Skip to main content

Advertisement

SpringerLink
Log in

Routine Laboratory Tests can Predict In-hospital Mortality in Acute Exacerbations of COPD

  • Published:
Lung Aims and scope Submit manuscript

Abstract

Chronic obstructive pulmonary disease (COPD) has a rising global incidence and acute exacerbation of COPD (AECOPD) carries a high health-care economic burden. Classification and regression tree (CART) analysis is able to create decision trees to classify risk groups. We analysed routinely collected laboratory data to identify prognostic factors for inpatient mortality with AECOPD from our large district hospital. Data from 5,985 patients with 9,915 admissions for AECOPD over a 7-year period were examined. Randomly allocated training (n = 4,986) or validation (n = 4,929) data sets were developed and CART analysis was used to model the risk of all-cause death during admission. Inpatient mortality was 15.5%, mean age was 71.5 (±11.5) years, 56.2% were male, and mean length of stay was 9.2 (±12.2) days. Of 29 variables used, CART analysis identified three (serum albumin, urea, and arterial pCO2) to predict in-hospital mortality in five risk groups, with mortality ranging from 3.0 to 23.4%. C statistic indices were 0.734 and 0.701 on the training and validation sets, respectively, indicating good model performance. The highest-risk group (23.4% mortality) had serum urea >7.35 mmol/l, arterial pCO2 >6.45 kPa, and normal serum albumin (>36.5 g/l). It is possible to develop clinically useful risk prediction models for mortality using laboratory data from the first 24 h of admission in AECOPD.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. (2008) Deaths from chronic obstructive pulmonary disease—United States, 2000–2005. MMWR Morb Mortal Wkly Rep 57:1229–1232

  2. British Thoracic Society (2006) The burden of lung disease: a statistical report from the British Thoracic Society, 2nd edn. British Thoracic Society, London

  3. Roche N, Zureik M, Soussan D, Neukirch F, Perrotin D (2008) Predictors of outcomes in COPD exacerbation cases presenting to the emergency department. Eur Respir J 32:953–961

    Article  PubMed  CAS  Google Scholar 

  4. Faustini A, Marino C, D’Ippoliti D, Forastiere F, Belleudi V, Perucci CA (2008) The impact on risk-factor analysis of different mortality outcomes in COPD patients. Eur Respir J 32:629–636

    Article  PubMed  CAS  Google Scholar 

  5. Dransfield MT, Rowe SM, Johnson JE, Bailey WC, Gerald LB (2008) Use of beta blockers and the risk of death in hospitalised patients with acute exacerbations of COPD. Thorax 63:301–305

    Article  PubMed  CAS  Google Scholar 

  6. Gunen H, Hacievliyagil SS, Kosar F et al (2005) Factors affecting survival of hospitalised patients with COPD. Eur Respir J 26:234–241

    Article  PubMed  CAS  Google Scholar 

  7. Mannino DM, Buist AS, Petty TL, Enright PL, Redd SC (2003) Lung function and mortality in the United States: data from the First National Health and Nutrition Examination Survey follow up study. Thorax 58:388–393

    Article  PubMed  CAS  Google Scholar 

  8. Tu JV (1996) Advantages and disadvantages of using artificial neural networks versus logistic regression for predicting medical outcomes. J Clin Epidemiol 49:1225–1231

    Article  PubMed  CAS  Google Scholar 

  9. Hosmer DW, Lemeshow S (2000) Applied logistic regression, 2nd edn. John Wiley & Sons, New York

    Book  Google Scholar 

  10. Hasford J, Ansari H, Lehmann K (1993) CART and logistic regression analyses of risk factors for first dose hypotension by an ACE-inhibitor. Therapie 48:479–482

    PubMed  CAS  Google Scholar 

  11. Hess KR, Abbruzzese MC, Lenzi R, Raber MN, Abbruzzese JL (1999) Classification and regression tree analysis of 1000 consecutive patients with unknown primary carcinoma. Clin Cancer Res 5:3403–3410

    PubMed  CAS  Google Scholar 

  12. Rainer TH, Lam PKW, Wong EMC, Cocks RA (1999) Derivation of a prediction rule for post-traumatic acute lung injury. Resuscitation 42:187–196

    Article  PubMed  CAS  Google Scholar 

  13. Spurgeon SEF, Hsieh Y-C, Rivadinera A, Beer TM, Mori M, Garzotto M (2006) Classification and regression tree analysis for the prediction of aggressive prostate cancer on biopsy. J Urol 175:918–922

    Article  PubMed  Google Scholar 

  14. Seemungal T, Donaldson G, Bhowmik A, Jeffries D, Wedzicha J (2000) Time course and recovery of exacerbations in patients with chronic obstructive pulmonary disease. Am J Respir Crit Care Med 161:1608–1613

    PubMed  CAS  Google Scholar 

  15. Prytherch D, Sirl JS, Weaver PC, Schmidt P, Higgins B, Sutton GL (2003) Towards a national clinical minimum data set for general surgery. Br J Surg 90:1300–1305

    Article  PubMed  CAS  Google Scholar 

  16. Breiman L, Friedman J, Olshen R, Stone C (1984) Classification and regression trees. Chapman & Hall CRC Press, Boca Raton, FL

    Google Scholar 

  17. Ai-Ping C, Lee KH, Lim TK (2005) In-hospital and 5-year mortality of patients treated in the ICU for acute exacerbation of COPD: a retrospective study. Chest 128:518–524

    Article  PubMed  Google Scholar 

  18. Fuso L, Incalzi RA, Pistelli R, Muzzolon R, Valente S, Pagliari G, Gliozzi F, Ciappi G (1995) Predicting mortality of patients hospitalized for acutely exacerbated chronic obstructive pulmonary disease. Am J Med 98:272–277

    Article  PubMed  CAS  Google Scholar 

  19. Murata GH, Kapsner CO, Lium DJ, Busby HK (1998) A multivariate model for predicting respiratory status in patients with chronic obstructive pulmonary disease. J Gen Intern Med 13:462–468

    Article  PubMed  CAS  Google Scholar 

  20. Weiss ST, DeMeo DL, Postma DS (2003) COPD: problems in diagnosis and measurement. Eur Respir J 21:4S–S12

    Article  Google Scholar 

  21. Landbo C, Prescott E, Lange P, Vestbo J, Almdal TP (1999) Prognostic value of nutritional status in chronic obstructive pulmonary disease. Am J Respir Crit Care Med 160:1856–1861

    PubMed  CAS  Google Scholar 

  22. Gray-Donald K, Gibbons L, Shapiro SH, Macklem PT, Martin JG (1996) Nutritional status and mortality in chronic obstructive pulmonary disease. Am J Respir Crit Care Med 153:961–966

    PubMed  CAS  Google Scholar 

  23. Celli BR, Cote CG, Marin JM et al (2004) The body-mass index, airflow obstruction, dyspnea, and exercise capacity index in chronic obstructive pulmonary disease. N Engl J Med 350:1005–1012

    Article  PubMed  CAS  Google Scholar 

  24. Connors AF Jr, Dawson NV, Thomas C et al (1996) Outcomes following acute exacerbation of severe chronic obstructive lung disease. The SUPPORT investigators (Study to Understand Prognoses and Preferences for Outcomes and Risks of Treatments). Am J Respir Crit Care Med 154:959–967

    PubMed  Google Scholar 

  25. Antonelli IR, Fuso L, De Rosa M et al (1997) Co-morbidity contributes to predict mortality of patients with chronic obstructive pulmonary disease. Eur Respir J 10:2794–2800

    Article  Google Scholar 

  26. Marquis K, Debigare R, Lacasse Y et al (2002) Midthigh muscle cross-sectional area is a better predictor of mortality than body mass index in patients with chronic obstructive pulmonary disease. Am J Respir Crit Care Med 166:809–813

    Article  PubMed  Google Scholar 

  27. Rothman K, Greenland S (1998) Cohort Studies. In: Rothman K, Greenland S (eds) Modern epidemiology, 2nd edn. Lippincott-Raven, Philadelphia, pp 71–91

    Google Scholar 

  28. Meade M, Guyatt G, Cook D et al (2001) Predicting success in weaning from mechanical ventilation. Chest 120:400S–424S

    Article  PubMed  CAS  Google Scholar 

  29. Varela G, Novoa N, Jimenez MF, Santos G (2003) Applicability of logistic regression (LR) risk modelling to decision making in lung cancer resection. Interact Cardiovasc Thorac Surg 2:12–15

    Article  PubMed  CAS  Google Scholar 

  30. Birim O, Kappetein AP, Waleboer M et al (2006) Long-term survival after non-small cell lung cancer surgery: Development and validation of a prognostic model with a preoperative and postoperative mode. J Thorac Cardiovasc Surg 132:491–498

    Article  PubMed  Google Scholar 

  31. Esteban C, Quintana JM, Aburto M, Moraza J, Capelastegui A (2006) A simple score for assessing stable chronic obstructive pulmonary disease. QJM 99:751–759

    Article  PubMed  CAS  Google Scholar 

  32. Wildman MJ, Sanderson C, Groves J et al (2009) Predicting mortality for patients with exacerbations of COPD and Asthma in the COPD and Asthma Outcome Study (CAOS). QJM 102:389–399

    Article  PubMed  CAS  Google Scholar 

Download references

Acknowledgments

We are grateful to the Departments of Clinical Coding, Cardiology, Haematology, and Biochemistry for providing the data and to Sumita Kerley for her assistance in data collection. This project was supported by a student bursary (for AA) from the University of Portsmouth.

Disclosure

All authors declare that there are no competing interests related to this manuscript.

Author information

Authors and Affiliations

  1. School of Health Sciences and Social Work, University of Portsmouth, Portsmouth, UK

    Alex C. Asiimwe, Bernie R. Higgins & Sally A. Kilburn

  2. Centre for Respiratory Research, University College London, London, UK

    Fraser J. H. Brims

  3. Portsmouth Hospitals NHS Trust, Portsmouth, UK

    Neil P. Andrews & Anoop J. Chauhan

  4. Centre for Healthcare Modelling and Informatics, University of Portsmouth, Portsmouth, Hampshire, UK

    Dave R. Prytherch

  5. Respiratory Centre, Queen Alexandra Hospital, PO6 3LY, Portsmouth, UK

    Anoop J. Chauhan

Authors
  1. Alex C. Asiimwe
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Fraser J. H. Brims
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Neil P. Andrews
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Dave R. Prytherch
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Bernie R. Higgins
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Sally A. Kilburn
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Anoop J. Chauhan
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Anoop J. Chauhan.

Additional information

A. C. Asiimwe and F. J. H. Brims are Joint first authors.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Asiimwe, A.C., Brims, F.J.H., Andrews, N.P. et al. Routine Laboratory Tests can Predict In-hospital Mortality in Acute Exacerbations of COPD. Lung 189, 225–232 (2011). https://doi.org/10.1007/s00408-011-9298-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00408-011-9298-z

Keywords

Search

Navigation