90.5). VALIDATION:0.74 (0.71 to 0.76); ?3; 84.5 (77.5 to 90.0). The AUROC curve and the sensitivity for mortality of the REDS score was better than that of the component scores. Specificity and mortality rates for REDS scores of ?3, ?5 and ?7 were 54.8%, 88.8% and 96.9% and 21.8%, 36.0% and 49.1%, respectively. CONCLUSION:The REDS score is a simple and objective score to risk-stratify ED patients with suspected sepsis.

Project description:BackgroundDeploying accurate computable phenotypes in pragmatic trials requires a trade-off between precise and clinically sensical variable selection. In particular, evaluating the medical encounter to assess a pattern leading to clinically significant impairment or distress indicative of disease is a difficult modeling challenge for the emergency department.ObjectiveThis study aimed to derive and validate an electronic health record-based computable phenotype to identify emergency department patients with opioid use disorder using physician chart review as a reference standard.MethodsA two-algorithm computable phenotype was developed and evaluated using structured clinical data across 13 emergency departments in two large health care systems. Algorithm 1 combined clinician and billing codes. Algorithm 2 used chief complaint structured data suggestive of opioid use disorder. To evaluate the algorithms in both internal and external validation phases, two emergency medicine physicians, with a third acting as adjudicator, reviewed a pragmatic sample of 231 charts: 125 internal validation (75 positive and 50 negative), 106 external validation (56 positive and 50 negative).ResultsCohen kappa, measuring agreement between reviewers, for the internal and external validation cohorts was 0.95 and 0.93, respectively. In the internal validation phase, Algorithm 1 had a positive predictive value (PPV) of 0.96 (95% CI 0.863-0.995) and a negative predictive value (NPV) of 0.98 (95% CI 0.893-0.999), and Algorithm 2 had a PPV of 0.8 (95% CI 0.593-0.932) and an NPV of 1.0 (one-sided 97.5% CI 0.863-1). In the external validation phase, the phenotype had a PPV of 0.95 (95% CI 0.851-0.989) and an NPV of 0.92 (95% CI 0.807-0.978).ConclusionsThis phenotype detected emergency department patients with opioid use disorder with high predictive values and reliability. Its algorithms were transportable across health care systems and have potential value for both clinical and research purposes.

Project description:ImportanceProfessional guidelines recommend noninvasive cardiac testing (NIT) within 72 hours of an emergency department (ED) evaluation for suspected acute coronary syndrome. However, there is inexact evidence that this strategy reduces the risk of future death or acute myocardial infarction (MI).ObjectiveTo evaluate the effectiveness of early NIT in reducing the risk of death or acute MI within 30 days.Design, setting, and participantsThis retrospective, multicenter cohort study within the Kaiser Permanente Southern California integrated health care delivery system compared the effectiveness of early noninvasive cardiac testing vs no testing in patients with chest pain and in whom acute MI was ruled out who presented to an ED from January 2015 to December 2017. Patients were followed up for up to 30 days after emergency department discharge.ExposuresNoninvasive cardiac testing performed within 3 days of an ED evaluation for suspected acute coronary syndrome.Main outcomes and measuresThe primary outcome was composite risk of death or acute MI, within 30 days of an ED discharge.ResultsA total of 79 040 patients were evaluated in this study, of whom 57.7% were female. The mean (SD) age of the cohort was 57 (16) years, and 16 164 patients (21%) had completed early NIT. The absolute risk of death or MI within 30 days was low (<1%). Early NIT had the minor benefit of reducing the absolute composite risk of death or MI (0.4% [95% CI, -0.6% to -0.3%]), and, separately, of death (0.2% [95% CI, -0.2% to -0.1%]), MI (-0.3% [95% CI, -0.5% to -0.1%]), and major adverse cardiac event (-0.5% [95% CI, -0.7% to -0.3%]). The number needed to treat was 250 to avoid 1 death or MI, 500 to avoid 1 death, 333 to avoid 1 MI, and 200 to avoid 1 major adverse cardiovascular event within 30 days. Subgroup analysis revealed a number needed to treat of 14 to avoid 1 death or MI in the subset of patients with elevated troponin.Conclusions and relevanceEarly NIT was associated with a small decrease in the risk of death or MI in patients admitted to the ED with suspected acute coronary syndrome, but this clinical strategy may not be optimal for most patients given the large number needed to treat.

Dataset Information

The early identification of disease progression in patients with suspected infection presenting to the emergency department: a multi-centre derivation and validation study.

Publications

The early identification of disease progression in patients with suspected infection presenting to the emergency department: a multi-centre derivation and validation study.

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