Frailty in the over 65’s undergoing elective surgery (FIT-65) – a three-day study examining the prevalence of frailty in patients presenting for elective surgery

Frailty in the over 65’s undergoing elective surgery (FIT-65) – a three-day study examining the prevalence of frailty in patients presenting for elective surgery | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Frailty in the over 65’s undergoing elective surgery (FIT-65) – a three-day study examining the prevalence of frailty in patients presenting for elective surgery Sarah Harrison, David Alexander Harvie, Lewis Matthews, Frances Wensley This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-982059/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract Background Frailty increases the risk of perioperative complications, length of stay, and the need for assisted-living after discharge. As the UK population ages the number of frail patients presenting for elective surgery in the UK is likely to grow. Despite the potential benefits of early diagnosis, frailty is not uniformly screened for in UK elective surgical patients and its prevalence remains unclear. The primary aim of this study was to assess the prevalence of frailty in patients aged over 65 years undergoing elective surgery. Methods We performed a prospective cross-sectional observational study in eight UK hospitals. Data were collected over three consecutive days with follow-up at 30 days. HRA approval was obtained (REC 20/SC/0121) and signed informed consent obtained. Participants were eligible for inclusion if they were 65 years or older and undergoing elective surgery. Pre-operative data were collected from hospital notes by anaesthetic trainees. A member of the research team blinded to the pre-operative dataset screened the participant for frailty pre-operatively using the Reported Edmonton Frail Scale (REFS). Post-operative data were collected from the notes on day of surgery and at 30 days. Participants were defined as “frail” if they scored 8 or more on the REFS. Results 228 participants were recruited during the study period of whom 218 proceeded to surgery. There were 103 females and 115 males. Median age was 75 years (interquartile range 70-80). Thirty-seven participants (17.0%) were identified as frail. Frail patients were older, had a higher ASA score, were more likely to have carers and were more likely to be anaemic and present with ECG abnormalities. There were no differences in gender, BMI, place of residence or smoking status for patients identified as frail versus non-frail. There was no difference in length-of-stay between frail and non-frail patients, although those identified as frail were less likely to be discharged to their own home. Conclusion We found the prevalence of frailty in a mixed population of elective surgical patients aged 65 or over to be 17.0%. Furthermore, we found the REFS to be a practical tool for pre-operative frailty screening. Frail patients presented for elective surgery with modifiable co-morbidities which could have been optimised pre-operatively. Early screening could highlight frail patients, allowing time for pre-operative planning and evidence-based optimisations of comorbidities. We therefore encourage the adoption of frailty assessment as a routine part of pre-operative assessment. Surgery Frailty Pre-operative risk assessment Reported Edmonton Frail Scale Pre-operative optimisation Figures Figure 1 Background The association between frailty and adverse surgical outcome is widely acknowledged( 1 , 2 ). Frailty, defined as a ‘’distinctive health state related to the ageing process in which multiple body systems gradually lose their in-built reserves,’’( 3 ) has been shown to increase the risk of surgical complications, length of stay, and the need for assisted-living following hospital discharge.( 4 – 6 ) Consequently, older people living with frailty are at increased risk of perioperative morbidity. Over the next 10 years the Office for National Statistics predicts a rise of 3.0 million in the United Kingdom’s (UK) overall population, with the number of people over 85 years expected to double in 25 years.( 7 ) With frailty and ageing going hand-in-hand, it is likely we will see a rising number of frail patients presenting to hospitals for elective surgery. This growing and ageing population, combined with an increasing number of surgical procedures available, has led to unprecedented demand on the National Health Service (NHS) for the provision of elective surgery. In England between 2014 and 2015, 2.5 million people aged over 75 years underwent surgery - a third of whom were aged over 85. This was a significant rise from just under 1.5 million who had surgery between 2006 and 2007.( 8 ) The intermittent suspension of elective operating during the Severe Acute Respiratory Syndrome Coronavirus 2 (COVID-19) pandemic has further increased demand, with over 5 million people now awaiting surgery in the UK. In a recent survey of anaesthetic Perioperative Medicine leads across the UK, screening and management of frailty were identified as priorities on a list of perioperative focuses( 9 ). Both screening and management, however, were recognised as being challenging to implement. Only 24% of respondents reported that their hospitals screened for frailty, and amongst those at least six different types of frailty assessment tool were in use.( 9 ) The range of frailty assessment tools available vary in subjectivity, objectivity, ease of use, and on the model of frailty they assess. The Comprehensive Geriatric Assessment is the gold standard for the assessment of frailty but is impractical for routine use in the pre-operative setting. It requires over an hour to complete and includes assessments from multiple multi-disciplinary team members. The ideal tool for screening in the pre-operative setting would be time and staff-efficient, easy to perform, objective, and with high sensitivity and specificity. The Edmonton Frail Scale (EFS) has evidence for use in the perioperative setting( 10 ) and is a tool supported by the British Geriatric Society (BGS)( 3 ). It is quick to perform taking approximately five minutes to complete and, importantly, is able to assess multiple domains of frailty which may be subject to optimisation in the pre-operative period( 11 ). Performing the physical assessment element of the EFS can be limiting in the pre-assessment setting. The Reported Edmonton Frail Scale (REFS) substitutes the observed “get up and go” assessment with a verbal report of physical function, and has been utilised in several studies.( 12 , 13 ) Despite its perceived importance, frailty is still not routinely screened for in all UK surgical patients. Its relevance in those attending for elective surgery therefore remains unclear. Our study aims to establish the prevalence of frailty in our local population during elective surgery. Additionally, we assessed whether frailty was associated with known peri-operative risk factors as well as length-of-stay and discharge status, thus evaluating its importance for patients during their perioperative journey. It is possible that better knowledge of prevalence would empower systematic changes in care pathways and subsequently improve outcomes for this high-risk group of patients. Methods A prospective multi-centre observational cohort study was carried out in eight hospitals within the Wessex School of Anaesthesia between 1st September and 30th October 2020. Sites comprised a mixture of small and large district general hospitals and one teaching hospital. The study was undertaken in collaboration with the trainee-led South Coast Perioperative Audit and Research Collaborative (SPARC). Ethical approval was given by the South Central Hampshire B Research Ethics committee (20/SC/0121). Patients were eligible for inclusion if they were aged 65 years or older and having elective surgery under general, regional or local anaesthesia. Patients were excluded if they declined to participate, were unable to give informed consent, were having emergency surgery or had difficulties with the English language. Written informed consent was obtained for all participants on the morning of surgery. Each of the study sites collected data over three consecutive weekdays during the study period. The timing of the three days during the study period was at the discretion of local site leads. Participants were identified from departmental operating lists either on the day before or day of surgery. Basic demographics, co-morbidities and bloods were collected pre-operatively by anaesthetic trainees independent of the anaesthetic team delivering perioperative care. A second study team member blinded to the participant’s pre-operative dataset completed the REFS prior to surgery. Based on the REFS score (out of a maximum eighteen) participants were classified as Not Frail (0-5); Vulnerable ( 6 – 7 ); Mildly Frail ( 8 – 9 ); Moderately Frail ( 10 – 11 ); Severely Frail ( 12 – 18 ). Intra-operative and recovery data were collected once patients had returned to the ward or surgical day unit. Participants were followed-up at 30 days to assess length of stay, discharge status and location. Analyses were conducted on all patients for whom a frailty score was available and proceeded to surgery. Patients were registered on day of surgery and followed up at 30 days for outcomes. Data were summarised using means and standard deviations or percentages of categorical variables. The Kolmogorov-Smirnov test was used to assess for normality. Variations between people with and without frailty were estimated using two-sampled t tests or rank sum tests (non-parametric data) for differences between means or medians respectively, and chi-squared tests for correlation between categorical variables. A number of different outcomes were used to assess the impact of frailty on patients undergoing surgery, including length of stay, post-operative destination, mortality and discharge destination. Data were analysed using SPSS Statistics 26.0 (IBM Corp. Released 2019. IBM SPSS Statistics for Windows, Version 26.0. Armonk, NY: IBM Corp). Results Data were collected on 228 patients during the study period. Ten patients did not proceed to surgery, therefore 218 patients were followed up at 30 days. Basic demographic data for these patients are summarised in Table 1 . Table 1 Participant demographics All participant demographics (n=218) Age (years) 75 (IQR 70-80) Gender Female 103 (47.2%) Male 115 (52.8%) BMI 27 (IQR 24-30) Smoking status Never smoked 108 (49.8%) Ex-smoker 87 (40.0%) Current smoker 12 (5.5%) Unknown 10 (4.6%) Usual residence Own home 211 (96.8%) Sheltered accommodation 2 (0.9%) Assisted living 1 (0.5%) Family/friend 4 (1.8%) Carers None 204 (93.6%) Weekly 7 (3.2%) Daily 4 (1.8%) More than daily 3 (1.4%) Walking aids Yes 61 (28.0%) Hearing aids Yes 37 (17.1%) Visual aids Yes 177 (81.6%) Cardiac history No failure 107 (49.1%) Diuretic, digoxin, antianginal or antihypertensive 91 (41.7%) Oedema, warfarin or borderline cardiomegaly 16 (7.3%) Raised JVP or cardiomegaly 2 (0.9%) Diabetes No 175 (80.3%) Type 2 (diet controlled) 24 (11.0%) Type 2 (tablet controlled) 7 (3.2%) Type 2 (on insulin) 11 (5.0%) ECG findings No abnormalities 117 (53.7%) AF rate 60-90 9 (4.1%) AF rate > 90, paced or other dysrhythmia 35 (16.1%) The median REFS score for all participants was 4 (Interquartile Range (IQR) 2-6). The distribution of REFS scores is displayed in Figure 1 . Thirty-seven (17.0%) participants had a REFS score of eight or more and were classified as frail. The remaining 181 (83.0%) had a REFS score of seven or less and were classified as not frail or vulnerable. The breakdown of the number of participants in each frailty category by REFS score is summarised in Table 2 . A large number of cases were day-case procedures, reflected in a median length-of-stay of zero days (IQR 0-3). The vast majority (95.0%) were discharged to their own homes. Table 2 Reported Edmonton Frail Scale scores All participants (n=218) Reported Edmonton Frail Scale outcome Not frail (REFS less than 8) 181 (83.0%) Frail (REFS 8 or more) 37 (17.0%) Frailty category Not frail (REFS 0-5) 158 (72.5%) Vulnerable (REFS 6-7) 23 (10.6%) Mildly frail (REFS 8-9) 28 (12.8%) Moderately frail (10-11) 7 (3.2%) Severely frail (12-18) 2 (0.9%) Length of stay (days) 0 (IQR 0-3) Discharged to own home Yes 207 (95.0%) No 7 (3.2%) Not known 4 (1.8%) Participants were recruited from a large number of surgical subspecialties, with orthopaedic, urological and ophthalmic procedures being the most commonly performed. The commonest American Society of Anaesthesiologists (ASA) score was 2, though a large number of participants did not have a pre-operative ASA score documented. The majority of participants had a general anaesthetic technique, most frequently using volatile anaesthetic agents. Important perioperative data are detailed in Table 3 . Table 3 Perioperative data All participants (n=218) Surgical specialty Orthopaedics 43 (19.7%) Urology 37 (17.0%) Eyes 22 (10.1%) Abdominal – Lower GI 20 (9.2%) Gynaecology 15 (6.9%) Burns & Plastics 14 (6.4%) Head & Neck 12 (5.5%) Abdominal – Upper GI 9 (4.1%) Cardiac 8 (3.7%) Thoracic 7 (3.2%) Vascular 7 (3.2%) Neurosurgery 6 (2.8%) Abdominal – Hepatobiliary 2 (0.9%) Other 16 (7.3%) ASA 1 4 (1.8%) 2 75 (34.4%) 3 53 (24.3%) 4 6 (2.8%) Not documented 80 (36.7%) Type of anaesthetic General - inhalational 84 (38.5%) General - target controlled infusion 51 (23.4%) Local infiltration only 41 (18.8%) Spinal 23 (10.6%) Regional block 11 (5.0%) Sedation 6 (2.8%) Unknown 2 (0.9%) summarises the differences between frail (n=37) and non-frail (n=181) participants. In general, patients who were frail were more likely to be older (median age 78 years [IQR 74 - 86]) than patients who were vulnerable or not frail (median age 74 years [IQR 70-79], p<0.001). There were no significant differences between frailty groups for other demographic variables such as gender (p=0.102), smoking status (p=0.095) and Body Mass Index (BMI) (p=0.297). Frail patients were more likely to have carers (p<0.001) and use walking aids (p<0.001). Overall, frail patients were more likely to have co-morbidities associated with poor surgical outcome than those who were not frail or vulnerable. Frail patients were more likely to be anaemic (62.1% vs. 32.6%, p = 0.003) and have multiple comorbidities as evidenced by higher ASA score (p<0.001). Though not statistically significant there was a trend towards an increased prevalence of diabetes in frail patients (29.7% vs. 17.2%, p=0.079) and similarly, frail patients were more likely to present with a history of cardiac disease (74.3% vs. 45.9%, p=0.002) and abnormal Electrocardiogram (ECG) findings (38.5% vs. 18.5%], p=0.024). Table 4 Comparison between frail and non-frail patients Not frail (n=181) Frail (n=37) p-value Age (years) 74 (IQR 70-79) 78 (IQR 74-86) <0.001 Gender Female 81 (44.8%) 22 (59.5%) 0.102 Male 100 (55.2%) 15 (40.5%) BMI 27.0 (IQR 24.0-30.4) 26.0 (IQR 24.1-29.4) 0.297 Smoking status Never/Ex 167 (95.4% 28 (87.5%) 0.095 Current 8 (4.6%) 4 (12.5%) Any carers No carers 176 (97.2%) 28 (75.7%) <0.001 Carers 5 (2.8%) 9 (24.3%) Walking aids Yes 39 (21.5%) 22 (59.5%) <0.001 Hearing aids Yes 28 (15.6%) 9 (24.3%) 0.196 Visual aids Yes 145 (80.6%) 32 (86.5%) 0.397 Cardiac disease Yes 83 (45.9%) 26 (74.3%) 0.002 Diabetes Non-diabetic 149 (82.8%) 26 (70.3%) 0.079 Diabetic 31 (17.2%) 11 (29.7%) ECG abnormalities Normal or rate controlled AF 110 (81.5%) 16 (61.5%) 0.024 AF rate > 90, paced or other dysrhythmia 25 (18.5%) 10 (38.5%) ASA score Not documented 68 (37.6%) 12 (32.4%) <0.001 1 4 (2.2%) - 2 70 (38.7%) 5 (13.5%) 3 35 (19.4%) 18 (48.7%) 4 4 (2.2%) 2 (5.4%) Haemoglobin (g/L) a 135.1 (+/-14.8) 126.4 (+/-14.8) 0.005 Anaemia (Haemoglobin < 130g/L) a Yes 43/132 (32.6%) 18/29 (62.1%) 0.003 Length of stay (days) 0 (IQR 0-2) 0 (IQR 0-4) 0.681 Discharged to own home No 1 (0.6%) 6 (17.1%) <0.001 Yes 178 (99.4%) 29 (82.9%) a Data available for 161 participants The mortality rate was less than 1% for the entirely study population. However, the one patient who passed away was frail according to REFS. Similarly, four patients were still in hospital at the end of the study period, two frail and two not frail. Length of stay did not differ between frail and non-frail participants (p-value = 0.681). Discharge destination was significantly different (p-value < 0.001), with frail patients more likely to be discharged with family and friends, into sheltered accommodation or to other destinations not their own home. However, the total number of cases in each of these groups was very small, as 29 [82.9%] frail patients were discharged to their own home compared to 178 [99.4%] not frail patients. Discussion In this prospective observational study of patients aged 65 or older undergoing elective surgery we established the prevalence of frailty to be 17.0% using the Reported Edmonton Frail scale. Frail patients were more likely to present with modifiable pre-operative co-morbidities, require carers, and were less likely to be discharged to their own homes following surgery. All of these are relevant factors in the planning of personalised perioperative care. To our knowledge, this is the first study to assess the prevalence of frailty in patients undergoing solely elective surgery in the UK. The prevalence of frailty in the surgical population varies widely in the literature and is influenced by both the tool being used and the population being assessed. The largest study to date of frailty in patients undergoing elective and emergency surgery (over 430,000 American veterans) found 8.5% patients to be frail( 14 ) whereas a recent meta-analysis of over 2000 general surgical patients (elective and emergency) estimated the prevalence to be higher, at between 10 and 37%.( 15 ) Few studies have been undertaken in the UK and all are a mix of elective and emergency patients, for example a study of emergency and elective vascular patients in a UK setting found 52% of patients aged over 60 were frail, using the Edmonton Frail Scale.( 16 ) One of the key findings of our study was that many frail patients had reached the day of planned surgery with medical problems which, had they been identified earlier, could have been corrected or optimised in advance. For example, nearly two thirds of frail patients were found to be anaemic compared to only a third of non-frail patients. Identifying and treating these frail patients, who appear to have a significantly higher risk of anaemia, could reduce associated post-operative complications( 15 ). There was also a trend towards frail patients having a higher rate of diabetes, another important perioperative risk factor. The use of a frailty screening tool such as the REFS could highlight these patients earlier in the perioperative pathway, allowing time for pre-operative optimisation and a reduction in post-operative complications( 17 , 18 ). The Royal College of Anaesthetists emphasises that frailty requires a cross-specialty approach to enable optimisation of medicines and improved management of non-surgical comorbidities. A challenge is that to achieve this requires both time and resources, especially when considering the impact of COVID-19 on elective surgery( 19 ). Whilst the REFS was easily implemented on the morning of surgery, clearly screening would be best performed earlier in the perioperative pathway to allow time for intervention, for example at time of referral from primary care. A practical alternative could be to integrate the REFS (or other frailty assessment tool) into the routine pre-operative assessment questionnaires already performed by hospital pre-admission teams. Knowledge of the presence and severity of frailty can help with assessing surgical risk ( 20 ) and, thus, help inform shared decision-making discussions and ensure validity of consent( 21 ). Having been informed of their higher-risk status, some patients may choose to proceed with planned surgery, whilst others may elect for an alternative procedure or choose not to have surgery at all( 22 ). Advanced knowledge of frailty can help ensure appropriate personnel and equipment are available in theatres on the day of surgery. For example, frail patients may be given a longer time-slot for induction of anaesthesia, or be cared for by a more senior anaesthetist. There may be adjustments that need to be made to the anaesthetic technique; such as additional monitoring or selection of regional blockade in place of general anaesthesia. Discussion of these interventions in advance of surgery will also allow patient expectations to be managed. From the point-of-view of post-operative care and discharge planning, an awareness of frailty pre-operatively can also ensure adequate planning and resource allocation. For example frail patients could be identified in advance of surgery so that physiotherapists, dietitians and a clinician with an interest in perioperative medicine for the elderly could be involved in planning their post-operative care. Not only could this improve quality of care but may also optimise hospital efficiency through reduced length-of-stay and cancellations. Although our study did not demonstrate significant differences in length-of-stay we did show that 99% of non-frail patients were discharged to their own home, compared to only 83% of frail patients. This again may suggest a benefit for discharge planning in identifying these patients early on in their surgical journey. One of the main strengths of this study was that it recruited participants from a wide geographical area incorporating a mixture of small and large hospitals serving a mixture of inner city, semi-rural and rural communities. In practice we found the REFS questionnaire to be quick to perform; taking only five minutes or less to complete. It was also found to be acceptable to patients. The junior doctors administering the questionnaire, predominantly anaesthetic trainees, did not require any additional training which suggests that the REFS would be quick and cost-effective to introduce into routine clinical practice. The delivery of a multi-centre study by doctors in training is another strength. However, this study has limitations. The participants were recruited from a heterogeneous group of surgical specialties and it is likely that different specialties will have differing rates of frailty. Furthermore, the COVID-19 pandemic impacted on elective surgery to an extent still difficult to ascertain. While this study was conducted during a period of relatively increased operating activity, it is likely that patients listed for surgery were selected because they were from a less vulnerable patient group or not shielding. The pandemic also led to a shortage of high dependency and intensive care beds, meaning fewer high-risk elective procedures were performed( 1 ). A further factor affecting the study’s generalisability was that patient’s without capacity were excluded. Some of the most severely frail patients presenting for surgery, for example with advanced dementia, will therefore not have been approached. Conclusions In conclusion, we found the prevalence of frailty in a mixed population of elective surgical patients aged 65 or over to be 17.0%. Furthermore, we found the REFS to be a practical tool for pre-operative frailty screening. Frail patients presented more frequently with modifiable co-morbidities, such as anaemia, which could have been optimised pre-operatively. Adequately powered future studies should further assess the impact of frailty, and we look forward to the results of the upcoming third Sprint National Audit Project( 23 ). Early screening for frailty could highlight frail patients and allow time for evidence-based pre-operative planning and interventions to be made and we therefore encourage frailty assessment to be a routine part of pre-operative assessment with the early involvement of relevant healthcare professionals. With waiting times for elective surgery at an unprecedented high, we have both an opportunity and responsibility to use this time well. Abbreviations ASA- American Society of Anaesthesiologists BMI – Body Mass Index COVID-19 – Severe Acute Respiratory Syndrome Coronavirus 2 ECG - Electrocardiogram EFS – Edmonton Frail Scale HRA – Health Research Authority IQR – Interquartile Range REFS – Reported Edmonton Frail Scale SD-Standard deviation SPARC – South Coast Perioperative Audit and Research Collaborative UK – United Kingdom NHS – National Health Service BGS – British Geriatric Society Declarations Ethics approval and consent to participate Ethical approval was given by the South Central Hampshire B Research Ethics committee (20/SC/0121). Consent for publication Not applicable Availability of data and Materials The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request Competing Interests The authors declare that they have no competing interests Funding The work was completed whilst Dr Lewis Matthews, Dr David Harvie and Dr Frances Wensley were funded National Institute for Healthcare Research (NIHR) Academic Clinical Fellowship. This article presents independent research to that funded by the NIHR. The views expressed are those of the author and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care. Authors Contributions SH lead organisation of collection of data across sites, data collection and writing the manuscript. LM was a major contributor to study design, analysis of data and writing the manuscript. FW was a local PI for data collection, analysed data and a contributor to writing the manuscript. 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Sprint Natioanl Anaesthesia Project (SNAP 3) Frailty and Delerium2022. Available from: https://www.niaa-hsrc.org.uk/Background-and-study-rationale#pt . Supplementary Files SupplementaryinformationListofcontributors.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviewer # 2 agreed at journal 27 Oct, 2021 Reviewer # 1 agreed at journal 24 Oct, 2021 Review # 1 received at journal 24 Oct, 2021 Reviewers invited by journal 23 Oct, 2021 Editor assigned by journal 17 Oct, 2021 Submission checks completed at journal 17 Oct, 2021 Editor invited by journal 17 Oct, 2021 First submitted to journal 15 Oct, 2021 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-982059","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research","associatedPublications":[],"authors":[{"id":59592258,"identity":"3d11c4b8-e39f-44d8-9aae-54611d869eab","order_by":0,"name":"Sarah Harrison","email":"","orcid":"","institution":"Queen Alexandra Hospital, Portsmouth","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Sarah","middleName":"","lastName":"Harrison","suffix":""},{"id":59592259,"identity":"d99c497f-eadc-477d-b3b7-7bdb8974888c","order_by":1,"name":"David Alexander Harvie","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABFElEQVRIie3RMWrDMBSA4ScE9iKSVaZDrmBTaCm4zVVsDOqSrqVTSDAoS7pr8EE6ygiaxTSrhy7F4CmDuhU6tHKcJUUuGTPoR3iw/AnJAnC5zjFpBumegBagvaM5zwaOCRLmI3KYoP8R6AkAJqeQ0aaK5A7eJ9ciWzbxYzyZ+s+NRi/xHChLbCSoZmFZQBsVdZpfzt5YtCabK4oqRg2RNhJKligCCglS8osHrhJCmQeIK0PuF1aybfdkasjq+6YnWCP+M0zqTHYkFf6SY9QToIjLwY0FdSPLIlSZIXmw7s5SvXo05VnASWs9/mib5nr3pG4F9j/0l/lj/opj/cnvxmOfhTZy2N7fF93yAxfpcrlcrhP6BbOlYY3z9IcxAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0003-4296-3254","institution":"University Hospital Southampton","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"David","middleName":"Alexander","lastName":"Harvie","suffix":""},{"id":59592260,"identity":"8762c9cb-41e2-472f-b334-072a262d1a0a","order_by":2,"name":"Lewis Matthews","email":"","orcid":"","institution":"University Hospital Southampton NHS Foundation Trust","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Lewis","middleName":"","lastName":"Matthews","suffix":""},{"id":59592261,"identity":"644168b3-fad3-4384-baaa-45b9055822f3","order_by":3,"name":"Frances Wensley","email":"","orcid":"","institution":"University Hospital Southampton NHS Foundation Trust","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Frances","middleName":"","lastName":"Wensley","suffix":""}],"badges":[],"createdAt":"2021-10-16 10:16:07","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-982059/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-982059/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":15034287,"identity":"b8e66ad6-90fa-4878-862f-a85082e3c096","added_by":"auto","created_at":"2021-10-29 16:31:14","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":11683,"visible":true,"origin":"","legend":"Participant Reported Edmonton Frail Scale scores (n=218)","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-982059/v1/d63744ad924cd22967d0af01.png"},{"id":15034288,"identity":"9214eb48-929c-49f6-a74b-5e47d40ab87f","added_by":"auto","created_at":"2021-10-29 16:31:17","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":439950,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-982059/v1/ccf5a616-540c-4f09-9e54-55b2726988d1.pdf"},{"id":15034286,"identity":"c98cf72f-ecd2-4444-8f94-9ae63d821d95","added_by":"auto","created_at":"2021-10-29 16:31:14","extension":"docx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":19389,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryinformationListofcontributors.docx","url":"https://assets-eu.researchsquare.com/files/rs-982059/v1/4df52d6156ddcaec18d93359.docx"}],"financialInterests":"","formattedTitle":"Frailty in the over 65’s undergoing elective surgery (FIT-65) – a three-day study examining the prevalence of frailty in patients presenting for elective surgery","fulltext":[{"header":"Background","content":"\u003cp\u003eThe association between frailty and adverse surgical outcome is widely acknowledged(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Frailty, defined as a \u0026lsquo;\u0026rsquo;distinctive health state related to the ageing process in which multiple body systems gradually lose their in-built reserves,\u0026rsquo;\u0026rsquo;(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) has been shown to increase the risk of surgical complications, length of stay, and the need for assisted-living following hospital discharge.(\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e) Consequently, older people living with frailty are at increased risk of perioperative morbidity.\u003c/p\u003e \u003cp\u003eOver the next 10 years the Office for National Statistics predicts a rise of 3.0 million in the United Kingdom\u0026rsquo;s (UK) overall population, with the number of people over 85 years expected to double in 25 years.(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e) With frailty and ageing going hand-in-hand, it is likely we will see a rising number of frail patients presenting to hospitals for elective surgery. This growing and ageing population, combined with an increasing number of surgical procedures available, has led to unprecedented demand on the National Health Service (NHS) for the provision of elective surgery. In England between 2014 and 2015, 2.5 million people aged over 75 years underwent surgery - a third of whom were aged over 85. This was a significant rise from just under 1.5 million who had surgery between 2006 and 2007.(\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e) The intermittent suspension of elective operating during the Severe Acute Respiratory Syndrome Coronavirus 2 (COVID-19) pandemic has further increased demand, with over 5 million people now awaiting surgery in the UK.\u003c/p\u003e \u003cp\u003eIn a recent survey of anaesthetic Perioperative Medicine leads across the UK, screening and management of frailty were identified as priorities on a list of perioperative focuses(\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Both screening and management, however, were recognised as being challenging to implement. Only 24% of respondents reported that their hospitals screened for frailty, and amongst those at least six different types of frailty assessment tool were in use.(\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e) The range of frailty assessment tools available vary in subjectivity, objectivity, ease of use, and on the model of frailty they assess. The Comprehensive Geriatric Assessment is the gold standard for the assessment of frailty but is impractical for routine use in the pre-operative setting. It requires over an hour to complete and includes assessments from multiple multi-disciplinary team members. The ideal tool for screening in the pre-operative setting would be time and staff-efficient, easy to perform, objective, and with high sensitivity and specificity. The Edmonton Frail Scale (EFS) has evidence for use in the perioperative setting(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e) and is a tool supported by the British Geriatric Society (BGS)(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). It is quick to perform taking approximately five minutes to complete and, importantly, is able to assess multiple domains of frailty which may be subject to optimisation in the pre-operative period(\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Performing the physical assessment element of the EFS can be limiting in the pre-assessment setting. The Reported Edmonton Frail Scale (REFS) substitutes the observed \u0026ldquo;get up and go\u0026rdquo; assessment with a verbal report of physical function, and has been utilised in several studies.(\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eDespite its perceived importance, frailty is still not routinely screened for in all UK surgical patients. Its relevance in those attending for elective surgery therefore remains unclear. Our study aims to establish the prevalence of frailty in our local population during elective surgery. Additionally, we assessed whether frailty was associated with known peri-operative risk factors as well as length-of-stay and discharge status, thus evaluating its importance for patients during their perioperative journey. It is possible that better knowledge of prevalence would empower systematic changes in care pathways and subsequently improve outcomes for this high-risk group of patients.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eA prospective multi-centre observational cohort study was carried out in eight hospitals within the Wessex School of Anaesthesia between 1st September and 30th October 2020. Sites comprised a mixture of small and large district general hospitals and one teaching hospital. The study was undertaken in collaboration with the trainee-led South Coast Perioperative Audit and Research Collaborative (SPARC). Ethical approval was given by the South Central Hampshire B Research Ethics committee (20/SC/0121).\u003c/p\u003e \u003cp\u003ePatients were eligible for inclusion if they were aged 65 years or older and having elective surgery under general, regional or local anaesthesia. Patients were excluded if they declined to participate, were unable to give informed consent, were having emergency surgery or had difficulties with the English language. Written informed consent was obtained for all participants on the morning of surgery.\u003c/p\u003e \u003cp\u003eEach of the study sites collected data over three consecutive weekdays during the study period. The timing of the three days during the study period was at the discretion of local site leads. Participants were identified from departmental operating lists either on the day before or day of surgery. Basic demographics, co-morbidities and bloods were collected pre-operatively by anaesthetic trainees independent of the anaesthetic team delivering perioperative care. A second study team member blinded to the participant\u0026rsquo;s pre-operative dataset completed the REFS prior to surgery. Based on the REFS score (out of a maximum eighteen) participants were classified as Not Frail (0-5); Vulnerable (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e); Mildly Frail (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e); Moderately Frail (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e); Severely Frail (\u003cspan additionalcitationids=\"CR13 CR14 CR15 CR16 CR17\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). Intra-operative and recovery data were collected once patients had returned to the ward or surgical day unit. Participants were followed-up at 30 days to assess length of stay, discharge status and location.\u003c/p\u003e \u003cp\u003eAnalyses were conducted on all patients for whom a frailty score was available and proceeded to surgery. Patients were registered on day of surgery and followed up at 30 days for outcomes. Data were summarised using means and standard deviations or percentages of categorical variables. The Kolmogorov-Smirnov test was used to assess for normality. Variations between people with and without frailty were estimated using two-sampled t tests or rank sum tests (non-parametric data) for differences between means or medians respectively, and chi-squared tests for correlation between categorical variables. A number of different outcomes were used to assess the impact of frailty on patients undergoing surgery, including length of stay, post-operative destination, mortality and discharge destination. Data were analysed using SPSS Statistics 26.0 (IBM Corp. Released 2019. IBM SPSS Statistics for Windows, Version 26.0. Armonk, NY: IBM Corp).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eData were collected on 228 patients during the study period. Ten patients did not proceed to surgery, therefore 218 patients were followed up at 30 days. Basic demographic data for these patients are summarised in Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eParticipant demographics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eAll participant demographics (n=218)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge (years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75 (IQR 70-80)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e103 (47.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e115 (52.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBMI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27 (IQR 24-30)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSmoking status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNever smoked\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e108 (49.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEx-smoker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e87 (40.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrent smoker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 (5.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (4.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eUsual residence\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOwn home\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e211 (96.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSheltered accommodation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (0.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAssisted living\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (0.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFamily/friend\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (1.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCarers\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e204 (93.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeekly\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (3.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDaily\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (1.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMore than daily\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (1.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWalking aids\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e61 (28.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHearing aids\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37 (17.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVisual aids\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e177 (81.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCardiac history\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo failure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e107 (49.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiuretic, digoxin, antianginal or antihypertensive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e91 (41.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOedema, warfarin or borderline cardiomegaly\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16 (7.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRaised JVP or cardiomegaly\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (0.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDiabetes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e175 (80.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eType 2 (diet controlled)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24 (11.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eType 2 (tablet controlled)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (3.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eType 2 (on insulin)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11 (5.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eECG findings\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo abnormalities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e117 (53.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAF rate 60-90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (4.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAF rate \u0026gt; 90, paced or other dysrhythmia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35 (16.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e The median REFS score for all participants was 4 (Interquartile Range (IQR) 2-6). The distribution of REFS scores is displayed in Figure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Thirty-seven (17.0%) participants had a REFS score of eight or more and were classified as frail. The remaining 181 (83.0%) had a REFS score of seven or less and were classified as not frail or vulnerable. The breakdown of the number of participants in each frailty category by REFS score is summarised in Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. A large number of cases were day-case procedures, reflected in a median length-of-stay of zero days (IQR 0-3). The vast majority (95.0%) were discharged to their own homes.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eReported Edmonton Frail Scale scores\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eAll participants (n=218)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eReported Edmonton Frail Scale outcome\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot frail (REFS less than 8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e181 (83.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFrail (REFS 8 or more)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37 (17.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFrailty category\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot frail (REFS 0-5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e158 (72.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVulnerable (REFS 6-7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23 (10.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMildly frail (REFS 8-9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28 (12.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerately frail (10-11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (3.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSeverely frail (12-18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (0.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLength of stay (days)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (IQR 0-3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDischarged to own home\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e207 (95.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (3.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot known\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (1.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eParticipants were recruited from a large number of surgical subspecialties, with orthopaedic, urological and ophthalmic procedures being the most commonly performed. The commonest American Society of Anaesthesiologists (ASA) score was 2, though a large number of participants did not have a pre-operative ASA score documented. The majority of participants had a general anaesthetic technique, most frequently using volatile anaesthetic agents. Important perioperative data are detailed in Table \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePerioperative data\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eAll participants (n=218)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSurgical specialty\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOrthopaedics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e43 (19.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e37 (17.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEyes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e22 (10.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbdominal \u0026ndash; Lower GI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20 (9.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGynaecology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15 (6.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBurns \u0026amp; Plastics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14 (6.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHead \u0026amp; Neck\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12 (5.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbdominal \u0026ndash; Upper GI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9 (4.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCardiac\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8 (3.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThoracic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7 (3.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVascular\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7 (3.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeurosurgery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6 (2.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbdominal \u0026ndash; Hepatobiliary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2 (0.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16 (7.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eASA\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4 (1.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e75 (34.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e53 (24.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6 (2.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot documented\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e80 (36.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eType of anaesthetic\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGeneral - inhalational\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e84 (38.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGeneral - target controlled infusion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e51 (23.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLocal infiltration only\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e41 (18.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpinal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e23 (10.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRegional block\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11 (5.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSedation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6 (2.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2 (0.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003esummarises the differences between frail (n=37) and non-frail (n=181) participants. In general, patients who were frail were more likely to be older (median age 78 years [IQR 74 - 86]) than patients who were vulnerable or not frail (median age 74 years [IQR 70-79], p\u0026lt;0.001). There were no significant differences between frailty groups for other demographic variables such as gender (p=0.102), smoking status (p=0.095) and Body Mass Index (BMI) (p=0.297). Frail patients were more likely to have carers (p\u0026lt;0.001) and use walking aids (p\u0026lt;0.001). Overall, frail patients were more likely to have co-morbidities associated with poor surgical outcome than those who were not frail or vulnerable. Frail patients were more likely to be anaemic (62.1% vs. 32.6%, p = 0.003) and have multiple comorbidities as evidenced by higher ASA score (p\u0026lt;0.001). Though not statistically significant there was a trend towards an increased prevalence of diabetes in frail patients (29.7% vs. 17.2%, p=0.079) and similarly, frail patients were more likely to present with a history of cardiac disease (74.3% vs. 45.9%, p=0.002) and abnormal Electrocardiogram (ECG) findings (38.5% vs. 18.5%], p=0.024).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison between frail and non-frail patients\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNot frail (n=181)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFrail (n=37)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge (years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e74 (IQR 70-79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e78 (IQR 74-86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e81 (44.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22 (59.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.102\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100 (55.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (40.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBMI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27.0 (IQR 24.0-30.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26.0 (IQR 24.1-29.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.297\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSmoking status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNever/Ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e167 (95.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28 (87.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.095\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (4.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (12.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAny carers\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo carers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e176 (97.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28 (75.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCarers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (2.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (24.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWalking aids\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39 (21.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22 (59.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHearing aids\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28 (15.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (24.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.196\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVisual aids\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e145 (80.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32 (86.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.397\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCardiac disease\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e83 (45.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26 (74.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDiabetes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-diabetic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e149 (82.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26 (70.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.079\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31 (17.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (29.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eECG abnormalities\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal or rate controlled AF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e110 (81.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16 (61.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.024\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAF rate \u0026gt; 90, paced or other dysrhythmia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25 (18.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (38.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eASA score\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot documented\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e68 (37.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (32.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (2.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70 (38.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (13.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35 (19.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18 (48.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (2.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (5.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHaemoglobin (g/L)\u003c/b\u003e\u003csup\u003e\u003cb\u003ea\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e135.1 (+/-14.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e126.4 (+/-14.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.005\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAnaemia (Haemoglobin \u0026lt; 130g/L)\u003c/b\u003e\u003csup\u003e\u003cb\u003ea\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43/132 (32.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18/29 (62.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.003\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLength of stay (days)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (IQR 0-2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (IQR 0-4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.681\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDischarged to own home\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (0.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (17.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e178 (99.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29 (82.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" colspan=\"4\"\u003e \u003cp\u003e\u003csup\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sup\u003e \u003cem\u003eData available for 161 participants\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe mortality rate was less than 1% for the entirely study population. However, the one patient who passed away was frail according to REFS. Similarly, four patients were still in hospital at the end of the study period, two frail and two not frail. Length of stay did not differ between frail and non-frail participants (p-value = 0.681). Discharge destination was significantly different (p-value \u0026lt; 0.001), with frail patients more likely to be discharged with family and friends, into sheltered accommodation or to other destinations not their own home. However, the total number of cases in each of these groups was very small, as 29 [82.9%] frail patients were discharged to their own home compared to 178 [99.4%] not frail patients.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this prospective observational study of patients aged 65 or older undergoing elective surgery we established the prevalence of frailty to be 17.0% using the Reported Edmonton Frail scale. Frail patients were more likely to present with modifiable pre-operative co-morbidities, require carers, and were less likely to be discharged to their own homes following surgery. All of these are relevant factors in the planning of personalised perioperative care.\u003c/p\u003e \u003cp\u003eTo our knowledge, this is the first study to assess the prevalence of frailty in patients undergoing solely elective surgery in the UK. The prevalence of frailty in the surgical population varies widely in the literature and is influenced by both the tool being used and the population being assessed. The largest study to date of frailty in patients undergoing elective and emergency surgery (over 430,000 American veterans) found 8.5% patients to be frail(\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e) whereas a recent meta-analysis of over 2000 general surgical patients (elective and emergency) estimated the prevalence to be higher, at between 10 and 37%.(\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e) Few studies have been undertaken in the UK and all are a mix of elective and emergency patients, for example a study of emergency and elective vascular patients in a UK setting found 52% of patients aged over 60 were frail, using the Edmonton Frail Scale.(\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eOne of the key findings of our study was that many frail patients had reached the day of planned surgery with medical problems which, had they been identified earlier, could have been corrected or optimised in advance. For example, nearly two thirds of frail patients were found to be anaemic compared to only a third of non-frail patients. Identifying and treating these frail patients, who appear to have a significantly higher risk of anaemia, could reduce associated post-operative complications(\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). There was also a trend towards frail patients having a higher rate of diabetes, another important perioperative risk factor. The use of a frailty screening tool such as the REFS could highlight these patients earlier in the perioperative pathway, allowing time for pre-operative optimisation and a reduction in post-operative complications(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). The Royal College of Anaesthetists emphasises that frailty requires a cross-specialty approach to enable optimisation of medicines and improved management of non-surgical comorbidities. A challenge is that to achieve this requires both time and resources, especially when considering the impact of COVID-19 on elective surgery(\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). Whilst the REFS was easily implemented on the morning of surgery, clearly screening would be best performed earlier in the perioperative pathway to allow time for intervention, for example at time of referral from primary care. A practical alternative could be to integrate the REFS (or other frailty assessment tool) into the routine pre-operative assessment questionnaires already performed by hospital pre-admission teams.\u003c/p\u003e \u003cp\u003eKnowledge of the presence and severity of frailty can help with assessing surgical risk (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e) and, thus, help inform shared decision-making discussions and ensure validity of consent(\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). Having been informed of their higher-risk status, some patients may choose to proceed with planned surgery, whilst others may elect for an alternative procedure or choose not to have surgery at all(\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). Advanced knowledge of frailty can help ensure appropriate personnel and equipment are available in theatres on the day of surgery. For example, frail patients may be given a longer time-slot for induction of anaesthesia, or be cared for by a more senior anaesthetist. There may be adjustments that need to be made to the anaesthetic technique; such as additional monitoring or selection of regional blockade in place of general anaesthesia. Discussion of these interventions in advance of surgery will also allow patient expectations to be managed.\u003c/p\u003e \u003cp\u003eFrom the point-of-view of post-operative care and discharge planning, an awareness of frailty pre-operatively can also ensure adequate planning and resource allocation. For example frail patients could be identified in advance of surgery so that physiotherapists, dietitians and a clinician with an interest in perioperative medicine for the elderly could be involved in planning their post-operative care. Not only could this improve quality of care but may also optimise hospital efficiency through reduced length-of-stay and cancellations. Although our study did not demonstrate significant differences in length-of-stay we did show that 99% of non-frail patients were discharged to their own home, compared to only 83% of frail patients. This again may suggest a benefit for discharge planning in identifying these patients early on in their surgical journey.\u003c/p\u003e \u003cp\u003e One of the main strengths of this study was that it recruited participants from a wide geographical area incorporating a mixture of small and large hospitals serving a mixture of inner city, semi-rural and rural communities. In practice we found the REFS questionnaire to be quick to perform; taking only five minutes or less to complete. It was also found to be acceptable to patients. The junior doctors administering the questionnaire, predominantly anaesthetic trainees, did not require any additional training which suggests that the REFS would be quick and cost-effective to introduce into routine clinical practice. The delivery of a multi-centre study by doctors in training is another strength.\u003c/p\u003e \u003cp\u003eHowever, this study has limitations. The participants were recruited from a heterogeneous group of surgical specialties and it is likely that different specialties will have differing rates of frailty. Furthermore, the COVID-19 pandemic impacted on elective surgery to an extent still difficult to ascertain. While this study was conducted during a period of relatively increased operating activity, it is likely that patients listed for surgery were selected because they were from a less vulnerable patient group or not shielding. The pandemic also led to a shortage of high dependency and intensive care beds, meaning fewer high-risk elective procedures were performed(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). A further factor affecting the study\u0026rsquo;s generalisability was that patient\u0026rsquo;s without capacity were excluded. Some of the most severely frail patients presenting for surgery, for example with advanced dementia, will therefore not have been approached.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn conclusion, we found the prevalence of frailty in a mixed population of elective surgical patients aged 65 or over to be 17.0%. Furthermore, we found the REFS to be a practical tool for pre-operative frailty screening. Frail patients presented more frequently with modifiable co-morbidities, such as anaemia, which could have been optimised pre-operatively. Adequately powered future studies should further assess the impact of frailty, and we look forward to the results of the upcoming third Sprint National Audit Project(\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). Early screening for frailty could highlight frail patients and allow time for evidence-based pre-operative planning and interventions to be made and we therefore encourage frailty assessment to be a routine part of pre-operative assessment with the early involvement of relevant healthcare professionals. With waiting times for elective surgery at an unprecedented high, we have both an opportunity and responsibility to use this time well.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eASA- American Society of Anaesthesiologists\u003c/p\u003e\n\u003cp\u003eBMI \u0026ndash; Body Mass Index\u003c/p\u003e\n\u003cp\u003eCOVID-19\u0026nbsp;\u0026ndash; Severe Acute Respiratory Syndrome Coronavirus 2\u003c/p\u003e\n\u003cp\u003eECG - Electrocardiogram\u003c/p\u003e\n\u003cp\u003eEFS\u0026nbsp;\u0026ndash; Edmonton Frail Scale\u003c/p\u003e\n\u003cp\u003eHRA\u0026nbsp;\u0026ndash; Health Research Authority\u003c/p\u003e\n\u003cp\u003eIQR\u0026nbsp;\u0026ndash;\u0026nbsp;Interquartile Range\u003c/p\u003e\n\u003cp\u003eREFS\u0026nbsp;\u0026ndash; Reported Edmonton Frail Scale\u003c/p\u003e\n\u003cp\u003eSD-Standard deviation\u003c/p\u003e\n\u003cp\u003eSPARC \u0026ndash;\u0026nbsp;South Coast Perioperative Audit and Research\u0026nbsp;Collaborative\u003c/p\u003e\n\u003cp\u003eUK \u0026ndash; United Kingdom\u003c/p\u003e\n\u003cp\u003eNHS \u0026ndash; National Health Service\u003c/p\u003e\n\u003cp\u003eBGS \u0026ndash; British Geriatric Society\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval was given by the South Central Hampshire B Research Ethics committee (20/SC/0121).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and Materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe work was completed whilst Dr Lewis Matthews, Dr David Harvie and Dr Frances Wensley\u0026nbsp;were funded National Institute for Healthcare Research (NIHR) Academic Clinical Fellowship. This article presents independent research\u0026nbsp;to that\u0026nbsp;funded by the NIHR. The views expressed are those of the author and not necessarily\u0026nbsp;those of the NHS, the NIHR or the Department of Health and Social Care.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSH\u0026nbsp;lead\u0026nbsp;organisation of collection of data across sites, data collection\u0026nbsp;and writing the manuscript. LM was\u0026nbsp;a major contributor to\u0026nbsp;study design, analysis of data and writing the manuscript. FW was a local PI for data collection, analysed data and a contributor to writing the manuscript. DH was\u0026nbsp;involved with study design and\u0026nbsp;a major contributor to\u0026nbsp;writing the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePlease see supplemental document on List of contributors for data collection.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBeggs T, Sepehri A, Szwajcer A, Tangri N, Arora RC. Frailty and perioperative outcomes: a narrative review. Canadian journal of anaesthesia = Journal canadien d'anesthesie. 2015;62(2):143\u0026ndash;57.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOakland K, Nadler R, Cresswell L, Jackson D, Coughlin PA. Systematic review and meta-analysis of the association between frailty and outcome in surgical patients. Ann R Coll Surg Engl. 2016;98(2):80\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBritish Geriatric S. Fit for Frailty:Consensus Best Practice Guidance for the care of older people living with frailty in community and outpatient settings - published by the British Geriatrics Society and the Royal College of Nursing in association with the Royal College of General Practitioners and Age UK. British Geriatric Society; 2017.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMakary MA, Segev DL, Pronovost PJ, Syin D, Bandeen-Roche K, Patel P, et al. Frailty as a predictor of surgical outcomes in older patients. J Am Coll Surg. 2010;210(6):901\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRobinson TN, Wallace JI, Wu DS, Wiktor A, Pointer LF, Pfister SM, et al. Accumulated Frailty Characteristics Predict Postoperative Discharge Institutionalization in the Geriatric Patient. J Am Coll Surg. 2011;213(1):37\u0026ndash;42.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRobinson TN, Eiseman B, Church SD, Wallace JI, Moss M, McFann KK, et al. Redefining geriatric preoperative assessment using frailty, disability and co-morbidity. Annals of surgery. 2009;250(3):449\u0026ndash;53.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNational Population Projections: 2018-based [Internet]. 2019. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ons.gov.uk/peoplepopulationandcommunity/populationandmigration/populationprojections/bulletins/nationalpopulationprojections/2018based\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eActivity HAPC. Hospital Episode Statistics, Admitted Patient Care - England, 2006-07. 2007.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBougeard AM, Brent A, Swart M, Snowden C. A survey of UK peri-operative medicine: pre-operative care. Anaesthesia. 2017;72(8):1010\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHe Y, Li LW, Hao Y, Sim EY, Ng KL, Lee R, et al. Assessment of predictive validity and feasibility of Edmonton Frail Scale in identifying postoperative complications among elderly patients: a prospective observational study. Sci Rep. 2020;10(1):14682.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRolfson DB, Majumdar SR, Tsuyuki RT, Tahir A, Rockwood K. Validity and reliability of the Edmonton Frail Scale. Age Ageing. 2006;35(5):526\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHilmer SN, Perera V, Mitchell S, Murnion BP, Dent J, Bajorek B, et al. The assessment of frailty in older people in acute care. Australasian Journal on Ageing. 2009;28(4):182\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBissot M, Aunac S, Henin PY, Colinet B, Barvais L, Simonet O, et al. Preoperative frailty assessment: A review. Acta Anaesthesiol Belg. 2016;67(4):157\u0026ndash;73.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShinall MC Jr, Arya S, Youk A, Varley P, Shah R, Massarweh NN, et al. Association of Preoperative Patient Frailty and Operative Stress With Postoperative Mortality. JAMA Surgery. 2020;155(1):e194620-e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHewitt J, Long S, Carter B, Bach S, McCarthy K, Clegg A. The prevalence of frailty and its association with clinical outcomes in general surgery: a systematic review and meta-analysis. Age Ageing. 2018;47(6):793\u0026ndash;800.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePartridge JSL, Fuller M, Harari D, Taylor PR, Martin FC, Dhesi JK. Frailty and poor functional status are common in arterial vascular surgical patients and affect postoperative outcomes. International journal of surgery (London England). 2015;18:57\u0026ndash;63.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBock M, Johansson T, Fritsch G, Flamm M, Hansbauer B, Mann E, et al. The impact of preoperative testing for blood glucose concentration and haemoglobin A1c on mortality, changes in management and complications in noncardiac elective surgery: A systematic review. European Journal of Anaesthesiology | EJA. 2015;32(3).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTao LS, MacKenzie CR, Charlson ME. Predictors of postoperative complications in the patient with diabetes mellitus. Journal of Diabetes its Complications. 2008;22(1):24\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e(CPOC) CoPC. Preoperative Assessment and Optimisation for Adult Surgery including consideration of COVID-19 and its implications2021. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.cpoc.org.uk/sites/cpoc/files/documents/2021-06Preoperative%20assessment%20and%20optimisation%20guidance.pdf\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBirkelbach O, M\u0026ouml;rgeli R, Spies C, Olbert M, Weiss B, Brauner M, et al. Routine frailty assessment predicts postoperative complications in elderly patients across surgical disciplines - a retrospective observational study. BMC anesthesiology. 2019;19(1):204-.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSkaar E, \u0026Oslash;ksnes A, Eide LSP, Norekv\u0026aring;l TM, Ranhoff AH, Nordrehaug JE, et al. Baseline frailty status and outcomes important for shared decision-making in older adults receiving transcatheter aortic valve implantation, a prospective observational study. Aging Clin Exp Res. 2021;33(2):345\u0026ndash;52.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDhesi JK, Lees NP, Partridge JS. Frailty in the perioperative setting. Clin Med. 2019;19(6):485\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAnaesthesia NIoA. Sprint Natioanl Anaesthesia Project (SNAP 3) Frailty and Delerium2022. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.niaa-hsrc.org.uk/Background-and-study-rationale#pt\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"perioperative-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"peri","sideBox":"Learn more about [Perioperative Medicine](http://perioperativemedicinejournal.biomedcentral.com)","snPcode":"13741","submissionUrl":"https://submission.nature.com/new-submission/13741/3","title":"Perioperative Medicine","twitterHandle":"@EMSurgeryBMC","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Frailty, Pre-operative risk assessment, Reported Edmonton Frail Scale, Pre-operative optimisation","lastPublishedDoi":"10.21203/rs.3.rs-982059/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-982059/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eFrailty increases the risk of perioperative complications, length of stay, and the need for assisted-living after discharge. As the UK population ages the number of frail patients presenting for elective surgery in the UK is likely to grow. Despite the potential benefits of early diagnosis, frailty is not uniformly screened for in UK elective surgical patients and its prevalence remains unclear. The primary aim of this study was to assess the prevalence of frailty in patients aged over 65 years undergoing elective surgery.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe performed a prospective cross-sectional observational study in eight UK hospitals. Data were collected over three consecutive days with follow-up at 30 days. HRA approval was obtained (REC 20/SC/0121) and signed informed consent obtained. Participants were eligible for inclusion if they were 65 years or older and undergoing elective surgery. Pre-operative data were collected from hospital notes by anaesthetic trainees. A member of the research team blinded to the pre-operative dataset screened the participant for frailty pre-operatively using the Reported Edmonton Frail Scale (REFS). Post-operative data were collected from the notes on day of surgery and at 30 days. Participants were defined as \u0026ldquo;frail\u0026rdquo; if they scored 8 or more on the REFS.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003e228 participants were recruited during the study period of whom 218 proceeded to surgery. There were 103 females and 115 males. Median age was 75 years (interquartile range 70-80). Thirty-seven participants (17.0%) were identified as frail. Frail patients were older, had a higher ASA score, were more likely to have carers and were more likely to be anaemic and present with ECG abnormalities. There were no differences in gender, BMI, place of residence or smoking status for patients identified as frail versus non-frail. There was no difference in length-of-stay between frail and non-frail patients, although those identified as frail were less likely to be discharged to their own home.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eWe found the prevalence of frailty in a mixed population of elective surgical patients aged 65 or over to be 17.0%. Furthermore, we found the REFS to be a practical tool for pre-operative frailty screening. Frail patients presented for elective surgery with modifiable co-morbidities which could have been optimised pre-operatively. Early screening could highlight frail patients, allowing time for pre-operative planning and evidence-based optimisations of comorbidities. We therefore encourage the adoption of frailty assessment as a routine part of pre-operative assessment.\u003c/p\u003e","manuscriptTitle":"Frailty in the over 65’s undergoing elective surgery (FIT-65) – a three-day study examining the prevalence of frailty in patients presenting for elective surgery","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-10-29 16:31:12","doi":"10.21203/rs.3.rs-982059/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"","date":"2021-10-28T00:00:00+00:00","index":2,"fulltext":""},{"type":"reviewerAgreed","content":"","date":"2021-10-25T00:00:00+00:00","index":1,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2021-10-25T00:00:00+00:00","index":1,"fulltext":"Recommendation: Reviewer's comments unavailable due to the journal's policy.\n"},{"type":"reviewersInvited","content":"","date":"2021-10-24T00:00:00+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2021-10-18T00:00:00+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2021-10-17T23:00:00+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2021-10-17T23:00:00+00:00","index":"","fulltext":""},{"type":"submitted","content":"","date":"2021-10-16T00:00:00+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"perioperative-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"peri","sideBox":"Learn more about [Perioperative Medicine](http://perioperativemedicinejournal.biomedcentral.com)","snPcode":"13741","submissionUrl":"https://submission.nature.com/new-submission/13741/3","title":"Perioperative Medicine","twitterHandle":"@EMSurgeryBMC","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f16e61d2-b269-4ee8-a452-b7e05f917140","owner":[],"postedDate":"October 29th, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":8181121,"name":"Surgery"}],"tags":[],"updatedAt":"2021-10-29T16:31:12+00:00","versionOfRecord":[],"versionCreatedAt":"2021-10-29 16:31:12","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-982059","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-982059","identity":"rs-982059","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}