NIH Roundtable on Emergency Trauma Research

Cairns, Charles B.; Maier, Ronald V.; Adeoye, Opeolu; Baptiste, Darryl C.; Barsan, William G.; Blackbourne, Lorne H.; Burd, Randall S.; Carpenter, Christopher R.; Chang, David C.; Cioffi, William G.; Cornwell, Edward E.; Dean, J. Michael; Dyer, Carmel B.; Jaffe, David M.; Manley, Geoff; Meurer, William J.; Neumar, Robert W.; Silbergleit, Robert; Stevens, Molly W.; Wang, Michael; Weiner, Debra K.; Wright, David W.; Conwit, Robin; Dunn, Billy; Eldadah, Basel; Egan, Debra; Filart, Rosemarie; Guerrero, Giovanna; Hack, Dallas; Handigan, Michael; Heppel, David; Hunt, Richard C.; Hicks, Ramona; Janis, Scott; Kerr, Mary Margaret; Kleitman, Naomi; Kopp, Jeffrey B.; Koroshetz, Walter J.; Korpela, Jukka; Mutter, Ryan; Nicholson, Carol; Martinelli, Angela M.; Panagis, James; Scott, Jane D; Somers, S. S.; Sopko, George; Thurmond, Veronica A.; Zalutsky, Bob

doi:10.1016/j.annemergmed.2010.05.029

Cited by 42 publications

(26 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…25 The ED represents a unique milieu and patient phenotype, so predictive instruments from other settings often fail in the chaotic environment of EM. 32 Nonetheless, future investigators should assess the feasibility and prognostic accuracy for future falls of clinical gestalt, 65 as well as existing instruments like the ABCS injurious fall screening tool, 66,67 CAREFALL, 68 FROP-Com, 69,70 HOME FAST, 71 Hendrich II Fall Risk Model, 72,73 STRATIFY, 74 University of Pittsburgh Medical Center screening tool, 67 New York–Presbyterian Fall and Injury Risk Assessment Tool, 73,75 Johns Hopkins Fall Risk Assessment Tool, 76 Maine Medical Center Fall Risk Assessment, 73 Morse Fall Scale, 73,77 Spartanburg Fall Risk Assessment Tool, 78 and risk scores described by Bongue et al 79 and Stel et al 80 No study has previously evaluated these instruments in ED settings. Previous systematic reviews of fall risk factors and prediction instruments neglected ED-based studies and did not report meta-analyses or LRs, but favored the Hendrich II Fall Risk Model 81 or STRATIFY instruments.…”

Section: Discussionmentioning

confidence: 99%

Predicting Geriatric Falls Following an Episode of Emergency Department Care: A Systematic Review

Carpenter¹,

Avidan

Wildes

et al. 2014

Academic Emergency Medicine

117

View full text Add to dashboard Cite

Background Falls are the leading cause of traumatic mortality in geriatric adults. Despite recent multispecialty guideline recommendations that advocate for proactive fall prevention protocols in the emergency department (ED), the ability of risk factors or risk stratification instruments to identify subsets of geriatric patients at increased risk for short-term falls is largely unexplored. Objectives This was a systematic review and meta-analysis of ED-based history, physical examination, and fall risk stratification instruments with the primary objective of providing a quantitative estimate for each risk factor’s accuracy to predict future falls. A secondary objective was to quantify ED fall risk assessment test and treatment thresholds using derived estimates of sensitivity and specificity. Methods A medical librarian and two emergency physicians (EPs) conducted a medical literature search of PUBMED, EMBASE, CINAHL, CENTRAL, DARE, the Cochrane Registry, and Clinical Trials. Unpublished research was located by a hand search of emergency medicine (EM) research abstracts from national meetings. Inclusion criteria for original studies included ED-based assessment of pre-ED or post-ED fall risk in patients 65 years and older with sufficient detail to reproduce contingency tables for meta-analysis. Original study authors were contacted for additional details when necessary. The Quality Assessment Tool for Diagnostic Accuracy Studies (QUADAS-2) was used to assess individual study quality for those studies that met inclusion criteria. When more than one qualitatively similar study assessed the same risk factor for falls at the same interval following an ED evaluation, then meta-analysis was performed using Meta-DiSc software. The primary outcomes were sensitivity, specificity, and likelihood ratios for fall risk factors or risk stratification instruments. Secondary outcomes included estimates of test and treatment thresholds using the Pauker method based on accuracy, screening risk, and the projected benefits or harms of fall prevention interventions in the ED. Results A total of 608 unique and potentially relevant studies were identified, but only three met our inclusion criteria. Two studies that included 660 patients assessed 29 risk factors and two risk stratification instruments for falls in geriatric patients in the 6 months following an ED evaluation, while one study of 107 patients assessed the risk of falls in the preceding 12 months. A self-report of depression was associated with the highest positive likelihood ratio (LR) of 6.55 (95% confidence interval [CI] = 1.41 to 30.48). Six fall predictors were identified in more than one study (past falls, living alone, use of walking aid, depression, cognitive deficit, and more than six medications) and meta-analysis was performed for these risk factors. One screening instrument was sufficiently accurate to identify a subset of geriatric ED patients at low risk for falls with a negative LR of 0.11 (95% CI = 0.06 to 0.20). The test threshold was 6.6% and the...

show abstract

Section: Discussionmentioning

confidence: 99%

Predicting Geriatric Falls Following an Episode of Emergency Department Care: A Systematic Review

Carpenter¹,

Avidan

Wildes

et al. 2014

Academic Emergency Medicine

117

View full text Add to dashboard Cite

show abstract

“…Our research adds to the literature by examining these issues an emergency department population. Despite the importance of this setting for the care of older adults [22] and the unique features of the emergency department for patient care [45], research has not examined the associations between age, health literacy, and cognitive dysfunction among older adults in this population. Our findings showed that three cognitive domains (i.e., registration-recall, verbal fluency, attention) were strongly related to health literacy among older patients, and this was not limited to cognitive tasks most directly related to literacy (i.e., spelling “world” backward) [18].…”

Section: Discussionmentioning

confidence: 99%

Effect of cognitive dysfunction on the relationship between age and health literacy

Kaphingst

Goodman

MacMillan

et al. 2014

Patient Education and Counseling

View full text Add to dashboard Cite

Objectives Age is generally an inverse predictor of health literacy. However, the role of cognitive dysfunction among older adults in this relationship is not understood. Methods We conducted a cross-sectional survey of 446 adult patients in a large urban academic level one trauma center, assessing health literacy and cognitive dysfunction. Results Removing older patients (60 years of age and older) who screened positive for cognitive dysfunction attenuated the relationship between age and health literacy (r= -0.16, p=0.001 vs. r= -0.35, p<0.0001). Older patients screening positive for cognitive dysfunction had significantly lower health literacy than older patients screening negative and patients less than 60 years; health literacy scores did not generally differ significantly between the latter groups. Conclusions Much of the relationship between age and health literacy was driven by cognitive dysfunction among a subset of older adults. Practice implications Our findings suggest that older patients with cognitive dysfunction have the greatest need for health literacy interventions.

show abstract

“…68 The ED is a unique laboratory to evaluate underrepresented populations and acute disease phenotypes that may require different approaches to the design and conduct of research. 69 This survey is a hypothesis-generating tool. The developers of the survey are familiar with the literature on geriatric emergency care and attempted to identify common strategies employed in this population.…”

Section: Discussionmentioning

confidence: 99%

A Profile of Acute Care in an Aging America: Snowball Sample Identification and Characterization of United States Geriatric Emergency Departments in 2013

Hogan

Olade

Carpenter

2014

Academic Emergency Medicine

View full text Add to dashboard Cite

Background: The aging of America poses a challenge to emergency departments (EDs). Studies show that elderly patients have poor outcomes despite increased testing, prolonged periods of observation, and higher admission rates. In response, emergency medicine (EM) leaders have implemented strategies for improved ED elder care, enhancing expertise, equipment, policies, and protocols. One example is the development of geriatric EDs gaining in popularity nationwide. To the authors' knowledge, this is the first research to systematically identify and qualitatively characterize the existence, locations, and features of geriatric EDs across the United States.

show abstract

NIH Roundtable on Emergency Trauma Research

Cited by 42 publications

References 10 publications

Predicting Geriatric Falls Following an Episode of Emergency Department Care: A Systematic Review

Predicting Geriatric Falls Following an Episode of Emergency Department Care: A Systematic Review

Effect of cognitive dysfunction on the relationship between age and health literacy

A Profile of Acute Care in an Aging America: Snowball Sample Identification and Characterization of United States Geriatric Emergency Departments in 2013

Contact Info

Product

Resources

About