Combining the Hospital Frailty Risk Score With the Charlson and Elixhauser Multimorbidity Indices to Identify Older Patients at Risk of Poor Outcomes in Acute Care.

OBJECTIVE: The Hospital Frailty Risk Score (HFRS) can be applied to medico-administrative datasets to determine the risks of 30-day mortality and long length of stay (LOS) in hospitalized older patients. The objective of this study was to compare the HFRS with Charlson and Elixhauser comorbidity indices, used separately or combined. DESIGN: A retrospective analysis of the French medical information database. The HFRS, Charlson index, and Elixhauser index were calculated for each patient based on the index stay and hospitalizations over the preceding 2 years. Different constructions of the HFRS were considered based on overlapping diagnostic codes with either Charlson or Elixhauser indices. We used mixed logistic regression models to investigate the association between outcomes, different constructions of HFRS, and associations with comorbidity indices. SETTING: 743 hospitals in France. PARTICIPANTS: All patients aged 75 years or older hospitalized as an emergency in 2017 (n=1,042,234).Main outcome measures: 30-day inpatient mortality and LOS >10 days. RESULTS: The HFRS, Charlson, and Elixhauser indices were comparably associated with an increased risk of 30-day inpatient mortality and long LOS. The combined model with the highest c-statistic was obtained when associating the HFRS with standard adjustment and Charlson for 30-day inpatient mortality (adjusted c-statistics: HFRS=0.654; HFRS + Charlson = 0.676) and with Elixhauser for long LOS (adjusted c-statistics: HFRS= 0.672; HFRS + Elixhauser =0.698). CONCLUSIONS: Combining comorbidity indices and HFRS may improve discrimination for predicting long LOS in hospitalized older people, but adds little to Charlson's 30-day inpatient mortality risk.

Development and external validation of the eFalls tool: a multivariable prediction model for the risk of ED attendance or hospitalisation with a fall or fracture in older adults.

BACKGROUND: Falls are common in older adults and can devastate personal independence through injury such as fracture and fear of future falls. Methods to identify people for falls prevention interventions are currently limited, with high risks of bias in published prediction models. We have developed and externally validated the eFalls prediction model using routinely collected primary care electronic health records (EHR) to predict risk of emergency department attendance/hospitalisation with fall or fracture within 1 year. METHODS: Data comprised two independent, retrospective cohorts of adults aged ≥65 years: the population of Wales, from the Secure Anonymised Information Linkage Databank (model development); the population of Bradford and Airedale, England, from Connected Bradford (external validation). Predictors included electronic frailty index components, supplemented with variables informed by literature reviews and clinical expertise. Fall/fracture risk was modelled using multivariable logistic regression with a Least Absolute Shrinkage and Selection Operator penalty. Predictive performance was assessed through calibration, discrimination and clinical utility. Apparent, internal-external cross-validation and external validation performance were assessed across general practices and in clinically relevant subgroups. RESULTS: The model's discrimination performance (c-statistic) was 0.72 (95% confidence interval, CI: 0.68 to 0.76) on internal-external cross-validation and 0.82 (95% CI: 0.80 to 0.83) on external validation. Calibration was variable across practices, with some over-prediction in the validation population (calibration-in-the-large, -0.87; 95% CI: -0.96 to -0.78). Clinical utility on external validation was improved after recalibration. CONCLUSION: The eFalls prediction model shows good performance and could support proactive stratification for falls prevention services if appropriately embedded into primary care EHR systems.

Core requirements of frailty screening in the emergency department: an international Delphi consensus study.

INTRODUCTION: Frailty is associated with adverse outcomes among patients attending emergency departments (EDs). While multiple frailty screens are available, little is known about which variables are important to incorporate and how best to facilitate accurate, yet prompt ED screening. To understand the core requirements of frailty screening in ED, we conducted an international, modified, electronic two-round Delphi consensus study. METHODS: A two-round electronic Delphi involving 37 participants from 10 countries was undertaken. Statements were generated from a prior systematic review examining frailty screening instruments in ED (logistic, psychometric and clinimetric properties). Reflexive thematic analysis generated a list of 56 statements for Round 1 (August-September 2021). Four main themes identified were: (i) principles of frailty screening, (ii) practicalities and logistics, (iii) frailty domains and (iv) frailty risk factors. RESULTS: In Round 1, 13/56 statements (23%) were accepted. Following feedback, 22 new statements were created and 35 were re-circulated in Round 2 (October 2021). Of these, 19 (54%) were finally accepted. It was agreed that ideal frailty screens should be short (<5 min), multidimensional and well-calibrated across the spectrum of frailty, reflecting baseline status 2-4 weeks before presentation. Screening should ideally be routine, prompt (<4 h after arrival) and completed at first contact in ED. Functional ability, mobility, cognition, medication use and social factors were identified as the most important variables to include. CONCLUSIONS: Although a clear consensus was reached on important requirements of frailty screening in ED, and variables to include in an ideal screen, more research is required to operationalise screening in clinical practice.

Current Pyuria Cutoffs Promote Inappropriate Urinary Tract Infection Diagnosis in Older Women.

BACKGROUND: Pre-existing lower urinary tract symptoms (LUTS), cognitive impairment, and the high prevalence of asymptomatic bacteriuria (ASB) complicate the diagnosis of urinary tract infection (UTI) in older women. The presence of pyuria remains the cornerstone of UTI diagnosis. However, >90% of ASB patients have pyuria, prompting unnecessary treatment. We quantified pyuria by automated microscopy and flowcytometry to determine the diagnostic accuracy for UTI and to derive pyuria thresholds for UTI in older women. METHODS: Women ≥65 years with ≥2 new-onset LUTS and 1 uropathogen ≥104 colony-forming units (CFU)/mL were included in the UTI group. Controls were asymptomatic and classified as ASB (1 uropathogen ≥105 CFU/mL), negative culture, or mixed flora. Patients with an indwelling catheter or antimicrobial pretreatment were excluded. Leukocyte medians were compared and sensitivity-specificity pairs were derived from a receiver operating characteristic curve. RESULTS: We included 164 participants. UTI patients had higher median urinary leukocytes compared with control patients (microscopy: 900 vs 26 leukocytes/µL; flowcytometry: 1575 vs 23 leukocytes/µL; P < .001). Area under the curve was 0.93 for both methods. At a cutoff of 264 leukocytes/µL, sensitivity and specificity of microscopy were 88% (positive and negative likelihood ratio: 7.2 and 0.1, respectively). The commonly used cutoff of 10 leukocytes/µL had a poor specificity (36%) and a sensitivity of 100%. CONCLUSIONS: The degree of pyuria can help to distinguish UTI in older women from ASB and asymptomatic controls with pyuria. Current pyuria cutoffs are too low and promote inappropriate UTI diagnosis in older women. Clinical Trials Registration. International Clinical Trials Registry Platform: NL9477 (https://trialsearch.who.int/Trial2.aspx?TrialID=NL9477).

Examining the effect of interventions in emergency care for older people using a system dynamics decision support tool.

BACKGROUND: Rising demand for Emergency and Urgent Care is a major international issue and outcomes for older people remain sub-optimal. Embarking upon large-scale service development is costly in terms of time, energy and resources with no guarantee of improved outcomes; computer simulation modelling offers an alternative, low risk and lower cost approach to explore possible interventions. METHOD: A system dynamics computer simulation model was developed as a decision support tool for service planners. The model represents patient flow through the emergency care process from the point of calling for help through ED attendance, possible admission, and discharge or death. The model was validated against five different evidence-based interventions (geriatric emergency medicine, front door frailty, hospital at home, proactive care and acute frailty units) on patient outcomes such as hospital-related mortality, readmission and length of stay. RESULTS: The model output estimations are consistent with empirical evidence. Each intervention has different levels of effect on patient outcomes. Most of the interventions show potential reductions in hospital admissions, readmissions and hospital-related deaths. CONCLUSIONS: System dynamics modelling can be used to support decisions on which emergency care interventions to implement to improve outcomes for older people.

New horizons in the role of digital data in the healthcare of older people.

There are national and global moves to improve effective digital data design and application in healthcare. This New Horizons commentary describes the role of digital data in healthcare of the ageing population. We outline how health and social care professionals can engage in the proactive design of digital systems that appropriately serve people as they age, carers and the workforce that supports them. KEY POINTS: Healthcare improvements have resulted in increased population longevity and hence multimorbidity. Shared care records to improve communication and information continuity across care settings hold potential for older people. Data structure and coding are key considerations. A workforce with expertise in caring for older people with relevant knowledge and skills in digital healthcare is important.

Organizational resilience in healthcare: a review and descriptive narrative synthesis of approaches to resilience measurement and assessment in empirical studies.

BACKGROUND: The coronavirus pandemic has had a profound impact on organization and delivery of care. The challenges faced by healthcare organizations in dealing with the pandemic have intensified interest in the concept of resilience. While effort has gone into conceptualising resilience, there has been relatively little work on how to evaluate organizational resilience. This paper reports on an extensive review of approaches to resilience measurement and assessment in empirical healthcare studies, and examines their usefulness for researchers, policymakers and healthcare managers. METHODS: Various databases (MEDLINE, EMBASE, PsycINFO, CINAHL (EBSCO host), Cochrane CENTRAL (Wiley), CDSR, Science Citation Index, and Social Science Citation Index) were searched from January 2000 to September 2021. We included quantitative, qualitative and modelling studies that focused on measuring or qualitatively assessing organizational resilience in a healthcare context. All studies were screened based on titles, abstracts and full text. For each approach, information on the format of measurement or assessment, method of data collection and analysis, and other relevant information were extracted. We classified the approaches to organizational resilience into five thematic areas of contrast: (1) type of shock; (2) stage of resilience; (3) included characteristics or indicators; (4) nature of output; and (5) purpose. The approaches were summarised narratively within these thematic areas. RESULTS: Thirty-five studies met the inclusion criteria. We identified a lack of consensus on how to evaluate organizational resilience in healthcare, what should be measured or assessed and when, and using what resilience characteristic and indicators. The measurement and assessment approaches varied in scope, format, content and purpose. Approaches varied in terms of whether they were prospective (resilience pre-shock) or retrospective (during or post-shock), and the extent to which they addressed a pre-defined and shock-specific set of characteristics and indicators. CONCLUSION: A range of approaches with differing characteristics and indicators has been developed to evaluate organizational resilience in healthcare, and may be of value to researchers, policymakers and healthcare managers. The choice of an approach to use in practice should be determined by the type of shock, the purpose of the evaluation, the intended use of results, and the availability of data and resources.

Factors associated with longer wait times, admission and reattendances in older patients attending emergency departments: an analysis of linked healthcare data.

BACKGROUND AND OBJECTIVE: Care for older patients in the ED is an increasingly important issue with the ageing society. To better assess the quality of care in this patient group, we assessed predictors for three outcomes related to ED care: being seen and discharged within 4 hours of ED arrival; being admitted from ED to hospital and reattending the ED within 30 days. We also used these outcomes to identify better-performing EDs. METHODS: The CUREd Research Database was used for a retrospective observational study of all 1 039 251 attendances by 368 754 patients aged 75+ years in 18 type 1 EDs in the Yorkshire and the Humber region of England between April 2012 and March 2017. We estimated multilevel logit models, accounting for patients' characteristics and contact with emergency services prior to ED arrival, time variables and the ED itself. RESULTS: Patients in the oldest category (95+ years vs 75-80 years) were more likely to have a long ED wait (OR=1.13 (95% CI=1.10 to 1.15)), hospital admission (OR=1.26 (95% CI=1.23 to 1.29)) and ED reattendance (OR=1.09 (95% CI=1.06 to 1.12)). Those who had previously attended (3+ vs 0 previous attendances) were more likely to have long wait (OR=1.07 (95% CI=1.06 to 1.08)), hospital admission (OR=1.10 (95% CI=1.09 to 1.12)) and ED attendance (OR=3.13 (95% CI=3.09 to 3.17)). Those who attended out of hours (vs not out of hours) were more likely to have a long ED wait (OR=1.33 (95% CI=1.32 to 1.34)), be admitted to hospital (OR=1.19 (95% CI=1.18 to 1.21)) and have ED reattendance (OR=1.07 (95% CI=1.05 to 1.08)). Those living in less deprived decile (vs most deprived decile) were less likely to have any of these three outcomes: OR=0.93 (95% CI=0.92 to 0.95), 0.92 (95% CI=0.90 to 0.94), 0.86 (95% CI=0.84 to 0.88). These characteristics were not strongly associated with long waits for those who arrived by ambulance. Emergency call handler designation was the strongest predictor of long ED waits and hospital admission: compared with those who did not arrive by ambulance; ORs for these outcomes were 1.18 (95% CI=1.16 to 1.20) and 1.85 (95% CI=1.81 to 1.89) for those designated less urgent; 1.37 (95% CI=1.33 to 1.40) and 2.13 (95% CI=2.07 to 2.18) for urgent attendees; 1.26 (95% CI=1.23 to 1.28) and 2.40 (95% CI=2.36 to 2.45) for emergency attendees; and 1.37 (95% CI=1.28 to 1.45) and 2.42 (95% CI=2.26 to 2.59) for those with life-threatening conditions. We identified two EDs whose patients were less likely to have a long ED, hospital admission or ED reattendance than other EDs in the region. CONCLUSIONS: Age, previous attendance and attending out of hours were all associated with an increased likelihood of exceeding 4 hours in the ED, hospital admission and reattendance among patients over 75 years. These differences were less pronounced among those arriving by ambulance. Emergency call handler designation could be used to identify those at the highest risk of long ED waits, hospital admission and ED reattendance.

Measuring health-related quality of life of older people with frailty receiving acute care: feasibility and psychometric performance of the EuroQol EQ-5D.

BACKGROUND: Although outcome goals for acute healthcare among older people living with frailty often include Health-Related Quality of Life (HRQoL) and other patient-reported outcome measures (PROMs), current quality metrics usually focus on waiting times and survival. Lay and patient review have identified the EuroQol EQ-5D as a candidate measure for this setting. This research appraised the EQ-5D for feasibility, psychometric performance, and respondents' outcomes in the acute frailty setting. METHODS: People aged 65 + with Clinical Frailty Scale (CFS) 5-8 were recruited from eight UK hospitals' emergency care and acute admissions settings. They completed the five-level EQ-5D and the EQ-VAS. Feasibility was assessed with completion times and completeness. For reliability, response distributions and internal consistency were analysed. Finally, EQ-Index values were compared with demographic characteristics and service outcomes for construct validity. RESULTS: The 232 participants were aged 65-102. 38% responded in emergency departments and 62% in admissions wards. Median completion time was 12 (IQR, 11) minutes. 98% responses were complete. EQ-5D had acceptable response distribution (SD 1.1-1.3) and internal consistency (Cronbach's alpha 0.69). EQ-VAS demonstrated a midpoint response pattern. Median EQ-Index was 0.574 (IQR, 0.410) and was related positively with increasing age (p = 0.010) and negatively with CFS (p < 0.001). Participants with higher CFS had more frequent problems with mobility, self-care, and usual activities. CONCLUSIONS: Administration of the EQ-5D was feasible in these emergency and acute frailty care settings. EQ-5D had acceptable properties, while EQ-VAS appeared problematic. Participants with more severe frailty had also poorer HRQoL.

The Hospital Frailty Risk Score and outcomes in head and neck cancer surgery.

OBJECTIVE: This study aimed to assess if the Hospital Frailty Risk Score (HFRS) could predict outcomes for older people undergoing head and neck procedures. DESIGN: A retrospective cohort study of patients admitted between April 2008 and February 2020, undergoing head and neck procedures defined as major resections using procedural codes. SETTING: The analysis was performed using data from the NHS Secondary Uses Service (SUS) electronic database. PARTICIPANTS: A number of 7479 patients were selected based on an age of 75 years and above and an admission associated with a diagnostic code associated with a head and neck cancer. Based on HFRS, 5153 patients were risk-stratified into mild, moderate, and severe frailty risk. MAIN OUTCOME MEASURES: The relationships between frailty risk and length of stay, readmission rate, and mortality were quantified using descriptive statistics. RESULTS: Severely frail patients had a median length of stay of 9 days compared to 3 for mildly frail patients. Twenty-seven percentage of severely frail patients were readmitted within 30 days of surgery. Rising levels of frailty correlate with a higher risk of death following surgery which is maintained in longer term mortality at 1 year and until the data were extracted in March 2022. Fifty percentage of moderately frail patients and 66% of severely frail patients had died in hospital by the end of the study period. CONCLUSION: The results quantify the relationship between frailty and adverse health outcomes. This information could be used to identify those that might benefit from holistic assessment, aid prognostication, commissioning, and service planning.

Urgent care for older people.

Geriatric medicine is the clinical specialty that focuses upon the care of older people-especially those with frailty (a state of increased vulnerability). In hospital, older people living with frailty are at high risk of developing a range of unpleasant outcomes such as delirium, falls, fractures, pressure sores and death. Comprehensive geriatric assessment is a form of holistic care that incorporates a specific set of clinical competencies that are able to reduce these adverse outcomes. Over the years, geriatric medicine has moved from being more of a community-based service towards a more acute specialty-encroaching now upon emergency department care. The challenge now is to work out how best to deliver geriatric care across the whole hospital (older people with frailty are not just cared for in geriatric wards!). The themed collection published on the Age & Ageing journal website outlines key articles that are attempting to develop solutions to this challenging conundrum. We hope that you enjoy reading them.

Geriatric emergency medicine-a model for frailty friendly healthcare.

As the world's population continues to age over the decades ahead, medical educators and researchers in every adult medical and surgical specialty will need to 'geriatricise' their clinical science. Many have already engaged with geriatrics. Here we describe the progress that has been made and the opportunities ahead in the field of Geriatric Emergency Medicine (GEM), a field that has taken large steps in integrating holistic care. Future opportunities exist in the three domains of evidence-based medicine: including patient preferences and needs, generating scientific evidence, and improving physician knowledge and expertise. Implementation requires new innovations also in the organisation of care. Similar strategies may be useful in other fields of medicine, in making holistic care the standard for older people.

External validation of the Hospital Frailty Risk Score in France.

BACKGROUND: The Hospital Frailty Risk Score (HFRS) has made it possible internationally to identify subgroups of patients with characteristics of frailty from routinely collected hospital data. OBJECTIVE: To externally validate the HFRS in France. DESIGN: A retrospective analysis of the French medical information database. SETTING: 743 hospitals in Metropolitan France. SUBJECTS: All patients aged 75 years or older hospitalised as an emergency in 2017 (n = 1,042,234). METHODS: The HFRS was calculated for each patient based on the index stay and hospitalisations over the preceding 2 years. Main outcome measures were 30-day in-patient mortality, length of stay (LOS) >10 days and 30-day readmissions. Mixed logistic regression models were used to investigate the association between outcomes and HFRS score. RESULTS: Patients with high HFRS risk were associated with increased risk of mortality and prolonged LOS (adjusted odds ratio [aOR] = 1.38 [1.35-1.42] and 3.27 [3.22-3.32], c-statistics = 0.676 and 0.684, respectively), while it appeared less predictive of readmissions (aOR = 1.00 [0.98-1.02], c-statistic = 0.600). Model calibration was excellent. Restricting the score to data prior to index admission reduced discrimination of HFRS substantially. CONCLUSIONS: HFRS can be used in France to determine risks of 30-day in-patient mortality and prolonged LOS, but not 30-day readmissions. Trial registration: Reference ID on clinicaltrials.gov: ID: NCT03905629.

What matters most in acute care: an interview study with older people living with frailty.

BACKGROUND: Healthcare outcome goals are central to person-centred acute care, however evidence among older people is scarce. Older people who are living with frailty have distinct requirements for healthcare delivery and have distinct risk for adverse outcomes from healthcare. There is insufficient evidence for whether those living with frailty also have distinct healthcare outcome goals. This study explored the nature of acute care outcome goals in people living with frailty. METHODS: Healthcare outcome goals were explored using semi-structured patient interviews. Participants aged over 65 with Clinical Frailty Score 5-8 (mild to very severe frailty) were recruited during their first 72 hours in a UK hospital. Purposive, maximum variation sampling was guided by lay partners from a Patient and Public Involvement Forum specialising in ageing-related research. Qualitative analysis used a blended approach based on framework and constant comparative methodologies for the identification of themes. Findings were validated through triangulation with participant, lay partner, and technical expert review. RESULTS: The 22 participants were aged 71 to 98 and had mild to very severe frailty. One quarter were living with dementia. Most participants had reflected on their situation and considered their outcome goals. Theme categories (and corresponding sub-categories) were 'Autonomy' (information, control, and security) and 'Functioning' (physical, psychosocial, and relief). A novel 'security' theme was identified, whereby participants sought to feel safe in their usual living place and with their health problems. Those living with milder frailty were concerned to maintain ability to support loved ones, while those living with most severe frailty were concerned about burdening others. CONCLUSIONS: Outcome goals for acute care among older participants living with frailty were influenced by the insecurity of their situation and fear of deterioration. Patients may be supported to feel safe and in control through appropriate information provision and functional support.

Living with frailty and haemodialysis: a qualitative study.

BACKGROUND: Frailty is highly prevalent in people receiving haemodialysis (HD) and is associated with poor outcomes. Understanding the lived experiences of this group is essential to inform holistic care delivery. METHODS: Semi-structured interviews with N = 25 prevalent adults receiving HD from 3 HD units in the UK. Eligibility criteria included a Clinical Frailty Scale (CFS) score of 4-7 and a history of at least one fall in the last 6 months. Sampling began guided by maximum variation sampling to ensure diversity in frailty status; subsequently theoretical sampling enabled exploration of preliminary themes. Analysis was informed by constructivist grounded theory; later we drew upon the socioecological model. RESULTS: Participants had a mean age of 69 ± 10 years, 13 were female, and 13 were White British. 14 participants were vulnerable or mildly frail (CFS 4-5), and 11 moderately or severely frail (CFS 6-7). Participants characterised frailty as weight loss, weakness, exhaustion, pain and sleep disturbance arising from multiple long-term conditions. Participants' accounts revealed: the consequences of frailty (variable function and psychological ill-health at the individual level; increasing reliance upon family at the interpersonal level; burdensome health and social care interactions at the organisational level; reduced participation at the community level; challenges with financial support at the societal level); coping strategies (avoidance, vigilance, and resignation); and unmet needs (overprotection from family and healthcare professionals, transactional health and social care exchanges). CONCLUSIONS: The implementation of a holistic needs assessment, person-centred health and social care systems, greater family support and enhancing opportunities for community participation may all improve outcomes and experience. An approach which encompasses all these strategies, together with wider public health interventions, may have a greater sustained impact. TRIAL REGISTRATION: ISRCTN12840463 .

Effect of Transcatheter Aortic Valve Implantation vs Surgical Aortic Valve Replacement on All-Cause Mortality in Patients With Aortic Stenosis: A Randomized Clinical Trial.

Importance: Transcatheter aortic valve implantation (TAVI) is a less invasive alternative to surgical aortic valve replacement and is the treatment of choice for patients at high operative risk. The role of TAVI in patients at lower risk is unclear. Objective: To determine whether TAVI is noninferior to surgery in patients at moderately increased operative risk. Design, Setting, and Participants: In this randomized clinical trial conducted at 34 UK centers, 913 patients aged 70 years or older with severe, symptomatic aortic stenosis and moderately increased operative risk due to age or comorbidity were enrolled between April 2014 and April 2018 and followed up through April 2019. Interventions: TAVI using any valve with a CE mark (indicating conformity of the valve with all legal and safety requirements for sale throughout the European Economic Area) and any access route (n = 458) or surgical aortic valve replacement (surgery; n = 455). Main Outcomes and Measures: The primary outcome was all-cause mortality at 1 year. The primary hypothesis was that TAVI was noninferior to surgery, with a noninferiority margin of 5% for the upper limit of the 1-sided 97.5% CI for the absolute between-group difference in mortality. There were 36 secondary outcomes (30 reported herein), including duration of hospital stay, major bleeding events, vascular complications, conduction disturbance requiring pacemaker implantation, and aortic regurgitation. Results: Among 913 patients randomized (median age, 81 years [IQR, 78 to 84 years]; 424 [46%] were female; median Society of Thoracic Surgeons mortality risk score, 2.6% [IQR, 2.0% to 3.4%]), 912 (99.9%) completed follow-up and were included in the noninferiority analysis. At 1 year, there were 21 deaths (4.6%) in the TAVI group and 30 deaths (6.6%) in the surgery group, with an adjusted absolute risk difference of -2.0% (1-sided 97.5% CI, -∞ to 1.2%; P < .001 for noninferiority). Of 30 prespecified secondary outcomes reported herein, 24 showed no significant difference at 1 year. TAVI was associated with significantly shorter postprocedural hospitalization (median of 3 days [IQR, 2 to 5 days] vs 8 days [IQR, 6 to 13 days] in the surgery group). At 1 year, there were significantly fewer major bleeding events after TAVI compared with surgery (7.2% vs 20.2%, respectively; adjusted hazard ratio [HR], 0.33 [95% CI, 0.24 to 0.45]) but significantly more vascular complications (10.3% vs 2.4%; adjusted HR, 4.42 [95% CI, 2.54 to 7.71]), conduction disturbances requiring pacemaker implantation (14.2% vs 7.3%; adjusted HR, 2.05 [95% CI, 1.43 to 2.94]), and mild (38.3% vs 11.7%) or moderate (2.3% vs 0.6%) aortic regurgitation (adjusted odds ratio for mild, moderate, or severe [no instance of severe reported] aortic regurgitation combined vs none, 4.89 [95% CI, 3.08 to 7.75]). Conclusions and Relevance: Among patients aged 70 years or older with severe, symptomatic aortic stenosis and moderately increased operative risk, TAVI was noninferior to surgery with respect to all-cause mortality at 1 year. Trial Registration: isrctn.com Identifier: ISRCTN57819173.

A comparison between the clinical frailty scale and the hospital frailty risk score to risk stratify older people with emergency care needs.

BACKGROUND: Older adults living with frailty who require treatment in hospitals are increasingly seen in the Emergency Departments (EDs). One quick and simple frailty assessment tool-the Clinical Frailty Scale (CFS)-has been embedded in many EDs in the United Kingdom (UK). However, it carries time/training and cost burden and has significant missing data. The Hospital Frailty Risk Score (HFRS) can be automated and has the potential to reduce costs and increase data availability, but has not been tested for predictive accuracy in the ED. The aim of this study is to assess the correlation between and the ability of the CFS at the ED and HFRS to predict hospital-related outcomes. METHODS: This is a retrospective cohort study using data from Leicester Royal Infirmary hospital during the period from 01/10/2017 to 30/09/2019. We included individuals aged + 75 years as the HFRS has been only validated for this population. We assessed the correlation between the CFS and HFRS using Pearson's correlation coefficient for the continuous scores and weighted kappa scores for the categorised scores. We developed logistic regression models (unadjusted and adjusted) to estimate Odds Ratios (ORs) and Confidence Intervals (CIs), so we can assess the ability of the CFS and HFRS to predict 30-day mortality, Length of Stay (LOS) > 10 days, and 30-day readmission. RESULTS: Twelve thousand two hundred thirty seven individuals met the inclusion criteria. The mean age was 84.6 years (SD 5.9) and 7,074 (57.8%) were females. Between the CFS and HFRS, the Pearson correlation coefficient was 0.36 and weighted kappa score was 0.15. When comparing the highest frailty categories to the lowest frailty category within each frailty score, the ORs for 30-day mortality, LOS > 10 days, and 30-day readmission using the CFS were 2.26, 1.36, and 1.64 and for the HFRS 2.16, 7.68, and 1.19. CONCLUSION: The CFS collected at the ED and the HFRS had low/slight agreement. Both frailty scores were shown to be predictors of adverse outcomes. More research is needed to assess the use of historic HFRS in the ED.

Does the Clinical Frailty Scale at Triage Predict Outcomes From Emergency Care for Older People?

STUDY OBJECTIVE: We determine whether the Clinical Frailty Scale applied at emergency department (ED) triage is associated with important service- and patient-related outcomes. METHODS: We undertook a single-center, retrospective cohort study examining hospital-related outcomes and their associations with frailty scores assessed at ED triage. Participants were aged 65 years or older, registered on their first ED presentation during the study period at a single, centralized ED in the United Kingdom. Baseline data included age, sex, Clinical Frailty Scale score, National Early Warning Score-2 and the Charlson Comorbidity Index score; outcomes included length of stay, readmissions (any future admissions), and mortality (inhospital or out of hospital) up to 2 years after ED presentation. Survival analysis methods (standard and competing risks) were applied to assess associations between ED triage frailty scores and outcomes. Unadjusted incidence curves and adjusted hazard ratios are presented. RESULTS: A total of 52,562 individuals representing 138,328 ED attendances were included; participants' mean age was 78.0 years, and 55% were women. Initial admission rates generally increased with frailty. Mean length of stay after 30- or 180-day follow-up was relatively low; all Clinical Frailty Scale categories included patients who experienced zero days' length of stay (ie, ambulatory care) and patients with relatively high numbers of inhospital days. Overall, 46% of study participants were readmitted by the 2-year follow-up. Readmissions increased with Clinical Frailty Scale score up until a score of 6 and then attenuated. Mortality rates increased with increasing frailty; the adjusted hazard ratio was 3.6 for Clinical Frailty Scale score 7 to 8 compared with score 1 to 3. CONCLUSION: Frailty assessed at ED triage (with the Clinical Frailty Scale) is associated with adverse outcomes in older people. Its use in ED triage might aid immediate clinical decisionmaking and service configuration.

A comparison of two national frailty scoring systems.

BACKGROUND: The electronic Frailty Index (eFI) has been developed in primary care settings. The Hospital Frailty Risk Score (HFRS) was derived using secondary care data. OBJECTIVE: Compare the two different tools for identifying frailty in older people admitted to hospital. DESIGN AND SETTING: Retrospective cohort study using the Secure Anonymised Information Linkage Databank, comprising 126,600 people aged 65+ who were admitted as an emergency to hospital in Wales from January 2013 up until December 2017. METHODS: Pearson's correlation coefficient and weighted kappa were used to assess the correlation between the tools. Cox and logistic regression were used to estimate hazard ratios (HRs) and odds ratios (ORs). The Concordance statistic and area under the receiver operating curves (AUROC) were estimated to determine discrimination. RESULTS: Pearson's correlation coefficient was 0.26 and the weighted kappa was 0.23. Comparing the highest to the least frail categories in the two scores the HRs for 90-day mortality, 90-day emergency readmission and care home admissions within 1-year using the HFRS were 1.41, 1.69 and 4.15 for the eFI 1.16, 1.63 and 1.47. Similarly, the ORs for inpatient death, length of stay greater than 10 days and readmission within 30-days were 1.44, 2.07 and 1.52 for the HFRS, and 1.21, 1.21 and 1.44 for the eFI. AUROC was determined as having no clinically relevant difference between the tools. CONCLUSIONS: The eFI and HFRS have a low correlation between their scores. The HRs and ORs were higher for the increasing frailty categories for both the HFRS and eFI.

The Hospital Frailty Risk Score-outcomes in specialised services.

BACKGROUND: Frailty is increasingly used to risk stratify older people, but across specialised services there is no standardised approach. The aim of this study was to assess if the Hospital Frailty Risk Score (HFRS) could describe outcomes for older people within English specialised services. DESIGN: A retrospective cohort study was performed using the Secondary Uses Service (SUS) electronic database for people aged 75 or older admitted between April 2017 and March 2018. METHODS: Based on HFRS, the populations were risk stratified into mild, moderate and severe frailty risk. The relationships with length of stay, readmission rate, mortality and some selected condition specific treatment complications were quantified using descriptive statistics. RESULTS: Very few individuals (<2%) could not be risk stratified for frailty risk. Frailty was differentially distributed across the specialties; around one-third had mild frailty; another third had moderate frailty and one-quarter severe frailty. Increasing frailty risk was associated with increased length of stay for the index admission, more days in hospital in the year following intervention and increased risk of dying in hospital. Severe frailty was a powerful discriminator of the risk of death; between 25 and 40% of those with severe frailty risk died at 30 months across all specialties. CONCLUSIONS: This study demonstrates the first application of the HFRS to a national dataset to describe service outcomes and mortality for older people undergoing a range of specialised interventions. This information could be used to identify those that might benefit from holistic assessment, aid prognostication, commissioning and service planning.