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(Chest. 2005;127:598-603.)
© 2005 American College of Chest Physicians

Shock on Admission Day Is the Best Predictor of Prolonged Mechanical Ventilation in the ICU*

Elisa Estenssoro, MD; Francisco González, MD; Enrique Laffaire, MD; Héctor Canales, MD; Gabriela Sáenz, MD; Rosa Reina, MD and Arnaldo Dubin, MD

* From Servicio de Terapia Intensiva, Hospital Interzonal General de Agudos San Martín. La Plata, Buenos Aires, Argentina.

Correspondence to: Elisa Estenssoro, MD, Calle 42 No. 577, 1900 La Plata, Buenos Aires, Argentina; e-mail: elisaestenssoro{at}speedy.com.ar


   Abstract
TOP
 Abstract
Introduction
 Materials and Methods
 Results
 Discussion
 References
 
Study objectives: To determine the incidence of prolonged mechanical ventilation (PMV), which is associated with increased health-care costs and risks of adverse events, and to identify its early predictors.

Design: Retrospective cohort.

Setting: A medical-surgical ICU in a university-affiliated hospital.

Patients or participants: All patients admitted to the ICU over 3 years who received mechanical ventilation (MV) for > 12 h.

Interventions: None.

Measurements: PMV was defined as MV lasting > 21 days. We recorded epidemiologic data, severity scores, worst PaO2/fraction of inspired oxygen (FIO2), presence of shock on ICU admission day, cause for MV, length of MV, ICU length of stay (LOS), and hospital LOS. PMV patients were compared to patients weaned before 21 days (non-PMV group) to determine predictors of PMV.

Results: Of 551 hospital admissions, 319 patients (58%) required MV > 12 h. One hundred thirty patients died early and were excluded. Seventy-nine patients (14%) required PMV. The non-PMV group consisted of 110 patients. Simplified acute physiology score (SAPS) II, APACHE (acute physiology and chronic health evaluation) II, therapeutic intervention scoring system, PaO2/FIO2, shock, ICU LOS, and hospital LOS differed significantly between groups. However, logistic regression identified shock on ICU admission day as the only independent predictor of PMV (odds ratio, 3.10; p = 0.001). SAPS II and PaO2/FIO2 had the nearest coefficients and were used to build the predictive model. Sensitivity analysis was performed including the 130 patients who died early, and shock remained the most powerful predictor.

Conclusions: PMV was a frequent event in this cohort. The presence of shock on ICU admission day was the only prognostic factor, even adjusting for severity of illness and hypoxemia.

Key Words: duration • intensive care • long-term outcomes • mechanical ventilation • prediction • shock


   Introduction
TOP
 Abstract
 Introduction
Materials and Methods
 Results
 Discussion
 References
 
Prolonged mechanical ventilation (PMV) can increase mechanical ventilation (MV) morbidity and costs.1 Although many definitions of PMV are available, most experts use the one provided by the Health Care Financing Administration (now the Center for Medicare and Medicaid Services), which characterizes PMV as MV lasting for > 21 days.12 Up to 7 to 15% of patients may become ventilator dependent in the ICU.3 These figures are expected to increase, since more patients with complex diseases survive due to advances in resuscitation techniques, MV protocols, metabolic control, and treatment of sepsis.4567

PMV patients account for > 37% of ICU costs.8 Estimation of the incidence of PMV could help allocate health-care resources more efficiently, allowing to rationally plan the number of long-term acute care facilities where weaning of chronic, critically ill patients is performed at lower costs.9 In addition, recognizing the early predictive factors of PMV also allows their prompt correction. Therefore, we performed this study to answer two questions: what is the incidence of PMV in our ICU, and which variables during the first 24 h in the ICU predict PMV?


   Materials and Methods
TOP
 Abstract
 Introduction
 Materials and Methods
Results
 Discussion
 References
 
This retrospective cohort study took place in an eight-bed, mixed medical-surgical ICU in a university-affiliated hospital in La Plata, Buenos Aires, Argentina. Patients were admitted to the hospital from November 1, 1999, to October 31, 2002, and received MV for > 12 h. Patients were included only if intubation was performed in our ICU or in the operative room within a few hours after ICU admission. All data on these patients were prospectively collected as part of our ICU database.

On the day of ICU admission, we recorded age, gender, severity-of-illness scores (APACHE [acute physiology and chronic health evaluation] II, simplified acute physiology score [SAPS] II), comorbidities (McCabe score), level of interventions during the first day (therapeutic intervention scoring system), and presence of shock. Shock was defined as systolic BP < 90 mm Hg or a reduction of > 40 mm Hg of systolic BP from baseline despite adequate fluid resuscitation, along with presence of perfusion abnormalities that might include oliguria, lactic acidosis, or acute altered mental status.10 We also registered underlying diagnoses and causes for initiation of MV. These last were considered as postoperative ventilation, hemodynamic, respiratory, and neurologic disorders.11

At ICU discharge, the day of tracheostomy, length of MV, ICU length of stay (LOS), and hospital LOS (in days) were recorded. In-hospital mortality was considered. The main outcome measure was the occurrence of PMV, defined as MV lasting > 21 days.12 Effective days of MV were considered, whether continuous or with interruptions. Days of failed weaning were included in the total sum.

Data Analysis
Patients with PMV were compared to patients surviving 21 days after ICU admission who were no longer receiving MV (non-PMV group). In the non-PMV group, patients who died before 21 days (early death group) were excluded from our main comparison, since they were not able to reach the primary outcome measure, which requires 21 days of survival. Nevertheless, to avoid selection bias, epidemiologic and severity-of-illness data of the early death group are also presented and compared to those of the PMV and non-PMV groups.

Continuous variables of parametric distribution were analyzed with one-way analysis of variance, and nonparametric continuous data were analyzed with the Kruskal-Wallis test. If the result of any test was p < 0.05, a t test or Mann-Whitney test adjusted for multiple comparisons were performed to identify differences between groups. {chi}2 was used for categorical data, with values adjusted for multiple comparisons.

We explored differences of variables that could act as possible PMV predictors in PMV and non-PMV groups. Variables presenting significant differences between groups (p < 0.10) were entered in stepwise logistic regression analysis, with the presence of PMV as the dependent variable. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated. A predictive model of PMV was constructed with the first two thirds of patients (developmental sample) and validated in the remaining third (validation sample).

The Hosmer-Lemeshow goodness-of-fit test was performed on the developmental and validation sample to evaluate model calibration. This test compares observed with predicted mortality, and p > 0.1 indicates a good agreement between them.12

A sensitivity analysis was conducted for each of the variables of the predictive model, to assess the behavior of the model when the patients who died before 21 days were included in the PMV group. We assigned to these early death patients the worst outcome of our study, the evolution to PMV (21 days of MV). Using this new grouping of patients, we rebuilt the regression model. Statistical analysis was performed with statistical software (Stata 7.0; Stata Corporation; College Station, TX).


   Results
TOP
 Abstract
 Introduction
 Materials and Methods
 Results
Discussion
 References
 
During the 3 years of our study, 551 patients were admitted to the ICU. Their mean age was 41 ± 17 years (± SD); 53% were men. Mean APACHE II and SAPS II scores were 18 ± 9 and 32 ± 18, respectively. The expected mortality rates were 31% and 28%, respectively, and the observed mortality rate was 31%.

Of the entire cohort, 348 patients (63%) received MV, and 319 patients (58%) received MV for > 12 h. Median length of MV was 7 days (interquartile range [IQR], 2 to 19 days). One hundred thirty patients died before day 21 (early death group). Of the 189 patients who survived at day 21, 110 patients had been weaned and most of them were discharged from the ICU (non-PMV group), while 79 patients were still receiving MV (PMV group). Epidemiologic, severity-of-illness, and main physiologic variables; length of MV; ICU LOS; hospital LOS; general causes of admission to the ICU; causes of initiation of MV; and underlying diagnoses of the three groups are displayed in Tables 123 .


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  		Table 1.. General Characteristics of the Groups*

 

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  		Table 2.. Causes of Initiation of MV*

 

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  		Table 3.. Underlying Clinical Diagnoses*

 
The PMV group represented 14% of ICU admissions. Survival and discharge from the ICU of this population was 73%. Mean time for tracheostomy was 15 ± 5 days (± SD), and median time was 16 days (IQR, 12 to 21 days). Fifty-four PMV patients (68%) received MV for > 30 days, and 8 patients (10%) received MV for > 90 days (mean, 136 ± 53 days). Half of these last eight patients could be weaned and discharged from the ICU.

Early death patients were older and had significantly higher acuity scores and comorbidities than PMV patients. However, physiologic alterations, assessed by PaO2/fraction of inspired oxygen (FIO2) and presence of shock, were similar in both groups. The intensity of treatment did not differ.

PMV patients were significantly sicker than non-PMV patients, according to severity-of-illness scores. The most striking difference with non-PMV patients resided in the incidence of shock on ICU admission day. They were also more hypoxemic and had more interventions during the first 24 h. Multiple trauma (excluding cranial trauma) and neuromuscular illnesses were significantly more frequent in the PMV group, although the number of patients in this last category was small.

When all significant variables were entered in a stepwise multiple logistic regression analysis, the only ones that remained significant were shock on ICU admission day or persistence of shock beyond day 3 (they must exclude each other because of co-linearity). Hence, of the tested variables, they separately acted as single independent predictors of PMV. SAPS II and PaO2/FIO2 had the nearest coefficients and were used to design the multivariable model. Since shock on ICU admission day and persistence of shock beyond day 3 acted as strong predictors of PMV, we chose the earliest predictor to build the regression model (Table 4 ). Values for persistence of shock beyond day 3 were as follows: OR, 5.96; 95% CI, 1.51 to 15.12; p < 0.001. We used the Hosmer-Lemeshow test to assess the goodness of fit of the developmental sample of the model (n = 126) on the validation sample (n = 63); p values were > 0.1 for both, which reflected an adequate fit between them.


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  		Table 4.. Multiple Logistic Regression Model With ORs for PMV

 
We tested the validity of shock on ICU admission day as predictor of PMV by a sensitivity analysis. We assigned the 130 patients who died before day 21 to the PMV group, and rebuilt the regression model. The result of the sensitivity analysis was the same: shock remained as the most important prognostic factor for PMV (Table 5 ).


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  		Table 5.. Multiple Logistic Regression Model With ORs for PMV*

 

   Discussion
TOP
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
References
 
As critical care is acutely directed at reversing a life-threatening condition, mortality is considered to be the primary outcome measure. However, morbidity outcomes also are relevant to patients, their families, health-care providers, and society as a whole. Recently, the importance of patient-centered outcomes has been emphasized, and long-term outcomes are considered important measurements.1314 The duration of MV, which is an indicator of serious health complications and significantly affects health-care costs, is thus a valid measure for research.1516

The need to predict the length of MV has long been recognized as important,17 and mathematical equations have been designed and applied to such predictions.18 Additionally, the analysis of observed vs predicted days of MV in a single unit has been proposed as a tool for quality improvement.31819

It seems logical to assume, however, that qualitative approaches that consider possible prognostic factors for PMV might also be useful. This information can aid in the design of trials that assess ventilation and weaning protocols, in planning the timing of tracheostomy,1117 and in providing information and counseling to patients and to their families.

We found circulatory impairment on ICU admission day as the main determinant of PMV, in contrast to other studies2021 that have evaluated PMV predictors. Our results are consistent with other mortality studies in which shock was associated with an increased risk of death. For instance, if shock develops, mortality in sepsis and in acute lung injury/ARDS increases.2021 However, the effects of shock on long-term sequelae have not been so thoroughly analyzed. A well-known cause of neuromuscular weakness and PMV in the ICU is critical illness polyneuropathy and myopathy (CIPNM). CIPNM has usually been linked to microcirculatory alterations causing nerve ischemia14 and to sepsis.22 The need of vasopressors for > 3 days, a marker of shock, has been shown as an independent predictor of CIPNM in critically ill patients.6 We also tested the hypothesis that the duration of shock (and not presence on ICU admission) was the true independent predictor of PMV, but we found that persistence of shock beyond day 3 offered no predictive advantage over shock on ICU admission.

We did not assess neuromuscular function by electromyography in all PMV patients, but it is possible that many of them acquired CIPNM. When prospectively looked for, CIPNM was found in 33% of critically ill patients.22 This figure increases to 72% in patients at high risk for CIPNM, those with systemic inflammatory response syndrome and a high APACHE III score.23

Our results for predictors of PMV did not match those described by other investigators, probably due to the characteristics of our cohort. Surprisingly, age, a usual prognostic factor of mortality and complications in the critically ill, was not found to be a predictor of PMV in our sample. A possible reason lies in the relatively young age of patients (mean, 41 years), compared to the mean ages of subjects in similar studies (approximately 54 to 67 years),17182425 or to that in a recently published large, international cohort26 of patients receiving MV.

Contrary to other studies, and despite variations between groups, no diagnostic category acted as an independent predictor of PMV. Differences in diagnosis distributions with other studies171825 can account for this. Albumin concentration, another referred predictive factor,1725 was not systematically measured in our patients.

Investigators1725 who found ICU admission severity scores as prognostic factors for PMV used definitions of PMV of shorter duration (> 72 h or 4 days). In our study, these scores failed to predict PMV. A possible explanation lies in the well-known loss of predictive power in ICU admission severity scores in patients with prolonged LOS.2627

Our cohort had a high incidence of PMV, but the use of MV was also higher than usual. Sixty-three percent of patients admitted to the ICU received MV, in contrast to 33% and 36%, respectively, reported in two recent international studies2629 of MV. Scarcity of ICU beds for our 470-bed hospital accounts for the frequent use of MV. The criteria for admission to our ICU generally reflect the need of ventilatory and/or inotropic support, as has been described.27 The severe physiologic derangement of our patients might be reflected by outcomes other than mortality (observed and predicted mortalities are similar), such as the high incidence of PMV. Notwithstanding this, 73% of patients with PMV survived to leave the hospital, as reported in other single-center or multicenter studies2430 conducted in either acute-care or long-term acute-care facilities. The high survival rate of PMV patients be due to the physiologic selection process that they have already undergone,26 given that many severely ill patients die during the first days of ICU stay, as shown by our 130 early death patients. The efforts and resources dedicated to PMV patients seem to be justified.

The median duration of MV (7 days) was similar to that shown in international studies2829: 5 to 7 days. However, IQRs differed greatly, probably due to the absolute lack of long-term acute care facilities in the state of Buenos Aires. PMV patients have to stay in the ICU until they are weaned or die, reflected by the 10% of patients who received MV for > 90 days. This distortion in resource availability biases in favor of longer duration of MV. The median length of MV in PMV patients in this study is 36 days (IQR, 26 to 57 days) but similar to that in a recent French study (36 ± 25 days in survivors, 37 ± 28 days in nonsurvivors).24

Other factors might extend MV. Sedation and analgesia protocols have a clear impact in MV duration. We cannot discard their effect, particularly before 2001, when the practice of daily sedative interruption was started in our ICU.3132 Ventilator-associated pneumonia has also been found to prolong MV, but we could not control for this variable due to the retrospective nature of our study.33

A limitation of our study is that our logistic regression model was built with the data of a single unit, which might preclude the generalizability of our conclusions. Prediction models tend to perform better on data on which the model was constructed than on different data. However, most similar studies1024 have been conducted in single ICUs, and include comparable numbers of patients.

In summary, we found a high incidence of PMV in our 3-year population of patients receiving MV. Shock on ICU admission was the only independent predictor for this long-term outcome, even adjusting for other variables, such as degree of hypoxemia, severity scores, and ICU admission diagnosis. Similarly to other studies, survival of these patients was good.


   Acknowledgements
 
We are indebted to Martha Swain for assistance in English editing of the manuscript.


   Footnotes
 
Abbreviations: APACHE = acute physiology and chronic health evaluation; CI = confidence interval; CIPNM = critical illness polyneuropathy and myopathy; FIO2 = fraction of inspired oxygen; IQR = interquartile range; LOS = length of stay; MV = mechanical ventilation; OR = odds ratio; PMV = prolonged mechanical ventilation; SAPS = simplified acute physiology score

Received for publication November 5, 2003. Accepted for publication September 8, 2004.


   References
TOP
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 References
 

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