Literature DB >> 25903561

Perceived frailty and measured frailty among adults undergoing hemodialysis: a cross-sectional analysis.

Megan L Salter1,2,3, Natasha Gupta4, Allan B Massie5,6, Mara A McAdams-DeMarco7,8, Andrew H Law9,10, Reside Lorie Jacob11, Luis F Gimenez12, Bernard G Jaar13,14,15,16, Jeremy D Walston17,18,19, Dorry L Segev20,21.   

Abstract

BACKGROUND: Frailty, a validated measure of physiologic reserve, predicts adverse health outcomes among adults with end-stage renal disease. Frailty typically is not measured clinically; instead, a surrogate-perceived frailty-is used to inform clinical decision-making. Because correlations between perceived and measured frailty remain unknown, the aim of this study was to assess their relationship.
METHODS: 146 adults undergoing hemodialysis were recruited from a single dialysis center in Baltimore, Maryland. Patient characteristics associated with perceived (reported by nephrologists, nurse practitioners (NPs), or patients) or measured frailty (using the Fried criteria) were identified using ordered logistic regression. The relationship between perceived and measured frailty was assessed using percent agreement, kappa statistic, Pearson's correlation coefficient, and prevalence of misclassification of frailty. Patient characteristics associated with misclassification were determined using Fisher's exact tests, t-tests, or median tests.
RESULTS: Older age (adjusted OR [aOR] = 1.36, 95%CI:1.11-1.68, P = 0.003 per 5-years older) and comorbidity (aOR = 1.49, 95%CI:1.27-1.75, P < 0.001 per additional comorbidity) were associated with greater likelihood of nephrologist-perceived frailty. Being non-African American was associated with greater likelihood of NP- (aOR = 5.51, 95%CI:3.21-9.48, P = 0.003) and patient- (aOR = 4.20, 95%CI:1.61-10.9, P = 0.003) perceived frailty. Percent agreement between perceived and measured frailty was poor (nephrologist, NP, and patient: 64.1%, 67.0%, and 55.5%). Among non-frail participants, 34.4%, 30.0%, and 31.6% were perceived as frail by a nephrologist, NP, or themselves. Older adults (P < 0.001) were more likely to be misclassified as frail by a nephrologist; women (P = 0.04) and non-African Americans (P = 0.02) were more likely to be misclassified by an NP. Neither age, sex, nor race was associated with patient misclassification.
CONCLUSIONS: Perceived frailty is an inadequate proxy for measured frailty among patients undergoing hemodialysis.

Entities:  

Mesh:

Year:  2015        PMID: 25903561      PMCID: PMC4428253          DOI: 10.1186/s12877-015-0051-y

Source DB:  PubMed          Journal:  BMC Geriatr        ISSN: 1471-2318            Impact factor:   3.921


Background

Frailty is a phenotype of poor physiologic reserve, multisystem dysregulation, and increased vulnerability to stressors [1]. While much of the early research on frailty occurred in populations of older adults [1-4], this validated measure is gaining importance among those with chronic conditions, such as end-stage renal disease (ESRD) [5]. As in older adult populations [1,4], being frail is predictive of falls [6], hospitalization and mortality [5], among patients with ESRD, irrespective of age. Furthermore, frailty is predictive of delayed graft function [7], early hospital readmission [8], and mortality [9] after kidney transplantation. Despite strong associations with poor outcomes for patients with ESRD, frailty is not routinely assessed clinically [10]; as such, clinical assessments of decreased physiologic reserve and vulnerability to stressors tend to be based on a combination of a provider’s clinical experience, provider perceptions of patient frailty, and patient perception of their own frailty, rather than a validated measure [2]. Moreover, the common perception that older adults and women generally tend to be more frail [11] may impact clinical decision-making such as choices about renal replacement therapies. Indeed, older adults and women have lower access to transplantation [12-17] even among appropriate transplant candidates [18]. Whether perceptions about frailty accurately reflect measured frailty remains unknown. To better understand the relationship between perceived and measured frailty, we sought 1) to assess and compare patient characteristics associated with measured, provider-perceived, and patient-perceived frailty, 2) to compare provider- and patient-perceived frailty with measured frailty, and 3) to identify patient characteristics associated with misclassification of frailty status.

Methods

Study population

In this cross-sectional study, 146 adults undergoing hemodialysis were recruited between January 2009 and March 2010 from a single dialysis center in Baltimore, Maryland. Inclusion criteria included: age ≥18 years and English-speaking. Because of the high prevalence of frailty among younger and older patients with ESRD, and because frailty is predictive of poor health outcomes in patients of all ages with renal disease [5,8], we included adults of all ages. All participants provided written informed consent, and all study procedures were approved by the Johns Hopkins Medical Institutions Institutional Review Board.

Participant characteristics

Demographics (age, sex, race, education, employment, and marital status), household size, smoking history, and time on dialysis were obtained through participant self-report. Body mass index (BMI) was calculated using measured height and dry weight with obesity defined as a BMI ≥ 30. Comorbidities were abstracted from medical records and included hypertension, diabetes, peripheral vascular disease, congestive heart failure, myocardial infarction, angina pectoris, chronic obstructive pulmonary disease, history of cancer, and rheumatoid arthritis. Disability was determined using participant-reported difficulties with six activities of daily living (ADLs) including: bathing, toileting, dressing, grooming, eating, and ambulation [19].

Measured frailty

The five components of frailty as defined by Fried et al. were measured: 1) shrinking (self-report of unintentional weight loss of more than 10 pounds in the past year based on dry weight, i.e. the weight of an individual undergoing hemodialysis without the excess fluid that accrues between dialysis treatments); 2) weakness (grip-strength below an established cut-off based on sex and BMI); 3) exhaustion (self-report); 4) low activity (kcal/week below an established cut-off); and 5) slow walking speed (time needed to walk 15 feet below an established cutoff based on sex and height) [1,3]. A frailty score was calculated as the number of frailty components reported for an individual (range 0–5) and categorized as non-frail (0–1 components), intermediately frail (2 components), and frail (3–5 components). As previously described [5], this categorization maintained Fried’s definition of frailty, but expanded non-frail to include a score of 1 to account for the small number (7%) of participants with a frailty score of 0.

Perceived frailty

Perceived frailty for each participant was assessed in three ways: 1) nephrologist-perceived frailty, 2) nurse practitioner (NP)-perceived-frailty, and 3) patient-perceived frailty. Nephrologists (N = 9) and NPs (N = 4) were informed that frailty is a syndrome characterized by a loss of physiologic reserve and assessed using the five components described above and then were asked to categorize their patients as non-frail, intermediately frail, or frail. Participants were asked, “how frail do you think you are?” and were asked to categorize themselves in the same manner.

Participant characteristics and frailty

Univariate and multivariable ordinal logistic regression models were used to estimate the log odds of measured or perceived frailty associated with various characteristics. The functional form of age was determined empirically to be continuous, as was the functional form of number of comorbidities and disability based on number of ADLs. Multivariable models included participant characteristics that were selected based on statistical significance or a priori rationale. Each participant was rated by one nephrologist and one NP. However, because each nephrologist and NP rated more than one participant, standard errors were estimated allowing for intragroup correlation.

Relationship between measured and perceived frailty

The relationship between measured and perceived frailty was assessed using percent agreement, and a weighted kappa statistic was calculated. Additionally, the correlation between measured and perceived frailty was determined using Pearson’s correlation coefficient.

Participant characteristics and misclassification

Prevalences of misclassification of frailty status by nephrologists, NPs, and patients were determined. Participant characteristics among those misclassified as intermediately frail or frail were compared to those correctly classified as non-frail using Fisher’s exact test for categorical variables, t-tests for pseudonormally distributed continuous variables, or Hodges-Lehmann’s test for equal medians for non-normally distributed continuous variables.

Statistical analysis

All analyses were performed using STATA 12.1/SE (College Station, Texas).

Results

Of 146 participants, the median age was 61 years (IQR: 53, 70), 46.6% were women, 84.3% were African American, the median number of comorbidities was 3 (IQR: 2, 4), and the median number of ADLs for which participants reported difficulty was 0 (IQR: 0, 1). The median time on dialysis was 3.6 years (IQR: 1.4-6.4) (Table 1).
Table 1

Participant characteristics: patients undergoing hemodialysis in a single center in Baltimore (n = 146)

% a , Total (n = 146)
Age (years), median [IQR]61 [53, 70]
Women46.6
African American race84.3
Post-secondary education25.4
Currently employed8.9
Marital status
 Married/cohabitating34.7
 Single28.5
 Separated/divorced18.8
 Widowed18.1
Lives with children30.8
History of smoking21.2
BMI, median [IQR]26.7 [23.0, 33.5]
No. comorbidities, median [IQR]3 [2,4]
 Hypertension89.0
 Diabetes65.8
 Peripheral vascular disease30.1
 Congestive heart failure39.0
 Myocardial infarction16.4
 Angina pectoris4.8
 COPD19.2
 History of cancer18.5
 Rheumatoid arthritis6.9
Number of ADLs, median [IQR]0 [0, 1]
Time on dialysis (years), median [IQR]3.6 [1.4, 6.4]

Abbreviations: IQR interquartile range, BMI body mass index, COPD chronic obstructive lung disease, ADLs activities of daily living.

aAll values are percentages unless otherwise indicated.

Participant characteristics: patients undergoing hemodialysis in a single center in Baltimore (n = 146) Abbreviations: IQR interquartile range, BMI body mass index, COPD chronic obstructive lung disease, ADLs activities of daily living. aAll values are percentages unless otherwise indicated. In multivariable models, only disability was associated with measured frailty (adjusted OR [aOR] = 1.47, 95% CI: 1.04-2.08, P = 0.03 for each additional ADL difficulty). In contrast, age (aOR = 1.36, 95% CI: 1.11-1.68, P = 0.003 per 5-year increase in age), smoking (aOR = 3.05, 95% CI: 1.28-7.29, P = 0.01), obesity (aOR = 0.21, 95% CI: 0.16-0.29, P < 0.001, and comorbidity (aOR = 1.49, 95% CI: 1.27-1.75, P < 0.001 per one additional comorbidity) were associated with nephrologist-perceived frailty. Being non-African American (aOR = 5.51, 95% CI: 3.21-9.48, P = 0.003), being intermediately frail (aOR = 6.23, 95% CI: 2.35-16.5, P < 0.001), being employed currently (aOR = 0.16, 95% CI: 0.05-0.53, P = 0.003), having a post-secondary education (aOR = 0.37, 95% CI: 0.31-0.45, p < 0.001), and being obese (aOR = 0.44, 95% CI: 0.27-0.72, P = 0.001) were associated with NP-perceived frailty. Being non-African American (aOR = 4.20, 95% CI: 1.61-10.9, P = 0.003), smoking (aOR = 3.69, 95% CI: 1.54-8.81, P = 0.01), disability (aOR = 1.43, 95% CI: 1.02-1.99, P < 0.04 for each additional ADL difficulty), and being older (aOR = 0.81, 95% CI: 0.70-0.95, P < 0.001) were associated with patient-perceived frailty (Table 2).
Table 2

Multivariable associations between participant characteristics and measured or perceived frailty

Odds ratio (95% CI) a
Measured frailty Nephrologist-perceived frailty NP-perceived frailty Patient-perceived frailty
Age (per 5-yr increase)1.08 (0.95-1.24) 1.36 (1.11-1.68)1.07 (0.76-1.51) 0.81 (0.70-0.95)
Being a woman1.34 (0.71-2.53)1.74 (0.91-3.31)2.25 (0.82-6.21)1.18 (0.57-2.42)
Non-African American race1.72 (0.71-4.17)1.30 (0.79-2.16) 5.51 (3.21-9.48) 4.20 (1.61-10.9)
Post-secondary education 0.37 (0.31-0.45)
Currently employed 0.16 (0.05-0.53)
History of smoking 3.05 (1.28-7.29) 3.69 (1.54-8.81)
Obese1.27 (0.65-2.47) 0.21 (0.16-0.29) 0.44 (0.27-0.72)
Comorbiditiesb 1.07 (0.83-1.38) 1.49 (1.27-1.75)1.23 (0.73-2.06)1.29 (0.97-1.72)
Disabilityc 1.47 (1.04-2.08)1.26 (0.70-2.24)1.97 (0.63-6.18) 1.43 (1.02-1.99)
Frailty
 Non frail-refrefref
 Intermediately frail-1.21 (0.53-2.78) 6.23 (2.35-16.5)2.06 (0.79-5.36)
 Frail-2.77 (0.87-8.83)4.19 (0.92-19.1)1.28 (0.50-3.30)

Abbreviations: NP Nurse Practitioner, CI confidence interval.

a95% CIs for the for neprhologist-perceived frailty and NP-perceived frailty were estimated allowing for intragroup correlation because the same nephrologist or NP was able to rate multiple participants.

bper one comorbidity increase.

cper reported increase in difficulty with one activity of daily living (ADL).

Bold indicates significance at the P<0.05 level.

Odds ratios were estimated using ordered logistic regression with an order of non-frail, intermediately frail, and frail. Under the proportional odds assumption, the estimated odds ratio applies to either of the two odds ratios being modeled: for example, participants who reported difficulty with one ADL were 1.47-fold more likely to be intermediately frail or frail compared to non-frail and 1.47-fold more likely to be frail compared to intermediately frail or non-frail relative to participants who reported no difficulty for any ADL.

Multivariable associations between participant characteristics and measured or perceived frailty Abbreviations: NP Nurse Practitioner, CI confidence interval. a95% CIs for the for neprhologist-perceived frailty and NP-perceived frailty were estimated allowing for intragroup correlation because the same nephrologist or NP was able to rate multiple participants. bper one comorbidity increase. cper reported increase in difficulty with one activity of daily living (ADL). Bold indicates significance at the P<0.05 level. Odds ratios were estimated using ordered logistic regression with an order of non-frail, intermediately frail, and frail. Under the proportional odds assumption, the estimated odds ratio applies to either of the two odds ratios being modeled: for example, participants who reported difficulty with one ADL were 1.47-fold more likely to be intermediately frail or frail compared to non-frail and 1.47-fold more likely to be frail compared to intermediately frail or non-frail relative to participants who reported no difficulty for any ADL.

Agreement between measured and perceived frailty

Among frail participants, only 42.0% and 39.2% were correctly perceived as frail by their nephrologist or NP, and only 4.9% perceived themselves as frail. Among non-frail participants, 34.4%, 30.0%, and 31.6% were incorrectly perceived as intermediately frail or frail by a nephrologist, NP, and themselves, respectively. The agreement between measured and perceived frailty was, at best, only slightly better than what would be expected by chance alone (nephrologists: 64.1% observed agreement vs. 52.9% expected agreement, kappa = 0.24; NPs: 67.0% observed agreement vs. 54.5% expected agreement, kappa = 0.27; patients: 55.5% observed agreement vs. 52.4% expected agreement, kappa = 0.07) (Table 3).
Table 3

Relationships between measured and perceived frailty

Perceived frailty Measured frailty
Non-frail, n (%) Intermediately frail, n (%) Frail, n (%) Percent agreement Kappa Correlation
Nephrologista
 Non-frail21 (65.6)20 (51.3)15 (30.0)64.10.240.32
 Intermediately frail7 (21.9)11 (28.1)14 (28.0)
 Frail4 (12.5)8 (20.5)21 (42.0)
Nurse Practitionerb
 Non-frail21 (70.0)9 (26.5)11 (21.6)67.00.270.35
 Intermediately frail5 (16.7)13 (38.2)20 (39.2)
 Frail4 (13.3)12 (35.3)20 (39.2)
Patientc
 Non-frail26 (68.4)23 (48.9)32 (52.5)55.50.070.09
 Intermediately frail10 (26.3)21 (44.7)26 (42.6)
 Frail2 (5.3)3 (6.4)3 (4.9)
Nurse practitioner b Nephrologist a perceived frailty d
Perceived frailty Non-frail, n (%) Intermediately frail, n (%) Frail, n (%) Percent agreement Kappa Correlation
 Non-frail25 (51.0)10 (32.3)5 (16.7)64.60.210.28
 Intermediately frail14 (28.6)10 (32.3)13 (43.3)
 Frail10 (20.4)11 (35.5)12 (40.0)

aOf the 146 participants with measured frailty, 121 were rated by a nephrologist.

bOf the 146 participants with measured frailty, 115 were rated by a nurse practitioner.

cOf the 146 participants with measured frailty, 146 provided self-rated frailty.

dOf the 146 participants, 110 participants were rated by both a nephrologist and a nurse practitioner.

Percents sum down columns. Thus, among participants who were non-frail based on measured frailty, 21.9% and 12.5% were misclassified as intermediately frail and frail by a nephrologist.

Relationships between measured and perceived frailty aOf the 146 participants with measured frailty, 121 were rated by a nephrologist. bOf the 146 participants with measured frailty, 115 were rated by a nurse practitioner. cOf the 146 participants with measured frailty, 146 provided self-rated frailty. dOf the 146 participants, 110 participants were rated by both a nephrologist and a nurse practitioner. Percents sum down columns. Thus, among participants who were non-frail based on measured frailty, 21.9% and 12.5% were misclassified as intermediately frail and frail by a nephrologist. Among those who were non-frail according to measured frailty, those misclassified as frail or intermediately frail by a nephrologist did not differ by sex (P = 0.28) or race (P = 0.27), but they were statistically significantly older (mean age of those misclassified of 67.5 vs. 47.0 of those not misclassified, P < 0.001). In contrast, those misclassified by an NP were more likely to be women (66.7% of those misclassified vs. 23.8% of those not misclassified, P = 0.04) or non-African American (33.3% of those misclassified vs. 0% of those not misclassified, P = 0.02); they were clinically, but not statistically significantly, older (mean age of those misclassified of 62.8 vs. 53.0 of those not misclassified, P = 0.09). Those who misclassified themselves did not differ by sex (P = 0.73), race (P = 0.58), or age (P = 0.83). None of the other participant characteristics (education, employment, smoking history, obesity, comorbidities, or disability) were associated with being misclassified as intermediately frail or frail (Table 4).
Table 4

Participant characteristics by misclassification of frailty status among non-frail participants

Nephrologist-perceived frailty, n = 32 P NP-perceived frailty, n = 30 P Patient-perceived frailty, n = 38 P
non-frail int. frail/frail non-frail int. frail/frail non-frail int. frail/frail
Age (years)a 47.067.5<0.00153.062.80.0954.855.80.83
Women33.354.60.2823.866.70.0438.550.00.73
Non-African American race4.818.20.270.033.30.027.716.70.58
Post-secondary education23.827.31.0028.622.21.0021.727.30.76
Currently employed19.118.21.0023.800.2921.79.10.31
History of smoking19.19.10.6419.111.11.0013.022.70.32
Obese33.327.31.0038.122.20.6830.427.31.00
Comorbiditiesb 2.33.20.072.43.00.272.52.70.56
Disabilityc 000.48000.35000.11

Abbreviations: NP nurse practitioner, Int. frail intermediately frail.

aMean.

bMedian number of comorbidities.

cMedian number of activities of daily living with which participant reported difficulty.

P-values were estimated using Fisher’s exact test for categorical variables, t-tests for pseudonormally distributed continuous variables, or Hodges-Lehmann’s test for equal medians for non-normally distributed continuous variables.

Participant characteristics by misclassification of frailty status among non-frail participants Abbreviations: NP nurse practitioner, Int. frail intermediately frail. aMean. bMedian number of comorbidities. cMedian number of activities of daily living with which participant reported difficulty. P-values were estimated using Fisher’s exact test for categorical variables, t-tests for pseudonormally distributed continuous variables, or Hodges-Lehmann’s test for equal medians for non-normally distributed continuous variables.

Discussion

In this cross-sectional study of adults undergoing hemodialysis, perceived frailty appeared to be an inadequate proxy for measured frailty, with fewer than half of frail patients correctly classified by themselves, their NPs, or their nephrologists. Perceived frailty according to nephrologists, NPs, and patients agreed with measured frailty only slightly better than what would be expected by chance alone. Moreover, participant characteristics associated with misclassification of frailty status as well as perceived frailty varied depending on who rated frailty status (nephrologist, NP, or patient) and differed from participant characteristics associated with measured frailty. While other studies have explored differences between patient and provider perceptions of health status [20,21], our study compared provider and patient perceptions of frailty to a validated measure. Our novel finding that perceived and measured frailty have poor correlation provides evidence that providers and patients are inaccurate in assessing physiologic reserve and ability to respond to stressors in the same manner as a validated measure of frailty. Further, the discordance between providers’ perceptions of frailty and measured frailty may be even greater in practice because providers in this study were informed of the criteria included in measured frailty. Additionally, our findings suggest that certain groups of patients (e.g. older adults, non-African Americans, and women) are more likely to be incorrectly perceived as frail. Although others suggest a potential relationship between perceived frailty and survival [22], whether such misclassification could influence clinical decisions for treatment courses remains unclear. Furthermore, because patients of all ages were misclassified, assessing the frailty status of younger and older adults using objective criteria in the setting of chronic disease may have clinical value. Interestingly, older participants in our study were less likely to perceive themselves as frail. Similarly, older individuals are less likely to perceive their overall health status as poor, even as their health declines [23]. One possible explanation is that older adults with ESRD compare themselves to their peers of similar age who are more likely to have other chronic health conditions. Thus, unlike younger patients with ESRD who are more likely to have healthy peers of similar age, the difference in health status between older adults with and without ESRD may not be as great, and older adults with ESRD may perceive themselves as equally healthy relative to their peers. This study has several limitations. First, participants were drawn from a small sample of patients at a single dialysis center, limiting generalizability and statistical power to detect small effect sizes. However, with such a major discordance between measured and perceived frailty, even a much larger study is unlikely to identify agreement. Second, the sampling strategy may induce prevalent sampling bias in which our results are only generalizable to those who become prevalent dialysis patients and not to those who initiate dialysis but do not live long enough to enroll in a study. While this sampling might limit generalizability, it does not affect internal validity, as the discordance between measured and perceived frailty did not change based on time-on-dialysis. Finally, while our finding that measured and perceived frailty are poorly correlated is interesting, and while measured frailty is a validated predictor of outcomes in ESRD patients, a larger study that examines the association between perceived frailty and outcomes would better inform the clinical relevance of our findings. This study also has several strengths. The novel collection of a validated, measured frailty construct in conjunction with patient- and provider-perceived frailty allowed ascertainment of discordance between measured and perceived frailty, which to our knowledge has not been studied previously.

Conclusions

In conclusion, provider and patient perceptions of frailty were not accurately reflective of measured frailty in a population of patients of all ages undergoing hemodialysis. Furthermore, participant characteristics associated with perceived frailty varied according to nephrologist, NP, and patients and were not consistent with participant characteristics associated with measured frailty. Notably, older adults and women were more likely to be misclassified as frail and are less likely to receive a transplant [12-18]. Thus, the impact of perceived frailty on clinical-decision making and patient outcomes warrants further investigation, as perceptions may influence patient and provider behaviors.
  22 in total

Review 1.  Untangling the concepts of disability, frailty, and comorbidity: implications for improved targeting and care.

Authors:  Linda P Fried; Luigi Ferrucci; Jonathan Darer; Jeff D Williamson; Gerard Anderson
Journal:  J Gerontol A Biol Sci Med Sci       Date:  2004-03       Impact factor: 6.053

2.  Frailty, hospitalization, and progression of disability in a cohort of disabled older women.

Authors:  Cynthia M Boyd; Qian-Li Xue; Crystal F Simpson; Jack M Guralnik; Linda P Fried
Journal:  Am J Med       Date:  2005-11       Impact factor: 4.965

Review 3.  Assessing self-maintenance: activities of daily living, mobility, and instrumental activities of daily living.

Authors:  S Katz
Journal:  J Am Geriatr Soc       Date:  1983-12       Impact factor: 5.562

4.  Frailty in older adults: evidence for a phenotype.

Authors:  L P Fried; C M Tangen; J Walston; A B Newman; C Hirsch; J Gottdiener; T Seeman; R Tracy; W J Kop; G Burke; M A McBurnie
Journal:  J Gerontol A Biol Sci Med Sci       Date:  2001-03       Impact factor: 6.053

5.  U.S. nephrologists' attitudes towards renal transplantation: results from a national survey.

Authors:  M Thamer; W Hwang; N E Fink; J H Sadler; E B Bass; A S Levey; R Brookmeyer; N R Powe
Journal:  Transplantation       Date:  2001-01-27       Impact factor: 4.939

Review 6.  Prevalence of frailty in community-dwelling older persons: a systematic review.

Authors:  Rose M Collard; Han Boter; Robert A Schoevers; Richard C Oude Voshaar
Journal:  J Am Geriatr Soc       Date:  2012-08-06       Impact factor: 5.562

7.  Frailty and early hospital readmission after kidney transplantation.

Authors:  M A McAdams-DeMarco; A Law; M L Salter; E Chow; M Grams; J Walston; D L Segev
Journal:  Am J Transplant       Date:  2013-06-03       Impact factor: 8.086

Review 8.  The social bases of discrepancies in health/illness perceptions.

Authors:  A E Molzahn; H C Northcott
Journal:  J Adv Nurs       Date:  1989-02       Impact factor: 3.187

9.  Frailty as a novel predictor of mortality and hospitalization in individuals of all ages undergoing hemodialysis.

Authors:  Mara A McAdams-DeMarco; Andrew Law; Megan L Salter; Brian Boyarsky; Luis Gimenez; Bernard G Jaar; Jeremy D Walston; Dorry L Segev
Journal:  J Am Geriatr Soc       Date:  2013-05-27       Impact factor: 7.538

10.  Frailty and falls among adult patients undergoing chronic hemodialysis: a prospective cohort study.

Authors:  Mara A McAdams-DeMarco; Sunitha Suresh; Andrew Law; Megan L Salter; Luis F Gimenez; Bernard G Jaar; Jeremy D Walston; Dorry L Segev
Journal:  BMC Nephrol       Date:  2013-10-16       Impact factor: 2.388

View more
  29 in total

1.  Report from the American Society of Transplantation on frailty in solid organ transplantation.

Authors:  Jon Kobashigawa; Darshana Dadhania; Sangeeta Bhorade; Deborah Adey; Joseph Berger; Geetha Bhat; Marie Budev; Andres Duarte-Rojo; Michael Dunn; Shelley Hall; Meera N Harhay; Kirsten L Johansen; Susan Joseph; Cassie C Kennedy; Evan Kransdorf; Krista L Lentine; Raymond J Lynch; Mara McAdams-DeMarco; Shunji Nagai; Michael Olymbios; Jignesh Patel; Sean Pinney; Joanna Schaenman; Dorry L Segev; Palak Shah; Lianne G Singer; Jonathan P Singer; Christopher Sonnenday; Puneeta Tandon; Elliot Tapper; Stefan G Tullius; Michael Wilson; Martin Zamora; Jennifer C Lai
Journal:  Am J Transplant       Date:  2018-12-22       Impact factor: 8.086

2.  Pre-Kidney Transplant Lower Extremity Impairment and Post-Kidney Transplant Mortality.

Authors:  A J Nastasi; M A McAdams-DeMarco; J Schrack; H Ying; I Olorundare; F Warsame; A Mountford; C E Haugen; M González Fernández; S P Norman; D L Segev
Journal:  Am J Transplant       Date:  2017-08-30       Impact factor: 8.086

3.  Frailty and Access to Kidney Transplantation.

Authors:  Christine E Haugen; Nadia M Chu; Hao Ying; Fatima Warsame; Courtenay M Holscher; Niraj M Desai; Miranda R Jones; Silas P Norman; Daniel C Brennan; Jacqueline Garonzik-Wang; Jeremy D Walston; Adam W Bingaman; Dorry L Segev; Mara McAdams-DeMarco
Journal:  Clin J Am Soc Nephrol       Date:  2019-03-19       Impact factor: 8.237

4.  Treatment of atrial fibrillation with warfarin among older adults with end stage renal disease.

Authors:  Jingwen Tan; Sunjae Bae; Jodi B Segal; Junya Zhu; Dorry L Segev; G Caleb Alexander; Mara McAdams-DeMarco
Journal:  J Nephrol       Date:  2017-01-24       Impact factor: 3.902

Review 5.  The impact of frailty on outcomes in dialysis.

Authors:  John Sy; Kirsten L Johansen
Journal:  Curr Opin Nephrol Hypertens       Date:  2017-11       Impact factor: 2.894

Review 6.  An overview of frailty in kidney transplantation: measurement, management and future considerations.

Authors:  Meera N Harhay; Maya K Rao; Kenneth J Woodside; Kirsten L Johansen; Krista L Lentine; Stefan G Tullius; Ronald F Parsons; Tarek Alhamad; Joseph Berger; XingXing S Cheng; Jaqueline Lappin; Raymond Lynch; Sandesh Parajuli; Jane C Tan; Dorry L Segev; Bruce Kaplan; Jon Kobashigawa; Darshana M Dadhania; Mara A McAdams-DeMarco
Journal:  Nephrol Dial Transplant       Date:  2020-07-01       Impact factor: 5.992

7.  Frailty, body composition and the risk of mortality in incident hemodialysis patients: the Predictors of Arrhythmic and Cardiovascular Risk in End Stage Renal Disease study.

Authors:  Jessica Fitzpatrick; Stephen M Sozio; Bernard G Jaar; Michelle M Estrella; Dorry L Segev; Rulan S Parekh; Mara A McAdams-DeMarco
Journal:  Nephrol Dial Transplant       Date:  2019-02-01       Impact factor: 5.992

8.  Provider Perception of Frailty Is Associated with Dialysis Decision Making in Patients with Advanced CKD.

Authors:  Ranveer S Brar; Reid H Whitlock; Paul V J Komenda; Claudio Rigatto; Bhanu Prasad; Clara Bohm; Navdeep Tangri
Journal:  Clin J Am Soc Nephrol       Date:  2021-03-26       Impact factor: 8.237

9.  Sex Disparity in Deceased-Donor Kidney Transplant Access by Cause of Kidney Disease.

Authors:  Patrick Ahearn; Kirsten L Johansen; Jane C Tan; Charles E McCulloch; Barbara A Grimes; Elaine Ku
Journal:  Clin J Am Soc Nephrol       Date:  2021-01-26       Impact factor: 8.237

10.  Frailty measures can be used to predict the outcome of kidney transplant evaluation.

Authors:  Priyadarshini Manay; Patrick Ten Eyck; Roberto Kalil; Melissa Swee; M Lee Sanders; Grace Binns; Jodell L Hornickel; Daniel A Katz
Journal:  Surgery       Date:  2020-08-26       Impact factor: 3.982

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.