Frailty is a syndrome characterized by the loss of physiologic reserve across multiple organ systems that reduces one’s ability to maintain or to restore homeostasis in the setting of an acute stressor (1,2). Although an important proportion of patients with critical illness have frailty before their admission to the ICU, 70% or more become critically ill without evidence of preexisting frailty (3–8). Nevertheless, because many survivors of critical illness often develop new or worsened chronic organ dysfunction (e.g., cardiovascular [9,10], respiratory [11,12], renal , immunologic ), disabilities in activities of daily living (15,16), or impairments in physical (17,18) and cognitive function (16,19) they may be at high risk for developing new-onset frailty, a syndrome related to, but distinct from, previously defined adverse long-term outcomes of critical illness.
In those without critical illness, frailty is associated with a greater risk for falls, new-onset disability, admission to long-term care, hospitalization, and death (20,21). Furthermore, frailty may be reversible (22–24). Therefore, identification and treatment of frailty in survivors of critical illness could serve as a target by which to reduce the burdens of critical illness survivorship. The extent to which newly acquired frailty is present in adult survivors of critical illness, the clinical course of frailty, and the degree to which frailty overlaps with disability or cognitive impairment in this population, however, is unclear (25).
To address these knowledge gaps, we conducted a prospective, multicenter, cohort study of survivors of critical illness, assessing frailty at enrollment and at 3 and 12 months after hospital discharge. We hypothesized that adult survivors of critical illness, age 18 years old and older, would transition to more severe states of frailty after their illness, that frailty would be present in those without disability or cognitive impairment, and that factors present before and during critical illness would be associated with frailty severity at follow-up.
We tested these hypotheses among participants enrolled in the identical (but with different enrolling sites) Bringing to Light the Risk Factors and Incidence of Neuropsychological Dysfunction in ICU Survivors (NCT00392795) (6,19) and Delirium and Dementia in Veterans Surviving ICU Care (NCT00400062) (6,26) studies.
Settings and Participants
As described in the online supplement (Supplemental Digital Content 1, http://links.lww.com/CCM/F580) and in previous publications (15,19), each day, trained study personnel screened the censuses from the medical or surgical ICUs at five U.S. centers for patients age 18 years old or older, treated for respiratory failure and/or shock for less than 72 hours. We excluded those who were moribund, had organ dysfunction for more than 72 hours, severe cognitive impairment, an inability to communicate in English, substance abuse disorder, psychotic disorder, homelessness, or who resided greater than 200 miles from an enrolling site. Participants or their proxies provided consent. The institutional review boards at each center approved the study.
At study enrollment, we obtained sociodemographics and data on coexisting illness, disabilities in basic and instrumental activities of daily living (ADLs), and cognitive function. During the index hospitalization, we prospectively collected physiologic and laboratory data (for up to 30 d). At 3 and 12 months after hospital discharge, study personnel who were blinded to the baseline Clinical Frailty Scale (CFS) score performed in-person follow-up assessments at the enrolling centers or in patients’ homes.
We used the well-validated, highly reliable, CFS to rate patients along the fitness to frailty continuum (27,28). CFS scores range from 1 (very fit) to 7 (severe frailty; Table S1, Supplemental Digital Content 1, http://links.lww.com/CCM/F580), where scores of 5 or greater represent frailty (27,28). Study personnel were trained by a geriatrician with expertise in frailty assessment (A.M.). These personnel used all available clinical and study-related data (e.g., patient/proxy interviews, medical records, and clinical and study-related measurements of comorbidity, disability, and cognitive function) to complete the CFS at baseline (i.e., at study enrollment, based on the participant’s status during the 2 mo before ICU admission) and again 3 and 12 months after hospital discharge. The Vanderbilt Coordinating Center Follow-up Core maintained standardization of follow-up assessments.
Determining the Co-Occurrence of Frailty With Disability and Cognitive Impairment
At 3 and 12 months, we assessed disability in ADLs using the Katz Index of Independence (Katz ADL) (29) and cognition using the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) (30). We considered disability to be present if the Katz ADL score was equal to 1 or greater (i.e., requiring assistance in at least 1 ADL) (31). We considered cognitive impairment to be present if the RBANS score was 78 or less (i.e., 1.5 sds below the age-adjusted norm) (19,31). Detailed descriptions of these instruments are presented in the online supplement (Supplemental Digital Content 1, http://links.lww.com/CCM/F580).
Factors Associated With Frailty Severity After Critical Illness
A priori, we selected seven baseline and six critical illness–related factors to evaluate their potential associations with CFS scores at follow-up: baseline CFS score, age, years of education, sex, Charlson Comorbidity Index score (32), baseline Katz ADL score (29), baseline Functional Activities Questionnaire (FAQ) score (33), duration of delirium (i.e., the number of days the Confusion Assessment Method for the ICU  was positive), duration of coma (i.e., the number of days the Richmond Agitation-Sedation Scale  was –4 or –5), duration of sepsis (i.e., the number of days Sepsis-2  criteria were met), duration of mechanical ventilation, daily modified Sequential Organ Failure Assessment (SOFA) score (37,38), and discharge location. Detailed descriptions of these factors are presented in the online supplement (Supplemental Digital Content 1, http://links.lww.com/CCM/F580).
To determine the proportion of patients who developed newly acquired frailty after their critical illness, we compared CFS scores at 3 and 12 months to CFS scores at baseline. We considered those patients who had CFS scores of greater than or equal to 5 at either 3- or 12-month follow-up, but who had CFS scores of less than 5 at baseline, to have newly acquired frailty.
To determine transitions between frailty states, we used previously published CFS score–based frailty categories (27). We considered patients to be fit if the CFS score was 1–3, vulnerable if the CFS score was 4, and frail if the CFS score was 5–7. To illustrate transitions between these frailty states from baseline to 3- and 12-month follow-up, we constructed alluvial flow diagrams. We considered transitions from fit to vulnerable, fit to frail, or from vulnerable to frail to be transitions to a worse frailty state. We considered transitions from frail to vulnerable, frail to fit, and from vulnerable to fit to be transitions to a better frailty state. Those remaining in the same frailty state were considered to have had no transition.
To describe the extent to which frailty overlaps with disability in basic activities of daily living and/or cognitive impairment at 3- or 12-month follow-up, we constructed Venn diagrams, restricted to patients with one of these syndromes using the cutoffs defined above (31). We categorized patients into seven groups: 1) frailty alone, 2) frailty with disability, 3) frailty with cognitive impairment, 4) frailty with disability and cognitive impairment, 5) disability alone, 6) disability with cognitive impairment, and 7) disability and cognitive impairment.
To evaluate potential associations between baseline and critical illness–related factors and CFS scores at follow-up, we used multivariable regression. We adjusted for the likelihood a patient would be alive, remain in the study, and participate in follow-up using inverse probability of attrition weighting (39,40). We used multiple imputation to account for missing covariate and incomplete outcome data (41). Continuous risk factors were allowed to be nonlinear using restricted cubic splines. Model assumptions were verified using graphical techniques. All model assumptions were met. We used R version 3.4.1 (R Project, Vienna, Austria) for all analyses. Descriptive data are reported as median and interquartile ranges (IQRs). p values less than 0.05 were considered significant.
Between March 2007 and December 2010, we enrolled 1,047 patients. After accounting for death, study withdraw, and loss to follow-up, we assessed CFS scores in 530/711 of survivors (75%) at 3 months and in 445/631 of survivors (70%) at 12 months (Fig. 1).
Overall, 567 unique patients contributed data to these analyses. As shown in Table 1, the median age was 61 years (IQR, 51–70), 41% were female, and severity of illness was high (median Acute Physiology and Chronic Health Evaluation II score of 23 [IQR, 17–29]).
TABLE 1. -
Demographic and Clinical Characteristics
n = 567
|Female sex, n (%)
|Clinical Frailty Scale score at baseline, n (%)
| 1: very fit
| 2: well
| 3: well with treated comorbid disease
| 4: apparently vulnerable
| 5: mildly frail
| 6: moderately frail
| 7: severely frail
|Charlson Comorbidity Index score
|Katz ADLs score at baseline
|Functional Activities Questionnaire of instrumental ADLs score at baseline
|Informant Questionnaire on Cognitive Decline in the Elderly score
|Acute Physiologic and Chronic Health Evaluation II score at ICU admission
|Mean daily Sequential Organ Failure Assessment score in the ICU
| Duration of delirium,b (d)
|Comatosec, n (%)
| Duration of coma,b (d)
|Septicd, n (%)
| Duration of sepsis,b (d)
|Mechanically ventilated, n (%)
| Duration of mechanical ventilation,b (d)
|ICU length of stay (d)
|Hospital length of stay (d)
ADL = Activities of Daily Living.
aDefined as the number of days the Confusion Assessment Method for the ICU was positive.
bAmong those with the clinical condition.
cDefined at the number of days the Richmond Agitation-Sedation Scale was –4 or –5.
dDefined according to Sepsis-2 definition for severe sepsis.
Data are median (interquartile range) unless otherwise indicated.
Frailty Status After Critical Illness
The prevalence of frailty increased following critical illness, and in most, was newly acquired. At enrollment, there were 135 of 567 patients (24%) with frailty (i.e., CFS score ≥ 5). At 3 months, however, 239/530 (45%) were frail, and at 12 months, 162/444 (36%) were frail. Of the 239 patients with frailty at 3-month follow-up, 146 (61%) were not frail (i.e., CFS score < 5) at enrollment. Likewise, of the 162 patients with frailty at 12-month follow-up, 98 (61%) were not frail at enrollment. Overall, the median increase in CFS scores was 1 (0–2) between enrollment and 3 months and 1 (0–1) between enrollment at 12 months.
As shown in Figure 2A, transitions between frailty states were common. In general, patients tended to transition to worse states of frailty in the period immediately following their critical illness (i.e., between baseline and 3-mo follow-up) and maintained these worse states of frailty over the longer term (i.e., between 3- and 12-mo follow-up). Transitions to worse frailty states occurred in 242/530 patients (46%) between enrollment and 3 months (Fig. 2B). There were 80/444 patients (18%) who transitioned to a worse frailty state between 3 and 12 months (Fig. 2B). Overall, 178/444 patients (40%) had transitioned to a worse frailty state between enrollment and 12 months. Few patients transitioned to better frailty states (67/530 [13%] between enrollment and 3 mo and 98/444 [22%] between 3 and 12 mo; Fig. 2C). No change in frailty state occurred in 221/530 patients (42%) between enrollment and 3 months and in 230/444 patients (52%) between 3 and 12 months (Fig. 2D). There were 203 of 444 (46%) who had the same frailty state at enrollment and 12 months. Descriptive characteristics of patients according to frailty state at 3 months and at 12 months are presented in Tables S2 and S3 (Supplemental Digital Content 1, http://links.lww.com/CCM/F580).
Overlap of Frailty With Disability and Cognitive Impairment
Of the 530 patients assessed at 3 months, there were 376 (71%) with either frailty, disability in ADLs, or cognitive impairment (Fig. 3A). Of these, 53 patients (14%) had frailty alone, 85 patients (23%) had both frailty and disability, 46 patients (12%) had frailty and cognitive impairment, and 55 patients (15%) had all three syndromes. At 12 months, 276/445 of patients (62%) had frailty, disability, or cognitive impairment (Fig. 3B). As at 3 months, 37 patients (13%) had frailty alone, 60 patients (22%) had frailty and disability, 31 patients (11%) had frailty and cognitive impairment, and 35 patients (13%) had all three syndromes.
Factors Associated With Severity of Frailty After Critical Illness
Three factors, baseline CFS score, baseline ADL score, and modified SOFA score during the ICU stay, were associated with frailty severity at both 3- and 12-month follow-up, although the magnitude of these associations was small and was not of clinical significance (Table 2; and Fig. S1, Supplemental Digital Content 1, http://links.lww.com/CCM/F580). After adjusting for all covariates, for example, patients with a baseline CFS score of 4 (the 75th percentile) had 3- and 12-month CFS scores that were 0.2 points (95% CI, 0.1–0.3) higher than that of patients with a baseline CFS score of 3 (the 25th percentile). Compared with a baseline Katz ADL score of 0, a score of 1 was associated with a 0.2 point (95% CI, 0.1–0.2) higher CFS score at both 3 and 12 months. In contrast, greater modified SOFA scores during the ICU stay were associated with lower CFS scores at follow-up (nonlinear association; p < 0.001 at 3 mo and p < 0.001 at 12 mo) (Table 2; and Fig. S1, Supplemental Digital Content 1, http://links.lww.com/CCM/F580).
TABLE 2. -
Factors Associated With Clinical Frailty
Scale Scores at 3 and 12 Months
|Baseline Clinical Frailty Scale score
||–0.1 to 0.3
||–0.2 to 0.0
||–0.2 to 0.0
||–0.3 to 0.1
||–0.2 to 0.2
|Charlson Index Score
|Katz ADL score
|Functional Activities Questionnaire for Instrumental ADLs score
|Duration of mechanical ventilation
||–0.1 to 0.6
||–0.6 to 0.1
|Duration of sepsis
||–0.4 to 0.3
||–0.1 to 0.5
|Duration of delirium
||–0.3 to 0.3
||–0.3 to 0.4
|Duration of coma
||–0.5 to 0.1
||–0.2 to 0.4
||–0.1 to 0.5
|Modified Sequential Organ Failure Assessment score
ADL = Activities of Daily Living.
Because this association was nonlinear, no single point estimate accurately describes the association. Therefore, the association is graphed in Figure S1 (Supplemental Digital Content 1, http://links.lww.com/CCM/F580
Reference values are those at the 25th percentile, and comparison values are those at the 75th percentile (except for sex and discharge location). Positive point estimates represent an increase in Clinical Frailty Scale (CFS) score at follow-up, indicating more severe frailty. For example, in a comparison of two patients, alike in all other ways (i.e., other factors adjusted to their median or mode value), a patient with a baseline CFS score of 4 would have 0.2-point higher CFS score at 12 mo compared with a patient with a baseline CFS score of 3. Although a number of factors demonstrate statistical significance, the magnitude of these changes in CFS scores is small and below the clinically significant change in CFS score of 1.
None of the remaining factors (i.e., age, years of education, sex, Charlson Comorbidity Index, baseline FAQ, duration of delirium, coma, sepsis, mechanical ventilation, or discharge location) were consistently associated with CFS scores at both 3 and 12 months (Table 2).
In this large, multicenter prospective cohort of survivors of critical illness, we found that four out of 10 survivors were frail at 3 and 12 months after hospital discharge. Among those with frailty at follow-up, 60% were not frail before their critical illness, supporting our hypothesis that critical illness promotes newly acquired frailty. Even among those who were not frail per traditional cutoffs, many transitioned to a worse frailty state after critical illness. Finally, frailty was not limited only to survivors with disability or cognitive impairment, as one in seven survivors without these syndromes had frailty.
The present study advances the understanding of frailty across the continuum of critical illness and survivorship by building on a previous Dutch study, to our knowledge, the only other study to perform longitudinal measures of frailty in survivors of critical illness (42). In contrast to our finding that 45% of survivors of critical illness were frail at 3 months and 36% were frail at 12 months, the prior study reported frailty to be present 18% and 10%, respectively. We assessed frailty using personnel who were trained by a geriatrician with expertise in the assessment of frailty and performed in-person assessments that included patient/proxy interviews, a review of medical records, and the assessment of disabilities and cognitive and physical function to complete the CFS, whereas the previous study relied on patient and proxies to assess frailty. Because patients/proxies and clinicians frequently disagree in their assessments of frailty during critical illness (with proxies typically rating patients less frail than clinicians) (43,44), our more comprehensive approach to frailty measurement may account for the higher prevalence seen in our study. Alternatively, our cohort characterized by diverse reasons for acute medical and surgical critical illness and had greater exposure to critical illness characterized by median ICU length of stay of 5 days and high proportions receiving mechanical ventilation, and experiencing sepsis, delirium, and coma. In contrast, the majority of patients in the previous study were admitted following elective surgery, three quarters were in the ICU for 2 days or fewer, and a lower proportion were mechanically ventilated. Thus, the overall “dose” of critical illness could account for the higher prevalence of frailty in the current study. Nevertheless, despite these differences, both studies report that the majority of survivors with frailty did not have the syndrome before their critical illness. Thus, future studies are needed to understand clinical outcomes associated with newly acquired frailty.
Our findings also build on previous work by Gill et al (45) who, in a 738-patient cohort of community dwelling, noncritically ill, adults age 70 years old or older, found that hospitalization increased the odds that patients would transition to a worse state of frailty and decreased the odds they would recover. In the present study, we found that a large number of survivors of critical illness, half of whom were younger than 61 years old, transitioned to worse frailty states. That survivors of critical illness of younger chronologic age develop frailty, a syndrome considered to be age related, suggests that critical illness may accelerate biologic processes of aging (46,47). Future studies are needed to evaluate the underlying biologic mechanisms by which hospitalization for critical illness contributes to the development of frailty in both older and younger adults.
We also found that, although frailty overlapped with disability and cognitive impairment in many survivors, 14% of patients in this cohort had frailty without either of these syndromes. Although frailty is a distinct clinical syndrome from disability and multimorbidity (21), it is not currently considered as part of the postintensive care syndrome (PICS). Coupled with our finding that frailty is newly acquired in majority, that survivors of critical illness have frailty without other PICS syndromes suggests that screening for frailty should occur in survivors of critical illness. Furthermore, because frailty is associated with poor long-term outcomes and is potentially reversible when detected early, identifying this syndrome in the post-ICU setting could serve as a means by which to improve outcomes for vulnerable population.
We hypothesized that factors present before and during critical illness would be associated with the severity of frailty at follow-up. Of the 13 a priori selected risk factors, only three were associated with CFS scores at follow-up, none of which were associated with clinically significant changes in CFS scores. Future studies to identify potentially modifiable factors present during critical illness (e.g., immobility, nutritional status, inflammation, perceived stress) which may be associated with worse frailty are needed.
Several limitations of our study are worthy of mention. First, we used the CFS to identify frailty, one of a number of different approaches to measuring frailty (1,48). The single systematic review on frailty assessment in those who become critically ill did not identify a preferred frailty measure; it did, however, identify the CFS as the most frequently used frailty assessment tool (7). Nevertheless, because different frailty instruments may identify different patient populations, future work is needed to understand the subtypes of frailty and their causes in survivors of critical illness (49). Second, although the CFS provides a brief set of descriptors for each category which rely on coexisting illnesses, disabilities in activities of daily living, and cognition, the instrument is intended to have an element of judgment, such that different aspects of health can be considered to determine the presence of frailty (27). Thus, factors present during the acute illness such as physical appearance and acute decrease in function could bias CFS scoring. Such bias, however, would most likely affect baseline CFS scores. Follow-up assessments, in contrast, were performed by study personnel blinded to events of the critical illness and occurred months after hospital discharge. Thus, our findings of an increase in frailty after critical illness may, if anything, be conservative. Third, CFS (and its parent tool, the Frailty Index) rely on measurement of a heterogenous group of domains and are thus best suited for overall risk assessment (50). Therefore, future studies building upon our data are needed to increase understanding of the mechanisms by which frailty develops in survivors of critical illness.
In addition to the strengths of our study detailed above, we enrolled a large multicenter cohort of adult patients from academic, community, and Veterans Affairs hospitals across the United States, thereby enhancing the generalizability to our findings. Finally, we achieved high rates of in-person follow-up over 12 months after hospital discharge and used modern statistical techniques to reduce bias related to death and study drop-out.
In conclusion, we found that frailty is common among adult survivors of critical illness; in the majority of these survivors, frailty is worsened or newly acquired. Studies to understand outcomes of critical illness–associated frailty and to identify factors which can be targeted for intervention in this potentially reversible syndrome are needed.
1. Morley JE, Vellas B, van Kan GA, et al. Frailty
consensus: A call to action. J Am Med Dir Assoc 2013; 14:392–397
2. Walston J, Hadley EC, Ferrucci L, et al. Research agenda for frailty
in older adults: Toward a better understanding of physiology and etiology: Summary from the American Geriatrics Society/National Institute on Aging Research Conference on Frailty
in Older Adults. J Am Geriatr Soc 2006; 54:991–1001
3. Bagshaw SM, Stelfox HT, McDermid RC, et al. Association between frailty
and short- and long-term outcomes among critically ill patients: A multicentre prospective cohort study. CMAJ 2014; 186:E95–E102
4. Heyland DK, Garland A, Bagshaw SM, et al. Recovery after critical illness
in patients aged 80 years or older: A multi-center prospective observational cohort study. Intensive Care Med 2015; 41:1911–1920
5. Hope AA, Gong MN, Guerra C, et al. Frailty
before critical illness
and mortality for elderly Medicare beneficiaries. J Am Geriatr Soc 2015; 63:1121–1128
6. Brummel NE, Bell SP, Girard TD, et al. Frailty
and subsequent disability and mortality among patients with critical illness
. Am J Respir Crit Care Med 2017; 196:64–72
7. Muscedere J, Waters B, Varambally A, et al. The impact of frailty
on intensive care unit outcomes: A systematic review and meta-analysis. Intensive Care Med 2017; 43:1105–1122
8. Ferrante LE, Pisani MA, Murphy TE, et al. The association of frailty
with post-ICU disability, nursing home admission, and mortality: A longitudinal study. Chest 2018; 153:1378–1386
9. Bergh C, Fall K, Udumyan R, et al. Severe infections and subsequent delayed cardiovascular disease. Eur J Prev Cardiol 2017; 24:1958–1966
10. Yende S, Linde-Zwirble W, Mayr F, et al. Risk of cardiovascular events in survivors
of severe sepsis. Am J Respir Crit Care Med 2014; 189:1065–1074
11. Neff TA, Stocker R, Frey HR, et al. Long-term assessment of lung function in survivors
of severe ARDS. Chest 2003; 123:845–853
12. Heyland DK, Groll D, Caeser M. Survivors
of acute respiratory distress syndrome: Relationship between pulmonary dysfunction and long-term health-related quality of life. Crit Care Med 2005; 33:1549–1556
13. Kellum JA, Sileanu FE, Bihorac A, et al. Recovery after acute kidney injury. Am J Respir Crit Care Med 2017; 195:784–791
14. Hotchkiss RS, Monneret G, Payen D. Sepsis-induced immunosuppression: From cellular dysfunctions to immunotherapy. Nat Rev Immunol 2013; 13:862–874
15. Jackson JC, Pandharipande PP, Girard TD, et al.; Bringing to Light the Risk Factors and Incidence of Neuropsychological Dysfunction in ICU Survivors
(BRAIN-ICU) Study Investigators: Depression, post-traumatic stress disorder, and functional disability in survivors
of critical illness
in the BRAIN-ICU study: A longitudinal cohort study. Lancet Respir Med 2014; 2:369–379
16. Iwashyna TJ, Ely EW, Smith DM, et al. Long-term cognitive impairment and functional disability among survivors
of severe sepsis. JAMA 2010; 304:1787–1794
17. Herridge MS, Tansey CM, Matté A, et al.; Canadian Critical Care Trials Group: Functional disability 5 years after acute respiratory distress syndrome. N Engl J Med 2011; 364:1293–1304
18. Fan E, Dowdy DW, Colantuoni E, et al. Physical complications in acute lung injury survivors
: A two-year longitudinal prospective study. Crit Care Med 2014; 42:849–859
19. Pandharipande PP, Girard TD, Jackson JC, et al.; BRAIN-ICU Study Investigators: Long-term cognitive impairment after critical illness
. N Engl J Med 2013; 369:1306–1316
20. Vermeiren S, Vella-Azzopardi R, Beckwée D, et al.; Gerontopole Brussels Study Group: Frailty
and the prediction of negative health outcomes: A meta-analysis. J Am Med Dir Assoc 2016; 17:1163.e1–1163.e17
21. Fried LP, Tangen CM, Walston J, et al.; Cardiovascular Health Study Collaborative Research Group: Frailty
in older adults: Evidence for a phenotype. J Gerontol A Biol Sci Med Sci 2001; 56:M146–M156
22. Cesari M, Vellas B, Hsu FC, et al.; LIFE Study Group: A physical activity intervention to treat the frailty
syndrome in older persons-results from the LIFE-P study. J Gerontol A Biol Sci Med Sci 2015; 70:216–222
23. Gill TM, Baker DI, Gottschalk M, et al. A prehabilitation program for physically frail community-living older persons. Arch Phys Med Rehabil 2003; 84:394–404
24. Ng TP, Feng L, Nyunt MS, et al. Nutritional, physical, cognitive, and combination interventions and frailty
reversal among older adults: A randomized controlled trial. Am J Med 2015; 128:1225–1236.e1
25. Hogan DB, Maxwell CJ, Afilalo J, et al. A scoping review of frailty
and acute care in middle-aged and older individuals with recommendations for future research. Can Geriatr J 2017; 20:22–37
26. Ely EW; MIND-ICU Study: Delirium and Dementia in Veterans Surviving ICU Care.Available at: https://clinicaltrials.gov/ct2/show/NCT00400062
. Accessed August 31, 2012
27. Rockwood K, Song X, MacKnight C, et al. A global clinical measure of fitness and frailty
in elderly people. CMAJ 2005; 173:489–495
28. Rockwood K, Fox RA, Stolee P, et al. Frailty
in elderly people: An evolving concept. CMAJ 1994; 150:489–495
29. Katz S, Ford AB, Moskowitz RW, et al. Studies of illness in the aged. The index of ADL: A standardized measure of biological and psychosocial function. JAMA 1963; 185:914–919
30. Randolph C, Tierney MC, Mohr E, et al. The Repeatable Battery for the Assessment of Neuropsychological Status (RBANS): Preliminary clinical validity. J Clin Exp Neuropsychol 1998; 20:310–319
31. Marra A, Pandharipande PP, Girard TD, et al. Co-occurrence of post-intensive care syndrome problems among 406 survivors
of critical illness
. Crit Care Med 2018; 46:1393–1401
32. Charlson ME, Pompei P, Ales KL, et al. A new method of classifying prognostic comorbidity in longitudinal studies: Development and validation. J Chronic Dis 1987; 40:373–383
33. Pfeffer RI, Kurosaki TT, Harrah CH Jr, et al. Measurement of functional activities in older adults in the community. J Gerontol 1982; 37:323–329
34. Ely EW, Inouye SK, Bernard GR, et al. Delirium in mechanically ventilated patients: Validity and reliability of the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU). JAMA 2001; 286:2703–2710
35. Ely EW, Truman B, Shintani A, et al. Monitoring sedation status over time in ICU patients: Reliability and validity of the Richmond Agitation-Sedation Scale (RASS). JAMA 2003; 289:2983–2991
36. Levy MM, Fink MP, Marshall JC, et al.; SCCM/ESICM/ACCP/ATS/SIS: 2001 SCCM/ESICM/ACCP/ATS/SIS International Sepsis Definitions Conference. Crit Care Med 2003; 31:1250–1256
37. Vincent JL, Moreno R, Takala J, et al.; On behalf of the Working Group on Sepsis-Related Problems of the European Society of Intensive Care Medicine. The SOFA (Sepsis-related Organ Failure Assessment) score to describe organ dysfunction/failure. Intensive Care Med 1996; 22:707–710
38. Vasilevskis EE, Pandharipande PP, Graves AJ, et al. Validity of a Modified Sequential Organ Failure Assessment score using the Richmond Agitation-Sedation Scale. Crit Care Med 2016; 44:138–146
39. Mansournia MA, Altman DG. Inverse probability weighting. BMJ 2016; 352:i189
40. Seaman SR, White IR. Review of inverse probability weighting for dealing with missing data. Stat Methods Med Res 2013; 22:278–295
41. Little RJ, D’Agostino R, Cohen ML, et al. The prevention and treatment of missing data in clinical trials. N Engl J Med 2012; 367:1355–1360
42. Geense W, Zegers M, Dieperink P, et al. Changes in frailty
among ICU survivors
and associated factors: Results of a one-year prospective cohort study using the Dutch Clinical Frailty
Scale. J Crit Care 2020; 55:184–193
43. Hope AA, Ng Gong M. Discordance about frailty
diagnosis between surrogates and physicians and its relationship to hospital mortality in critically ill older adults. J Frailty
Aging 2019; 8:176–179
44. Hope AA, Munoz M, Hsieh SJ, et al. Surrogates’ and researchers’ assessments of prehospital frailty
in critically ill older adults. Am J Crit Care 2019; 28:117–123
45. Gill TM, Gahbauer EA, Han L, et al. The relationship between intervening hospitalizations and transitions between frailty
states. J Gerontol A Biol Sci Med Sci 2011; 66:1238–1243
46. Belsky DW, Caspi A, Houts R, et al. Quantification of biological aging in young adults. Proc Natl Acad Sci U S A 2015; 112:E4104–E4110
47. Levine ME. Modeling the rate of senescence: Can estimated biological age predict mortality more accurately than chronological age? J Gerontol A Biol Sci Med Sci 2013; 68:667–674
48. Malmstrom TK, Miller DK, Morley JE. A comparison of four frailty
models. J Am Geriatr Soc 2014; 62:721–726
49. Xue QL, Tian J, Walston JD, et al. Discrepancy in frailty
identification: Move beyond predictive validity. J Gerontol A Biol Sci Med Sci 2020; 75:387–393
50. Walston JD, Bandeen-Roche K. Frailty
: A tale of two concepts. BMC Med 2015; 13:185