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Development and validation of a prediction model for estimating one-month mortality of adult COVID-19 patients presenting at emergency department with suspected pneumonia: a multicenter analysis

ABSTRACT: There are only a few models developed for risk-stratifying COVID-19 patients with suspected pneumonia in the emergency department (ED). We aimed to develop and validate a model, the COVID-19 ED pneumonia mortality index (CoV-ED-PMI), for predicting mortality in this population. We retrospectively included adult COVID-19 patients who visited EDs of five study hospitals in Texas and who were diagnosed with suspected pneumonia between March and November 2020. The primary outcome was 1-month mortality after the index ED visit. In the derivation cohort, multivariable logistic regression was used to develop the CoV-ED-PMI model. In the chronologically split validation cohort, the discriminative performance of the CoV-ED-PMI was assessed by the area under the receiver operating characteristic curve (AUC) and compared with other existing models. A total of 1678 adult ED records were included for analysis. Of them, 180 patients sustained 1-month mortality. There were 1174 and 504 patients in the derivation and validation cohorts, respectively. Age, body mass index, chronic kidney disease, congestive heart failure, hepatitis, history of transplant, neutrophil-to-lymphocyte ratio, lactate dehydrogenase, and national early warning score were included in the CoV-ED-PMI. The model was validated with good discriminative performance (AUC: 0.83, 95% confidence interval [CI]: 0.79–0.87), which was significantly better than the CURB-65 (AUC: 0.74, 95% CI: 0.69–0.79, p-value: < 0.001). The CoV-ED-PMI had a good predictive performance for 1-month mortality in COVID-19 patients with suspected pneumonia presenting at ED. This free tool is accessible online, and could be useful for clinical decision-making in the ED.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11739-021-02882-x.

SUBMITTER: Chou E

PROVIDER: S-EPMC8609507 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundThere 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.MethodsAn 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.ResultsOne 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.ConclusionsIn 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.

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:Background and importancemRNA-based host response signatures have been reported to improve sepsis diagnostics. Meanwhile, prognostic markers for the rapid and accurate prediction of severity in patients with suspected acute infections and sepsis remain an unmet need. IMX-SEV-2 is a 29-host-mRNA classifier designed to predict disease severity in patients with acute infection or sepsis.ObjectiveValidation of the host-mRNA infection severity classifier IMX-SEV-2.Design, settings and participantsProspective, observational, convenience cohort of emergency department (ED) patients with suspected acute infections.Outcome measures and analysisWhole blood RNA tubes were analyzed using independently trained and validated composite target genes (IMX-SEV-2). IMX-SEV-2-generated risk scores for severity were compared to the patient outcomes in-hospital mortality and 72-h multiorgan failure.Main resultsOf the 312 eligible patients, 22 (7.1%) died in hospital and 58 (18.6%) experienced multiorgan failure within 72 h of presentation. For predicting in-hospital mortality, IMX-SEV-2 had a significantly higher area under the receiver operating characteristic (AUROC) of 0.84 [95% confidence intervals (CI), 0.76-0.93] compared to 0.76 (0.64-0.87) for lactate, 0.68 (0.57-0.79) for quick Sequential Organ Failure Assessment (qSOFA) and 0.75 (0.65-0.85) for National Early Warning Score 2 (NEWS2), ( P = 0.015, 0.001 and 0.013, respectively). For identifying and predicting 72-h multiorgan failure, the AUROC of IMX-SEV-2 was 0.76 (0.68-0.83), not significantly different from lactate (0.73, 0.65-0.81), qSOFA (0.77, 0.70-0.83) or NEWS2 (0.81, 0.75-0.86).ConclusionThe IMX-SEV-2 classifier showed a superior prediction of in-hospital mortality compared to biomarkers and clinical scores among ED patients with suspected infections. No improvement for predicting multiorgan failure was found compared to established scores or biomarkers. Identifying patients with a high risk of mortality or multiorgan failure may improve patient outcomes, resource utilization and guide therapy decision-making.

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Development and validation of a prediction model for estimating one-month mortality of adult COVID-19 patients presenting at emergency department with suspected pneumonia: a multicenter analysis

Supplementary Information

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