Development of a Nomogram for Predicting Mortality Risk in Sepsis Patients During Hospitalization: A Retrospective Study

References

• Rhee C, Dantes R, Epstein L, et al. Incidence and trends of sepsis in US hospitals using clinical vs claims data, 2009–2014. JAMA. 2017;318(13):1241–1249. doi:10.1001/jama.2017.13836
   PubMed Web of Science ®Google Scholar
• Fleischmann C, Scherag A, Adhikari NK, et al. Assessment of global incidence and mortality of hospital-treated sepsis. Current estimates and limitations. Am J Respir Crit Care Med. 2016;193(3):259–272. doi:10.1164/rccm.201504-0781OC
   PubMed Web of Science ®Google Scholar
• Singer M, Deutschman CS, Seymour CW, et al. The third international consensus definitions for sepsis and septic shock (sepsis-3). JAMA. 2016;315(8):801–810. doi:10.1001/jama.2016.0287
   PubMed Web of Science ®Google Scholar
• Knaus WA, Draper EA, Wagner DP, Zimmerman JE. Prognosis in acute organ-system failure. Ann Surg. 1985;202(6):685–693. doi:10.1097/00000658-198512000-00004
   PubMed Web of Science ®Google Scholar
• Beck DH, Smith GB, Taylor BL. The impact of low-risk intensive care unit admissions on mortality probabilities by SAPS II, APACHE II and APACHE III. Anaesthesia. 2002;57(1):21–26. doi:10.1046/j.1365-2044.2002.02362.x
   PubMed Web of Science ®Google Scholar
• Weng J, Hou R, Zhou X, et al. Development and validation of a score to predict mortality in ICU patients with sepsis: a multicenter retrospective study. J Transl Med. 2021;19(1):322. doi:10.1186/s12967-021-03005-y
   PubMed Web of Science ®Google Scholar
• Dabhi AS, Khedekar SS, Mehalingam V. A prospective study of comparison of APACHE-IV & SAPS-II scoring systems and calculation of standardised mortality rate in severe sepsis and septic shock patients. J Clin Diagn Res. 2014;8(10):Mc09–13 doi:10.7860/JCDR/2014/9925.5052
   PubMedGoogle Scholar
• Huang CT, Ruan SY, Tsai YJ, Ku SC, Yu CJ. Clinical trajectories and causes of death in septic patients with a low APACHE II score. J Clin Med. 2019;8(7):1064. doi:10.3390/jcm8071064
   PubMed Web of Science ®Google Scholar
• Churpek MM, Zadravecz FJ, Winslow C, Howell MD, Edelson DP. Incidence and prognostic value of the systemic inflammatory response syndrome and organ dysfunctions in ward patients. Am J Respir Crit Care Med. 2015;192(8):958–964. doi:10.1164/rccm.201502-0275OC
   PubMed Web of Science ®Google Scholar
• Fernando SM, Tran A, Taljaard M, et al. Prognostic accuracy of the quick sequential organ failure assessment for mortality in patients with suspected infection: a systematic review and meta-analysis. Ann Intern Med. 2018;168(4):266–275. doi:10.7326/m17-2820
   PubMed Web of Science ®Google Scholar
• Raith EP, Udy AA, Bailey M, et al. Prognostic accuracy of the SOFA score, SIRS criteria, and qSOFA score for in-hospital mortality among adults with suspected infection admitted to the intensive care unit. JAMA. 2017;317(3):290–300. doi:10.1001/jama.2016.20328
   PubMed Web of Science ®Google Scholar
• Vincent JL, Moreno R, Takala J, et al. The SOFA (Sepsis-Related Organ Failure Assessment) score to describe organ dysfunction/failure. On behalf of the working group on sepsis-related problems of the European Society of Intensive Care Medicine. Intensive Care Med. 1996;22(7):707–710. doi:10.1007/bf01709751
   PubMed Web of Science ®Google Scholar
• Abdullah Smob RH, Nielsen FE, Nielsen FE. Prognostic accuracy of SOFA, qSOFA, and SIRS for mortality among emergency department patients with infections. Infect Drug Resist. 2021;14:2763–2775. doi:10.2147/idr.S304952
   PubMed Web of Science ®Google Scholar
• Park SY. Nomogram: an analogue tool to deliver digital knowledge. J Thorac Cardiovasc Surg. 2018;155(4):1793. doi:10.1016/j.jtcvs.2017.12.107
   PubMed Web of Science ®Google Scholar
• Jiang X, Wang Y, Pan Y, Zhang W. Prediction models for sepsis-associated thrombocytopenia risk in intensive care units based on a machine learning algorithm. Front Med. 2022;9:837382. doi:10.3389/fmed.2022.837382
   Web of Science ®Google Scholar
• Levy MM, Fink MP, Marshall JC, et al. 2001 SCCM/ESICM/ACCP/ATS/SIS international sepsis definitions conference. Crit Care Med. 2003;31(4):1250–1256. doi:10.1097/01.Ccm.0000050454.01978.3b
   PubMed Web of Science ®Google Scholar
• Cummings P. Missing data and multiple imputation. JAMA Pediatr. 2013;167(7):656–661. doi:10.1001/jamapediatrics.2013.1329
   PubMed Web of Science ®Google Scholar
• Shen Y, Huang X, Zhang W. Platelet-to-lymphocyte ratio as a prognostic predictor of mortality for sepsis: interaction effect with disease severity-A retrospective study. BMJ Open. 2019;9(1):e022896. doi:10.1136/bmjopen-2018-022896
   PubMed Web of Science ®Google Scholar
• Zhang K, Zhang S, Cui W, Hong Y, Zhang G, Zhang Z. Development and validation of a sepsis mortality risk score for sepsis-3 patients in intensive care unit. Front Med. 2020;7:609769. doi:10.3389/fmed.2020.609769
   Web of Science ®Google Scholar
• Niu XK, He WF, Zhang Y, et al. Developing a new PI-RADS v2-based nomogram for forecasting high-grade prostate cancer. Clin Radiol. 2017;72(6):458–464. doi:10.1016/j.crad.2016.12.005
   PubMed Web of Science ®Google Scholar
• Vickers AJ, Holland F. Decision curve analysis to evaluate the clinical benefit of prediction models. Spine J. 2021;21(10):1643–1648. doi:10.1016/j.spinee.2021.02.024
   PubMed Web of Science ®Google Scholar
• Wang D, Li J, Sun Y, et al. A machine learning model for accurate prediction of sepsis in ICU patients. Front Public Health. 2021;9:754348. doi:10.3389/fpubh.2021.754348
   PubMed Web of Science ®Google Scholar
• Zhongheng Z, Chen L, Ping X, Hong Y. Predictive analytics with ensemble modeling in laparoscopic surgery: a technical note. Laparosc Endosc Robot Surg. 2022;5(1):25–34. doi:10.1016/j.lers.2021.12.003
   Google Scholar
• Zhang L, Wang Z, Zhou Z, et al. Developing an ensemble machine learning model for early prediction of sepsis-associated acute kidney injury. iScience. 2022;25(9):104932. doi:10.1016/j.isci.2022.104932
   PubMed Web of Science ®Google Scholar
• Peng ZL, Huang LW, Yin J, Zhang KN, Xiao K, Qing GZ. Association between early serum cholinesterase activity and 30-day mortality in sepsis-3 patients: a retrospective cohort study. PLoS One. 2018;13(8):e0203128. doi:10.1371/journal.pone.0203128
   PubMed Web of Science ®Google Scholar
• Zivkovic AR, Decker SO, Zirnstein AC, et al. A sustained reduction in serum cholinesterase enzyme activity predicts patient outcome following sepsis. Mediators Inflamm. 2018;2018:1942193. doi:10.1155/2018/1942193
   PubMed Web of Science ®Google Scholar
• Xiao Y, Yan X, Shen L, et al. Evaluation of qSOFA score, and conjugated bilirubin and creatinine levels for predicting 28-day mortality in patients with sepsis. Exp Ther Med. 2022;24(1):447. doi:10.3892/etm.2022.11374
   PubMed Web of Science ®Google Scholar
• Martín-Rodríguez F, Melero-Guijarro L, Ortega GJ, et al. Combination of prehospital NT-proBNP with qSOFA and NEWS to predict sepsis and sepsis-related mortality. Dis Markers. 2022;2022:5351137. doi:10.1155/2022/5351137
   PubMed Web of Science ®Google Scholar
• Ping F, Li Y, Cao Y, et al. Metabolomics analysis of the development of sepsis and potential biomarkers of sepsis-induced acute kidney injury. Oxid Med Cell Longev. 2021;2021:6628847. doi:10.1155/2021/6628847
   PubMed Web of Science ®Google Scholar
• Varis E, Pettilä V, Poukkanen M, et al. Evolution of blood lactate and 90-day mortality in septic shock. A post hoc analysis of the FINNAKI study. Shock. 2017;47(5):574–581. doi:10.1097/shk.0000000000000772
   PubMed Web of Science ®Google Scholar
• Han X, Edelson DP, Snyder A, et al. Implications of centers for medicare and Medicaid services severe sepsis and septic shock early management bundle and initial lactate measurement on the management of sepsis. Chest. 2018;154(2):302–308. doi:10.1016/j.chest.2018.03.025
   PubMed Web of Science ®Google Scholar
• Ko BS, Kim K, Choi SH, et al. Prognosis of patients excluded by the definition of septic shock based on their lactate levels after initial fluid resuscitation: a prospective multi-center observational study. Crit Care. 2018;22(1):47. doi:10.1186/s13054-017-1935-3
   PubMedGoogle Scholar
• Wacker C, Prkno A, Brunkhorst FM, Schlattmann P. Procalcitonin as a diagnostic marker for sepsis: a systematic review and meta-analysis. Lancet Infect Dis. 2013;13(5):426–435. doi:10.1016/s1473-3099(12)70323-7
   PubMed Web of Science ®Google Scholar
• Tan M, Lu Y, Jiang H, Zhang L. The diagnostic accuracy of procalcitonin and C-reactive protein for sepsis: a systematic review and meta-analysis. J Cell Biochem. 2019;120(4):5852–5859. doi:10.1002/jcb.27870
   PubMed Web of Science ®Google Scholar
• Jensen JU, Heslet L, Jensen TH, Espersen K, Steffensen P, Tvede M. Procalcitonin increase in early identification of critically ill patients at high risk of mortality. Crit Care Med. 2006;34(10):2596–2602. doi:10.1097/01.Ccm.0000239116.01855.61
   PubMed Web of Science ®Google Scholar
• Aloisio E, Dolci A, Panteghini M. Procalcitonin: between evidence and critical issues. Clin Chim Acta. 2019;496:7–12. doi:10.1016/j.cca.2019.06.010
   PubMed Web of Science ®Google Scholar
• Bachler M, Hell T, Schausberger L, et al. Response patterns of routinely measured inflammatory and coagulatory parameters in sepsis. Peer J. 2019;7:e7147. doi:10.7717/peerj.7147
   PubMed Web of Science ®Google Scholar
• Guo F, Zhu X, Wu Z, Zhu L, Wu J, Zhang F. Clinical applications of machine learning in the survival prediction and classification of sepsis: coagulation and heparin usage matter. J Transl Med. 2022;20(1):265. doi:10.1186/s12967-022-03469-6
   PubMed Web of Science ®Google Scholar
• Guarracino F, Bertini P, Pinsky MR. Cardiovascular determinants of resuscitation from sepsis and septic shock. Crit Care. 2019;23(1):118. doi:10.1186/s13054-019-2414-9
   PubMedGoogle Scholar
• Asfar P, Meziani F, Hamel JF, et al. High versus low blood-pressure target in patients with septic shock. N Engl J Med. 2014;370(17):1583–1593. doi:10.1056/NEJMoa1312173
   PubMed Web of Science ®Google Scholar
• Cheng B, Li Z, Wang J, et al. Comparison of the performance between sepsis-1 and sepsis-3 in ICUs in China: a retrospective multicenter study. Shock. 2017;48(3):301–306. doi:10.1097/shk.0000000000000868
   PubMed Web of Science ®Google Scholar
• Moreno-Torres V, Royuela A, Múñez E, et al. Better prognostic ability of NEWS2, SOFA and SAPS-II in septic patients. Med Clin. 2022;159(5):224–229. doi:10.1016/j.medcli.2021.10.021
   PubMed Web of Science ®Google Scholar
• Liu Z, Meng Z, Li Y, et al. Prognostic accuracy of the serum lactate level, the SOFA score and the qSOFA score for mortality among adults with sepsis. Scand J Trauma Resusc Emerg Med. 2019;27(1):51. doi:10.1186/s13049-019-0609-3
   PubMed Web of Science ®Google Scholar
• Kelly CJ, Karthikesalingam A, Suleyman M, Corrado G, King D. Key challenges for delivering clinical impact with artificial intelligence. BMC Med. 2019;17(1):195. doi:10.1186/s12916-019-1426-2
   PubMed Web of Science ®Google Scholar