Original ArticleFrailty in Acute Cardiology: Comparison of a Quick Clinical Assessment Against a Validated Frailty Assessment Tool
Introduction
The assessment of frailty is increasingly topical in both cardiac surgery and cardiology. Frail patients are more vulnerable to the stresses of acute illnesses and are at increased risk of surgical complications, recurrent hospital admissions, eventual institutionalisation and death [1], [2], [3], [4], [5]. Increasingly frail patients are presenting to be referred for invasive cardiac interventions and cardiac surgery. It is therefore important to identify frail patients who are unlikely to benefit from such procedures or whom may in fact come to harm.
There is no gold standard in the assessment of frailty [6], [7], [8], [9], [10]. In an acute setting where a comprehensive assessment by a geriatrician is seldom practical, patient's frailty assessment is often done at the foot-of the bed based on visual appearance and a quick clinical judgment [9], [10]. Various frailty assessment tools have been developed to make frailty assessment more objective and to make the decision-making more transparent. Most of these are also time consuming and have not been formally assessed in the acute cardiology setting. Many frailty assessment tools assess around 30-70 domains of frailty and these tools are usually poorly understood by non-geriatricians [9], [11], [12].
Simplified tools have been developed for use in settings such as acute care clinical practice [13], [14]. One such tool is the Edmonton Frail Scale [14]. This scale uses 11 items to assess physical and psychosocial features of frailty and incorporates some performance measures. It has been validated against a geriatrician's comprehensive assessment, the Geriatric Clinical Impression of Frailty (GCIF). In an acute care setting, however, performance based measures may be confounded by performance limitation related to the acute illness. The Reported Edmonton Frail Scale (REFS) which was adapted from the Edmonton Frail Scale, uses participants’ self-reported function overcoming the limitations of performance assessment [13]. It is a scale that can be readily completed in a few minutes by staff without specific geriatric training. The REFS has been performed by non-geriatrician researchers and has been cross-validated against the GCIF in an Australian acute care hospital and was found to correlate moderately well (R=0.61) with the GCIF with an excellent inter-rater reliability (kappa=0.83) [13].
The aim of this study was to evaluate the utility of a quick clinical assessment against this validated frailty assessment tool to determine if an elderly patient is frail or not. We hypothesised that a traditional foot-of-the-bed frailty assessment is closely related to a frailty assessment tool with little inter-observer variability.
The secondary aim of this study was to evaluate the frailty status of elderly patients who have been offered coronary intervention or cardiac surgery at the Christchurch Hospital. We hypothesised that based on current practice, patients who are offered either coronary intervention or cardiac surgery were more likely to be non-frail.
Section snippets
Methods
This prospective study was conducted in Christchurch Hospital. Ethical approval for the study was obtained from the Health and Disabilities Ethics Committees (HDEC). We recruited cardiology in-patients 70 years or older. Patients admitted for elective procedures were excluded. Patients who met inclusion criteria were identified using the hospital electronic database and were approached. Patients who declined consent or who were unable to provide consent were not assessed.
Patients were first
Results
Due to the acute nature of cardiology inpatient care 50 patients were approached for consent during a study period of 45 days. Three patients declined to participate. Patient demographics of the 47 cardiology inpatients we studied are shown in Table 2.
Based on their REFS, patients were divided into non-frail (0-7) and frail (8-18). Participants’ baseline characteristics, are shown in Table 3. There were no differences between the two groups in terms of age, gender, and living circumstances.
Discussion
Frailty is a difficult topic with there being no single definition of frailty. Traditionally the five phenotypes of frailty are: weakness, sarcopenia, weight loss, physical inactivity and slowness [5], [10]. However, there exists an overlap between frailty and other syndromes associated with ageing [1], [8], [11], [12]. Therefore the inclusion of disability and comorbidity has been recommended when assessing frailty.
A comprehensive geriatric assessment depends on clinical judgement and would
Study Limitations
The sample size of this prospective study was small. This was mainly due to early patient discharges and the Registrar not being able to reach these patients before discharge. These patients were likely to be well, have non-cardiac or non-acute cardiac issues and would likely have low REFS. Despite being a small sample size, our patient population was sufficiently reflective of the typical elderly patients admitted under cardiology. A longer study period with a larger study population may be
Conclusion
Data from our study suggest that a quick foot-of-the-bed clinical assessment is not a reliable way to determine frailty. There was poor agreement between clinicians and in particular patients who were considered borderline frail on their REFS. In addition, the role for REFS or other frailty indices in setting of acute cardiology remains highly uncertain. Therefore, we would recommend that when making major cardiac interventional or surgical decisions, it is important to spend time with the
Conflict of Interest
None to declare
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The prevalence of frailty and pre-frailty among geriatric hospital inpatients and its association with economic prosperity and healthcare expenditure: A systematic review and meta-analysis of 467,779 geriatric hospital inpatients
2022, Ageing Research ReviewsCitation Excerpt :The median score of the Joanna Briggs Institute critical appraisal tool for studies reporting prevalence data for the 96 included studies was 8 out of 9 (range 7–9) (Appendix 7). Ninety-six studies, comprising of data from of n = 467,779 geriatric hospital inpatients, were eligible for inclusion in the overall pooled prevalence analysis of frailty (Alonso Salinas et al., 2018; Amblàs-Novellas et al., 2018; Andela et al., 2010; Andrew et al., 2017; Attisano et al., 2017; Baldwin et al., 2014; Blanco et al., 2017; Bo et al., 2015; Bo et al., 2016; Cheung et al., 2017; Chew et al., 2017; Chia et al., 2016; Chong et al., 2017; Coleman et al., 2012; Courtney-Brooks et al., 2012; Crozier-Shaw, Joyce, 2018; Dal Moro et al., 2017; Dent et al., 2014; Dorner et al., 2014; Drudi et al., 2018; Dutzi et al., 2017; Eamer et al., 2018;; Eeles et, al., 2012; Ekerstad et al., 2011; Engelhardt et al., 2018; Ferrero et al., 2017; Ga et al., 2018; Gleason et al., 2017; Goldfarb et al., 2018; Guidet et al., 2018; Gullón et al., 2018; Hartley et al., 2017; Heppenstall et al., 2011; Hewitt et al., 2015, 2016; Hii et al., 2014; Hilmer et al., 2011; Ibrahim et al., 2019; Induruwa et al., 2017; Jacobs et al., 2017; Jokar et al., 2016; Joosten et al., 2014; Joseph et al., 2014, 2016; Juma et al., 2016; Kang et al., 2015; Karlekar et al., 2017; Keevil et al., 2018; Kenig et al., 2015; Khan et al., 2019; Kobe et al., 2016; Koyama et al., 2018; Kusunose et al., 2018; Le Maguet et al., 2014; Lee et al., 2018; Lin et al., 2017; Llaó et al., 2018; Ma et al., 2013; Madni et al., 2018; Martín et al., 2018; Mason et al., 2018; Maxwell et al., 2018; McGuckin et al., 2018; McIsaac et al., 2019; Morton et al., 2018; Muessig et al., 2018; Müller et al., 2017; Myint et al., 2018; Nguyen et al., 2016; Nolan et al., 2016; Oliveira et al., 2013; Öztürk et al., 2017; Papageorgiou et al., 2018; Papakonstantinou et al., 2018; Parmar et al., 2019; Pasqualetti et al., 2018; Patel et al., 2018; Peel et al., 2017; Pelavski et al., 2017; Perera et al., 2009; Pollack et al., 2017; Poudel et al., 2016; Purser et al., 2006; Ritt et al., 2015; Rose et al., 2014; Sánchez et al., 2011; Sanchis et al., 2015;; Sikder et al., 2019; Sündermann et al., 2014; Thai et al., 2015; Ticinesi et al., 2016; Timmons et al., 2015; Valentini et al., 2018; Vidán et al., 2014; Wallis et al., 2015; Wou et al., 2013); 62 studies, comprising of data from n = 35,348 geriatric hospital inpatients in the overall pooled prevalence analysis of pre-frailty (Alonso Salinas et al., 2018; Amblàs-Novellas et al., 2018; Andrew et al., 2017; Baldwin et al., 2014; Blanco et al., 2017; Cheung et al., 2017; Chong et al., 2017; Coleman et al., 2012; Courtney-Brooks et al., 2012; Dal Moro et al., 2017; Dent et al., 2014; Dorner et al., 2014; Dutzi et al., 2017; Eamer et al., 2018; Ekerstad et al., 2011; Ga et al., 2018; Gleason et al., 2017; Guidet et al., 2018; Hartley et al., 2017; Heppenstall et al., 2011; Hewitt et al., 2015; Hewitt et al., 2016; Hii et al., 2014; Ibrahim et al., 2019; Induruwa et al., 2017; Joosten et al., 2014; Joseph et al., 2016; Juma et al., 2016; Kang et al., 2015; Karlekar et al., 2017; Keevil et al., 2018; Koyama et al., 2018; Kusunose et al., 2018; Le Maguet et al., 2014; Lin et al., 2017; Ma et al., 2013; Madni et al., 2018; Martín et al., 2018; Mason et al., 2018; Maxwell et al., 2018; McGuckin et al., 2018; Muessig et al., 2018; Müller et al., 2017; Myint et al., 2018; Nolan et al., 2016; Oliveira, Öztürk et al., 2013, 2017; Papageorgiou et al., 2018; Papakonstantinou et al., 2018; Parmar et al., 2019; Pasqualetti et al., 2018; Peel et al., 2017; Pelavski et al., 2017; Pollack et al., 2017; Ritt et al., 2015; Rose et al., 2014; Sanchis et al., 2015; Sikder et al., 2019; Ticinesi et al., 2016; Timmons et al., 2015; Valentini et al., 2018; Wallis et al., 2015). The overall pooled prevalence of frailty and pre-frailty among geriatric hospital inpatients was 47.4% (95% CI 43.7–51.1%), and 25.8% (95% CI 22.0–29.6%) respectively (Fig. 2, Supplementary Figure A).
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