Abstract
Purpose
To evaluate if severity of illness in the intensive care unit influences patients' retrospective recall of their baseline physical function from prior to hospital admission.
Materials and Methods
A prospective cohort study of 193 acute lung injury (ALI) survivors who, prior to hospital discharge, retrospectively reported their pre-hospitalization physical function using the SF-36 quality of life survey.
Results
Four measures were used to evaluate ICU severity of illness: (1) Acute Physiology and Chronic Health Evaluation II Acute Physiologic Score at ICU admission, (2) Lung Injury Score at ALI diagnosis, (3) Sequential Organ Failure Assessment (SOFA) score at study enrollment, and (4) maximum daily SOFA 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
ICU severity of illness was not associated with patients' retrospectively recalled baseline physical function. Patients with a lower level of education maybe 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
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 prior to 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.[4–7] 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.[5,9–11] 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 since 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 acute lung injury (ALI) patients, an archetype of ICU patients with a high severity of illness.[17]
Methods
Study Design and Participants
This analysis is part of an ongoing prospective cohort study of ALI patients.[18] Participants were enrolled from 13 ICUs in four 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) pre-existing cognitive impairment, 3) pre-existing illness with a predicted life expectancy of <6 months, and 4) homelessness. The study protocol was approved by the institutional review boards at Johns Hopkins University and the other participating institutions.
Exposures, outcomes and confounders
Prior to 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 prior to 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 four measures of ICU severity of illness. Each of these four 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 since it was specifically developed and validated to predict the SF-36 Physical Function domain after hospital discharge for ALI patients.[27,28]
Statistical Analysis
Descriptive statistics were reported using median and inter-quartile range 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 (LOWESS) 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; gender, race (Caucasian versus non-Caucasian), 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 LOWESS analyses.
Using simple linear regression, each potential confounding variable was analyzed for its association with the primary outcome. Variables with an association of p <0.10 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 four 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 <0.05 was considered statistically significant. All data were analyzed using STATA version 10.0 (College Station, TX).
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 due to delirium, assessed using the Confusion Assessment Method for the ICU [30] and other cognitive impairment at hospital discharge, while a small proportion of consenting patients could not complete it due to other reasons, including being physical incapable (3%). Hence, a total of 193 consenting survivors completed the SF-36 survey to evaluate pre admission QOL (Figure 1). These 193 participants were 53% male with a median (interquartile range [IQR]) age of 48 (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).
Figure 1.
Study flow diagram
Table 1.
Description of study participants
| Patient Characteristics | N=193a |
|---|---|
| Age, median (IQR) years | 48 (40, 58) |
| Male, no. (%) | 103 (53%) |
| Caucasian, no. (%) | 120 (62%) |
| Education, median (IQR) years | 12 (11, 14) |
| Co-morbidity | |
| Body Mass Index, no. (%) | |
| 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, no. (%) | |
| Never | 46 (24%) |
| Former | 67 (35%) |
| Current | 79 (41%) |
| Charlson Co-morbidity Index, no. (%) | |
| 0 | 63 (33%) |
| 1 | 43 (22%) |
| 2 | 26 (13%) |
| 3 | 15 (8%) |
| ≥4 | 46 (24%) |
| Functional Co-morbidity Index, no. (%) | |
| 0 | 48 (25%) |
| 1 | 55 (28%) |
| 2 | 35 (18%) |
| 3 | 30 (16%) |
| ≥4 | 25 (13%) |
| ICU Severity of Illness Measures, median (IQR) | |
| APACHE II Acute Physiology Score | 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) |
Abbreviations: APACHE II – Acute Physiology and Chronic Health Evaluation II; ICU – intensive care unit; IQR – inter-quartile range; SOFA – Sequential Organ Failure Assessment
Proportions may not add to 100% due to rounding. Education and smoking status were missing for 1 patient.
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 (versus 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 | p-valueb |
|---|---|---|
| Age (per year) | −0.7 (−1.0, −0.4) | <0.001 |
| Male | 13.6 (4.4, 22.8) | 0.004 |
| Caucasian | −4.3 (−13.9, 5.3) | 0.38 |
| Education (per year) | 2.0 (0.3, 3.7) | 0.03 |
| Body Mass Index | ||
| Underweight (<18.5 kg/m2) | −28.8 (−50.6, −7.0) | 0.01 |
| Normal (18.5 – 25 kg/m2) | Reference | |
| Overweight (25.1 – 30 kg/m2) | −7.6 (−19.2, 4.1) | 0.20 |
| Obese (30+ kg/m2) | −6.3 (217.8, 5.1) | 0.28 |
| Smoking | ||
| Never | Reference | |
| Former | −6.0 (−18.3, 6.4) | 0.35 |
| Current | −1.5 (−13.6, 10.5) | 0.80 |
| Co-morbidities | ||
| Charlson Comorbidity Index | −8.6 (−11.3, −5.9) | <0.001 |
| Functional Comorbidity Index | −8.2 (−11.5, −5.0) | <0.001 |
The estimated minimum clinically important difference for SF-36 Physical Function is 10 [42]
estimated using simple linear regression of the patient factor with retrospective baseline SF-36 physical function domain score measured on a scale of 0 to 100 with a higher score indicating better function.
Table 3.
Associations of ICU severity of illness measures with retrospective baseline SF-36 Physical Function
| Severity of Illness Measure | Bivariate Associationa, b | p-valuea | Multivariate Associationc, b | p-valuec |
|---|---|---|---|---|
| APACHE II APS | −0.06 (−0.71, 0.60) | 0.860 | −0.10 (−0.70, 0.51) | 0.67 |
| Lung Injury Score | 10.4 (3.4, 17.3) | 0.004 | 5.7 (−0.7, 12.1) | 0.08 |
| SOFA, enrollment | 0.72 (−0.69, 2.13) | 0.315 | 0.68 (−0.57, 1.94) | 0.26 |
| SOFA, maximum | 0.97 (−0.39, 2.33) | 0.162 | 0.98 (−0.24, 2.19) | 0.10 |
Abbreviations: APACHE II APS – Acute Physiology and Chronic Health Evaluation II acute physiologic score; SOFA – Sequential Organ Failure Assessment
estimated using simple linear regression
The estimated minimum clinically important difference for SF-36 Physical Function is 10 [42]
estimated using multiple linear regression, adjusted for age, sex, education, body mass index, Charlson Comorbidity Index category, and Functional Comorbidity Index category.
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 (i.e. 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
| Adjusted Association of Severity of Illness with Physical Function by Years of Educationa, b |
|||||||
|---|---|---|---|---|---|---|---|
| Severity of Illness Measure | Interaction coefficient | p-value for interaction | 9 years (10th percentile) | 11 years (25th percentile) | 12 years (50th percentile) | 14 years (75th percentile) | 16 years (90th percentile) |
| APACHE II APS | −0.3 (−0.5, 0.0) | 0.03 | 0.8 (−0.2, 1.9) | 0.3 (−0.4, 1.0) | 0.0 (−0.6, 0.7) | −0.5 (−1.2, 0.2) | −1.0 (−2.0, 0.0) |
| Lung Injury Score | −1.1 (−3.7, 1.4) | 0.38 | 9.7 (−0.9, 20.3) | 7.4 (0.3, 14.5) | 6.3 (−0.1, 12.6) | 4.0 (−3.6, 11.6) | 1.7 (−9.6, 13.0) |
| SOFA, enrollment | −0.5 (−0.9, −0.1) | 0.2 | 2.7 (0.6, 4.7) | 1.7 (0.2, 3.1) | 1.2 (−0.1, 2.5) | 0.2 (−1.2, 1.5) | −0.9 (−2.6, 0.9) |
| SOFA, maximum | −0.6 (−1.0, −0.2) | <0.01 | 3.3 (1.3, 5.3) | 2.1 (0.7, 3.5) | 1.5 (0.2, 2.7) | 0.2 (−1.0, 1.5) | −1.0 (−2.8, 0.8) |
Abbreviations: APACHE II APS – Acute Physiology and Chronic Health Evaluation II acute physiologic score; SOFA – Sequential Organ Failure Assessment
Linear regression analysis coefficient (95% confidence interval), by years of education, for the association of each severity of illness measure with the retrospective baseline SF-36 physical function outcome measure, adjusted for age, sex, body mass index, Charlson Comorbidity Index category, and Functional Comorbidity Index category.
The estimated minimum clinically important difference for SF-36 Physical Function is 10 [42]
Discussion
In evaluating for potential recall bias in ALI survivors' retrospective reports of physical function prior to 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. While other sources of recall bias may exist, exploration of severity of illness is particularly important within critical care, since 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 patient's baseline quality of life prior to hospitalization is important in evaluating to what extent patients recover after hospital discharge.[2,7,21,31] Due to the emergent nature of critical illness, patients generally cannot provide a self-report of their pre-hospitalization quality of life status at ICU admission. Consequently, three 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 versus population norms. [4–7,15] Second, within critical care, some studies have demonstrated poor to fair agreement of proxy versus 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 ALI patients while 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 prior to 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 prior to 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 gender.[37]
A prior study [38] found an association between baseline quality of life and ICU severity of illness measured by APACHE III. This study differed from ours since 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 ALI patients 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.[39–41] 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 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 due to 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 ALI patients' outcomes.[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 ALI patients recruited from teaching hospitals in a single U.S. city. Hence, the results may not be generalizeable 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 prior to hospital admission providing greater confidence in the use of retrospective measures of QOL in ALI patients. However, special attention may be warranted in patient groups with particularly low educational levels since these patients may be more strongly affected by ICU severity of illness when providing retrospective recall of baseline physical function.
Acknowledgment
We 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.
This research was supported by the National Institutes of Health (Acute Lung Injury SCCOR Grant # P050 HL 73994). The funding bodies had no role in the study design, manuscript writing or decision to submit the manuscript for publication.
Footnotes
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