ORIGINAL ARTICLE
Feasibility of screening for preinjury frailty in hospitalized injured older adults Cathy A. Maxwell, PhD, Lorraine C. Mion, PhD, Kaushik Mukherjee, MD, Mary S. Dietrich, PhD, Ann Minnick, PhD, Addison May, MD, and Richard S. Miller, MD, Nashville, Tennessee
Frailty assessment of injured older adults (IOAs) is important for clinical management; however, the feasibility of screening for preinjury frailty has not been established in a Level I trauma center. The aims of our study were to assess enrollment rates of IOAs and their surrogates as well as completion rates of selected brief frailty screening instruments. METHODS: We conducted a prospective cohort study on patients, age 65 years and older with a primary injury diagnosis. Patients and/or surrogates were interviewed within 48 hours of admission using the Vulnerable Elders Survey (VES-13), Barthel Index (BI), and the Life Space Assessment (LSA). Data analysis included frequency distributions, W2 statistics, Mann-Whitney and Kruskal-Wallis tests, and general linear modeling (analysis of variance). RESULTS: Of 395 admitted patients, 188 were enrolled with subsequent surrogate screening. Corresponding patient interviews were conducted for 77 patients (41%). Screening time was less than 5 minutes for each instrument, and item completion was 100%. Forty-two enrolled patients (22%) had nurse-reported delirium, and 69 (37%) patients either did not feel like answering questions or were unable to be interviewed secondary to their medical condition. The median score of surrogate responses for the VES-13 was 3.5 (interquartile range, 2Y7), with 64% of the sample having a score of 3 or greater, indicating vulnerability or frailty. Median scores for the BI (19.0) and LSA (56.0) indicated high numbers with limitations in activities of daily living and limitations in mobilization. CONCLUSION: Screening for preinjury frailty in IOAs is feasible yet highly dependent on the presence of a surrogate respondent. A clinically significant percentage of patients have functional deficits consistent with frailty, dependence in activities of daily living, and limitations in mobilization. Implementation of validated brief screening instruments to identify frailty in clinical settings is warranted for targeting timely, efficient, and effective care interventions. (J Trauma Acute Care Surg. 2015;78: 844Y851. Copyright * 2015 Wolters Kluwer Health, Inc. All rights reserved.) LEVEL OF EVIDENCE: Epidemiologic study, level II. KEY WORDS: Frailty; screening; trauma; injury; geriatric. BACKGROUND:
F
railty is a syndrome of vulnerability involving domains of functional status, deficit accumulation, and biologic indices.1 It places patients at risk for poor outcomes following even minor illness or injury and is predictive of mortality, postoperative complications, and discharge to skilled nursing facilities.2,3 Frailty assessment is needed in clinical care; Clegg et al.4 called for instruments that are clinically sensible, are multidimensional, and can facilitate goal-directed care. A number of valid and reliable instruments, including the Vulnerable Elders Survey (VES-13),5,6 assessment of activities of daily living (ADLs),7 the frailty index (FI),8,9
Submitted: August 11, 2014, Revised: November 21, 2014, Accepted: November 24, 2014, Published online: March 4, 2015. From the School of Nursing (C.A.M., L.C.M., M.S.D., A.Mi.) and Division of Trauma and Surgical Critical Care (K.M., A.Ma., R.S.M.), Vanderbilt University Medical Center, Nashville, Tennessee. This study was presented as a poster at the 73rd annual meting of the American Association for the Surgery of Trauma, September 9Y13, 2014, in Philadelphia, Pennsylvania. Address for reprints: Richard S. Miller, MD, Division of Trauma and Surgical Critical Care, Vanderbilt University Medical Center, 404 Medical Arts Bldg, 1211 Medical Center Dr, Nashville, TN 37212; email: [email protected]. DOI: 10.1097/TA.0000000000000551
ambulatory status,10 the Barthel Index (BI),3 and the Life Space Assessment (LSA),11 have been used to assess for and quantify degree of frailty in older adults. Although studies have highlighted the need for frailty assessment, they have not addressed the following several issues that affect injured older patients: (1) the inability to respond to questions because of altered consciousness, pain, dementia, and sedation; (2) the length of time required for assessment; and (3) a potentially overwhelming response burden to patients and/or their surrogates, especially at the time of admission. The need to determine the feasibility of assessing preexisting frailty among hospitalized injured older adults (IOAs) prompted this study. As part of a larger study to evaluate the influence of preinjury impairments on care processes and outcomes (soon to conclude), we determined the following aims related to assessment: (a) enrollment rates of hospitalized IOA patients and surrogates, and (b) completion rates of selected brief screening instruments by IOA patients and their surrogates. We hypothesized that brief screening instruments could be used to assess frailty in acutely injured geriatric patients. In addition, we explored the characteristics of this sample by type of admitting service (trauma, geriatrics, orthopedics) to guide future estimation of recruitment by service. J Trauma Acute Care Surg Volume 78, Number 4
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PATIENTS AND METHODS After obtaining approval from the Vanderbilt University Institutional Review Board (#130992), we began a prospective cohort study of English-speaking patients, age 65 years and older, who were treated in the emergency department of a Level I trauma center with a primary injury diagnosis and admitted to the hospital. Permission was obtained to approach patients admitted to three services (trauma, geriatrics, and orthopedics) between October 1, 2013, and March 31, 2014. Patients and/or their surrogates were enrolled within 48 hours of admission.
Instruments More than 30 instruments were reviewed before selection for the study. Selection of instruments was based on our interest in multidimensionality as well as the potential for future use by bedside providers. Criteria for instrument selection included the following: administration time of 5 minutes or less, psychometric properties established in other older populations, availability, no cost, use in inpatient settings, and usable with both patients and surrogate respondents. Table 1 provides a summary of selected instruments. The VES-13 is a 13-item instrument that assigns points to four categories or domains as follows: age, self-rated health, common physical tasks, and ADLs.12 Scores range from 0 to 10, with a score of 3 or greater indicating vulnerability or frailty or a 2-year risk for further functional decline and death.12 Min et al.5 found that in IOAs, each additional point greater than 3 was associated with greater risk of complication or death. The VES-13 has a sensitivity of 67% to 87% and specificity of 62% to 86% for identifying impairments in older populations, as compared with impairments identified through comprehensive geriatric assessment.13Y16 Although the VES13 was developed for use with patient respondents, other studies5,6,17,18 have used the instrument with proxy/surrogate respondents. The BI is a 10-item instrument that assesses 10 ADLs on a scale that ranges from 0 to 20, with a score of 20 indicating no disability and lower scores indicating partial-to-full dependence.19,20 Kim et al.3 used the BI to assess physical function in moderate- to high-risk older surgical patients and found that dependence in ADLs and instrumental ADLs
(e.g., housekeeping, shopping) was associated with mortality. A recent meta-analysis21 reported excellent interrater agreement (J = 0.93) in varied rater populations and stroke patients. The LSA is built on the work of Stalvey et al.22 yet is distinct in that it determines a patient’s usual pattern of movement within the community and environment during the month preceding the assessment by determining how far and how often the person leaves his home and the degree of independence.23 Restricted life space reflects actual mobility within the community22,24 and is associated with impaired physical function.25 Five questions establish movement from within ‘‘life spaces’’ ranging from one’s own home to places outside of one’s town. The frequency of movement and need for assistive devices or personal assistance are also assessed. A composite score ranges from 0 to 120, with higher scores indicating greater independence. Older adults who experienced falls over 4 years had lower baseline scores.11 A recent study26 reported statistically significant agreement with an intraclass correlation of 0.88 (p G 0.01) between community-residing older adults and proxy respondents. Although not a measure of frailty, two questions from the Paffenbarger Physical Activity Questionnaire27 were included as a covariate. One question (#5 in the actual measure) asks, ‘‘At least once a week, do you engage in regular activity akin to brisk walking, jogging, bicycling, swimming, etc. long enough to work up a sweat, get your heart thumping, or get out of breath?’’ The other question (#8 in actual measure) ranks activity in a typical 24-hour day in five categories as follows: sleeping or reclining, sitting activity, light activity, moderate activity, and vigorous activity. Based on the Harvard Alumni Health Study of more than 13,000 participants, Lee and Paffenbarger28 reported that vigorous activity predicted lower mortality rates. A recent study29 demonstrated good predictive validity compared with health/fitness measurements (r = j0.27 to 0.20, p G 0.05).
Procedures Before the study, research assistants (RAs) received 8 hours of training in patient/surrogate enrollment and instrument administration. All RAs were registered nurses. Practice screening was conducted in the hospital with older patients until
TABLE 1. Summary of Brief Screening Instruments Instrument VES-13
Strength mobility
BI
Physical disability ADLs Mobility Mobility Function
LSA
Cost
Use With Proxy Respondents
Settings
Time to Administer
Sensitivity, 0.67Y.87 Specificity, 0.62Y0.86 J = 0.93
Free
Yes
Community inpatient
2 min
Online RAND Health
Free
Yes
Inpatient Long-term care
4 min
Online
Intraclass correlation, 0.88 Test/retest, 0.96
Free
Yes
Inpatient subacute
5 min
UAB* Center for Aging
Domains
Psychometrics
Availability
*University of Alabama at Birmingham.
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interrater agreement with the principal investigator reached a 95% level. We conducted screening over a 6-month period. RAs determined patient eligibility before approaching patients and/ or surrogates for enrollment. A surrogate was defined as a patient representative who had known the patient for at least 5 years and who lived with the patient or spent at least 4 hours per week with the patient. Surrogate eligibility criteria were based on consultation with our geriatric content expert (L.C.M.) who has conducted multiple studies requiring surrogate respondents. Before speaking with a patient or surrogate, the RAs asked the patient’s nurse if the patient had experienced acute confusion or delirium and if the nurse felt it was appropriate to approach. If nurse-reported or RA-observed patient delirium, acute confusion or drowsiness, or medical condition precluded a patient interview, then only the surrogate was approached. If both patient and surrogate were interviewed, the surrogate was questioned separately. The patient was excluded from the study if the surrogate was not available within 48 hours after admission because the main study required surrogate participation. Demographics (age, sex, race, and ethnicity), living location (house/apartment, assisted living, skilled nursing facility), and living arrangements (alone, with a spouse, or with others) as well as the Paffenbarger activity information were obtained from either the patient or the surrogate. The brief screening instruments were administered to patients and/or their surrogates. Patients and surrogates were asked to answer based on the patient’s preinjury status, defined as 2 weeks preceding the causal injury for admission. Upon discharge from the hospital, other variables, including comorbidities, injury severity, discharge disposition, and advanced directive (do-not-resuscitate [DNR]) status, were obtained from the patient’s medical record. Comorbidities were derived from DRG International Classification of DiseasesV9th Rev. codes and categorized according to the Elixhauser comorbidity classification system that identifies 29 distinct conditions.30 Point values were assigned to comorbidities based on the work of van Walraven et al.31 that identified independent associations of various comorbidities with inpatient mortality. Points were summed to
create a cumulative score or Elixhauser comorbidity index. Injury Severity Scores (ISSs) were calculated according to the American Association for Automotive Medicine Abbreviated Injury Scale (AIS).32 The principal investigator (trained in AIS coding) calculated ISS from injuries documented in the medical record.
Statistical Analysis Data were entered into SPSS 20.0 for analysis.33 Frequency distributions were used to summarize the nominal (e.g., sex, injury mechanism) and ordinal (e.g., age group) variables. Comparisons of these data distributions between enrolled and unenrolled as well as among admitting services were conducted using Pearson W2 statistics with Bonferroni-corrected post hoc tests for statistically significant findings. All of the continuous variables either had a floor effect (e.g., age) or were severely positively skewed (e.g., Comorbidity Index, Injury Severity). These variables were summarized with the median and 25th to 75th interquartile range (IQR). Mann-Whitney U-tests were used to compare the unenrolled patients with those enrolled. Comparisons among the admitting services were conducted using Kruskal-Wallis tests and confirmed using general linear modeling (analysis of variance [ANOVA]) of transformed data. Pairwise post hoc tests of the overall statistically significant findings were conducted within the ANOVA framework using Dunnett CYcorrected >’s. With the exception of the corrections for post hoc tests as noted, an > level of 0.05 (p G 0.05) was used for determining statistical significance.
RESULTS Patient Enrollment and Characteristics Over the 6-month enrollment period, 395 IOAs were admitted to one of three services (Fig. 1). One patient was ineligible because both the patient and surrogate were nonYEnglish speaking. Two hundred six (52%) were not enrolled: 77 (19%) declined enrollment, and 23 (6%) were excluded because nurses recommended not approaching for individual reasons (e.g., family
Figure 1. Study cohort: admissions and enrollments. 846
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grief, enrolled in another study). For the remaining 106 unenrolled patients (27%), exclusion from the study was based on inability to interview the patient or surrogate within 48 hours for a variety of reasons (patient unavailable [e.g., off unit, visitors present]), patient condition, early discharge, surrogate unavailable). Characteristics of the enrolled sample (n = 188) and those not enrolled (n = 207) are shown (Table 2). With the exception of admitting service, there were no statistically significant differences in the demographic characteristics of the two groups (Table 2). The median age of the enrolled patients was 77.0 years (IQR, 69Y86 years). More than half (58%) were 75 years or older. Slightly more than half of the sample was female (56%). Fifty-two percent were admitted for a fall from standing. As noted in Table 2, compared with the unenrolled sample, a higher percentage was admitted to the trauma service (76% vs. 65%) with a corresponding lower percentage admitted to orthopedics (13% vs. 22%, p = 0.39).
Characteristics of enrolled patients by admitting service are shown in Table 3. As noted earlier, approximately 56% were female, most were white (93%), admitted from home or apartment (89%), and lived with others (73%). The median comorbidity index value was 3.0 (IQR, 0Y9; minimum, 7; maximum, 27). There were no statistically significant differences in the distributions of these characteristics among the admitting services. Injured older patients admitted to the trauma service were younger than those admitted to the geriatric
TABLE 2. Characteristics of the Study Sample of IOAs (N = 395)
Age, median (IQR) Admitting service Trauma Geriatrics Orthopedics Sex Female Male Mechanism of injury Fall from standing Fall from other MVCYdriver MVCYpassenger Pedestrian struck Gunshot wound Stabbing Other
77.0 (69Y86) n (%) 278 (70.4) 48 (12.2) 69 (17.5) 210 (53.2) 185 46.8) 210 (53.2) 50 (12.7) 76 (19.2) 15 (3.8) 6 (1.5) 5 (1.3) 1 (0.3) 32 (8.1)
Enrolled (n = 188)
Unenrolled (n = 207)
p
77.0 (69Y86) 78.0 (70Y85) 0.557* n (%) n (%) 0.039** 143 (76.1) 135 (65.2) 21 (11.2) 27 (13.0) 24 (12.8) 45 (21.7) 0.222† 106 (56.4) 104 (49.8) 82 (43.6) 103 (50.2) 0.285‡ 97 (51.6) 113 (54.6) 26 (13.8) 24 (11.6) 38 (20.2) 38 (18.4) 10 (5.3) 5 (2.4) 3 (1.6) 3 (1.4) 0 (0.0) 5 (2.4) 0 (0.0) 1 (0.5) 14 (7.4) 18 (8.7)
*Mann-Whitney test, z = 0.66. **Pearson W22 = 6.47. †Pearson W21 = 1.49. ‡Pearson W27 = 8.57. MVC, motor vehicle crash.
Patient Preinjury Activity Level Ninety-six percent of the patients or surrogates (n = 180) responded to at least some of the Paffenbarger Physical Activity questions (Table 3). Twenty-nine percent (50 of 180) engaged in weekly activity that increased their heart rate and respirations. There was a statistically significant interaction effect of activity level and admitting service on the reported daily activity (p = 0.026, Table 3). Median daily time spent in vigorous, moderate, or light activity before the injury was statistically significantly greater for those patients admitted to trauma and orthopedic services (Bonferroni-corrected p G 0.05). Conversely, patients admitted to the geriatric service reported spending greater time during an average work day in sitting and/ or reclining activities (Table 3).
Injury Mechanism and Severity
Patient Characteristics by Admitting Service
Total (N = 395)
service (median ages 71 years [IQR, 67Y86] vs. 84 years [IQR, 78Y88]; post hocYcorrected p G 0.05).
As would be expected, those admitted to the trauma service had statistically significantly higher injury severity (median 13; IQR, 9Y19) than did those patients admitted to either the orthopedic or the geriatric services (median, 9 [IQR, 4Y9] and 4 [IQR, 1Y9], respectively; p G 0.001; Table 4). Analysis of AIS injury severity scores by body region showed head/neck injuries in 51% of patients (95 of 188), followed by extremity injuries in 44% (82 of 188). Other regions in descending order of prevalence were chest (36%, 68 of 188), abdomen (20%, 38 of 188), external (14%, 27 of 188), and face (13%, 25 of 188). As displayed in Table 4, patients admitted to trauma had statistically significantly higher AIS head/neck, chest, and abdomen severity scores than did those admitted to orthopedics or geriatrics (p G 0.05). To the contrary, patients admitted to orthopedics had higher AIS extremity injury scores than those admitted to trauma or geriatrics. Finally, there was a statistically significant difference among all the services in the distribution of injury mechanism (p = 0.029). Most of the patients admitted to the geriatric service were injured via falls from standing (17 of 19, 90%), while only 47% (67 of 143) admitted to the trauma service were injured in that manner. Conversely, 25% (35 of 142) admitted to trauma were injured as the driver in motor vehicle crashes, while only 4% (1 of 27) were injured in that way within the orthopedic service (Table 4).
Advance Care Directives and Discharge Disposition Patient advanced directive (DNR) status and discharge disposition are also summarized in Table 4. Forty-eight patients had a DNR status in the medical record, and 28 (58%) of those 48 received palliative care consults during hospitalization. A higher percentage of patients admitted to the geriatric service had a DNR status compared with those admitted on the orthopedic service. Eighty-nine percent (n = 167) of the patients were admitted from a home setting; of these, 53 (28%) returned home. Eighteen patients (10%) died in the hospital, and 117 (62%) were discharged to a facility other than home. Of the discharges other than home, the highest percentage was discharge to a
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TABLE 3. Characteristics of Enrolled Patients by Admitting Service (n = 188)
Characteristic Age Comorbidity Index Age group 65Y74 75Y84 85+ Sex Female Male Race/ethnicity White Black Asian Hispanic Living location House/apartment Assisted living Skilled nursing facility Living arrangement Lives alone Lives with spouse only Lives with others At least once a week, do you engage in regular activity to get your heart thumping or get out of breath? (n = 175) Weekday activity† (h/d) Vigorous Moderate Light Sitting Reclining/sleeping
Total (n = 188)
Trauma Service (n = 142)
Geriatric Service (n = 19)
Orthopedic Service (n = 27)
Median (IQR)
Median (IQR)
Median (IQR)
Median (IQR)
p
77 (69Y86) 3 (0Y9) n (%)
77 (69Y83) 3 (0Y9) n (%)
71 (67Y86) 2 (0Y7) n (%)
0.021* 0.094
78 (41.5) 61 (32.4) 49 (26.1)
60 (42.3) 50 (35.2) 32 (22.5)
3 (15.8) 7 (36.8) 9 (47.4)
15 (55.6) 4 (14.8) 8 (29.6)
106 (56.4) 82 (43.6)
81 (57.0) 61 (43.0)
10 (52.6) 9 (47.4)
15 (55.6) 12 (44.4)
175 (93.1) 12 (6.4) 1 (0.5) 0 (0.0)
134 (94.4) 7 (4.9) 1 (0.7) 0 (0.0)
16 (84.2) 3 (15.8) 0 (0.0) 0 (0.0)
25 (92.6) 2 (7.4) 0 (0.0) 0 (0.0)
167 (88.9) 14 (7.4) 7 (3.7)
128 (90.1) 9 (6.3) 5 (3.5)
15 (78.9) 3 (15.8) 1 (5.3)
24 (88.9) 2 (7.4) 1 (3.7)
84 (78Y88) 7 (3Y13) n (%)
0.022**
0.932
0.454
0.666
0.587 51 88 49 50
(27.1) (46.8) (26.1) (27.8)
42 (39.6) 65 (45.8) 35 (24.6) 38 (27.9)
4 (21.1) 8 (42.1) 7 (36.8) 3 (16.7)
5 15 7 9
(18.5) (55.6) (25.9) (34.6)
0.0 0.0 4.0 8.0 8.0
(0Y0) (0Y3) (2Y6) (6Y12) (7Y10)
0.0 (0Y0) 0.0 (0Y4) 4.0 (2Y6) 8.0 (5Y12) 8.0 (7Y10)
0.0 (0Y0) 0.0 (0Y0) 2.0 (1Y4) 11.0 (8Y14) 9.5 (8Y12)
0.0 1.0 4.5 7.5 8.0
(0Y1) (0Y5) (1Y7) (4Y12) (6Y10)
0.424 0.026‡
*ANOVA transformed data: F2,185 = 3.97, post hoc Dunnett CYcorrected p G 0.05, trauma G geriatrics. **Pearson W24 = 11.49; post hoc BonferroniYcorrected p G 0.05; 65Y74, geriatric G orthopedics. †ANOVA transformed data: F2,185 = 30.18, post hoc Dunnett C-corrected p G 0.05, orthopedics > trauma, geriatrics. ‡Statistically significant interaction effect of activity and admitting service; mixed-effects general linear modeling, log-link function: Wald W27 = 15.87, post hoc Bonferroni-corrected p G 0.05; vigorous, moderate, light activity: geriatric G trauma, orthopedic; sitting, relining activity: geriatric 9 trauma, orthopedic.
skilled nursing facility (33%, 62 of 188), followed by discharge to a rehabilitation facility (26%, 48 of 188). No statistically significant differences were observed in these rates among the three services (p = 0.299, Table 4).
Patient and Surrogate Interviews Of the 188 patients, 77 (41.0%) could be interviewed. Of the remaining 111 patients (59.0%) who could not be interviewed, 42 (37.8%) were reported by patients’ nurses to have confusion or delirium and thus unable to complete the measures. The other 69 patients (62.2%) either did not feel like answering questions or were unable to be interviewed secondary to their medical condition. The distribution of the relationship of the surrogate to the patient for the entire sample (n = 188) included the following: spouse (66, 35%), child (101, 54%), sibling (6, 3%), grandchild 848
(4, 2%), parent/mother (1, G1%), and other relative or friend (10, 5%).
Measures of Preinjury Frailty A summary of the scores on the preinjury frailty measures completed by surrogates and patients are shown in Table 5. All surrogates and patients who completed the instruments did so with no missing items. As shown, the median score of surrogate responses for the VES-13 was 3.5 (IQR, 2Y7). Sixtyfour percent of those scores were at least 3, indicating a report by the surrogate of vulnerability or frailty. Median score from the surrogates on the BI was 19 (IQR, 17Y20), indicating that many patients have some level of dependency in at least one ADL. Finally, the LSA median score from the surrogates was 56 (IQR, 33Y80), placing those scores in the middle-to-lower portion of the possible range of 0 to 120 on that measure. * 2015 Wolters Kluwer Health, Inc. All rights reserved.
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TABLE 4. Injury, Advanced Directives, and Discharge Status of Enrolled Patients by Admitting Service (n = 188) Total (n = 188)
Trauma Service (n = 142)
Geriatric Service (n = 19)
Orthopedic Service (n = 27)
Characteristics
Median (IQR)
Median (IQR)
Median (IQR)
Median (IQR)
p
Injury severity AIS body region Head/neck Face Chest Abdomen Extremity External
10 (9Y17) Median (75th percentile, maximum) 1 (9, 25) 0 (0, 9) 0 (4, 16) 0 (0, 25) 0 (8, 16) 0 (0, 4) n (%)
13 (9Y19)
4 (1Y9)
9 (4Y9)
G0.001*
0 (4, 16) 0 (0, 4) 0 (0, 1) 0 (0, 4) 0 (1, 9) 0 (1, 1) n (%)
0 (0, 0) 0 (0, 1) 0 (0, 0) 0 (0, 0) 9 (9, 16) 0 (0, 1) n (%)
G0.001† 0.115 G0.001‡ 0.027§ G0.001¶ 0.320
Mechanism of injury Fall from standing Fall from other MVCYdriver MVCYPassenger Pedestrian MCC Other Advanced directive (DNR) Palliative care consult Discharge disposition Home Long-term acute care Rehabilitation Skilled nursing facility Assisted living facility Inpatient hospice Expired
4 (9, 25) 0 (0, 9) 0 (9, 16) 0 (2, 25) 0 (4, 16) 0 (0, 4) n (%)
0.029|| 102 (54.3) 24 (12.8) 37 (19.7) 10 (5.3) 3 (2.6) 2 (1.1) 10 (5.3) 48 (25.5) 28 (14.9)
67 (47.2) 18 (12.7) 35 (24.6) 10 (7.0) 3 (2.1) 2 (1.4) 7 (4.9) 38 (26.8) 24 (16.9)
17 (89.5) 1 (5.3) 1 (5.3) 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) 8 (42.1) 3 (15.8)
18 (66.7) 5 (18.5) 1 (3.7) 0 (0.0) 0 (0.0) 0 (0.0) 3 (11.1) 2 (7.4) 1 (3.7)
53 (28.2) 3 (1.6) 48 (25.5) 62 (33.0) 2 (1.1) 2 (1.1) 18 (9.6)
37 (26.1) 3 (2.1) 37 (26.1) 46 (32.4) 1 (0.7) 1 (0.7) 17 (12.0)
5 (26.3) 0 (0.0) 4 (21.1) 7 (36.8) 1 (5.3) 1 (5.3) 1 (5.3)
11 (40.7) 0 (0.0) 7 (25.9) 9 (33.3) 0 (0.0) 0 (0.0) 0 (0.0)
0.023†† 0.209 0.299
*ANOVA transformed data: F2,185 = 28.60, post hoc Dunnett CYcorrected p G 0.05, trauma G orthopedics. †ANOVA transformed data: F2,185 = 14.70, post hoc Dunnett CYcorrected p G 0.05, trauma 9 geriatrics 9 orthopedics. ‡ANOVA transformed data: F2,185 = 15.18, post hoc Dunnett CYcorrected p G 0.05, trauma 9 orthopedics, geriatrics. §ANOVA transformed data: F2,185 = 3.70, post hoc Dunnett CYcorrected p G 0.05, trauma 9 orthopedics, geriatrics. ¶ANOVA transformed data: F2,185 = 30.18, post hoc Dunnett CYcorrected p G 0.05, orthopedics 9 trauma, geriatrics. ||Pearson W212 = 22.86; post hoc Bonferroni-corrected p G 0.05, falls from standing: trauma G geriatrics, MVC driver: trauma 9 orthopedics. Total, n = 180; trauma, n = 136; geriatrics, n = 18; orthopedics, n = 26. Total, n = 175; trauma, n = 131; geriatrics, n = 18; orthopedics, n = 26. ††Pearson X22 = 7.52; post hoc Bonferroni-corrected p G 0.05, geriatric 9 orthopedic. DNR, do not resuscitate; MCC, motorcycle crash; MVC, motor vehicle crash.
Given that the 77 patients able to complete the frailty measures themselves would be expected to be higher functioning than those not able to (see reasons for not completing mentioned earlier), it was not surprising to note that their summary scores were slightly higher than those from the entire sample of surrogates on all three instruments (Table 4). Fifty-three percent (41 of 77) of that subsample had scores of 3 or greater on the VES-13 compared with 64% of the entire sample of patients as reported by surrogates (Table 5). Preinjury frailty by admitting services is presented in Table 6. Statistically significant differences among the services were observed on all of the measures of preinjury frailty (p G 0.05). In general, patients admitted to the geriatric service were considerably more frail before the injury than those admitted to the other services. Approximately 90% (17 of 19) of the
patients admitted to the geriatric service had a VES-13 score of 3 or greater (indicating frailty) compared with a respective percentage of 64% (91 of 142) to the trauma service and 56% (15 of 27) to the orthopedic services (Table 6).
DISCUSSION In this study, we examined whether it is feasible to collect preinjury measures of frailty in hospitalized IOAs. We were able to enroll half of those admitted and/or their surrogates. One-fifth of the cohort declined because it was a research study. The remaining 30% of the cohort were not enrolled because of research personnel’s inability to contact and obtain informed consent within 48 hours. Under normal circumstances,
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TABLE 5. Surrogate and Patient Summaries Brief Screening Instruments Related to Mobility/Physical Function Surrogates (n = 188) VES-13 Median (IQR; minimum, maximum) Scores Q 3,* n (%) BI Median (IQR; minimum, maximum) LSA Median (IQR; minimum, maximum)
3.50 (2Y7; 0, 10) 123 (65.4)
Patients (n = 77) 3.00 (1Y6; 0, 10) 41 (53.2)
19.0 (17Y20; 3, 20)
20.0 (18Y20; 7, 20)
56.0 (33Y80 0, 120)
62.0 (39Y82; 8, 100)
*Indicative of frailty.
it is reasonable to assume that clinicians would have more opportunities to administer brief screening instruments, particularly if completed along with other admission requirements. Future work is needed to assess the willingness of clinicians to screen patients or surrogates as well as the additional time required during admission procedures. Among enrolled patients, we were able to complete instruments on 77 patient-surrogate dyads (41%). For the remaining 111 patients (59%), surrogate-only interviews were necessary to obtain preinjury measures of frailty. Joseph et al.9 screened geriatric trauma patients for preinjury frailty and also required both patients and surrogate respondents at a Level I trauma center; however, they did not report the percentage of surrogates. Maxwell6 reported that 34% required surrogate reports for IOAs at a Level II trauma center and nontrauma center. Similar to other patient populations,34 the feasibility of screening for preinjury frailty using validated brief screening instruments necessitates the availability of surrogates in providing information on behalf of older patients. Reliance on surrogate-reported patient information related to frailty may be problematic; however, others have demonstrated good agreement between older patients and surrogates in assessments of ADLs (intraclass correlations, 0.61Y0.91).35
Importantly, we identified a significant percentage of frailty or functional deficits in our sample of IOAs. While there is, as yet, lack of consensus on a definition of frailty, it is clear that frailty is associated with physical function decline in multiple models of frailty.4,36 Fried et al.37 identified five phenotype model indicators (weight loss, exhaustion, low energy expenditure, slow gait speed, and weak grip strength). Rockwood et al.38 described a cumulative deficit model that identifies baseline variables (or deficits) associated with frailty. These deficits include long-term disabilities, help for shopping and household chores, walking difficulty, dexterity problems, less activity, and difficulty carrying light weights. The brief screening instruments used in this study incorporate variables from both frailty models and may serve as a starting point for the identification of frailty by clinicians. The use of these screening instruments along with other pertinent variables (i.e., cognitive measures, comorbidities, injury severity) may facilitate development of geriatric trauma prediction models. Such models could provide research-based guidance for clinicians to facilitate survival prognostication and postinjury decision making. This study has both strengths and limitations. First, although the VES-13 was designed for patient self-report, the instrument was used with surrogate respondents in this and other studies5,6,17,18 in the absence of patient-proxy validation. Of note, we have conducted an analysis of patient-proxy agreement from this sample (currently under peer review) that reports acceptable patient-proxy agreement. A second limitation is conduction of the study at a single site, thus limiting generalizability. Among its strengths, our prospective cohort design that included patients from three services allowed for a more accurate reflection of the population of IOAs and generalizability across settings regardless of trauma status. Methodologic rigor was used in the study design, training of RAs, and data collection practices. Frailty research in geriatric trauma is likely to increase in the coming years as researchers and clinicians clarify the concept of frailty. Given the high proportion of IOAs who did not return to the home setting, routine screening for preinjury frailty is warranted for the development of effective interventions. Our next steps include determining the influence of preinjury frailty on geriatric trauma outcomes, agreement
TABLE 6. Preinjury Frailty by Admitting Service (n = 188) Characteristic VES-13 Median (IQR) Score Q 3, n (%) BI Median (IQR) LSA Median (IQR)
Total (n = 188)
Trauma Service (n = 142)
Geriatric Service (n = 19)
Orthopedic Service (n = 27)
p
3.5 (2Y7) 123 (65.4)
3.0 (1Y7) 91 (64.1)
7.0 (5Y9) 17 (89.5)
3.0 (0Y7) 15 (55.6)
0.008* 0.047**
19.0 (17Y20)
19.0 (17Y20)
17.0 (15Y19)
20.0 (19Y20)
G0.001†
56.0 (33Y80)
60.0 (34Y80)
20.0 (19Y20)
74.0 (40Y84)
0.009‡
*ANOVA transformed data: F2,185 = 4.97, post hoc Dunnett CYcorrected p G 0.05, geriatrics 9 trauma, orthopedic. **Pearson W22 = 6.13; post hoc Bonferroni-corrected p G 0.05, geriatric 9 orthopedics. †ANOVA transformed data: F2,185 = 8.98, post hoc Dunnett CYcorrected p G 0.05, geriatrics G trauma, orthopedic. ‡ANOVA transformed data: F2,185 = 4.83, post hoc Dunnett CYcorrected p G 0.05, geriatrics G trauma, orthopedic.
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between patients and surrogates, and the feasibility of incorporating these screening instruments into provider workflow.
17.
AUTHORSHIP C.A.M., L.C.M., A.M., K.M., and R.S.M. designed this study. C.A.M. searched the literature and collected data. C.A.M. and M.S.D. analyzed the data. All authors participated in the data interpretation, manuscript writing, and revision.
18.
19.
DISCLOSURE
20.
The authors declare no conflicts of interest.
21.
REFERENCES
22.
1. Malmstrom TK, Miller DK, Morley JE. A comparison of four frailty models. J Am Geriatr Soc. 2014;62(4):721Y726. 2. Makary MA, Segev DL, Pronovost PJ, et al. Frailty as a predictor of surgical outcomes in older patients. J Am Coll Surg. 2010;210(6):901Y908. 3. Kim SW, Han HS, Jung HW, et al. Multidimensional frailty score for the prediction of postoperative mortality risk. JAMA Surg. 2014;149:633Y640. 4. Clegg A, Young J, Iliffe S, Rikkert MO, Rockwood K. Frailty in elderly people. Lancet. 2013;381(9868):752Y762. 5. Min L, Ubhayakar N, Saliba D, et al. The vulnerable elders survey-13 predicts hospital complications and mortality in older adults with traumatic injury: a pilot study. J Am Geriatr Soc. 2011;59(8):1471Y1476. 6. Maxwell CA. Screening hospitalized injured older adults for cognitive impairment and pre-injury functional impairment. Appl Nurs Res. 2013;26(3):146Y150. 7. Gill TM, Murphy TE, Gahbauer EA, Allore HG. The course of disability before and after a serious fall injury. JAMA Intern Med. 2013;173(19): 1780Y1786. 8. Joseph B, Pandit V, Rhee P, et al. Predicting hospital discharge disposition in geriatric trauma patients: is frailty the answer? J Trauma Acute Care Surg. 2014;76(1):196Y200. 9. Joseph B, Pandit V, Zangbar B, et al. Superiority of frailty over age in predicting outcomes among geriatric trauma patients: a prospective analysis. JAMA Surg. 2014;149:766Y772. 10. Ting B, Zurakowski D, Herder L, Wagner K, Appleton P, Rodriguez EK. Preinjury ambulatory status is associated with 1-year mortality following lateral compression type I fractures in the geriatric population older than 80 years. J Trauma Acute Care Surg. 2014;76(5):1306Y1309. 11. Lo AX, Brown CJ, Sawyer P, Kennedy RE, Allman RM. Life-space mobility declines associated with incident falls and fractures. J Am Geriatr Soc. 2014;62(5):919Y923. 12. Saliba D, Elliott M, Rubenstein LZ, et al. The Vulnerable Elders Survey: a tool for identifying vulnerable older people in the community. J Am Geriatr Soc. 2001;49(12):1691Y1699. 13. Smets IH, Kempen GI, Janssen-Heijnen ML, Deckx L, Buntinx FJ, van den Akker M. Four screening instruments for frailty in older patients with and without cancer: a diagnostic study. BMC Geriatr. 2014;14:26. 14. Biganzoli L, Boni L, Becheri D, et al. Evaluation of the cardiovascular health study (CHS) instrument and the Vulnerable Elders Survey-13 (VES-13) in elderly cancer patients. Are we still missing the right screening tool? Ann Oncol. 2013;24(2):494Y500. 15. Luciani A, Ascione G, Bertuzzi C, et al. Detecting disabilities in older patients with cancer: comparison between comprehensive geriatric assessment and vulnerable elders survey-13. J Clin Oncol. 2010;28(12):2046Y2050. 16. Mohile SG, Bylow K, Dale W, et al. A pilot study of the vulnerable elders survey-13 compared with the comprehensive geriatric assessment for
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identifying disability in older patients with prostate cancer who receive androgen ablation. Cancer. 2007;109(4):802Y810. Arora VM, Fish M, Basu A, et al. Relationship between quality of care of hospitalized vulnerable elders and postdischarge mortality. J Am Geriatr Soc. 2010;58(9):1642Y1648. Brand CA, Martin-Khan M, Wright O, et al. Development of quality indicators for monitoring outcomes of frail elderly hospitalised in acute care health settings: study protocol. BMC Health Serv Res. 2011;11(1):281. Sainsbury A, Seebass G, Bansal A, Young JB. Reliability of the Barthel Index when used with older people. Age Ageing. 2005;34(3):228Y232. Collin C, Wade DT, Davies S, Horne V. The Barthel ADL Index: a reliability study. Int Disabil Stud. 1988;10(2):61Y63. Duffy L, Gajree S, Langhorne P, Stott DJ, Quinn TJ. Reliability (inter-rater agreement) of the Barthel Index for assessment of stroke survivors: systematic review and meta-analysis. Stroke. 2013;44(2):462Y468. Stalvey BT, Owsley C, Sloane ME, Ball K. The Life Space Questionnaire: a measure of the extent of mobility of older adults. J Appl Gerontol. 1999;18(4):460Y478. Baker PS, Bodner EV, Allman RM. Measuring life-space mobility in community-dwelling older adults. J Am Geriatr Soc. 2003;51(11): 1610Y1614. Sawyer P, Allman R. Resilience in mobility in the context of chronic disease and aging: cross-sectional and prospective findings from the UAB Study of Aging. New Frontiers of Resilient Aging, Life Strengths and Wellness in Late Life. 2010:310Y339. Portegijs E, Iwarsson S, Rantakokko M, Viljanen A, Rantanen T. Lifespace mobility assessment in older people in Finland; measurement properties in winter and spring. BMC Res Notes. 2014;7(1):323. Cavanaugh JT, Crawford K. Life-Space Assessment and physical activity scale for the elderly: validity of proxy informant responses. Arch Phys Med Rehabil. 2014;95:1527Y1532. Paffenbarger RS Jr., Wing AL, Hyde RT. Physical activity as an index of heart attack risk in college alumni. Am J Epidemiol. 1978;108(3):161Y175. Lee IM, Paffenbarger RS Jr. Associations of light, moderate, and vigorous intensity physical activity with longevity. The Harvard Alumni Health Study. Am J Epidemiol. 2000;151(3):293Y299. Simpson K, Parker B, Capizzi J, et al. Validity and reliability question eight of the paffenbarger physical activity questionnaire among healthy adults. J Phys Act Health. 2014 [Epub ahead of print]. Elixhauser A, Steiner C, Harris DR, Coffey RM. Comorbidity measures for use with administrative data. Med Care. 1998;36(1):8Y27. van Walraven C, Austin PC, Jennings A, Quan H, Forster AJ. A modification of the Elixhauser comorbidity measures into a point system for hospital death using administrative data. Med Care. 2009;47(6):626Y633. Association for the Advancement of Automotive Medicine (AAAM). The abbreviated Injury Scale 2005 (Update 2008). Barrington, IL: AAAM. 2008. IBM SPSS Statistics for Windows. Armonk, NY: IBM Corp.; 2010. Derrett S, Black J, Herbison GP. Outcome after injury-a systematic literature search of studies using the EQ-5D. J Trauma. 2009;67(4):883Y890. Oczkowski C, O’Donnell M. Reliability of proxy respondents for patients with stroke: a systematic review. J Stroke Cerebrovasc Dis. 2010;19(5): 410Y416. Mohandas A, Reifsnyder J, Jacobs M, Fox T. Current and future directions in frailty research. Popul Health Manag. 2011;14(6):277Y283. Fried LP, Tangen CM, Walston J, et al. Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci. 2001;56(3):M146YM156. Rockwood K, Song X, MacKnight C, et al. A global clinical measure of fitness and frailty in elderly people. Can Med Assoc J. 2005;173(5): 489Y495.
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Feasibility of screening for preinjury frailty in hospitalized injured older adults Cathy A. Maxwell, PhD, Lorraine C. Mion, PhD, Kaushik Mukherjee, MD, Mary S. Dietrich, PhD, Ann Minnick, PhD, Addison May, MD, and Richard S. Miller, MD, Nashville, Tennessee
Frailty assessment of injured older adults (IOAs) is important for clinical management; however, the feasibility of screening for preinjury frailty has not been established in a Level I trauma center. The aims of our study were to assess enrollment rates of IOAs and their surrogates as well as completion rates of selected brief frailty screening instruments. METHODS: We conducted a prospective cohort study on patients, age 65 years and older with a primary injury diagnosis. Patients and/or surrogates were interviewed within 48 hours of admission using the Vulnerable Elders Survey (VES-13), Barthel Index (BI), and the Life Space Assessment (LSA). Data analysis included frequency distributions, W2 statistics, Mann-Whitney and Kruskal-Wallis tests, and general linear modeling (analysis of variance). RESULTS: Of 395 admitted patients, 188 were enrolled with subsequent surrogate screening. Corresponding patient interviews were conducted for 77 patients (41%). Screening time was less than 5 minutes for each instrument, and item completion was 100%. Forty-two enrolled patients (22%) had nurse-reported delirium, and 69 (37%) patients either did not feel like answering questions or were unable to be interviewed secondary to their medical condition. The median score of surrogate responses for the VES-13 was 3.5 (interquartile range, 2Y7), with 64% of the sample having a score of 3 or greater, indicating vulnerability or frailty. Median scores for the BI (19.0) and LSA (56.0) indicated high numbers with limitations in activities of daily living and limitations in mobilization. CONCLUSION: Screening for preinjury frailty in IOAs is feasible yet highly dependent on the presence of a surrogate respondent. A clinically significant percentage of patients have functional deficits consistent with frailty, dependence in activities of daily living, and limitations in mobilization. Implementation of validated brief screening instruments to identify frailty in clinical settings is warranted for targeting timely, efficient, and effective care interventions. (J Trauma Acute Care Surg. 2015;78: 844Y851. Copyright * 2015 Wolters Kluwer Health, Inc. All rights reserved.) LEVEL OF EVIDENCE: Epidemiologic study, level II. KEY WORDS: Frailty; screening; trauma; injury; geriatric. BACKGROUND:
F
railty is a syndrome of vulnerability involving domains of functional status, deficit accumulation, and biologic indices.1 It places patients at risk for poor outcomes following even minor illness or injury and is predictive of mortality, postoperative complications, and discharge to skilled nursing facilities.2,3 Frailty assessment is needed in clinical care; Clegg et al.4 called for instruments that are clinically sensible, are multidimensional, and can facilitate goal-directed care. A number of valid and reliable instruments, including the Vulnerable Elders Survey (VES-13),5,6 assessment of activities of daily living (ADLs),7 the frailty index (FI),8,9
Submitted: August 11, 2014, Revised: November 21, 2014, Accepted: November 24, 2014, Published online: March 4, 2015. From the School of Nursing (C.A.M., L.C.M., M.S.D., A.Mi.) and Division of Trauma and Surgical Critical Care (K.M., A.Ma., R.S.M.), Vanderbilt University Medical Center, Nashville, Tennessee. This study was presented as a poster at the 73rd annual meting of the American Association for the Surgery of Trauma, September 9Y13, 2014, in Philadelphia, Pennsylvania. Address for reprints: Richard S. Miller, MD, Division of Trauma and Surgical Critical Care, Vanderbilt University Medical Center, 404 Medical Arts Bldg, 1211 Medical Center Dr, Nashville, TN 37212; email: [email protected]. DOI: 10.1097/TA.0000000000000551
ambulatory status,10 the Barthel Index (BI),3 and the Life Space Assessment (LSA),11 have been used to assess for and quantify degree of frailty in older adults. Although studies have highlighted the need for frailty assessment, they have not addressed the following several issues that affect injured older patients: (1) the inability to respond to questions because of altered consciousness, pain, dementia, and sedation; (2) the length of time required for assessment; and (3) a potentially overwhelming response burden to patients and/or their surrogates, especially at the time of admission. The need to determine the feasibility of assessing preexisting frailty among hospitalized injured older adults (IOAs) prompted this study. As part of a larger study to evaluate the influence of preinjury impairments on care processes and outcomes (soon to conclude), we determined the following aims related to assessment: (a) enrollment rates of hospitalized IOA patients and surrogates, and (b) completion rates of selected brief screening instruments by IOA patients and their surrogates. We hypothesized that brief screening instruments could be used to assess frailty in acutely injured geriatric patients. In addition, we explored the characteristics of this sample by type of admitting service (trauma, geriatrics, orthopedics) to guide future estimation of recruitment by service. J Trauma Acute Care Surg Volume 78, Number 4
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PATIENTS AND METHODS After obtaining approval from the Vanderbilt University Institutional Review Board (#130992), we began a prospective cohort study of English-speaking patients, age 65 years and older, who were treated in the emergency department of a Level I trauma center with a primary injury diagnosis and admitted to the hospital. Permission was obtained to approach patients admitted to three services (trauma, geriatrics, and orthopedics) between October 1, 2013, and March 31, 2014. Patients and/or their surrogates were enrolled within 48 hours of admission.
Instruments More than 30 instruments were reviewed before selection for the study. Selection of instruments was based on our interest in multidimensionality as well as the potential for future use by bedside providers. Criteria for instrument selection included the following: administration time of 5 minutes or less, psychometric properties established in other older populations, availability, no cost, use in inpatient settings, and usable with both patients and surrogate respondents. Table 1 provides a summary of selected instruments. The VES-13 is a 13-item instrument that assigns points to four categories or domains as follows: age, self-rated health, common physical tasks, and ADLs.12 Scores range from 0 to 10, with a score of 3 or greater indicating vulnerability or frailty or a 2-year risk for further functional decline and death.12 Min et al.5 found that in IOAs, each additional point greater than 3 was associated with greater risk of complication or death. The VES-13 has a sensitivity of 67% to 87% and specificity of 62% to 86% for identifying impairments in older populations, as compared with impairments identified through comprehensive geriatric assessment.13Y16 Although the VES13 was developed for use with patient respondents, other studies5,6,17,18 have used the instrument with proxy/surrogate respondents. The BI is a 10-item instrument that assesses 10 ADLs on a scale that ranges from 0 to 20, with a score of 20 indicating no disability and lower scores indicating partial-to-full dependence.19,20 Kim et al.3 used the BI to assess physical function in moderate- to high-risk older surgical patients and found that dependence in ADLs and instrumental ADLs
(e.g., housekeeping, shopping) was associated with mortality. A recent meta-analysis21 reported excellent interrater agreement (J = 0.93) in varied rater populations and stroke patients. The LSA is built on the work of Stalvey et al.22 yet is distinct in that it determines a patient’s usual pattern of movement within the community and environment during the month preceding the assessment by determining how far and how often the person leaves his home and the degree of independence.23 Restricted life space reflects actual mobility within the community22,24 and is associated with impaired physical function.25 Five questions establish movement from within ‘‘life spaces’’ ranging from one’s own home to places outside of one’s town. The frequency of movement and need for assistive devices or personal assistance are also assessed. A composite score ranges from 0 to 120, with higher scores indicating greater independence. Older adults who experienced falls over 4 years had lower baseline scores.11 A recent study26 reported statistically significant agreement with an intraclass correlation of 0.88 (p G 0.01) between community-residing older adults and proxy respondents. Although not a measure of frailty, two questions from the Paffenbarger Physical Activity Questionnaire27 were included as a covariate. One question (#5 in the actual measure) asks, ‘‘At least once a week, do you engage in regular activity akin to brisk walking, jogging, bicycling, swimming, etc. long enough to work up a sweat, get your heart thumping, or get out of breath?’’ The other question (#8 in actual measure) ranks activity in a typical 24-hour day in five categories as follows: sleeping or reclining, sitting activity, light activity, moderate activity, and vigorous activity. Based on the Harvard Alumni Health Study of more than 13,000 participants, Lee and Paffenbarger28 reported that vigorous activity predicted lower mortality rates. A recent study29 demonstrated good predictive validity compared with health/fitness measurements (r = j0.27 to 0.20, p G 0.05).
Procedures Before the study, research assistants (RAs) received 8 hours of training in patient/surrogate enrollment and instrument administration. All RAs were registered nurses. Practice screening was conducted in the hospital with older patients until
TABLE 1. Summary of Brief Screening Instruments Instrument VES-13
Strength mobility
BI
Physical disability ADLs Mobility Mobility Function
LSA
Cost
Use With Proxy Respondents
Settings
Time to Administer
Sensitivity, 0.67Y.87 Specificity, 0.62Y0.86 J = 0.93
Free
Yes
Community inpatient
2 min
Online RAND Health
Free
Yes
Inpatient Long-term care
4 min
Online
Intraclass correlation, 0.88 Test/retest, 0.96
Free
Yes
Inpatient subacute
5 min
UAB* Center for Aging
Domains
Psychometrics
Availability
*University of Alabama at Birmingham.
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interrater agreement with the principal investigator reached a 95% level. We conducted screening over a 6-month period. RAs determined patient eligibility before approaching patients and/ or surrogates for enrollment. A surrogate was defined as a patient representative who had known the patient for at least 5 years and who lived with the patient or spent at least 4 hours per week with the patient. Surrogate eligibility criteria were based on consultation with our geriatric content expert (L.C.M.) who has conducted multiple studies requiring surrogate respondents. Before speaking with a patient or surrogate, the RAs asked the patient’s nurse if the patient had experienced acute confusion or delirium and if the nurse felt it was appropriate to approach. If nurse-reported or RA-observed patient delirium, acute confusion or drowsiness, or medical condition precluded a patient interview, then only the surrogate was approached. If both patient and surrogate were interviewed, the surrogate was questioned separately. The patient was excluded from the study if the surrogate was not available within 48 hours after admission because the main study required surrogate participation. Demographics (age, sex, race, and ethnicity), living location (house/apartment, assisted living, skilled nursing facility), and living arrangements (alone, with a spouse, or with others) as well as the Paffenbarger activity information were obtained from either the patient or the surrogate. The brief screening instruments were administered to patients and/or their surrogates. Patients and surrogates were asked to answer based on the patient’s preinjury status, defined as 2 weeks preceding the causal injury for admission. Upon discharge from the hospital, other variables, including comorbidities, injury severity, discharge disposition, and advanced directive (do-not-resuscitate [DNR]) status, were obtained from the patient’s medical record. Comorbidities were derived from DRG International Classification of DiseasesV9th Rev. codes and categorized according to the Elixhauser comorbidity classification system that identifies 29 distinct conditions.30 Point values were assigned to comorbidities based on the work of van Walraven et al.31 that identified independent associations of various comorbidities with inpatient mortality. Points were summed to
create a cumulative score or Elixhauser comorbidity index. Injury Severity Scores (ISSs) were calculated according to the American Association for Automotive Medicine Abbreviated Injury Scale (AIS).32 The principal investigator (trained in AIS coding) calculated ISS from injuries documented in the medical record.
Statistical Analysis Data were entered into SPSS 20.0 for analysis.33 Frequency distributions were used to summarize the nominal (e.g., sex, injury mechanism) and ordinal (e.g., age group) variables. Comparisons of these data distributions between enrolled and unenrolled as well as among admitting services were conducted using Pearson W2 statistics with Bonferroni-corrected post hoc tests for statistically significant findings. All of the continuous variables either had a floor effect (e.g., age) or were severely positively skewed (e.g., Comorbidity Index, Injury Severity). These variables were summarized with the median and 25th to 75th interquartile range (IQR). Mann-Whitney U-tests were used to compare the unenrolled patients with those enrolled. Comparisons among the admitting services were conducted using Kruskal-Wallis tests and confirmed using general linear modeling (analysis of variance [ANOVA]) of transformed data. Pairwise post hoc tests of the overall statistically significant findings were conducted within the ANOVA framework using Dunnett CYcorrected >’s. With the exception of the corrections for post hoc tests as noted, an > level of 0.05 (p G 0.05) was used for determining statistical significance.
RESULTS Patient Enrollment and Characteristics Over the 6-month enrollment period, 395 IOAs were admitted to one of three services (Fig. 1). One patient was ineligible because both the patient and surrogate were nonYEnglish speaking. Two hundred six (52%) were not enrolled: 77 (19%) declined enrollment, and 23 (6%) were excluded because nurses recommended not approaching for individual reasons (e.g., family
Figure 1. Study cohort: admissions and enrollments. 846
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grief, enrolled in another study). For the remaining 106 unenrolled patients (27%), exclusion from the study was based on inability to interview the patient or surrogate within 48 hours for a variety of reasons (patient unavailable [e.g., off unit, visitors present]), patient condition, early discharge, surrogate unavailable). Characteristics of the enrolled sample (n = 188) and those not enrolled (n = 207) are shown (Table 2). With the exception of admitting service, there were no statistically significant differences in the demographic characteristics of the two groups (Table 2). The median age of the enrolled patients was 77.0 years (IQR, 69Y86 years). More than half (58%) were 75 years or older. Slightly more than half of the sample was female (56%). Fifty-two percent were admitted for a fall from standing. As noted in Table 2, compared with the unenrolled sample, a higher percentage was admitted to the trauma service (76% vs. 65%) with a corresponding lower percentage admitted to orthopedics (13% vs. 22%, p = 0.39).
Characteristics of enrolled patients by admitting service are shown in Table 3. As noted earlier, approximately 56% were female, most were white (93%), admitted from home or apartment (89%), and lived with others (73%). The median comorbidity index value was 3.0 (IQR, 0Y9; minimum, 7; maximum, 27). There were no statistically significant differences in the distributions of these characteristics among the admitting services. Injured older patients admitted to the trauma service were younger than those admitted to the geriatric
TABLE 2. Characteristics of the Study Sample of IOAs (N = 395)
Age, median (IQR) Admitting service Trauma Geriatrics Orthopedics Sex Female Male Mechanism of injury Fall from standing Fall from other MVCYdriver MVCYpassenger Pedestrian struck Gunshot wound Stabbing Other
77.0 (69Y86) n (%) 278 (70.4) 48 (12.2) 69 (17.5) 210 (53.2) 185 46.8) 210 (53.2) 50 (12.7) 76 (19.2) 15 (3.8) 6 (1.5) 5 (1.3) 1 (0.3) 32 (8.1)
Enrolled (n = 188)
Unenrolled (n = 207)
p
77.0 (69Y86) 78.0 (70Y85) 0.557* n (%) n (%) 0.039** 143 (76.1) 135 (65.2) 21 (11.2) 27 (13.0) 24 (12.8) 45 (21.7) 0.222† 106 (56.4) 104 (49.8) 82 (43.6) 103 (50.2) 0.285‡ 97 (51.6) 113 (54.6) 26 (13.8) 24 (11.6) 38 (20.2) 38 (18.4) 10 (5.3) 5 (2.4) 3 (1.6) 3 (1.4) 0 (0.0) 5 (2.4) 0 (0.0) 1 (0.5) 14 (7.4) 18 (8.7)
*Mann-Whitney test, z = 0.66. **Pearson W22 = 6.47. †Pearson W21 = 1.49. ‡Pearson W27 = 8.57. MVC, motor vehicle crash.
Patient Preinjury Activity Level Ninety-six percent of the patients or surrogates (n = 180) responded to at least some of the Paffenbarger Physical Activity questions (Table 3). Twenty-nine percent (50 of 180) engaged in weekly activity that increased their heart rate and respirations. There was a statistically significant interaction effect of activity level and admitting service on the reported daily activity (p = 0.026, Table 3). Median daily time spent in vigorous, moderate, or light activity before the injury was statistically significantly greater for those patients admitted to trauma and orthopedic services (Bonferroni-corrected p G 0.05). Conversely, patients admitted to the geriatric service reported spending greater time during an average work day in sitting and/ or reclining activities (Table 3).
Injury Mechanism and Severity
Patient Characteristics by Admitting Service
Total (N = 395)
service (median ages 71 years [IQR, 67Y86] vs. 84 years [IQR, 78Y88]; post hocYcorrected p G 0.05).
As would be expected, those admitted to the trauma service had statistically significantly higher injury severity (median 13; IQR, 9Y19) than did those patients admitted to either the orthopedic or the geriatric services (median, 9 [IQR, 4Y9] and 4 [IQR, 1Y9], respectively; p G 0.001; Table 4). Analysis of AIS injury severity scores by body region showed head/neck injuries in 51% of patients (95 of 188), followed by extremity injuries in 44% (82 of 188). Other regions in descending order of prevalence were chest (36%, 68 of 188), abdomen (20%, 38 of 188), external (14%, 27 of 188), and face (13%, 25 of 188). As displayed in Table 4, patients admitted to trauma had statistically significantly higher AIS head/neck, chest, and abdomen severity scores than did those admitted to orthopedics or geriatrics (p G 0.05). To the contrary, patients admitted to orthopedics had higher AIS extremity injury scores than those admitted to trauma or geriatrics. Finally, there was a statistically significant difference among all the services in the distribution of injury mechanism (p = 0.029). Most of the patients admitted to the geriatric service were injured via falls from standing (17 of 19, 90%), while only 47% (67 of 143) admitted to the trauma service were injured in that manner. Conversely, 25% (35 of 142) admitted to trauma were injured as the driver in motor vehicle crashes, while only 4% (1 of 27) were injured in that way within the orthopedic service (Table 4).
Advance Care Directives and Discharge Disposition Patient advanced directive (DNR) status and discharge disposition are also summarized in Table 4. Forty-eight patients had a DNR status in the medical record, and 28 (58%) of those 48 received palliative care consults during hospitalization. A higher percentage of patients admitted to the geriatric service had a DNR status compared with those admitted on the orthopedic service. Eighty-nine percent (n = 167) of the patients were admitted from a home setting; of these, 53 (28%) returned home. Eighteen patients (10%) died in the hospital, and 117 (62%) were discharged to a facility other than home. Of the discharges other than home, the highest percentage was discharge to a
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TABLE 3. Characteristics of Enrolled Patients by Admitting Service (n = 188)
Characteristic Age Comorbidity Index Age group 65Y74 75Y84 85+ Sex Female Male Race/ethnicity White Black Asian Hispanic Living location House/apartment Assisted living Skilled nursing facility Living arrangement Lives alone Lives with spouse only Lives with others At least once a week, do you engage in regular activity to get your heart thumping or get out of breath? (n = 175) Weekday activity† (h/d) Vigorous Moderate Light Sitting Reclining/sleeping
Total (n = 188)
Trauma Service (n = 142)
Geriatric Service (n = 19)
Orthopedic Service (n = 27)
Median (IQR)
Median (IQR)
Median (IQR)
Median (IQR)
p
77 (69Y86) 3 (0Y9) n (%)
77 (69Y83) 3 (0Y9) n (%)
71 (67Y86) 2 (0Y7) n (%)
0.021* 0.094
78 (41.5) 61 (32.4) 49 (26.1)
60 (42.3) 50 (35.2) 32 (22.5)
3 (15.8) 7 (36.8) 9 (47.4)
15 (55.6) 4 (14.8) 8 (29.6)
106 (56.4) 82 (43.6)
81 (57.0) 61 (43.0)
10 (52.6) 9 (47.4)
15 (55.6) 12 (44.4)
175 (93.1) 12 (6.4) 1 (0.5) 0 (0.0)
134 (94.4) 7 (4.9) 1 (0.7) 0 (0.0)
16 (84.2) 3 (15.8) 0 (0.0) 0 (0.0)
25 (92.6) 2 (7.4) 0 (0.0) 0 (0.0)
167 (88.9) 14 (7.4) 7 (3.7)
128 (90.1) 9 (6.3) 5 (3.5)
15 (78.9) 3 (15.8) 1 (5.3)
24 (88.9) 2 (7.4) 1 (3.7)
84 (78Y88) 7 (3Y13) n (%)
0.022**
0.932
0.454
0.666
0.587 51 88 49 50
(27.1) (46.8) (26.1) (27.8)
42 (39.6) 65 (45.8) 35 (24.6) 38 (27.9)
4 (21.1) 8 (42.1) 7 (36.8) 3 (16.7)
5 15 7 9
(18.5) (55.6) (25.9) (34.6)
0.0 0.0 4.0 8.0 8.0
(0Y0) (0Y3) (2Y6) (6Y12) (7Y10)
0.0 (0Y0) 0.0 (0Y4) 4.0 (2Y6) 8.0 (5Y12) 8.0 (7Y10)
0.0 (0Y0) 0.0 (0Y0) 2.0 (1Y4) 11.0 (8Y14) 9.5 (8Y12)
0.0 1.0 4.5 7.5 8.0
(0Y1) (0Y5) (1Y7) (4Y12) (6Y10)
0.424 0.026‡
*ANOVA transformed data: F2,185 = 3.97, post hoc Dunnett CYcorrected p G 0.05, trauma G geriatrics. **Pearson W24 = 11.49; post hoc BonferroniYcorrected p G 0.05; 65Y74, geriatric G orthopedics. †ANOVA transformed data: F2,185 = 30.18, post hoc Dunnett C-corrected p G 0.05, orthopedics > trauma, geriatrics. ‡Statistically significant interaction effect of activity and admitting service; mixed-effects general linear modeling, log-link function: Wald W27 = 15.87, post hoc Bonferroni-corrected p G 0.05; vigorous, moderate, light activity: geriatric G trauma, orthopedic; sitting, relining activity: geriatric 9 trauma, orthopedic.
skilled nursing facility (33%, 62 of 188), followed by discharge to a rehabilitation facility (26%, 48 of 188). No statistically significant differences were observed in these rates among the three services (p = 0.299, Table 4).
Patient and Surrogate Interviews Of the 188 patients, 77 (41.0%) could be interviewed. Of the remaining 111 patients (59.0%) who could not be interviewed, 42 (37.8%) were reported by patients’ nurses to have confusion or delirium and thus unable to complete the measures. The other 69 patients (62.2%) either did not feel like answering questions or were unable to be interviewed secondary to their medical condition. The distribution of the relationship of the surrogate to the patient for the entire sample (n = 188) included the following: spouse (66, 35%), child (101, 54%), sibling (6, 3%), grandchild 848
(4, 2%), parent/mother (1, G1%), and other relative or friend (10, 5%).
Measures of Preinjury Frailty A summary of the scores on the preinjury frailty measures completed by surrogates and patients are shown in Table 5. All surrogates and patients who completed the instruments did so with no missing items. As shown, the median score of surrogate responses for the VES-13 was 3.5 (IQR, 2Y7). Sixtyfour percent of those scores were at least 3, indicating a report by the surrogate of vulnerability or frailty. Median score from the surrogates on the BI was 19 (IQR, 17Y20), indicating that many patients have some level of dependency in at least one ADL. Finally, the LSA median score from the surrogates was 56 (IQR, 33Y80), placing those scores in the middle-to-lower portion of the possible range of 0 to 120 on that measure. * 2015 Wolters Kluwer Health, Inc. All rights reserved.
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J Trauma Acute Care Surg Volume 78, Number 4
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TABLE 4. Injury, Advanced Directives, and Discharge Status of Enrolled Patients by Admitting Service (n = 188) Total (n = 188)
Trauma Service (n = 142)
Geriatric Service (n = 19)
Orthopedic Service (n = 27)
Characteristics
Median (IQR)
Median (IQR)
Median (IQR)
Median (IQR)
p
Injury severity AIS body region Head/neck Face Chest Abdomen Extremity External
10 (9Y17) Median (75th percentile, maximum) 1 (9, 25) 0 (0, 9) 0 (4, 16) 0 (0, 25) 0 (8, 16) 0 (0, 4) n (%)
13 (9Y19)
4 (1Y9)
9 (4Y9)
G0.001*
0 (4, 16) 0 (0, 4) 0 (0, 1) 0 (0, 4) 0 (1, 9) 0 (1, 1) n (%)
0 (0, 0) 0 (0, 1) 0 (0, 0) 0 (0, 0) 9 (9, 16) 0 (0, 1) n (%)
G0.001† 0.115 G0.001‡ 0.027§ G0.001¶ 0.320
Mechanism of injury Fall from standing Fall from other MVCYdriver MVCYPassenger Pedestrian MCC Other Advanced directive (DNR) Palliative care consult Discharge disposition Home Long-term acute care Rehabilitation Skilled nursing facility Assisted living facility Inpatient hospice Expired
4 (9, 25) 0 (0, 9) 0 (9, 16) 0 (2, 25) 0 (4, 16) 0 (0, 4) n (%)
0.029|| 102 (54.3) 24 (12.8) 37 (19.7) 10 (5.3) 3 (2.6) 2 (1.1) 10 (5.3) 48 (25.5) 28 (14.9)
67 (47.2) 18 (12.7) 35 (24.6) 10 (7.0) 3 (2.1) 2 (1.4) 7 (4.9) 38 (26.8) 24 (16.9)
17 (89.5) 1 (5.3) 1 (5.3) 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) 8 (42.1) 3 (15.8)
18 (66.7) 5 (18.5) 1 (3.7) 0 (0.0) 0 (0.0) 0 (0.0) 3 (11.1) 2 (7.4) 1 (3.7)
53 (28.2) 3 (1.6) 48 (25.5) 62 (33.0) 2 (1.1) 2 (1.1) 18 (9.6)
37 (26.1) 3 (2.1) 37 (26.1) 46 (32.4) 1 (0.7) 1 (0.7) 17 (12.0)
5 (26.3) 0 (0.0) 4 (21.1) 7 (36.8) 1 (5.3) 1 (5.3) 1 (5.3)
11 (40.7) 0 (0.0) 7 (25.9) 9 (33.3) 0 (0.0) 0 (0.0) 0 (0.0)
0.023†† 0.209 0.299
*ANOVA transformed data: F2,185 = 28.60, post hoc Dunnett CYcorrected p G 0.05, trauma G orthopedics. †ANOVA transformed data: F2,185 = 14.70, post hoc Dunnett CYcorrected p G 0.05, trauma 9 geriatrics 9 orthopedics. ‡ANOVA transformed data: F2,185 = 15.18, post hoc Dunnett CYcorrected p G 0.05, trauma 9 orthopedics, geriatrics. §ANOVA transformed data: F2,185 = 3.70, post hoc Dunnett CYcorrected p G 0.05, trauma 9 orthopedics, geriatrics. ¶ANOVA transformed data: F2,185 = 30.18, post hoc Dunnett CYcorrected p G 0.05, orthopedics 9 trauma, geriatrics. ||Pearson W212 = 22.86; post hoc Bonferroni-corrected p G 0.05, falls from standing: trauma G geriatrics, MVC driver: trauma 9 orthopedics. Total, n = 180; trauma, n = 136; geriatrics, n = 18; orthopedics, n = 26. Total, n = 175; trauma, n = 131; geriatrics, n = 18; orthopedics, n = 26. ††Pearson X22 = 7.52; post hoc Bonferroni-corrected p G 0.05, geriatric 9 orthopedic. DNR, do not resuscitate; MCC, motorcycle crash; MVC, motor vehicle crash.
Given that the 77 patients able to complete the frailty measures themselves would be expected to be higher functioning than those not able to (see reasons for not completing mentioned earlier), it was not surprising to note that their summary scores were slightly higher than those from the entire sample of surrogates on all three instruments (Table 4). Fifty-three percent (41 of 77) of that subsample had scores of 3 or greater on the VES-13 compared with 64% of the entire sample of patients as reported by surrogates (Table 5). Preinjury frailty by admitting services is presented in Table 6. Statistically significant differences among the services were observed on all of the measures of preinjury frailty (p G 0.05). In general, patients admitted to the geriatric service were considerably more frail before the injury than those admitted to the other services. Approximately 90% (17 of 19) of the
patients admitted to the geriatric service had a VES-13 score of 3 or greater (indicating frailty) compared with a respective percentage of 64% (91 of 142) to the trauma service and 56% (15 of 27) to the orthopedic services (Table 6).
DISCUSSION In this study, we examined whether it is feasible to collect preinjury measures of frailty in hospitalized IOAs. We were able to enroll half of those admitted and/or their surrogates. One-fifth of the cohort declined because it was a research study. The remaining 30% of the cohort were not enrolled because of research personnel’s inability to contact and obtain informed consent within 48 hours. Under normal circumstances,
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TABLE 5. Surrogate and Patient Summaries Brief Screening Instruments Related to Mobility/Physical Function Surrogates (n = 188) VES-13 Median (IQR; minimum, maximum) Scores Q 3,* n (%) BI Median (IQR; minimum, maximum) LSA Median (IQR; minimum, maximum)
3.50 (2Y7; 0, 10) 123 (65.4)
Patients (n = 77) 3.00 (1Y6; 0, 10) 41 (53.2)
19.0 (17Y20; 3, 20)
20.0 (18Y20; 7, 20)
56.0 (33Y80 0, 120)
62.0 (39Y82; 8, 100)
*Indicative of frailty.
it is reasonable to assume that clinicians would have more opportunities to administer brief screening instruments, particularly if completed along with other admission requirements. Future work is needed to assess the willingness of clinicians to screen patients or surrogates as well as the additional time required during admission procedures. Among enrolled patients, we were able to complete instruments on 77 patient-surrogate dyads (41%). For the remaining 111 patients (59%), surrogate-only interviews were necessary to obtain preinjury measures of frailty. Joseph et al.9 screened geriatric trauma patients for preinjury frailty and also required both patients and surrogate respondents at a Level I trauma center; however, they did not report the percentage of surrogates. Maxwell6 reported that 34% required surrogate reports for IOAs at a Level II trauma center and nontrauma center. Similar to other patient populations,34 the feasibility of screening for preinjury frailty using validated brief screening instruments necessitates the availability of surrogates in providing information on behalf of older patients. Reliance on surrogate-reported patient information related to frailty may be problematic; however, others have demonstrated good agreement between older patients and surrogates in assessments of ADLs (intraclass correlations, 0.61Y0.91).35
Importantly, we identified a significant percentage of frailty or functional deficits in our sample of IOAs. While there is, as yet, lack of consensus on a definition of frailty, it is clear that frailty is associated with physical function decline in multiple models of frailty.4,36 Fried et al.37 identified five phenotype model indicators (weight loss, exhaustion, low energy expenditure, slow gait speed, and weak grip strength). Rockwood et al.38 described a cumulative deficit model that identifies baseline variables (or deficits) associated with frailty. These deficits include long-term disabilities, help for shopping and household chores, walking difficulty, dexterity problems, less activity, and difficulty carrying light weights. The brief screening instruments used in this study incorporate variables from both frailty models and may serve as a starting point for the identification of frailty by clinicians. The use of these screening instruments along with other pertinent variables (i.e., cognitive measures, comorbidities, injury severity) may facilitate development of geriatric trauma prediction models. Such models could provide research-based guidance for clinicians to facilitate survival prognostication and postinjury decision making. This study has both strengths and limitations. First, although the VES-13 was designed for patient self-report, the instrument was used with surrogate respondents in this and other studies5,6,17,18 in the absence of patient-proxy validation. Of note, we have conducted an analysis of patient-proxy agreement from this sample (currently under peer review) that reports acceptable patient-proxy agreement. A second limitation is conduction of the study at a single site, thus limiting generalizability. Among its strengths, our prospective cohort design that included patients from three services allowed for a more accurate reflection of the population of IOAs and generalizability across settings regardless of trauma status. Methodologic rigor was used in the study design, training of RAs, and data collection practices. Frailty research in geriatric trauma is likely to increase in the coming years as researchers and clinicians clarify the concept of frailty. Given the high proportion of IOAs who did not return to the home setting, routine screening for preinjury frailty is warranted for the development of effective interventions. Our next steps include determining the influence of preinjury frailty on geriatric trauma outcomes, agreement
TABLE 6. Preinjury Frailty by Admitting Service (n = 188) Characteristic VES-13 Median (IQR) Score Q 3, n (%) BI Median (IQR) LSA Median (IQR)
Total (n = 188)
Trauma Service (n = 142)
Geriatric Service (n = 19)
Orthopedic Service (n = 27)
p
3.5 (2Y7) 123 (65.4)
3.0 (1Y7) 91 (64.1)
7.0 (5Y9) 17 (89.5)
3.0 (0Y7) 15 (55.6)
0.008* 0.047**
19.0 (17Y20)
19.0 (17Y20)
17.0 (15Y19)
20.0 (19Y20)
G0.001†
56.0 (33Y80)
60.0 (34Y80)
20.0 (19Y20)
74.0 (40Y84)
0.009‡
*ANOVA transformed data: F2,185 = 4.97, post hoc Dunnett CYcorrected p G 0.05, geriatrics 9 trauma, orthopedic. **Pearson W22 = 6.13; post hoc Bonferroni-corrected p G 0.05, geriatric 9 orthopedics. †ANOVA transformed data: F2,185 = 8.98, post hoc Dunnett CYcorrected p G 0.05, geriatrics G trauma, orthopedic. ‡ANOVA transformed data: F2,185 = 4.83, post hoc Dunnett CYcorrected p G 0.05, geriatrics G trauma, orthopedic.
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between patients and surrogates, and the feasibility of incorporating these screening instruments into provider workflow.
17.
AUTHORSHIP C.A.M., L.C.M., A.M., K.M., and R.S.M. designed this study. C.A.M. searched the literature and collected data. C.A.M. and M.S.D. analyzed the data. All authors participated in the data interpretation, manuscript writing, and revision.
18.
19.
DISCLOSURE
20.
The authors declare no conflicts of interest.
21.
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