Advertisement

Development and validation of a simple nomogram for predicting the short-term prognosis of patients with pulmonary embolism

  • Jia-Liang Zhu
    Affiliations
    Department of Intensive Care Unit, The First Affiliated Hospital of Jinan University, No.613, Huangpu Road West, Guangzhou, Guangdong Province, China

    Guangzhou Women and Children's Medical Center, Guangzhou Medical University, No. 9 Jinsui Road, Guangzhou, Guangdong Province, China
    Search for articles by this author
  • Shi-Qi Yuan
    Affiliations
    Department of Neurology, The First Affiliated Hospital of Jinan University, No.613, Huangpu Road West, Guangzhou, Guangdong Province, China
    Search for articles by this author
  • Xin-Yi Wei
    Affiliations
    Department of Cardiology, The third hospital of Jinan, Wangsheren North Street 1, Gongye North Road, Jinan, Shandong Province, China
    Search for articles by this author
  • Hai-Yan Yin
    Affiliations
    Department of Intensive Care Unit, The First Affiliated Hospital of Jinan University, No.613, Huangpu Road West, Guangzhou, Guangdong Province, China
    Search for articles by this author
  • Xue-Hao Lu
    Affiliations
    Department of Intensive Care Unit, The First Affiliated Hospital of Jinan University, No.613, Huangpu Road West, Guangzhou, Guangdong Province, China
    Search for articles by this author
  • Jian-Rui Wei
    Correspondence
    Corresponding authors.
    Affiliations
    Guangzhou Women and Children's Medical Center, Guangzhou Medical University, No. 9 Jinsui Road, Guangzhou, Guangdong Province, China
    Search for articles by this author
  • Jun Lyu
    Correspondence
    Corresponding authors.
    Affiliations
    Department of Clinical Research, The First Affiliated Hospital of Jinan University, No.613, Huangpu Road West, Guangzhou, Guangdong Province, China

    Guangdong Provincial Key Laboratory of Traditional Chinese Medicine Informatization, Guangzhou, Guangdong, China
    Search for articles by this author
Published:October 03, 2022DOI:https://doi.org/10.1016/j.hrtlng.2022.09.010

      Highlights

      • Pulmonary embolism (PE) is a common and dangerous disease. PESI can accurately stratify the risk of PE patients. However, there are many variables in PESI, and for emergency or respiratory physicians with busy clinical work, it takes more time and effort to evaluate. In addition, previous studies have shown that the prognosis of PE patients varies by race. The aim of this study was to develop a new, simpler multiracial model to assess 30-day survival in PE patients.
      • This study used the MIMIC-III database to construct a new nomogram for predicting 30-day survival in PE patients. The new nomogram contains only 7 variables, which is more convenient to use. Compared with PESI, the new nomogram also had good predictive power. The new nomogram incorporates the race variable and thus can assess the prognosis of PE patients of different races.
      • Our new nomogram makes it easier for clinicians to assess the prognosis of PE patients and saves time and effort in assessment. In addition, our model also has the ability to evaluate the prognosis of PE patients of different races, and also has good predictive power.

      Abstract

      Background

      Pulmonary embolism (PE) is a disease caused by blood clots, tumor embolism, and other emboli within the pulmonary arteries. Various scoring scales are used for PE. One such same is the PESI, but it has 12 variables, making it inconvenient for clinical application.

      Objectives

      The aim of this study was to develop a new simple nomogram model to assess 30-day survival in PE patients. The new nomogram makes it easier and faster for clinicians to assess the prognosis of patients with PE.

      Methods

      We collected data about the patients with PE from the Medical Information Mart for Intensive Care-III (MIMIC-III) database and used the receiver operating characteristic (ROC) curve, area under the ROC curve (AUROC), calibration plot, integrated discrimination improvement (IDI), and decision curve analysis (DCA) to evaluate the predictive power of the new model, and compared these with the PESI.

      Results

      According to the multivariable Cox regression model results, alongside the actual clinical conditions, we included the following seven variables: race, bicarbonate, age, tumor, systolic blood pressure (SBP), body temperature, and oxygen saturation (Spo2). The AUROC of the new model was greater than 0.70. Its IDI exceeded 0, but with P-value>0.05.

      Conclusion

      The predictive performance of the new model was not worse than the PESI, but the new model only has seven variables, and is therefore more convenient for clinicians to use.

      Keywords

      Abbreviation:

      MIMIC-III (medical information mart for intensive care III), INR (international normalized ratio), PLT (platelets), PT (prothrombin time), SBP (systolic blood pressure), DBP (diastolic blood pressure), Spo2 (blood oxygen saturation), Aids (acquired immune deficiency syndrome)
      To read this article in full you will need to make a payment

      Purchase one-time access:

      Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online access
      One-time access price info
      • For academic or personal research use, select 'Academic and Personal'
      • For corporate R&D use, select 'Corporate R&D Professionals'

      Subscribe:

      Subscribe to Heart & Lung: The Journal of Cardiopulmonary and Acute Care
      Already a print subscriber? Claim online access
      Already an online subscriber? Sign in
      Institutional Access: Sign in to ScienceDirect

      References

        • Goldhaber S.Z.
        • Visani L.
        • De Rosa M.
        Acute pulmonary embolism: clinical outcomes in the International Cooperative Pulmonary Embolism Registry (ICOPER).
        Lancet. 1999; 353 (Apr 24): 1386-1389https://doi.org/10.1016/s0140-6736(98)07534-5
        • Aujesky D.
        • Obrosky D.S.
        • Stone R.A.
        • et al.
        Derivation and validation of a prognostic model for pulmonary embolism.
        Am J Respir Crit Care Med. 2005; 172 (Oct 15Epub 2005 Jul 14): 1041-1046https://doi.org/10.1164/rccm.200506-862OC
        • Erkens P.M.
        • Gandara E.
        • Wells P.
        • et al.
        Safety of outpatient treatment in acute pulmonary embolism.
        J Thromb Haemost. 2010; 8 (Nov): 2412-2417https://doi.org/10.1111/j.1538-7836.2010.04041.x
        • Kovacs M.J.
        • Hawel J.D.
        • Rekman J.F.
        • Lazo-Langner A.
        Ambulatory management of pulmonary embolism: a pragmatic evaluation.
        J Thromb Haemost. 2010; 8 (Nov): 2406-2411https://doi.org/10.1111/j.1538-7836.2010.03981.x
        • Kohn C.G.
        • Mearns E.S.
        • Parker M.W.
        • Hernandez A.V.
        • Coleman C.I.
        Prognostic accuracy of clinical prediction rules for early post-pulmonary embolism all-cause mortality: a bivariate meta-analysis.
        Chest. 2015; 147 (Apr): 1043-1062https://doi.org/10.1378/chest.14-1888
        • Yang J.
        • Li Y.
        • Liu Q.
        • et al.
        Brief introduction of medical database and data mining technology in the big data era.
        J Evid Based Med. 2020; 13 (Feb): 57-69https://doi.org/10.1111/jebm.12373. Epub 2020 Feb 22
        • Wu W.T.
        • Li Y.J.
        • Feng A.Z.
        • et al.
        Data mining in clinical big data: the frequently used databases, steps, and methodological models.
        Mil Med Res. 2021; 8 (Aug 11): 44https://doi.org/10.1186/s40779-021-00338-z
        • Lilienfeld D.E.
        Decreasing mortality from pulmonary embolism in the United States, 1979-1996.
        Int J Epidemiol. 2000; 29 (Jun): 465-469
        • White R.H.
        • Zhou H.
        • Murin S.
        • Harvey D.
        Effect of ethnicity and gender on the incidence of venous thromboembolism in a diverse population in California in 1996.
        Thromb Haemost. 2005; 93 (Feb): 298-305https://doi.org/10.1160/TH04-08-0506
        • Stein P.D.
        • Hull R.D.
        • Patel K.C.
        • et al.
        Venous thromboembolic disease: comparison of the diagnostic process in blacks and whites.
        Arch Intern Med. 2003; 163 (Aug 11-25): 1843-1848https://doi.org/10.1001/archinte.163.15.1843
        • Siddique R.M.
        • Siddique M.I.
        • Connors Jr, A.F.
        • Rimm A.A.
        Thirty-day case-fatality rates for pulmonary embolism in the elderly.
        Arch Intern Med. 1996; 156 (Nov 11): 2343-2347
        • Stein P.D.
        • Kayali F.
        • Olson R.E.
        Estimated case fatality rate of pulmonary embolism, 1979 to 1998.
        Am J Cardiol. 2004; 93 (May 1): 1197-1199https://doi.org/10.1016/j.amjcard.2004.01.058
        • Horlander K.T.
        • Mannino D.M.
        • Leeper K.V.
        Pulmonary embolism mortality in the United States, 1979-1998: an analysis using multiple-cause mortality data.
        Arch Intern Med. 2003; 163 (Jul 28): 1711-1717https://doi.org/10.1001/archinte.163.14.1711
        • Patel R.K.
        • Lambie J.
        • Bonner L.
        • Arya R.
        Venous thromboembolism in the black population.
        Arch Intern Med. 2004; 164 (Jun 28): 1348-1349https://doi.org/10.1001/archinte.164.12.1348
        • Ibrahim S.A.
        • Stone R.A.
        • Obrosky D.S.
        • Sartorius J.
        • Fine M.J.
        • Aujesky D.
        Racial differences in 30-day mortality for pulmonary embolism.
        Am J Public Health. 2006; 96 (DecEpub 2006 Oct 31): 2161-2164https://doi.org/10.2105/AJPH.2005.078618
        • Ganz D.A.
        • Glynn R.J.
        • Mogun H.
        • Knight E.L.
        • Bohn R.L.
        • Avorn J.
        Adherence to guidelines for oral anticoagulation after venous thrombosis and pulmonary embolism.
        J Gen Intern Med. 2000; 15 (Nov): 776-781https://doi.org/10.1046/j.1525-1497.2000.91022.x
        • Yamashita Y.
        • Bikdeli B.
        • Monreal M.
        • et al.
        COMMAND VTE Registry Investigators; RIETE Investigators. Difference between Japanese and White patients with acute pulmonary embolism.
        Thromb Res. 2021; 204 (AugEpub 2021 Jun 11): 52-56https://doi.org/10.1016/j.thromres.2021.06.008
        • Chau K.Y.
        • Yuen S.T.
        • Wong M.P.
        Clinicopathological pattern of pulmonary thromboembolism in Chinese autopsy patients: comparison with Caucasian series.
        Pathology. 1997; 29 (Aug): 263-266https://doi.org/10.1080/00313029700169035
        • Wigger O.
        • Bloechlinger S.
        • Berger D.
        • et al.
        Baseline serum bicarbonate levels independently predict short-term mortality in critically ill patients with ischaemic cardiogenic shock.
        Eur Heart J Acute Cardiovasc Care. 2018; 7 (FebEpub 2016 Dec 14): 45-52https://doi.org/10.1177/2048872616683526
        • Tan L.
        • Xu Q.
        • Li C.
        • Chen X.
        • Bai H.
        Association between the admission serum bicarbonate and short-term and long-term mortality in acute aortic dissection patients admitted to the intensive care unit.
        Int J Gen Med. 2021; 14 (Aug 5): 4183-4195https://doi.org/10.2147/IJGM.S321581