medigraphic.com
ISSN 1561-302X (Print)

2012, Number 1

<< Back Next >>

Rev cubana med 2012; 51 (1)

Mortality and adjustment by risk in the intensive care unit of the

Tamargo BTO, Jiménez PRE, López LS

Language: Spanish
References: 23
Page: 35-47
PDF size: 251.59 Kb.


ABSTRACT

Introduction: Mortality is the main indicator of results of care quality in Intensive Care Units (ICUs). Despite to be care units for severe patients, where inevitably they dye, care received by these patients is directed to avoid death.
Objective: To develop a function of the variables allowing the appropriate estimation of the probability of dye.
Methods: A cohort and retrospective study was conducted in the intensive care unit of the "Hermanos Ameijeiras" Clinical Surgical Hospital of La Habana, from January, 2002 to June, 2004. Sample including 537 medical records with complete data was randomized divided in two groups, of 269 and 268 medical records, respectively. In the first group authors estimated la ecuación de regresión logística, the dependent variable was the mortality and the independent variables: APACHE II value, age, sex, and surgical status and in the second one, the diagnosis. In the second part of sample for validation, it was assessed the discrimination by means of the ROC curve and the calibration using the Hosmer and Lemeshow test.
Results: The distribution of all variables was similar in both groups, only the sex distribution showed significant differences among them. The variables index of severity APACHE II, diagnosis and type of patient (surgical or not) determine the mortality in the ICU according to the expected in hypothesis.
Conclusions: It was possible to model the probability of dye in such a way that the model may be used in other patients to estimate the potential number of deaths in a determined period obtaining a powerful tool to look for and to detect the problems of care quality.


REFERENCES

  1. Jiménez Paneque RE. Indicadores de calidad y eficiencia de los servicios hospitalarios: una mirada actual. Rev Cubana Salud Pública. 2004;30(1):17-36.

  2. Donabedian A. Prioridades para el progreso de la evaluación y monitoreo de la calidad de la atención. Salud Pública de México. 1993;35(1):94-7.

  3. Cockings JGL, Cook DA, Iqbal RK. Process monitoring in intensive care with the use of cumulative expected minus observed mortality and risk-adjusted p charts. Critical Care. [Serie en Internet] 2006 [citado 20 de marzo de 2007];10(1):R28 [9 p.]. Disponible en: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1550849/pdf/cc3996.pdf

  4. Rothen HU, Stricker K, Einfalt J, Bauer P, Metnitz PGH, Moreno RP. Variability in outcome and resource use in intensive care units. Intensive Care Med. 2007;33:1329-36.

  5. Saadat-Niaki A, Abtahi D. Predicting the risk of death in patients in Intensive Care Unit. Arch Iranian Med. 2007;10(3):321-6.

  6. Knaus WA, Draper EA, Lawrence DE. APACHE: acute physiology and chronic health evaluation: a phisiologically based classification system.Crit Care Med. 1981;9:591-7.

  7. Higging TL. Quantifying risk and benchmarking performance in the adult intensive care unit. J Intensive Care Med. 2007;22(3):141-56.

  8. Schusterschitz N, Joannidis M. Predictive capacity of severity scoring systems in the ICU. Contrib Nephrol. 2007;156:92-100.

  9. Cavallazzi R, Marik PE, Hirani A, Pachinburavan M, Vasu TS, Leiby BE. Association between time of admission to the ICU and mortality: a systematic review and metaanalysis. Chest. Jul. 2010;138(1):68-75.

  10. Luyt CE, Combes A, Aegerter P, Guidet B, Trouillet JL, Gibert C, et al. Mortality among patients admitted to intensive care units during weekday day shifts compared with "off" hours. Crit Care Med. 2007;35(1):3-11.

  11. Mas Font S, Abizanda Campos R. Actualidad y reto de los sistemas de estimación pronóstica en pacientes críticos. Med Intensiva. 2006;30(3):93-4.

  12. Steyerberg EW. Clinical Prediction Models. A Practical Approach to Development, Validation, and Updating. New York: Springer Science+Business Media LLC; 2009. p. 260-79.

  13. Ho KM. Forest and funnel plots illustrated the calibration of a prognostic model: a descriptive study. J Clin Epidemiol. 2007(7):746-51.

  14. Donahoe L, McDonald E, kho ME, Maclennan M, Stratford PW, Cook DJ. Increasing Reliability of APACHE II Scores in a Medical-Surgical Intensive Care Unit: A Quality Improvement Study. Am J Crit Care. 2009;18:58-64.

  15. Arévalo Castillo IM, Santos Reyes S, Gálvez Rivero W. Validación de los scores Sofa y Apache II en la Unidad de Cuidados Críticos de Emergencia del Hospital Edgardo Rebagliati Martins. Emergencia. 2007;1(1)18-30.

  16. Billington EO, Zygun DA, Stelfox HT, Peets AD. Intensivists' base specialty of training is associated with variations in mortality and practice patterns. Critical Care. [Serie en Internet] 2009 [citado 21 de marzo de 2010];13:R209[7 p.]. Disponible en: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2811951/pdf/cc8227.pdf

  17. Moran JL, Bristol P, Solomon, PJ, George C, Hart GK. Mortality and length-ofstay outcomes, 1993-2003, in the binational Australian and New Zealand intensive care adult patient database. Crit Care Med. 2008;36(1):46-61.

  18. Meynaar IA, Van der Spoel JI, Rommes JH, Van Spreuwel-Verheije M, Bosman RI, Spronk PE. Off hour admission to an intensivist-led ICU is not associated with increased mortality. Critical Care. [Serie en Internet] 2009 [citado 21 de marzo de 2010];13:R84[7 p.]. Disponible en: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2717451/pdf/cc7904.pdf

  19. Gursel G, Demirtas S. Value of APACHE II, SOFA and CPIS Scores in Predicting Prognosis in Patients with Ventilator-Associated Pneumonia. Respiration. 2006;73:503-8.

  20. Le Gall JR, Neumann A, Hemery François, Bterio JP, Fulgencio JP, Garrigues B, et al. Mortality prediction using SAPS II: an update for French intensive care units. Critical Care. 2005;9:R645-R652.

  21. Mbongo CL, Monedero P, Guillen-Grima F, Yepes MJ, Vives M, Echari G. Performance of SAPS3, compared with APACHE II and SOFA, to predict hospital mortality in a general ICU in Southern Europe. Eur J Anaesthesiol. 2009;26(11):940-5.

  22. Kuzniewicz MW, Vasilevskis EE, Lane R, Dean ML, Trivedi NG, Rennie DJ, et al. Variation in ICU Risk-Adjusted Mortality: Impact of Methods of Assessment and Potential Confounders. Chest. 2008;133;1319-27.

  23. Terzi BC, Lage SG, Desanka Dragosavac RG, Severe Heart Failure at Intensive Therapy Unit - Is there an Ideal Prognostic Index? Arq Bras Cardiol. 2006;87(3):344-51.




2020     |     www.medigraphic.com