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SPCI - Sociedade Portuguesa de Cuidados Intensivos

Revista Brasileira de Terapia Intensiva

AMIB - Associação de Medicina Intensiva Brasileira


ISSN: 0103-507X
Online ISSN: 1982-4335

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Stein FC, Barros RK, Feitosa FS, Toledo DO, Silva Junior JM, Ísola AM, et al. Fatores prognósticos em pacientes idosos admitidos em unidade de terapia intensiva. Rev Bras Ter Intensiva. 2009;21(3):255-261



Original Article

Prognostic factors in elderly patients admitted in the intensive care unit

Fatores prognósticos em pacientes idosos admitidos em unidade de terapia intensiva

Francine de Cristo SteinI, Raffaelle Kasprowicz BarrosI, Fernanda Seligman FeitosaI, Diogo Oliveira ToledoII, João Manoel da Silva JuniorII, Alexandre Marini ÍsolaII, Ederlon RezendeII

IResident Physician Intensive Care Service, Hospital do Servidor Público Estadual "Francisco Morato de Oliveira" - HSPE-FMO - São Paulo (SP), Brazil
IIPhysicians Intensive Care Service, Hospital do Servidor Público Estadual "Francisco Morato de Oliveira" - HSPE-FMO - São Paulo (SP), Brazil

Submitted on July 13, 2009
Accepted on September 14, 2009

Corresponding author:

Ederlon Rezende
Rua Pedro de Toledo, 1800 - 6º andar - Vila Clementino
CEP: 04039-901 - São Paulo (SP), Brazil
Phone/Fax: (11) 5088-8146
E-mail: [email protected]



Currently, aging of the population is a widespread global phenomenon. Therefore, the assessment of prognosis in elderly patients is needed. This study aims to identify risk factors in a population of elderly patients admitted in the intensive care unit
METHODS: A prospective study in the intensive care unit of a general tertiary hospital was carried out for five months. Patients with 65 years or more of age, who stayed in the intensive care unit for 24 hours or more were included and those at the-end-of-life, patients readmitted to intensive care unit during the same hospital stay were excluded.
RESULTS: In this study 199 patients were involved, with a mean age of 75.4±6.8 years, and 58.8% were female. Mortality was 57.3%. The mean APACHE II, SOFA, MODS and Katz index (assessment of daily activities) were respectively 20.0±5.8, 6.8±3.9, 2.4±1.9 and 5.3±1.6. Most patients were postoperative 59.3% and 41.6% were under invasive mechanical ventilation. At regression analysis, the independent determinants of higher mortality were: older age (76.9±6.7 years death versus 73.3±6.5 years discharge, P<0.001, OR=1.08, CI 95% 1.01-1. 16), the Katz index (4.9±1.9 deaths versus 5.7±0.9 discharge, p=0.001, OR=0.66, CI 95% 0.45-0.98), hyperglycemia (158.1±69.0 death versus 139.6±48.5 discharge p=0.041; OR=1.02; CI 95% 1.01-1.03) and need for mechanical ventilation at admission to the intensive care unit (57.0% death versus 20.5% discharge p <0.001, OR=3.57, CI 95% 1.24-10.3).
CONCLUSION: Elderly patients admitted to the intensive care unit that have difficulties in performing daily activities, hyperglycemia and who are under invasive mechanical ventilation had a worse hospital prognosis.

Keywords: Elderly; Intensive care units; Prognosis; Risk factors




Currently aging of the population is a prevailing global phenomenon. In the United States, the fastest growing segment of population includes those aged over 65 years. There, the number of people present in this group increased approximately 1000%, from 3.1 million in 1900 to 35 million in 2000.(1) In Brazil, a recent review of the Brazilian Institute of Geography and Statistics (IBGE) showed that in 2000, 30% of Brazilians were in the age bracket of up to 14 years, while those over 65 years of age accounted for 5% of the population. In a projection for 2050, these two age groups will be equal: each representing 18% of the overall Brazilian population.(2)

In intensive care units (ICU) of the U.S., the aged represent 42% to 52% of all admissions and almost 60% of all daily ICU charges.(3) Advanced age is associated with increased mortality in these patients.(4) However, studies in specific subgroups of the elderly have shown that mortality can range from 4.3% to 22.1% for patients more that 85 years old, admitted because of surgery, 15% to 25% for neurosurgical causes and 39 to 48% for medical clinical causes.(5,6) Therefore, age is not solely responsible for the lower survival, but also the individual's functional capacity prior to ICU admission and severity of the disease causing admission.(7)

Faced with aging, the body's functional reserves become reduced, with a decline of the cardiovascular, pulmonary and renal functions. In addition, there is a reduction of muscle mass and strength as well as loss of memory. These changes significantly impact the environment of the ICU, where, considering age alone, management of ventilatory and hemodynamic conditions would be difficult.(3)

A practice that has been introduced since 1981 with the publication of the Acute Physiology and Chronic Health Evaluation (APACHE),(8) is the assessment of severity and prognosis of patients admitted to ICU. Prognostic indices such as APACHE are assessment tools related to clinical outcome, laboratory and physiological changes that can orient care while providing parameters for clinical follow-up and patient prognosis.(9)

Since then, several studies have been conducted to obtain the best correlation between the prognostic index and the real outcome of these patients. Many other models and variables have been published and validated. However, little is known neither about the actual correlation of this data in geriatric patients, nor about the impact of cognitive and functional status prior to admission to the ICU.

Considering the need for assessment of prognosis in elderly patients in the ICU the purpose of this study was to identify risk factors in a population of elderly patients admitted to ICU.



After approval by the Ethics and Research Committee a prospective longitudinal study was conducted in general ICU of a tertiary hospital, from December 1, 2006 to April 30, 2007.

Patients aged 65 years or more, with a 24 hours or more stay in the ICU were included in the study. Patients at the end- of- life or at end-stage of chronic or neoplastic disease and those readmitted to ICU during the same hospital stay were excluded, that is to say, only the first admission was considered.

Demographic data of patients admitted and who met the inclusion criteria for this study were collected, also for calculation of prognostic scores, considering the worst results of the last 24 hours prior to inclusion in the study, found in the routine laboratory tests as part of the ICU care. Variables of perfusion, Basic Activities of Daily Living (Katz) index(10,11) and complications of stay , were also collected (Table 1).

Disease severity was assessed using the Acute Physiology and Chronic Health Evaluation II (APACHE II),(12) Sequential Organ Failure Assessment (SOFA),(13) Multiple Organ Dysfunction Score (MODS)(14) and KATZ (10,11) scores. Patients were followed until discharge or hospital death.

Data were expressed as mean ± standard deviation, median (25-75%) and percentages. Continuous variables with normal distribution were evaluated by parametric method Student's t test and categorical variables by Chi-square test. Patient characteristics and odds ratio (OR) and corresponding confidence intervals (CI) were calculated by stepwise logistic regression analysis to identify independent risk factors and control confusion effects.

Only the significant variables in univariate analysis were submitted to logistic regression. The addition of other variables that are considered important from a clinical point of view (e.g., length of hospital stay before ICU admission) would provide4 the model with many degrees of freedom and collinearities, which make the regression unstable. Thus, only variables with greater statistical power were considered in the model. That is why we decided to maintain in the regression only variables with significance in univariate analysis.

All significance probabilities (p values) presented were of the double-tailed type and values of less than 0.05 were considered statistically significant. Statistical analysis was performed using the SPSS (v13, Chicago, IL).



A total of 453 patients was admitted to the ICU during this period, 237 patients were older than 65 years, however only 199 patients participated in the study, 9 patients were considered at the-end-of-life , 3 were discharged before 24 hours of ICU and 26 patients readmitted were also excluded. The mean age was 75.4±6.8 years, 58.8% were female. Mortality in the ICU and hospital in this population was respectively 28.1% and 57.3% (Table 2).

At univariate analysis the variables that discriminated in-hospital mortality were age, clinical patients, emergency surgery, APACHE II, SOFA, MODS, Katz index, use of vasopressors, invasive mechanical ventilation, urine output, lower Glasgow score and blood glucose (Table 3).

At logistic regression, considering only the significant variables in univariate analysis, only age, Katz index, blood glucose and use of invasive mechanical ventilation independently discriminated hospital mortality (Table 4).

Regarding ICU mortality, it was noted that besides the Katz index and use of invasive mechanical ventilation, use of vasopressors (OR = 3.12, p = 0.015, CI = 1.24-7.83) and SOFA score (OR = 1. 12, p = 0.047, CI = 1. 04-1.28), were also independent factors of death in the ICU. Furthermore, age and blood glucose did not show the same statistical power when compared to hospital mortality. However, considering the short time of assessment when ICU mortality was analyzed, hospital outcome continued to be the main objective.



In this study the main risk factors associated with death of the elderly are related to their old age, Katz index, high blood glucose and need for invasive mechanical ventilation upon ICU admission.

In the present study higher hospital mortality was found than in the ICU. Among the elderly, chronic conditions tend to be more pronounced and in this phase, often occur simultaneously. Such conditions usually are not fatal; however they tend to significantly impair the quality of life of older people. In most cases, they may spur what might be called the disabling process, that is to say, the process by which a given condition (acute or chronic) affects the elderly functionality and, consequently, the performance of daily activities.(15) This fact that may have contributed to higher hospital mortality in relation to that in the ICU, therefore, these patients require greater care after discharge from the ICU, which may provide a worse hospital outcome.

Advanced age interferes with the prognosis, as shown in this study, some research shows advanced age as an important independent predictor of mortality.(16,17) Survival in the short term, of patients with more than 65 years of age is significantly lower than in the younger.(18) Finally, after discharge, deaths occur predominantly during the first three months.(18) As such, aging per se is a risk factor for mortality in the long-term, risk of death increases with the number of comorbidities, poor cognitive function and difficulty in performing routine activities.

Based upon these assumptions, that the assessment of capacity to perform routine activities can affect the evolution of elderly patients, this study showed that assessment of the Katz index was better than other scores to reach a prognosis in this population.

Katz et al. significantly demonstrated that recovery of functional performance of six activities considered basic in the daily life of elderly with disabilities (bathing, dressing, toileting, moving around, being continent and feeding himself) are biological and psychosocial primary functions.(19) Katz and Akpom(20) presented the classification of the Index by the number of functions in which the assessed individual is dependent. The ranking from 0, 1, 2, 3, 4, 5 or 6 reflects in a summarized manner, the number of areas of dependence.(20)

Many theories and measurement tools have been developed such as APACHE, SOFA and MODS, but in this analysis none of them was able to determine in-hospital mortality in the elderly patients. The APACHE II score was developed for the general population in intensive care and for not specific populations, elderly patients are poorly assessed by this score, because it provides high scores for the aged and for patients over 65 years of age the score is practically the same, changing just 01 point above 75 years of age.(12) For this reason, it may poorly evaluate a population over 65 years of age. On the other hand, the SOFA and MODS scores, only assess organ dysfunction and age is not included in these scores, furthermore they were developed for daily assessments, specifying the evolutionary tendency of patients are therefore not able to reach a hospital prognosis with a single assessment,(13,14) especially in an aged population that previously had presented impaired organs.

According to Katz et al., measures that appeared to be clinically reliable did not present the same reliability in their use, due to a vague or poorly defined terminology. Since they are not accurate, the information obtained with these tools is not adequate for prognosis and decision taking about treatment or care to be provided to the elderly.(19)

Moreover, it was observed in this study that in a population of elderly patients occurrence of hyperglycemia also is detrimental, recalling that in the elderly patients there is a high prevalence of sub-clinical arterial disease with potential cardiac and brain damage(21,22) reducing tolerance to hyperglycemia.(23,24)

Hyperglycemia is common in the extensive range of severe illnesses, regardless prior diagnosis of diabetes. This stress hyperglycemia was considered beneficial to ensure glucose supplementation as an energy source for organs that did not require insulin for glucose uptake, including the brain and the immune system. However, it now becomes clear that even a moderate hyperglycemia is related to unfavorable outcomes.(25)

Hyperglycemia has been identified as a risk factor for worse prognosis in many types of clinical observations including severe brain injury,(26) trauma,(27,28) myocardial infarction(29) and stroke.(30) Moderate levels of hyperglycemia occur even after ICU admission and were associated to substantial increase of death during hospital stay.(31)

Furthermore, this study showed that use of invasive mechanical ventilation was an important risk factor for death in this population. In 40 institutions of the United States and 36 from France, the proportion of patients over 65 years of age admitted to the ICU was 48% and 36% respectively.(32,33) In addition, the incidence of respiratory failure increases almost exponentially with increasing age.(34) The incidence of respiratory failure in patients over 65 years of age is two times higher than in the group of patients with 55 and 65 years of age and is three times higher than in younger patients.

Ray et al. evaluated a population of elderly patients with respiratory failure in the emergency wards, just as the present study evaluated in the ICU and found that 29% of the patients needed admission to the ICU within the first 24 hours and mortality rates were higher in other patients. Since, the PaCO2, the creatinine clearance, increased levels of natriuretic peptides and the presence of paradoxical breathing were independent variables associated with death.(35)

Thus, greater importance should be given to elderly patients who have difficulties in daily activities, hyperglycemia and are under invasive mechanical ventilation.

However, there are noteworthy limitations in this study such as an observational study which can provide bias in patient selection, for example, the fact that the vast majority were high risk surgical patients. In addition, the study was conducted in a single hospital, a fact that hinders definitive conclusions on the subject, nevertheless calculations show enough statistical power in the study. In addition, complementary data were missing in the analysis such as previous diseases associated to the cause of ICU admission and specific type of surgeries, however the number of scores involved in the analyses has the power to determine severity of the patients studied.

Thus, further studies with adequate designs are required to confirm the findings of this research.



Follow-up of elderly patients requiring admission to the ICU requires new prognostic models aiming to correcting errors and improve performance of the service, and the Katz index was an important discriminator for poor outcome in this population. Furthermore, hyperglycemia and mechanical ventilation are risky in these patients and must be monitored and reversed as soon as possible.



1. US Census Bureau: Population Projections of the United States by Age, Sex, Race, Hispanic Origin and Nativity: 1999 to 2100. Washington: US Census Bureau; 2000.

2. Instituto Brasileiro de Geografia e Estatística - IBGE. Projeção da População do Brasil por sexo e idade: 1980- 2050. Revisão 2004.

3. Marik PE. Management of the critically ill geriatric patient. Crit Care Med. 2006;34(9 Suppl):S176-82.

4. Wood KA, Ely EW. What does it mean to be critically ill and elderly? Curr Opin Crit Care. 2003;9(4):316-20.

5. Van Den Noortgate N, Vogelaers D, Afschrift M, Colardyn F. Intensive care for very elderly patients: outcome and risk factors for in-hospital mortality. Age Ageing. 1999;28(3):253-6.

6. Nierman DM, Schechter CB, Cannon LM, Meier DE. Outcome prediction model for very elderly critically ill patients. Crit Care Med. 2001;29(10):1853-9.

7. de Rooij SE, Abu-Hanna A, Levi M, de Jonge E. Factors that predict outcome of intensive care treatment in very elderly patients: a review. Crit Care. 2005;9(4):R307-14.

8. Knaus WA, Zimmerman JE, Wagner DP, Draper EA, Lawrence DE. APACHE-acute physiology and chronic health evaluation: a physiologically based classification system. Crit Care Med. 1981;9(8):591-7.

9. Szostak M. Solução tecnológica para medição e avaliação de índices prognósticos [dissertação]. Curitiba: Pontifícia Universidade Católica do Paraná; 2005.

10. Katz S, Downs TD, Cash HR, Grotz RC. Progress in the development of the index of ADL. Gerontologist. 1970;10(1):20-30.

11. Katz S, Ford AB, Moskowitz RW, Jackson BA, Jaffe MW. Studies of illness in the aged. The index of ADL: a standardized measure of biological ans psychosocial function. JAMA. 1963;185(12):914-9.

12. Knaus WA, Draper EA, Wagner DP, Zimmerman JE. APACHE II: a severity of disease classification system. Crit Care Med. 1985;13(10):818-29.

13. Vincent JL, de Mendonca A, Cantraine F, Moreno R, Takala J, Suter PM, et al. Use of the SOFA score to assess the incidence of organ dysfunction/failure in intensive care units: results of a multicenter, prospective study. Working group on "sepsis-related problems" of the European Society of Intensive Care Medicine. Crit Care Med. 1998;26(11):1793-800.

14. Marshall JC, Cook DJ, Christou NV, Bernard GR, Sprung CL, Sibbald WJ. Multiple organ dysfunction score: a reliable descriptor of a complex clinical outcome. Crit Care Med. 1995;23(10):1638-52.

15. Verbrugge LM, Jette AM. The disablement process. Soc Sci Med. 1994;38(1):1-14.

16. Angus DC, Linde-Zwirble WT, Lidicker J, Clermont G, Carcillo J, Pinsky MR. Epidemiology of severe sepsis in the United States: analysis of incidence, outcome, and associated costs of care. Crit Care Med. 2001;29(7):1303-10.

17. Rezende E, Silva JM Jr, Isola AM, Campos EV, Amendola CP, Almeida SL. Epidemiology of severe sepsis in the emergency department and difficulties in the initial assistance. Clinics (Sao Paulo). 2008;63(4):457-64.

18. Somme D, Maillet JM, Gisselbrecht M, Novara A, Ract C, Fagon JY. Critically ill old and the oldest-old patients in intensive care: short-and long-term outcomes. Intensive Care Med. 2003;29(12):2137-43.

19. Katz S, Stroud MW 3rd. Functional assessment in geriatrics. A review of progress and directions. J Am Geriatr Soc. 1989;37(3):267-71.

20. Katz S, Akpom CA. A measure of primary sociobiological functions. Int J Health Serv. 1976;6(3):493-508.

21. Chaitman BR, Bourassa MG, Davis K, Rogers WJ, Tyras DH, Berger R, et al. Angiographic prevalence of high-risk coronary artery disease in patient subsets (CASS). Circulation. 1981;64(2):360-7.

22. Hubbard BL, Gibbons RJ, Lapeyre AC 3rd, Zinsmeister AR, Clements IP. Identification of severe coronary artery disease using simple clinical parameters. Arch Intern Med. 1992;152(2):309-12.

23. Levy PS, Kim SJ, Eckel PK, Chavez R, Ismail EF, Gould SA, et al. Limit to cardiac compensation during acute isovolemic hemodilution: influence of coronary stenosis. Am J Physiol. 1993;265(1 Pt 2):H340-9.

24. Levy PS, Chavez RP, Crystal GJ, Kim SJ, Eckel PK, Sehgal LR, et al. Oxygen extraction ratio: a valid indicator of transfusion need in limited coronary vascular reserve? J Trauma. 1992;32(6):769-73; discussion 773-4.

25. Mebis L, Gunst J, Langouche L, Vanhorebeek I, Van den Berghe G. Indication and practical use of intensive insulin therapy in the critically ill. Curr Opin Crit Care. 2007;13(4):392-8.

26. Rovlias A, Kotsou S. The influence of hyperglycemia on neurological outcome in patients with severe head injury. Neurosurgery. 2000;46(2):335-42; discussion 342-3.

27. Yendamuri S, Fulda GJ, Tinkoff GH. Admission hyperglycemia as a prognostic indicator in trauma. J Trauma. 2003;55(1):33-8.

28. Bochicchio GV, Sung J, Joshi M, Bochicchio K, Johnson SB, Meyer W, Scalea TM. Persistent hyperglycemia is predictive of outcome in critically ill trauma patients. J Trauma. 2005;58(5):921-4. Erratum in: J Trauma. 2005;59(5):1277-8.

29. Capes SE, Hunt D, Malmberg K, Gerstein HC. Stress hyperglycaemia and increased risk of death after myocardial infarction in patients with and without diabetes: a systematic overview. Lancet. 2000;355(9206):773-8.

30. Capes SE, Hunt D, Malmberg K, Pathak P, Gerstein H. Stress hyperglycemia and prognosis of stroke in nondiabetic and diabetic patients: a systematic overview. Stroke. 2001;32(10):2426-32.

31. Krinsley JS. Association between hyperglycemia and increased hospital mortality in a heterogeneous population of critically ill patients. Mayo Clin Proc. 2003;78(12):1471-8.

32. Yu W, Ash AS, Levinsky NG, Moskowitz MA. Intensive care unit use and mortality in the elderly. J Gen Intern Med. 2000;15(2):97-102.

33. Boumendil A, Aegerter P, Guidet B; CUB-Rea Network. Treatment intensity and outcome of patients aged 80 and older in intensive care units: a multicenter matched-cohort study. J Am Geriatr Soc. 2005;53(1):88-93.

34. Behrendt CE. Acute respiratory failure in the United States: incidence and 31-day survival. Chest. 2000;118(4):1100-5.

35. Ray P, Birolleau S, Lefort Y, Becquemin MH, Beigelman C, Isnard R, et al. Acute respiratory failure in the elderly: etiology, emergency diagnosis and prognosis. Crit Care. 2006;10(3):R82.



Received from the Intensive Care Service of the Hospital do Servidor Público Estadual "Francisco Morato de Oliveira" - HSPE-FMO - São Paulo (SP), Brazil.



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