Does intensive care unit severity of illness influence recall of baseline physical function?☆

Article Outline

• Abstract
• 1. Introduction
• 2. Methods
  • 2.1. Study design and participants
  • 2.2. Exposures, outcomes, and confounders
  • 2.3. Statistical analysis
• 3. Results
• 4. Discussion
• Acknowledgment
• References
• Copyright

Abstract 

Purpose

The aim of this study is to evaluate if severity of illness in the intensive care unit influences patients' retrospective recall of their baseline physical function from before hospital admission.

Materials and Methods

This is a prospective cohort study of 193 acute lung injury survivors who, before hospital discharge, retrospectively reported their prehospitalization physical function using the Short Form 36 quality of life survey.

Results

Four measures were used to evaluate intensive care unit (ICU) severity of illness: (1) Acute Physiology and Chronic Health Evaluation II Acute Physiologic Score at ICU admission, (2) Lung Injury Score at acute lung injury diagnosis, (3) Sequential Organ Failure Assessment score at study enrollment, and (4) maximum daily Sequential Organ Failure Assessment score during the entire ICU stay. In multivariable linear regression analysis, no measure of severity of illness was associated with prehospitalization physical function. Education level significantly modified the relationship between ICU severity of illness and baseline physical function with lower educational attainment having a stronger association with baseline physical function.

Conclusion

Intensive care unit severity of illness was not associated with patients' retrospectively recalled baseline physical function. Patients with a lower level of education may be more influenced by ICU severity of illness, but the magnitude of this effect may not be clinically meaningful.

Keywords: Critical care, Quality of life, Respiratory distress syndrome, adult, Health status, Mental recall, Bias, epidemiologic

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1. Introduction 

As the mortality of intensive care unit (ICU) patients improves and research focuses on reducing long-term morbidity, understanding ICU patients' baseline quality of life before hospital admission becomes increasingly important. Assessment of baseline quality of life is helpful in prognostication of short-term mortality [1], in evaluating post-ICU measures of quality of life, and in determining whether patients recover to their pre-ICU status [2], [3]. Age- and sex-matched population norms are commonly used as a reference point in understanding patients' recovery from critical illness. However, patients who experience critical illness may have baseline quality-of-life measures that are lower than population norms [4], [5], [6], [7]. Hence, using population norms can potentially overstate patients' post-ICU impairments in quality of life. Consequently, a patient-specific baseline estimate of quality of life may help in establishing a reference point for post-ICU follow-up measurements [2], [8].

Despite its importance, it is difficult to obtain a valid baseline measure of quality of life for ICU patients. Emergent admission and critical illness prevent patients from providing self-reported baseline quality of life at the time of ICU admission. Moreover, proxy assessment of patients' baseline quality of life often differs from the patient's assessment [5], [9], [10], [11]. Proxies may be under great stress at the time of patients' ICU admission, which may contribute to difficulty in accurately estimating patients' baseline status. An alternative is seeking ICU survivors' own retrospective recall of their baseline quality of life. However, such a retrospective quality-of-life measure may be affected by recall bias [12], [13]. Factors such as severity of current symptoms may bias patients' recall of baseline status [12], [14], but these issues have not been empirically explored among critically ill patients [8].

Our objective was to evaluate the relationship between ICU severity of illness and patients' post-ICU retrospective assessment of their baseline quality of life. Specifically, we focused on the physical function domain within the Short Form 36 (SF-36) quality-of-life instrument because it is often severely impaired after critical illness [15], [16]. A significant association between ICU severity of illness and patients' pre-ICU physical function score would help inform our understanding of potential recall bias in patients' retrospective assessment of baseline quality of life. We specifically evaluated this objective using a cohort of patients with acute lung injury (ALI), an archetype of ICU patients with a high severity of illness [17].

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2. Methods 

2.1. Study design and participants 

This analysis is part of an ongoing prospective cohort study of patients with ALI [18]. Participants were enrolled from 13 ICUs in 4 hospitals in Baltimore, MD. Eligible patients were mechanically ventilated and met criteria for ALI as defined by the American-European Consensus Conference [19]. Relevant exclusion criteria included (1) baseline language or communication barrier, (2) preexisting cognitive impairment, (3) preexisting illness with a predicted life expectancy of less than 6 months, and (4) homelessness. The study protocol was approved by the institutional review boards at Johns Hopkins University and the other participating institutions.

2.2. Exposures, outcomes, and confounders 

Before hospital discharge and after informed consent (with negative screening for delirium [20]), the validated SF-36 quality-of-life instrument [2], [15] was administered in person to participants surviving their ICU stay. To retrospectively evaluate baseline quality of life, as done in prior research [6], [7], [21], [22], participants were asked to respond to the SF-36 questions based upon their quality-of-life status immediately before the onset of the illness causing this hospitalization. The primary outcome for this analysis was the retrospective baseline physical function domain of the SF-36.

The primary exposure variables in this analysis were 4 measures of ICU severity of illness. Each of these 4 measures was separately evaluated for their association with the retrospective baseline physical function outcome measure: Acute Physiology and Chronic Health Evaluation II Acute Physiologic Score (APACHE II APS) at ICU admission [23], Lung Injury Score at ALI diagnosis [24], Sequential Organ Failure Assessment (SOFA) score at study enrollment [25], and maximum daily SOFA score during the entire ICU stay.

Based upon prior literature, relevant variables that were potentially associated with the primary outcome (SF-36 physical function) were evaluated as potential confounders in this analysis. These variables were age, sex, race, number of years of education, body mass index (BMI), smoking status, and comorbidity status. Comorbidity status was measured using both the Charlson Comorbidity Index [26] and the Functional Comorbidity Index. The Functional Comorbidity Index is a particularly relevant comorbidity measure because it was specifically developed and validated to predict the SF-36 physical function domain after hospital discharge for patients with ALI [27], [28].

2.3. Statistical analysis 

Descriptive statistics were reported using median and interquartile range (IQR) for continuous data and proportions for categorical data. Each variable was modeled based on clinically relevant thresholds or available information in the published literature. When such information was not available, a locally weighted least-squares regression plot of the variable vs the primary outcome measure was used to determine an appropriate modeling method. Based on this approach, variables were modeled as follows: age as a quadratic variable; sex, race (white vs nonwhite), BMI (underweight, <18.5 kg/m²; normal, 18.5-25 kg/m²; overweight, 25.1-30 kg/m²; and obese, >30 kg/m²), and smoking status (never, former, or current) as categorical variables; and education, APACHE II APS, Lung Injury Score, and SOFA as continuous variables. The Charlson Comorbidity Index and the Functional Comorbidity Index were each modeled as a 5-level categorical variable (0, 1, 2, 3, ≥4 points), which were then analyzed as continuous variables given their linear relationship with the primary outcome variable in the exploratory locally weighted least-squares analyses.

Using simple linear regression, each potential confounding variable was analyzed for its association with the primary outcome. Variables with an association of P < .10 were included in multivariable linear regression models evaluating the association of each ICU severity-of-illness measure with the physical function SF-36 score. We created 4 separate regression models, each evaluating the association between a specific severity-of-illness measure and the primary outcome. To evaluate for multicollinearity, we used variance inflation factors [29], with multicollinearity not detected. Confounding variables included in the multivariable regression models were also separately evaluated for statistical interaction with each of the ICU severity-of-illness measures using an interaction term. For all multivariable analyses, P < .05 was considered statistically significant. All data were analyzed using STATA version 10.0 (College Station, TX).

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3. Results 

Of the 520 subjects enrolled, 269 (52%) survived until the time of post-ICU consent and survey administration, of whom 33 (12%) had no consent for the survey at time of discharge. Consistent with prior research findings [20], [30], approximately 11% of the remaining eligible subjects could not complete the SF-36 because of delirium, assessed using the Confusion Assessment Method for the ICU [30] and other cognitive impairment at hospital discharge, whereas a small proportion of consenting patients could not complete it because of other reasons, including being physical incapable (3%). Hence, a total of 193 consenting survivors completed the SF-36 survey to evaluate preadmission quality of life (Fig. 1). These 193 participants were 53% male, with a median (IQR) age of 48 years (40-58 years) (Table 1). Participants' median (IQR) ICU severity-of-illness scores were APACHE II APS 19 (15-24), Lung Injury Score 2.8 (2.3-3.5), enrollment SOFA 8 (5-10), and maximum SOFA 9 (7-11).

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• Fig. 1. 

  Study flow diagram.

Table 1. Description of study participants

Patient characteristics	N = 193a
Age, median (IQR) years	48 (40-58)
Male, n (%)	103 (53)
White, n (%)	120 (62)
Education, median (IQR) years	12 (11-14)
Comorbidity
Body mass index, n (%)
Underweight (<18.5 kg/m2)	10 (5)
Normal (18.5-25 kg/m2)	65 (34)
Overweight (25.1-30 kg/m2)	57 (30)
Obese (>30 kg/m2)	61 (32)
Smoking, n (%)
Never	46 (24)
Former	67 (35)
Current	79 (41)
Charlson comorbidity index, n (%)
0	63 (33)
1	43 (22)
2	26 (13)
3	15 (8)
≥4	46 (24)
Functional comorbidity index, n (%)
0	48 (25)
1	55 (28)
2	35 (18)
3	30 (16)
≥4	25 (13)
ICU severity-of-illness measures, median (IQR)
APACHE II APS	19 (15-24)
Lung Injury Score	2.8 (2.3-3.5)
SOFA Score, at enrollment	8 (5-10)
SOFA Score, maximum in ICU	9 (7-11)

Significant predictors of the SF-36 physical function domain are reported in Table 2. Baseline SF-36 physical function scores were significantly lower with increasing patient age and comorbidity (both Charlson and Functional Comorbidity indices) and with low (vs normal) BMI. Male sex and higher education level were associated with significantly higher physical function scores. After adjustment for these potential confounders, separate multivariable linear regression analyses demonstrated no significant associations between each measure of ICU severity of illness and retrospective baseline physical function (Table 3).

Table 2. Bivariate association of patient factors with retrospective baseline SF-36 physical function

Patient factor	Simple linear regression coefficienta	Pb
Age (per y)	−0.7 (−1.0, −0.4)	<.001
Male	13.6 (4.4, 22.8)	.004
White	−4.3 (−13.9, 5.3)	.38
Education (per y)	2.0 (0.3, 3.7)	.03
Body mass index
Underweight (<18.5 kg/m2)	−28.8 (−50.6, −7.0)	.01
Normal (18.5-25 kg/m2)	Reference
Overweight (25.1-30 kg/m2)	−7.6 (−19.2, 4.1)	.20
Obese (30+ kg/m2)	−6.3 (−17.8, 5.1)	.28
Smoking
Never	Reference
Former	−6.0 (−18.3, 6.4)	.35
Current	−1.5 (−13.6, 10.5)	.80
Comorbidities
Charlson Comorbidity Index	−8.6 (−11.3, −5.9)	<.001
Functional Comorbidity Index	−8.2 (−11.5, −5.0)	<.001

Table 3. Associations of ICU severity-of-illness measures with retrospective baseline SF-36 physical function

Among all variables included in the multivariable regression models, only education had a statistically significant interaction with 3 of the 4 measures of ICU severity of illness (Table 4). In patients with lower education levels, there was a stronger association between severity of illness and retrospective recall of baseline physical function. However, even across the extremes of educational level (ie, 10th and 90th percentile), the associations were frequently not statistically significant.

Table 4. Analysis of statistical interaction between ICU severity of illness and education with retrospective baseline SF-36 physical function

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4. Discussion 

In evaluating for potential recall bias in ALI survivors' retrospective reports of physical function before hospital admission, we investigated whether 4 measures of ICU severity of illness were independently associated with retrospectively patient-reported baseline physical function. Consistent with other quality of life literature, patients' SF-36 physical function score was associated with age, sex, education, BMI, and comorbidity, thus providing some assurance regarding the validity of this retrospective measure. Moreover, after adjustment for these predictors, the 4 ICU severity-of-illness measures were not associated with recalled baseline physical function. Survivors with the lowest level of education demonstrated a stronger association between ICU severity of illness and higher baseline physical function; however, the magnitude of this association is likely not clinically important.

The lack of association between the 4 different severity-of-illness measures and baseline physical function has important implications for researchers. It helps provide some assurance that ICU severity of illness is not a source of recall bias. Although other sources of recall bias may exist, exploration of severity of illness is particularly important within critical care because illness severity can be high, is easily and commonly measured, and has a strong association with ICU survivors' status shortly after ICU discharge [4], the time point at which baseline quality of life may be most easily measured.

Understanding patients' baseline quality of life before hospitalization is important in evaluating to what extent patients recover after hospital discharge [2], [7], [21], [31]. Because of the emergent nature of critical illness, patients generally cannot provide a self-report of their prehospitalization quality-of-life status at ICU admission. Consequently, 3 methods are commonly considered in estimating baseline status: (1) age- and sex-matched population norms, (2) proxy reports, and (3) patients' retrospective recall. None of these methods are ideal. First, several studies demonstrate that ICU patients have lower baseline quality of life vs population norms [4], [5], [6], [7], [15]. Second, within critical care, some studies have demonstrated poor to fair agreement of proxy vs patient quality-of-life assessments [5], [9], although others have reported moderate to excellent agreement [10], [11], [32], [33]. These differences in findings may arise due to the patient population studied, with those reporting poor to fair agreement specifically focused on patients with ALI, whereas the other studies enrolled populations of general ICU patients who were substantially less severely ill. Lastly, patients' retrospective assessment of baseline quality of life may suffer from recall bias, whereby patients' critical illness and post-ICU status may influence their recall of quality of life before critical illness [13], [14]. Given the growing interest in research evaluating ICU survivors' long-term outcomes, understanding their baseline state and potential recall bias in patients' retrospective reports is an area of growing importance to critical care [34], [35].

Our analyses demonstrated that age, sex, education level, BMI, and both the Charlson and Functional Comorbidity indices were associated with baseline physical function, retrospectively reported before hospital discharge. The Functional Comorbidity Index was developed to predict the SF-36 physical function domain in ALI survivors [27], and it is notable that our analyses indicated its association with recalled baseline physical function as well. In addition, prospective studies using SF-36 to assess outcomes after ICU have found associations with the patients' age [36] and sex [37].

A prior study [38] found an association between baseline quality of life and ICU severity of illness measured by Acute Physiology and Chronic Health Evaluation III. This study differed from ours because it used a custom-made quality-of-life instrument, which was completed around the time of ICU admission. In addition, about half of responders were proxies, whose perceptions may be associated with the patient's severity of illness, complicating such analyses. In contrast, our study used the SF-36 instrument and was completed exclusively by patients with ALI after ICU discharge. These distinctions in methodology may account for the differences in findings.

The statistically significant interaction between participants' educational level and severity of illness indicates that those with lower education may have a stronger association between severity of illness and retrospective recall of physical function. Research in other fields has demonstrated that lower educational achievement is associated with less accurate recall [39], [40], [41]. However, even at the extremes of educational level, the magnitude of this potential association in our analyses is likely not clinically important given a minimum clinically important difference of 10 points for the SF-36 physical function domain [42]. Hence, although we believe that this finding indicates that educational level should be considered as a potential factor influencing the accuracy of patient recall of quality of life, it should not prevent retrospective assessments of quality of life from being considered in future studies.

There are several potential limitations of this study. Among consenting participants, 18% did not complete the retrospective assessment of physical function primarily because of cognitive impairment at hospital discharge. This finding and limitation is common in ALI research studies evaluating patient-reported outcomes. However, despite this issue, our analysis included a relatively large number of baseline assessments and provided a novel analysis to help address an important question within the field of critical care medicine [32]. Future research should evaluate the association between post-ICU cognitive impairment and recall bias. Second, we investigated only a single potential source of recall bias for patients' retrospective reports of physical function. Other factors, such as current health status or symptoms at the time of interview, may be a source of recall bias for ICU survivors [12]. We chose to investigate ICU severity of illness given existing robust measures for this factor within critical care and its important role in influencing the outcomes of patients with ALI [2]. However, more methodological research is needed in evaluating the appropriateness of patients' retrospective reports. Third, only a single domain of the SF-36 quality-of-life instrument, physical function, was investigated in this analysis. This domain was specifically investigated because impaired physical function is a frequent, severe, and long-lasting impairment in ALI survivors; however, further investigation of factors affecting retrospective recall of other quality-of-life domains, including mental health and social function, also would be important to the field of study. Future research should investigate these other domains and evaluate if retrospective recall is affected differently among the various quality-of-life domains. Finally, this study focused only on patients with ALI recruited from teaching hospitals in a single US city. Hence, the results may not be generalizable to other critically ill patients from other hospital settings or locations. We hope that other researchers will perform similar analyses to help investigate the generalizability of these findings.

In conclusion, ICU severity of illness does not appear to influence ALI survivors' retrospective recall of their physical function before hospital admission providing greater confidence in the use of retrospective measures of QOL in patients with ALI. However, special attention may be warranted in patient groups with particularly low educational levels because these patients may be more strongly affected by ICU severity of illness when providing retrospective recall of baseline physical function.

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Acknowledgment 

The authors thank all patients who participated in the study and the dedicated research staff who assisted with the study: Ms Rachel Bell, Ms Kim Boucher, Dr Sanjay Desai, Ms Carinda Feild, Ms Thelma Harrington, Dr Praveen Kondreddi, Ms Stacey Murray, Dr Abdulla Damluji, Ms Arabela Sampaio, and Ms Kristin Sepulveda.

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