Frailty and Health Related Outcomes in Acute Care
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Background: Current frailty screening tools have not been validated for day-to-day use in acute care (Binder, 2015). Many recommended tools include subjective questions and take too much time to complete in a fast-paced clinical environment (Morley et al., 2013). It is for this reason that hand grip strength and gait speed have been chosen as tools to be evaluated for their feasibility and potential utility as single indicators of frailty for use in acute care. A useful indicator should add value to a clinical assessment, such as predicting key outcomes to identify those patients who need more intensive treatment. The predictive validity of frailty measures has been studied extensively in the literature in connection to many different health related outcomes. However, their predictive validity in relation to length of hospital stay and quality of life during and post-discharge from acute care requires further investigation. The More-2-Eat study provides an ideal opportunity to address these knowledge gaps. Purpose: (1) To determine the feasibility of two frailty indicators (5m and HGS) for acute care patients, (2) to determine the predictive validity of these tools with respect to LOS, and (3) to determine if these frailty indicators predict quality of life during and post-discharge from acute care. Methods and findings: More-2-Eat was a multi-site participatory action research study with a before-after time series design. The primary objective of the study was to implement and evaluate the Integrated Nutrition Pathway for Acute Care (INPAC) in Canadian hospitals. Each site was led by an interdisciplinary team, which offered coaching and improvement strategies towards implementing nutrition care best practices. The study population were all patients on the chosen medical unit for implementation of INPAC at the: Royal Alexandra Hospital (Edmonton, AB), Regina General Hospital (Regina, SK), Concordia Hospital (Winnipeg, MB), Niagara Health System, General Site (Niagara Falls, ON), and Ottawa Hospital (Ottawa, ON). There were two key aspects of data collection at the patient level; an 1) audit of nutrition care practices for all patients on the unit during monthly audit days, and 2) a detailed assessment of nutrition, frailty, disability, quality of life and food intake on a subset of patients recruited each month. This latter data collection was used for this study. There were 1250 detailed patient data collections over a 15-month period for analysis. Data included demographics, primary admission diagnosis, length of stay, nutritional risk (and diagnosis of malnutrition if relevant), an estimate of a single meal’s food intake, barriers to food intake, self-reported quality of life, self-reported disability, frailty indicators, patient reported perceptions on adequacy of food intake and nutritional health, and nutrition care provided in the hospital at the time of the data collection. All data were typically collected over one to three days for each patient. Items used in this thesis include: handgrip strength (HGS) (n=1146, mean=20.82 kg), five meter timed walk (5m) (n=535, median=6.79 sec), subjective global assessment (SGA), perceived functional status (Nagi scale), length of stay (LOS), quality of life (QOL), demographics, and reasons for non-completion of assessments. (1) Descriptive statistics revealed that HGS is a more feasible indicator of frailty than the 5m in acute care medical patients, as the completion rate was over 90%; 5m walk could not be completed in more than 50% of patients. Further, HGS had high completion rates across all sites and for diverse populations (diagnoses, sex). HGS was associated with key patient characteristics such as nutritional status (t=4.13, p<0.0001) and perceived functional status (t=10.69, p<0.0001). (2) Multiple linear regression modeling revealed that the addition of HGS as an indicator of frailty significantly improved the predictive value for both male (X2=3.9, p<0.0001) and females (X2=2.0, p<0.05) for LOS, whereas 5m was not useful as a predictor across sex. Yet, standardized cut-points for both measures had low sensitivity and specificity. (3) Multiple linear regression modeling also revealed that the addition of HGS as an indicator of frailty significantly improved the predictive value of both the male (X2= 31.78, p<0.01) and female models (X2= 21.02, p<0.01) with respect to the physical component of QOL in hospital (PCS1) and post-discharge (PCS2) (X2=10.62, p<0.01; X2= 10.75, p<0.01), whereas 5m added significant predictive value across sexes for the physical component of QOL in hospital (PCS1) (X2=9.42, p<0.01; X2=15.72, p<0.01), but not 30 days post-discharge (PCS2). Conclusion: Overall, HGS appears to be a more appropriate single indicator of frailty for consideration in acute care. This tool is feasible for diverse patients and results are associated with nutritional status and perceived functional disability, indicating that it is likely measuring frailty (as defined by Fried, 2001). HGS also appears to be relevant for predicting important outcomes and clinical decision-making. Lower HGS values were correlated with longer LOS and poorer physical QOL. HGS also provided additional predictive value for LOS and physical QOL in hospital and 30 days post-discharge when adjusting for other covariates that would be collected in a clinical setting, including nutritional status. Consideration for use of this tool in acute care is appropriate once useful cut-points have been determined.
Cite this work
Tara McNicholl (2017). Frailty and Health Related Outcomes in Acute Care. UWSpace. http://hdl.handle.net/10012/12350