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Table of Contents
ORIGINAL ARTICLE
Year : 2015  |  Volume : 5  |  Issue : 3  |  Page : 144-148

Prognosis of critical surgical patients depending on the duration of stay in the ICU


1 Department of Intensive Care, Hospital Universitario Insular de Gran Canaria, Las Palmas, Spain
2 Department of General Surgery and Digestive System, Hospital Universitario Insular de Gran Canaria, Las Palmas, Spain
3 University of Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Las Palmas, Spain

Date of Web Publication10-Sep-2015

Correspondence Address:
Luciano Santana-Cabrera
Avenida Marítima del Sur, s/n. Las Palmas de Gran Canaria, Canary Islands-35016
Spain
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/2229-5151.164919

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   Abstract 

Objective: To analyze the epidemiological and prognostic differences between critical surgical patients admitted to intensive care unit (ICU) according to length of stay in the ICU.
Materials and Methods: Retrospective observational study on patients with surgical pathology admitted to ICU of a tertiary hospital, during 7 years, with a stay ≥ 5 days. The variables analyzed were age, sex, Acute Physiology and Chronic Health Evaluation II (APACHE II), duration of stay, hospital and ICU mortality, original service, reason for admission, geographical place of residence, and the use of invasive techniques such as mechanical ventilation (MV), tracheotomy, and techniques of continuous renal replacement (CRR). Two groups were defined; one with intermediate stay, the one that exceeds the average of our population (> 5 days) and another with long stay patients (> 14 days). Readmissions were excluded. Firstly, the analysis of differential characteristics of patients was performed, this was according to the duration of their stay using either a contrast equal averages when the variable contrast between the two groups was quantitative or the Chi-square test when the variable analyzed was qualitative. For both tests, the existence of significant differences between groups was considered when the significance level was less than 5%. And, secondly, a model forecast ICU survival of these patients, regardless of length of stay in ICU, using a binary logistic regression analysis was performed.
Results: Among the 540 patients analyzed, no significant differences were observed, depending on the length of stay in the ICU, except the need for invasive techniques such as MV or tracheotomy in those of longer stay (P = 0.000). However, ICU mortality was significantly higher for patients with intermediate stay (30 vs 17: 5%; P = 0.000), without observing differences in hospital mortality. ICU survival was influenced by age, APACHE II levels, admission to the ICU in a coma state, and the application of the three invasive techniques discussed.
Conclusion: Surgical patients who survive in the ICU, regardless of the length of their stay in it, have the same odds of hospital survival. Found as predictors of mortality in ICU APACHE II, age, admission in a coma state, and application of invasive techniques.

Keywords: Critical illness, prognosis, stay, surgery


How to cite this article:
Santana-Cabrera L, Martin-Santana JD, Lorenzo-Torrent R, Perez HR, Sanchez-Palacios M, Hernandez JR. Prognosis of critical surgical patients depending on the duration of stay in the ICU. Int J Crit Illn Inj Sci 2015;5:144-8

How to cite this URL:
Santana-Cabrera L, Martin-Santana JD, Lorenzo-Torrent R, Perez HR, Sanchez-Palacios M, Hernandez JR. Prognosis of critical surgical patients depending on the duration of stay in the ICU. Int J Crit Illn Inj Sci [serial online] 2015 [cited 2021 Aug 2];5:144-8. Available from: https://www.ijciis.org/text.asp?2015/5/3/144/164919


   Introduction Top


For critical surgical patients, organ failure is the leading cause of admission to intensive care unit (ICU); it is what will determine the length of their stay and, of course, the prognosis. [1],[2],[3],[4] This organ failure usually results from specific presurgical and postsurgical complications such as sepsis or systemic inflammatory response syndrome associated with underlying disease requiring surgery. These patients will need an organic carrier such as mechanical ventilation (MV), continuous renal replacement (CRR), or the use of catecholamines. The needs of these therapies for a long time will increase, as is logical, the ICU stay and its costs. [5],[6] It is, therefore, interesting to identify what factors influence or determine a more or less prolonged ICU stay in surgical patients, and to predict based on a number of factors, survival of these patients in ICU. On this basis, we establish the objective to analyze the epidemiological and prognostic differences between surgical patients admitted to intensive care unit (ICU) with intermediate stay (5-13 days) versus prolonged stay (> 14 days).


   Materials and methods Top


Observational retrospective study of patients with surgical pathology admitted to the ICU of a tertiary hospital from January 2004 to December 2010, with ≥ 5 days stay. The number of patients with these characteristics was 540. The variables analyzed were age, sex, Acute Physiology and Chronic Health Evaluation II (APACHE II), duration of stay, hospital and ICU mortality, original service, reason for admission, geographical place of residence, and the use of invasive techniques such as MV, tracheotomy, and techniques of CRR. Two groups were defined, one with intermediate ICU stay, that is, all that exceeds our population average, which is > 5 days but less than 14 days, based on the average stay of the population studied is 5.6 days and the 75 percentile is in 5 days. Also, prolonged stay was defined as one that was ≥ 14 days, serving most of the studies cited in the literature review that addressed the analysis of prolonged stay. [7] Readmissions were excluded to avoid multiple prognostic assessments of the same patient and, in the long-term prognostic study, the visitors for failure to keep track of them due to the fact that they return to their place of origin.

SPSS version 15.0 software was used as a tool for analysis. Firstly, an analysis of the differential characteristics of patients according to the duration of their stay using either a contrast equal averages, when the variable to compare between the two groups (intermediate stay vs prolonged stay) was quantitative or Chi-square test, when the variable analyzed was qualitative. For both tests, the existence of significant differences between groups was considered when the significance level was less than 5%. Secondly, a predictive model of survival in the ICU of these patients, regardless of length of stay in the ICU, was performed by analyzing binary logistic regression, using as a method of building block model, not proceeding therefore, a definition of the introduction rule or output variables in the model. However, the maximum likelihood model was chosen.


   Results Top


During the study period, from 2004 to 2010 inclusive, 6,069 patients were admitted to the ICU, of who 1,906 (31.4%) were surgical, and 540 (28.33%) of those required a stay over 5 days, which is the study population of the present study. To meet the objectives of this study, firstly, an analysis of differences in personal, clinical, and prognosis characteristics of surgical patients based on length of stay (intermediate vs prolonged) was done. The results are shown in [Table 1], where no significant differences were observed in the majority of variables analyzed. However, statistical differences in the hospital stay, and the need for MV and tracheotomy were observed with the group of prolonged ICU stay, which showed higher levels in these three variables.
Table 1: Differences in personal, clinical, and prognosis characteristics of surgical patients based on length of stay (intermediate vs prolonged)

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Therefore, it can be said that longer duration of stay entails a greater need for invasive techniques. Nevertheless, it is noted that ICU mortality was significantly higher in patients of intermediate stay compared to those of prolonged stay (30 and 17.5%, respectively); the occurrence is not same with hospital mortality. Finally we proceeded to estimate a logistic regression model aimed at predicting survival in surgical ICU patients with intermediate or prolonged stay, although altogether to avoid very small samples that lead to unreliable results.

In this logistic regression model, the ICU survival was used as the dependent variable, and as independent variables those available in the database and that could, according to the literature reviewed, affect patient survival, such as: Length of stay before ICU admission (pre-ICU), APACHE II, age, days of MV, and days of CRR as quantitative variables; and gender and reason for admission as qualitative variables. The gender and the need for tracheotomy have dichotomous character, not being necessary its recodification, although positive values (value 1) corresponded to the man and need to perform a tracheotomy categories.

As to the reason for admission variable, only the four most frequent reasons (monitoring, acute respiratory failure, coma, and septic shock) were considered, proceeding to create four dichotomous variables, which are the ones that were included in the model. The results of this regression analysis for surgical patients [Table 2] show that the factors that best define survival, introducing the Wald statistic levels above or very close to 5% significance, are the APACHE II, age, having entered in a coma state, and the use of the three invasive techniques discussed. Thus, surgical patients with intermediate or long stay in the ICU will have better prognosis when they have low APACHE II levels, younger age, do not enter in the ICU in a coma state, requiring fewer days of MV and CRR, and finally, if a tracheotomy has been performed.
Table 2: Logistic regression model aimed at predicting survival in surgical ICU patients with intermediate or prolonged stay

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The predictive nature of both APACHE II and age might be, at first, due to the relationship between both factors (r = 0.398, P = 0.000); this is, from the existence of multicollinearity. Therefore, we proceeded to make two logistic regression analyses with the same variables except the APACHE II and the age. The results of both analyzes showed that both the APACHE II (Wald = 27.172, P = 0.000) and age (Wald = 25.784, P = 0.000) were still two significant predictors of survival. With this model it is able to predict with 93.8% of accuracy the survival of the group of patients who were discharged alive from the ICU; but it is not possible to predict the survival of the group who died (25.8%). In statistical terms, this means that the model is able to correctly predict 77.3% of surgical patients with intermediate or long stay. Likewise, the model presents a Nagelkerke R 2 , which measures the overall fit of the model, of 0.275 and a Hosmer and Lemeshow value, which measures the correspondence of actual and predicted values of the dependent variable, of 15.266, which it is not significant at a 5% level; indicating an adequate model adjustment. [Figure 1] shows the receiver operating characteristic (ROC) curve for the previous logistic regression model, where the area under the curve is 0.794, indicating that the predictive model has quite acceptable discrimination ability, if it has a value higher than 0.50.
Figure 1: Receiver operating characteristic (ROC) curve

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   Discussion Top


From the results of our study, we can conclude that patients who survive in the ICU, regardless of their length of stay, have the same chances of survival (>85%). This fact has already been observed by other authors, such as Weiler et al., where they saw that their postoperative patients from major abdominal and thoracic surgery and who spent more days in the ICU had similar chances of survival than those who remained least. [8]

In the survival analysis, we found that surgical patients with intermediate or long stay in the ICU will have a better prognosis when they have low APACHE II at admission, younger age, have not entered in a coma state, fewer days of MV, and CRR requirements, and finally, that a tracheotomy have been performed. The fact that tracheotomy affects the prognosis of patients in the long-term can only be checked when large-scale randomized controlled studies is carried. We might have missed, in the present study, factors associated with the decision to perform a tracheostomy that might alter outcomes, as weaning failure, nosocomial pneumonia, etc.

The APACHE II prognostic index has been widely used to evaluate the prognosis of critically-ill patients and our results agree with those reported by other authors, which have pointed it out as an index, with high sensitivity and specificity that can predict prognosis and death risk in critically ill patients, either medical or surgical. [9]

In relation to the CRR, there is no evidence on the impact of the use of CRR on mortality in this group of patients because, traditionally, most studies in critically-ill patients with acute renal failure have focused on short-term outcomes, often associated with hospital discharge, being only a few who describe the long-term evolution. [10],[11],[12]

In our study population, more than 90% of patients required MV, which indicates that respiratory failure is a very important prognostic factor in these types of patients. Acute respiratory failure in surgical patients is closely related with an increase in mortality. Some researches refer that patients who required MV, mortality may exceed 40%. [13]

As for the limitations of our work, one of them is that being realized at a single center, also as a tertiary hospital is a reference for others, extrapolation of some of our results to other ICUs is not always possible, since they depend on the similarity of these with the one studied. For example, our results do not apply to health systems possessing intermediate care or other chronic ventilator type units which can evacuate patients with consequent positive impact on the average stay of patients.

There is also another factor that we have not taken into account is the treatment limitation carried out, which is subjected to many variations that will depend not only on clinical judgment but also on their family. Also, given the fact that we started from a base created in "RSIGMA" (Integrated Management and Administrative Modernization System), even before 2004, we did not have more severity indicators other than Sequential Organ Failure Assessment (SOFA).

Another fact that should not be overlooked is that the sample comes from a period of 7 years, when the praxis indicates that every 5 years changes in healthcare happen, whether in technical, pharmacological, organizational aspects, etc., which can modify, by themselves, the results of patient care. To the extent that this aspect can affect the results, we believe that it should be considered as a limitation itself of the proper work.

Other factors that we have not taken into account when conducting this study is the previous quality of life or after suffering a prolonged stay in the ICU. Many studies have shown that the quality of life of the patients who survived is very good. [13],[14],[15],[16]

Finally, the ICU patients have a moderate-to-severe degree of malnutrition and it has been shown that this degree of malnutrition has a significant negative impact on clinical outcome, factor that we have not taken into account when conducting this study. [17]

In conclusion, surgical patients that survive in the ICU, regardless of their length of stay; have the same odds of hospital survival. Furthermore, only APACHE II, age, entering in a coma state, and the necessity of applying invasive techniques were demonstrated as predictors of mortality in the ICU.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.

 
   References Top

1.
Barie PS, Hydo LJ, Fischer E. Utility of illness severity scoring for prediction of prolonged surgical critical care. J Trauma 1996;40:513-8.  Back to cited text no. 1
    
2.
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3.
Vincent JL, de Mendonca A, Cantraine F, Moreno R, Takala J, Suter PM, et al. Use of 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;26:1793-800.  Back to cited text no. 3
    
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Fertmann J, Wolf H, Kuchenhoff H, Hofner B, Jauch KW, Hartl WH. Prognostic factors in critically ill surgical patients requiring continuous renal replacement therapy. J Nephrol 2008;21:909-18.  Back to cited text no. 6
    
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Heyland DK, Konopad E, Noseworthy TW, Johnston R, Gafni A. Is it ′worthwhile′ to continue treating patients with a prolonged stay (> 14 days) in the ICU? An economic evaluation. Chest 1998;114:192-8.  Back to cited text no. 7
    
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Weiler N, Waldmann J, Bartsch DK, Rolfes C, Fendrich V. Outcome in patients with long-term treatment in a surgical intensive care unit. Langenbecks Arch Surg 2012;397:995-9.  Back to cited text no. 8
    
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Barie PS, Hydo LJ, Fischer E. Comparison of APACHE II and III scoring systems for mortality prediction in critical surgical illness. Arch Surg 1995;130:77-82.  Back to cited text no. 9
    
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Bagshaw SM, Mortis G, Doig CJ, Godinez-Luna T, Fick GH, Laupland KB. One-year mortality in critically ill patients by severity of kidney dysfunction: A population-based assessment. Am J Kidney Dis 2006;48:402-9.  Back to cited text no. 10
    
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Schiffl H, Fischer R. Five-year outcomes of severe acute kidney injury requiring renal replacement therapy. Nephrol Dial Transplant 2008;23:2235-41.  Back to cited text no. 11
    
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Korkeila M, Ruokonen E, Takala J. Costs of care, long-term prognosis and quality of life in patients requiring renal replacement therapy during intensive care. Intensive Care Med 2000;26:1824-31.  Back to cited text no. 12
    
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Forrest JB, Rehder K, Cahalon MK, Goldsmith CH. Multicenter study of general anesthesia: III. Predictors of severe perioperative adverse outcomes. Anesthesiology 1992;76:3-15.  Back to cited text no. 13
    
14.
Isgro F, Skuras JA, Kiessling AH, Lehmann A, Saggau W. Survival and quality of life after a long-term intensive care stay. Thorac Cardiovasc Surg 2002;50:95-9.  Back to cited text no. 14
    
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Niskanen M, Ruokonen E, Takala J, Rissanen P, Kari A. Quality of life after prolonged intensive care. Crit Care Med 1999;27:1132-9.  Back to cited text no. 15
    
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Trouillet JL, Scheimberg A, Vuagnat A, Fagon JY, Chastre J, Gibert C. Long-term outcome and quality of life of patients requiring multidisciplinary intensive care unit admission after cardiac operations. J Thorac Cardiovasc Surg 1996;112:926-34.  Back to cited text no. 16
    
17.
Gharsallah H, Hajjej Z, Naas I, Aouni Z, Stambouli N, Labbène I, et al. Assessment of nutritional status and prognosis in surgical intensive care unit: The prognostic and inflammatory nutritional index (PINI). Int J Nutr Food Sci 2014;3:477-83.  Back to cited text no. 17
    


    Figures

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    Tables

  [Table 1], [Table 2]



 

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