Literature DB >> 27941328

Upper-Extremity Function Predicts Adverse Health Outcomes among Older Adults Hospitalized for Ground-Level Falls.

Bellal Joseph1, Nima Toosizadeh, Tahereh Orouji Jokar, Michelle R Heusser, Jane Mohler, Bijan Najafi.   

Abstract

BACKGROUND: Despite National Surgical Quality Improvement guidelines to integrate frailty into surgical elder assessments, a quick, accurate, and simple frailty assessment tool suitable for busy clinical settings is still not available. Recently, we have demonstrated that a simple upper-extremity function (UEF) test based on wearable sensors could identify frailty with high agreement with conventional assessments by testing 20-s repetitive elbow flexion and extension.
OBJECTIVE: We examined whether UEF parameters are sensitive for predicting adverse health outcomes in bedbound older adults admitted to hospital due to ground-level fall injuries. STUDY
DESIGN: Frailty was assessed in 101 eligible older adults (age: 79 ± 9 years) admitted to a trauma setting using the UEF test at the time of admission. All participants were followed up for 2 months using phone calls and chart reviews. The measured health outcomes included (1) discharge disposition (favorable: discharge home or rehabilitation; unfavorable: discharge to skilled nursing facility or death), (2) hospital length of stay, (3) 30-day readmission, (4) 60-day readmission, and (5) 30-day prospective falls. Multivariate analyses were used to identify independent predictors of adverse health outcomes based on participants' demographic parameters (i.e., age, gender, and body mass index [BMI]) and UEF index.
RESULTS: Based on the UEF frailty status, 53 (52%) of the participants were frail and 48 (48%) were non-frail. Among all adverse health outcomes, age was only a significant predictor of 30-day prospective falls (p = 0.023). On the other hand, the UEF index was a significant predictor of all measured outcomes except hospital length of stay (p < 0.010). Among the UEF parameters, those indicating slowness, weakness, and exhaustion had the highest effect sizes to predict an unfavorable discharge disposition (p < 0.010; effect size = 0.65-0.92).
CONCLUSION: The results of this study suggest that a 20-s UEF test is practical in the trauma setting and could be used as a quick measure for predicting adverse events and outcomes among bedbound patients after discharge. Assessing frailty using UEF may assist in objective triage, treatment, and post-discharge decision-making with regard to geriatric trauma patients.
© 2016 S. Karger AG, Basel.

Entities:  

Keywords:  Bedbound patients; Discharge disposition; Fall incident; Frailty; Functional test; Inpatient care; Inpatient triage; Readmission; Trauma; Wearable technology

Mesh:

Year:  2016        PMID: 27941328      PMCID: PMC5466851          DOI: 10.1159/000453593

Source DB:  PubMed          Journal:  Gerontology        ISSN: 0304-324X            Impact factor:   5.140


  37 in total

1.  Just what defines frailty?

Authors:  Alfred L Fisher
Journal:  J Am Geriatr Soc       Date:  2005-12       Impact factor: 5.562

Review 2.  Falls in older people: epidemiology, risk factors and strategies for prevention.

Authors:  Laurence Z Rubenstein
Journal:  Age Ageing       Date:  2006-09       Impact factor: 10.668

3.  Cognitive impairment in older adults with heart failure: prevalence, documentation, and impact on outcomes.

Authors:  John A Dodson; Tuyet-Trinh N Truong; Virginia R Towle; Gerard Kerins; Sarwat I Chaudhry
Journal:  Am J Med       Date:  2013-02       Impact factor: 4.965

4.  Assessing Upper-Extremity Motion: An Innovative, Objective Method to Identify Frailty in Older Bed-Bound Trauma Patients.

Authors:  Nima Toosizadeh; Bellal Joseph; Michelle R Heusser; Tahereh Orouji Jokar; Jane Mohler; Herb A Phelan; Bijan Najafi
Journal:  J Am Coll Surg       Date:  2016-05-04       Impact factor: 6.113

5.  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

6.  Frailty: an outcome predictor for elderly gynecologic oncology patients.

Authors:  Madeleine Courtney-Brooks; A Rauda Tellawi; Jennifer Scalici; Linda R Duska; Amir A Jazaeri; Susan C Modesitt; Leigh A Cantrell
Journal:  Gynecol Oncol       Date:  2012-04-19       Impact factor: 5.482

7.  The positive effects of negative work: increased muscle strength and decreased fall risk in a frail elderly population.

Authors:  Paul C LaStayo; Gordon A Ewy; David D Pierotti; Richard K Johns; Stan Lindstedt
Journal:  J Gerontol A Biol Sci Med Sci       Date:  2003-05       Impact factor: 6.053

8.  Predicting hospital discharge disposition in geriatric trauma patients: is frailty the answer?

Authors:  Bellal Joseph; Viraj Pandit; Peter Rhee; Hassan Aziz; Moutamn Sadoun; Julie Wynne; Andrew Tang; Narong Kulvatunyou; Terence O'Keeffe; Mindy J Fain; Randall S Friese
Journal:  J Trauma Acute Care Surg       Date:  2014-01       Impact factor: 3.313

9.  Prevalence of frailty and its association with mortality in general surgery.

Authors:  Jonathan Hewitt; Susan J Moug; Maeve Middleton; Mohua Chakrabarti; Micheal J Stechman; Kathryn McCarthy
Journal:  Am J Surg       Date:  2014-07-27       Impact factor: 2.565

10.  Action seniors! - secondary falls prevention in community-dwelling senior fallers: study protocol for a randomized controlled trial.

Authors:  Teresa Liu-Ambrose; Jennifer C Davis; Chun Liang Hsu; Caitlin Gomez; Kelly Vertes; Carlo Marra; Penelope M Brasher; Elizabeth Dao; Karim M Khan; Wendy Cook; Meghan G Donaldson; Ryan Rhodes; Larry Dian
Journal:  Trials       Date:  2015-04-10       Impact factor: 2.279

View more
  13 in total

1.  Toward Using a Smartwatch to Monitor Frailty in a Hospital Setting: Using a Single Wrist-Wearable Sensor to Assess Frailty in Bedbound Inpatients.

Authors:  Hyoki Lee; Bellal Joseph; Ana Enriquez; Bijan Najafi
Journal:  Gerontology       Date:  2017-11-25       Impact factor: 5.140

Review 2.  ICT technologies as new promising tools for the managing of frailty: a systematic review.

Authors:  Alessia Gallucci; Pietro Davide Trimarchi; Carlo Abbate; Cosimo Tuena; Elisa Pedroli; Fabrizia Lattanzio; Marco Stramba-Badiale; Matteo Cesari; Fabrizio Giunco
Journal:  Aging Clin Exp Res       Date:  2020-07-23       Impact factor: 3.636

3.  Instrumented Trail-Making Task: Application of Wearable Sensor to Determine Physical Frailty Phenotypes.

Authors:  He Zhou; Javad Razjouyan; Debopriyo Halder; Anand D Naik; Mark E Kunik; Bijan Najafi
Journal:  Gerontology       Date:  2018-10-25       Impact factor: 5.140

4.  Physical and Cognitive Function Assessment to Predict Postoperative Outcomes of Abdominal Surgery.

Authors:  Martha Ruiz; Miguel Peña; Audrey Cohen; Hossein Ehsani; Bellal Joseph; Mindy Fain; Jane Mohler; Nima Toosizadeh
Journal:  J Surg Res       Date:  2021-07-09       Impact factor: 2.192

5.  Gait Impairment and Upper Extremity Disturbance Are Associated With Total Magnetic Resonance Imaging Cerebral Small Vessel Disease Burden.

Authors:  Yutong Hou; Yue Li; Shuna Yang; Wei Qin; Lei Yang; Wenli Hu
Journal:  Front Aging Neurosci       Date:  2021-05-12       Impact factor: 5.750

6.  Frail phenotype might herald bone health worsening among end-stage renal disease patients.

Authors:  Chia-Ter Chao; Jenq-Wen Huang; Ding-Cheng Chan
Journal:  PeerJ       Date:  2017-07-10       Impact factor: 2.984

7.  Wearable Sensors and the Assessment of Frailty among Vulnerable Older Adults: An Observational Cohort Study.

Authors:  Javad Razjouyan; Aanand D Naik; Molly J Horstman; Mark E Kunik; Mona Amirmazaheri; He Zhou; Amir Sharafkhaneh; Bijan Najafi
Journal:  Sensors (Basel)       Date:  2018-04-26       Impact factor: 3.576

8.  Toward Smart Footwear to Track Frailty Phenotypes-Using Propulsion Performance to Determine Frailty.

Authors:  Hadi Rahemi; Hung Nguyen; Hyoki Lee; Bijan Najafi
Journal:  Sensors (Basel)       Date:  2018-06-01       Impact factor: 3.576

9.  Upper-extremity function prospectively predicts adverse discharge and all-cause COPD readmissions: a pilot study.

Authors:  Hossein Ehsani; Martha Jane Mohler; Todd Golden; Nima Toosizadeh
Journal:  Int J Chron Obstruct Pulmon Dis       Date:  2018-12-18

Review 10.  Using wearable technology to predict health outcomes: a literature review.

Authors:  Jason P Burnham; Chenyang Lu; Lauren H Yaeger; Thomas C Bailey; Marin H Kollef
Journal:  J Am Med Inform Assoc       Date:  2018-09-01       Impact factor: 4.497

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.