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The effects of performance status one week before hospital admission on the outcomes of critically ill patients

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Abstract

Purpose

To assess the impact of performance status (PS) impairment 1 week before hospital admission on the outcomes in patients admitted to intensive care units (ICU).

Methods

Retrospective cohort study in 59,693 patients (medical admissions, 67 %) admitted to 78 ICUs during 2013. We classified PS impairment according to the Eastern Cooperative Oncology Group (ECOG) scale in absent/minor (PS = 0–1), moderate (PS = 2) or severe (PS = 3–4). We used univariate and multivariate logistic regression analyses to investigate the association between PS impairment and hospital mortality.

Results

PS impairment was moderate in 17.3 % and severe in 6.9 % of patients. The hospital mortality was 14.4 %. Overall, the worse the PS, the higher the ICU and hospital mortality and length of stay. In addition, patients with worse PS were less frequently discharged home. PS impairment was associated with worse outcomes in all SAPS 3, Charlson Comorbidity Index and age quartiles as well as according to the admission type. Adjusting for other relevant clinical characteristics, PS impairment was associated with higher hospital mortality (odds-ratio (OR) = 1.96 (95 % CI 1.63–2.35), for moderate and OR = 4.22 (3.32–5.35), for severe impairment). The effects of PS on the outcome were particularly relevant in the medium range of severity-of-illness. These results were consistent in the subgroup analyses. However, adding PS impairment to the SAPS 3 score improved only slightly its discriminative capability.

Conclusion

PS impairment was associated with worse outcomes independently of other markers of chronic health status, particularly for patients in the medium range of severity of illness.

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References

  1. Moreno RP, Metnitz PGH, Almeida E et al (2005) SAPS 3–from evaluation of the patient to evaluation of the intensive care unit. Part 2: development of a prognostic model for hospital mortality at ICU admission. Intensive Care Med 31:1345–1355. doi:10.1007/s00134-005-2763-5

    Article  PubMed  PubMed Central  Google Scholar 

  2. Salluh JIF, Soares M (2014) ICU severity of illness scores: APACHE, SAPS and MPM. Curr Opin Crit Care 20:557–565. doi:10.1097/MCC.0000000000000135

    Article  PubMed  Google Scholar 

  3. Zimmerman JE, Kramer AA, McNair DS, Malila FM (2006) Acute Physiology and Chronic Health Evaluation (APACHE) IV: hospital mortality assessment for today’s critically ill patients. Crit Care Med 34:1297–1310. doi:10.1097/01.CCM.0000215112.84523.F0

    Article  PubMed  Google Scholar 

  4. Higgins TL, Teres D, Copes WS et al (2007) Assessing contemporary intensive care unit outcome: an updated Mortality Probability Admission Model (MPM0-III). Crit Care Med 35:827–835. doi:10.1097/01.CCM.0000257337.63529.9F

    Article  PubMed  Google Scholar 

  5. Zampieri FG, Colombari F (2014) The impact of performance status and comorbidities on the short-term prognosis of very elderly patients admitted to the ICU. BMC Anesthesiol 14:59. doi:10.1186/1471-2253-14-59

    Article  PubMed  PubMed Central  Google Scholar 

  6. Rosolem MM, Rabello LSCF, Lisboa T et al (2012) Critically ill patients with cancer and sepsis: clinical course and prognostic factors. J Crit Care 27:301–307. doi:10.1016/j.jcrc.2011.06.014

    Article  PubMed  Google Scholar 

  7. Torres VBL, Azevedo LCP, Silva UVA et al (2015) Sepsis-associated outcomes in critically ill patients with malignancies. Ann Am Thorac Soc 12:1185–1192. doi:10.1513/AnnalsATS.201501-046OC

    PubMed  Google Scholar 

  8. Bagshaw SM, Stelfox HT, McDermid RC et al (2014) Association between frailty and short- and long-term outcomes among critically ill patients: a multicentre prospective cohort study. CMAJ 186:E95–E102. doi:10.1503/cmaj.130639

    Article  PubMed  PubMed Central  Google Scholar 

  9. Park C-M, Koh Y, Jeon K et al (2014) Impact of Eastern Cooperative Oncology Group Performance Status on hospital mortality in critically ill patients. J Crit Care 29:409–413. doi:10.1016/j.jcrc.2014.01.016

    Article  PubMed  Google Scholar 

  10. Azoulay E, Mokart D, Pène F et al (2013) Outcomes of critically ill patients with hematologic malignancies: prospective multicenter data from France and Belgium–a groupe de recherche respiratoire en réanimation onco-hématologique study. J Clin Oncol 31:2810–2818. doi:10.1200/JCO.2012.47.2365

    Article  PubMed  Google Scholar 

  11. Dolgin NH, Martins PNA, Movahedi B et al (2016) Functional status predicts postoperative mortality after liver transplantation. Clin Transplant. doi:10.1111/ctr.12808

    PubMed  Google Scholar 

  12. Soares M, Bozza FA, Angus DC et al (2015) Organizational characteristics, outcomes, and resource use in 78 Brazilian intensive care units: the ORCHESTRA study. Intensive Care Med 41:2149–2160. doi:10.1007/s00134-015-4076-7

    Article  PubMed  Google Scholar 

  13. Vincent JL, Moreno R, Takala J et al (1996) 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 22:707–710

    Article  CAS  PubMed  Google Scholar 

  14. Charlson ME, Pompei P, Ales KL, MacKenzie CR (1987) A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis 40:373–383

    Article  CAS  PubMed  Google Scholar 

  15. Oken MM, Creech RH, Tormey DC et al (1982) Toxicity and response criteria of the Eastern Cooperative Oncology Group. Am J Clin Oncol 5:649–655

    Article  CAS  PubMed  Google Scholar 

  16. Stekhoven DJ, Bühlmann P (2012) MissForest–non-parametric missing value imputation for mixed-type data. Bioinformatics 28:112–118. doi:10.1093/bioinformatics/btr597

    Article  CAS  PubMed  Google Scholar 

  17. Vesin A, Azoulay E, Ruckly S et al (2013) Reporting and handling missing values in clinical studies in intensive care units. Intensive Care Med 39:1396–1404. doi:10.1007/s00134-013-2949-1

    Article  PubMed  Google Scholar 

  18. Pencina MJ, D’Agostino RB, Demler OV (2012) Novel metrics for evaluating improvement in discrimination: net reclassification and integrated discrimination improvement for normal variables and nested models. Stat Med 31:101–113. doi:10.1002/sim.4348

    Article  PubMed  Google Scholar 

  19. Chirag R, Parikh HT (2014) Key concepts and limitations of statistical methods for evaluating biomarkers of kidney disease. J Am Soc Nephrol 25:1621

    Article  Google Scholar 

  20. Steyerberg EW, Vickers AJ, Cook NR et al (2010) Assessing the performance of prediction models: a framework for traditional and novel measures. Epidemiology 21:128–138. doi:10.1097/EDE.0b013e3181c30fb2

    Article  PubMed  PubMed Central  Google Scholar 

  21. Kerr KF, Wang Z, Janes H et al (2014) Net reclassification indices for evaluating risk prediction instruments: a critical review. Epidemiology 25:114–121. doi:10.1097/EDE.0000000000000018

    Article  PubMed  PubMed Central  Google Scholar 

  22. R Core Team (2015) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna

  23. Harrell FE Jr (2001) Regression modeling strategies: with applications to linear models, logistic regression, and survival analysis. Springer-Verlag, New York. doi:10.1007/978-1-4757-3462-1

    Book  Google Scholar 

  24. Wickham H (2009) ggplot2: elegant graphics for data analysis. Springer, New York

    Book  Google Scholar 

  25. Prigerson HG, Bao Y, Shah MA et al (2015) Chemotherapy use, performance status, and quality of life at the end of life. JAMA Oncol 1:778–784. doi:10.1001/jamaoncol.2015.2378

    Article  PubMed  PubMed Central  Google Scholar 

  26. Soares M, Toffart A-C, Timsit J-F et al (2014) Intensive care in patients with lung cancer: a multinational study. Ann Oncol 25:1829–1835. doi:10.1093/annonc/mdu234

    Article  CAS  PubMed  Google Scholar 

  27. Soares M, Caruso P, Silva E et al (2010) Characteristics and outcomes of patients with cancer requiring admission to intensive care units: a prospective multicenter study. Crit Care Med 38:9–15. doi:10.1097/CCM.0b013e3181c0349e

    Article  PubMed  Google Scholar 

  28. Cook NR (2007) Use and misuse of the receiver operating characteristic curve in risk prediction. Circulation 115:928–935. doi:10.1161/CIRCULATIONAHA.106.672402

    Article  PubMed  Google Scholar 

  29. Vickers AJ, Cronin AM, Begg CB (2011) One statistical test is sufficient for assessing new predictive markers. BMC Med Res Methodol 11:13. doi:10.1186/1471-2288-11-13

    Article  PubMed  PubMed Central  Google Scholar 

  30. Buccheri G, Ferrigno D, Tamburini M (1996) Karnofsky and ECOG performance status scoring in lung cancer: a prospective, longitudinal study of 536 patients from a single institution. Eur J Cancer 32A:1135–1141

    Article  CAS  PubMed  Google Scholar 

  31. Soares M, Salluh JIF, Spector N, Rocco JR (2005) Characteristics and outcomes of cancer patients requiring mechanical ventilatory support for >24 hrs. Crit Care Med 33:520–526

    Article  PubMed  Google Scholar 

  32. Forte DN, Vincent JL, Velasco IT, Park M (2012) Association between education in EOL care and variability in EOL practice: a survey of ICU physicians. Intensive Care Med 38:404–412. doi:10.1007/s00134-011-2400-4

    Article  PubMed  Google Scholar 

Download references

Acknowledgments

This study was supported by the National Council for Scientific and Technological Development (CNPq) (Grant No 304240/2014-1), Carlos Chagas Filho Foundation for Research Support of the State of Rio de Janeiro (FAPERJ) and by departmental funds from the D’Or Institute for Research and Education.

Author information

Authors and Affiliations

  1. Research Institute, Hospital do Coração (HCor), São Paulo, Brazil

    Fernando G. Zampieri

  2. Intensive Care Unit, Hospital Alemão Oswaldo Cruz, São Paulo, Brazil

    Fernando G. Zampieri

  3. Department of Critical Care, D’Or Institute for Research and Education, Rua Diniz Cordeiro, 30, Botafogo, Rio de Janeiro, 22281-100, Brazil

    Fernando A. Bozza, Giulliana M. Moralez, Jorge I. F. Salluh & Marcio Soares

  4. Instituto Nacional de Infectologia Evandro Chagas, Instituto Oswaldo Cruz-Fiocruz, Rio de Janeiro, Brazil

    Fernando A. Bozza

  5. Intensive Care Unit, Hospital Estadual Getúlio Vargas, Rio de Janeiro, Brazil

    Giulliana M. Moralez

  6. Intensive Care Unit, Hospital São Luiz–Unidade Jabaquara, São Paulo, Brazil

    Débora D. S. Mazza

  7. Intensive Care Unit, Hospital Israelita Albert Sabin, Rio de Janeiro, Brazil

    Alexandre V. Scotti

  8. Intensive Care Unit, Hospital Barra D’Or, Rio de Janeiro, Brazil

    Marcelo S. Santino

  9. Intensive Care Unit, Hospital Anchieta, Taguatinga, Brazil

    Rubens A. B. Ribeiro

  10. Complexo Hospitalar Santa Casa de Misericórdia de Porto Alegre, Porto Alegre, Brazil

    Edison M. Rodrigues Filho

  11. Intensive Care Unit, Hospital São Marcos, Recife, Brazil

    Maurício M. Cabral

  12. Intensive Care Unit, Hospital Santa Luzia, Brasília, Brazil

    Marcelo O. Maia

  13. Intensive Care Unit, Clínica São Vicente, Rio de Janeiro, Brazil

    Patrícia S. D’Alessandro

  14. Intensive Care Unit, Hospital Bangu, Rio de Janeiro, Brazil

    Sandro V. Oliveira

  15. Intensive Care Unit, Hospital Oeste D’Or, Rio de Janeiro, Brazil

    Márcia A. M. Menezes

  16. Intensive Care Unit, Hospital Unimed Vitória, Vitória, Brazil

    Eliana B. Caser

  17. Intensive Care Unit, Hospital Municipal Souza Aguiar, Rio de Janeiro, Brazil

    Roberto S. Lannes

  18. Intensive Care Unit, Hospital Regional do Cariri, Juazeiro do Norte, Brazil

    Meton S. Alencar Neto

  19. Intensive Care Unit, Hospital Agenor Paiva, Salvador, Brazil

    Maristela M. Machado

  20. Intensive Care Unit, Santa Casa de Caridade de Diamantina, Diamantina, Brazil

    Marcelo F. Sousa

  21. Postgraduate Program of Internal Medicine, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil

    Jorge I. F. Salluh & Marcio Soares

Authors
  1. Fernando G. Zampieri
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  2. Fernando A. Bozza
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  3. Giulliana M. Moralez
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  4. Débora D. S. Mazza
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  5. Alexandre V. Scotti
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  6. Marcelo S. Santino
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  7. Rubens A. B. Ribeiro
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  8. Edison M. Rodrigues Filho
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  9. Maurício M. Cabral
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  10. Marcelo O. Maia
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  11. Patrícia S. D’Alessandro
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  12. Sandro V. Oliveira
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  13. Márcia A. M. Menezes
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  14. Eliana B. Caser
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  15. Roberto S. Lannes
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  16. Meton S. Alencar Neto
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  17. Maristela M. Machado
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  18. Marcelo F. Sousa
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  19. Jorge I. F. Salluh
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  20. Marcio Soares
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Corresponding author

Correspondence to Marcio Soares.

Ethics declarations

Conflicts of interest

Dr. Soares and Dr. Salluh are founders and equity shareholders of Epimed Solutions®, which markets the Epimed Monitor System®, a cloud-based software for ICU management and benchmarking. The other authors declare that they have no conflict of interest.

Additional information

We dedicate this work to the memory of our colleague, Dr. Marcelo Lugarinho, who recently passed away.

Take-home message: Impaired performance status at 1 week prior to hospital admission is associated with worse outcomes independently of other markers of baseline health status, such as comorbidities and age. This association is more distinguishable in the mid-range severity of illness scores.

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Zampieri, F.G., Bozza, F.A., Moralez, G.M. et al. The effects of performance status one week before hospital admission on the outcomes of critically ill patients. Intensive Care Med 43, 39–47 (2017). https://doi.org/10.1007/s00134-016-4563-5

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  • DOI: https://doi.org/10.1007/s00134-016-4563-5

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