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Intensive Care Medicine

, Volume 32, Issue 11, pp 1832–1838 | Cite as

Predictors of early recovery of health status after intensive care

  • Maurizia Capuzzo
  • Rui P. Moreno
  • Barbara Jordan
  • Peter Bauer
  • Raffaele Alvisi
  • Philipp G. H. Metnitz
Original

Abstract

Objective

To identify factors predictive of good or poor recovery of health status and health-related quality of life (HRQOL) 90 days after admission to an intensive care unit (ICU).

Design and setting

Prospective international multicentre study in 19 ICUs participating in the HRQOL substudy of the SAPS 3 project.

Intervention

The EuroQol questionnaire (EQ) was administered to discharged ICU patients 90 days after admission. A question to compare present health status with that 3 months before ICU admission (same/better/worse) was added.

Patients

Six hundred and eighteen patients who spent > 24 h in an ICU and survived for 90 days. EQ data and health comparison were available in 559 (90.5%) of them.

Measurements and results

Patients reported their general level of health to be better (33.8%), the same (31.1%), or worse (35.1%) in comparison with baseline. Recovery was considered to be good for answers “better” or “the same”. Regression analysis showed that transplantation surgery [odds ratio (OR) 0.07, 95% confidence interval (CI) 0.01–0.63], coronary artery bypass surgery without valvular repair (OR 0.39, 95% CI 0.17–0.92) and being admitted to the ICU from a ward or other location (OR 0.55, 95% CI 0.31–0.95) predicted good recovery of health. Predictors of poor recovery (all present at the time of ICU admission) were unplanned ICU admission, hypothermia, serum creatinine level ≥ 2 mg/dl, pH ≤ 7.25 and metastatic cancer.

Conclusions

More than 60% of ICU patients report good recovery of their health 90 days after ICU admission, depending on their illness and circumstances of ICU admission.

Keywords

Health status Quality of life Intensive care Critical care Outcome 

Notes

Acknowledgements

The SAPS 3 project was endorsed in June 2002 by the European Society of Intensive Care Medicine (ESICM). It received support from the Austrian Centre for Documentation and Quality Assurance in Intensive Care Medicine (ASDI), the Portuguese Society of Intensive Care (SPCI), and the Medical Economics and Research Centre in Sheffield, UK. An unrestricted educational grant from Merck Sharp & Dohme Portugal to the SPCI funded the installation of the Coordination and Communication Centre in Lisbon. iMDsoft (Tel Aviv, Israel), developed and provided free of charge, was the Internet-based data collection software. Statistical analysis was supported by a grant from the Fund of the Austrian National Bank, project 10995 ONB. We thank Eduardo Almeida, who developed the SAPS 3 stand-alone database system, including the variables used in the present substudy. We are grateful to the participating ICUs who made this project possible. We also thank the EuroQol group, who gave us permission to use EQ-5D and provided the appropriate language versions free of charge.

Supplementary material

134_2006_307_MOESM1_ESM.rtf (143 kb)
Electronic Supplementary Material (RTF 144K)

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Copyright information

© Springer-Verlag 2006

Authors and Affiliations

  • Maurizia Capuzzo
    • 1
  • Rui P. Moreno
    • 2
  • Barbara Jordan
    • 3
  • Peter Bauer
    • 3
  • Raffaele Alvisi
    • 1
  • Philipp G. H. Metnitz
    • 4
  1. 1.Department of Surgical, Anaesthetic and Radiological Sciences, Service of Anaesthesiology & Intensive CareUniversity Hospital of FerraraFerraraItaly
  2. 2.Unidade de Cuidados Intensivos PolivalenteHospital de St. António dos CapuchosLisbonPortugal
  3. 3.Department of Medical StatisticsMedical University of ViennaViennaAustria
  4. 4.Department of Anaesthesiology and General Intensive CareMedical University of ViennaViennaAustria

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