Corfield AR, Lees F, Zealley I et al (2014) Utility of a single early warning score in patients with sepsis in the emergency department. Emerg Med J 31:482–487. https://doi.org/10.1136/emermed-2012-202186
Freund Y, Lemachatti N, Krastinova E et al (2017) Prognostic accuracy of sepsis-3 criteria for in-hospital mortality among patients with suspected infection presenting to the emergency department. JAMA 317:301–308. https://doi.org/10.1001/jama.2016.20329
Subbe CP, Kruger M, Rutherford P et al (2001) Validation of a modified early warning score in medical admissions. QJM 94:521–526. https://doi.org/10.1093/qjmed/94.10.521
Article CAS PubMed Google Scholar
Takada T, Hoogland J, Yano T et al (2020) Added value of inflammatory markers to vital signs to predict mortality in patients suspected of severe infection. Am J Emerg Med 38:1389–1395. https://doi.org/10.1016/j.ajem.2019.11.030
Povoa P, Teixeira-Pinto AM, Carneiro AH et al (2011) C-reactive protein, an early marker of community-acquired sepsis resolution: a multi-center prospective observational study. Crit Care 15:R169. https://doi.org/10.1186/cc10313
Article PubMed PubMed Central Google Scholar
Dragoescu AN, Padureanu V, Stanculescu AD et al (2021) Neutrophil to lymphocyte ratio (NLR)—a useful tool for the prognosis of sepsis in the ICU. Biomedicines. https://doi.org/10.3390/biomedicines10010075
Article PubMed PubMed Central Google Scholar
Salciccioli JD, Marshall DC, Pimentel MA et al (2015) The association between the neutrophil-to-lymphocyte ratio and mortality in critical illness: an observational cohort study. Crit Care 19:13. https://doi.org/10.1186/s13054-014-0731-6
Article PubMed PubMed Central Google Scholar
Golcuk Y, Golcuk B, Bilge A et al (2015) Combination of mean platelet volume and the CURB-65 score better predicts 28-day mortality in patients with community-acquired pneumonia. Am J Emerg Med 33:648–652. https://doi.org/10.1016/j.ajem.2015.02.001
Kim CH, Kim SJ, Lee MJ et al (2015) An increase in mean platelet volume from baseline is associated with mortality in patients with severe sepsis or septic shock. PLoS ONE 10:e0119437. https://doi.org/10.1371/journal.pone.0119437
Article CAS PubMed PubMed Central Google Scholar
Constantino BT (2013) Red cell distribution width, revisited. Lab Med 44:e2–e9. https://doi.org/10.1309/lmz1gky9lqtvfbl7
Jo YH, Kim K, Lee JH et al (2013) Red cell distribution width is a prognostic factor in severe sepsis and septic shock. Am J Emerg Med 31:545–548. https://doi.org/10.1016/j.ajem.2012.10.017
Collins GS, Reitsma JB, Altman DG et al (2015) Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement. Ann Intern Med 162:55–63. https://doi.org/10.7326/M14-0697
Moons KG, Altman DG, Reitsma JB et al (2015) Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): explanation and elaboration. Ann Intern Med 162:W1-73. https://doi.org/10.7326/M14-0698
Churpek MM, Snyder A, Sokol S et al (2017) Investigating the impact of different suspicion of infection criteria on the accuracy of quick sepsis-related organ failure assessment, systemic inflammatory response syndrome, and early warning scores. Crit Care Med 45:1805–1812. https://doi.org/10.1097/CCM.0000000000002648
Article PubMed PubMed Central Google Scholar
Julienne J, Douillet D, Mozziconacci MS et al (2023) Prognostic accuracy of using lactate in addition to the quick Sequential Organ Failure Assessment score and the National Early Warning Score for emergency department patients with suspected infection. Emerg Med J 40:28–35. https://doi.org/10.1136/emermed-2021-211271
Shapiro NI, Wolfe RE, Moore RB et al (2003) Mortality in Emergency Department Sepsis (MEDS) score: a prospectively derived and validated clinical prediction rule. Crit Care Med 31:670–675. https://doi.org/10.1097/01.CCM.0000054867.01688.D1
Graham PL, Cook DA (2004) Prediction of risk of death using 30-day outcome: a practical end point for quality auditing in intensive care. Chest 125:1458–1466
Janssen KJ, Donders AR, Harrell FE Jr et al (2010) Missing covariate data in medical research: to impute is better than to ignore. J Clin Epidemiol 63:721–727. https://doi.org/10.1016/j.jclinepi.2009.12.008
Moons KG, Donders RA, Stijnen T et al (2006) Using the outcome for imputation of missing predictor values was preferred. J Clin Epidemiol 59:1092–1101. https://doi.org/10.1016/j.jclinepi.2006.01.009
Marshall A, Altman DG, Holder RL et al (2009) Combining estimates of interest in prognostic modelling studies after multiple imputation: current practice and guidelines. BMC Med Res Methodol 9:57. https://doi.org/10.1186/1471-2288-9-57
Article PubMed PubMed Central Google Scholar
Steyerberg EW (2009) Clinical prediction model: a practical approach to development, validation, and updating. Springer, New York
Singer M, Deutschman CS, Seymour CW et al (2016) The third international consensus definitions for sepsis and septic shock (Sepsis-3). JAMA 315:801–810. https://doi.org/10.1001/jama.2016.0287
Article CAS PubMed PubMed Central Google Scholar
Team RC. R: A language and environment for statistical computing. Available from: http://www.R-project.org/
Knaus WA, Wagner DP, Draper EA et al (1991) The APACHE III prognostic system. Risk prediction of hospital mortality for critically ill hospitalized adults. Chest 100:1619–1636
Article CAS PubMed Google Scholar
Groenwold RH, Moons KG, Pajouheshnia R et al (2016) Explicit inclusion of treatment in prognostic modeling was recommended in observational and randomized settings. J Clin Epidemiol 78:90–100. https://doi.org/10.1016/j.jclinepi.2016.03.017
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