The physical phenotype of frailty for risk stratification of older medical inpatients

Patient Priorities Care Increases Long-Term Service and Support Use: Propensity Match Cohort Study

OBJECTIVES

Patient priorities care (PPC) is an evidence-based approach designed to help patients achieve what matters most to them by identifying their health priorities and working with clinicians to align the care they provide to the patient's priorities. This study examined the impact of the PPC approach on long-term service and support (LTSS) use among veterans.

DESIGN

Quasi-experimental study examining differences in LTSS use between veterans exposed to PPC and propensity-matched controls not exposed to PPC adjusting for covariates.

SETTING AND PARTICIPANTS

Fifty-six social workers in 5 Veterans Health Administration (VHA) sites trained in PPC in 2018, 143 veterans who used the PPC approach, and 286 matched veterans who did not use the PPC approach.

METHODS

Veterans with health priorities identified through the PPC approach were the intervention group (n = 143). The usual care group included propensity-matched veterans evaluated by the same social workers in the same period who did not participate in PPC (n = 286). The visit with the social worker was the index date. We examined LTSS use, emergency department (ED), and urgent care visits, 12 months before and after this date for both groups. Electronic medical record notes were extracted with a validated natural language processing algorithm (84% sensitivity, 95% specificity, and 92% accuracy).

RESULTS

Most participants were white men, mean age was 76, and 30% were frail. LTSS use was 48% higher in the PPC group compared with the usual care group [odds ratio (OR), 1.48; 95% CI, 1.00-2.18; P = .05]. Among those who lived >2 years after the index date, new LTSS use was higher (OR, 1.69; 95% CI, 1.04-2.76; P = .036). Among nonfrail individuals, LTSS use was also higher in the PPC group (OR, 1.70; 95% CI, 1.06-2.74; P = .028). PPC was not associated with higher ED or urgent care use.

CONCLUSIONS AND IMPLICATIONS

PPC results in higher LTSS use but not ED or urgent care in these veterans. LTSS use was higher for nonfrail veterans and those living longer. The PPC approach helps identify health priorities, including unmet needs for safe and independent living that LTSS can support.

Application of the (fr)AGILE scale in the evaluation of multidimensional frailty in elderly inpatients from internal medicine wards: a cross-sectional observational study

Background

With the rapid growth of an aging global population and proportion, the prevalence of frailty is constantly increasing. Therefore, finding a frailty assessment tool suitable for clinical application by physicians has become the primary link in the comprehensive management of frailty in elderly patients. This study used the (fr)AGILE scale to investigate the frailty status of elderly patients from internal medicine wards and identified relevant factors that affect the severity of frailty.

Method

In this study, 408 elderly inpatients in internal medicine departments of Qilu Hospital of Shandong University from May 2021 to August 2022 were enrolled as research subjects, and a cross-sectional observational study was conducted. Researchers evaluated the frailty based on the (fr)AGILE scale score. The general condition, past medical history, physical examination, laboratory examination, nutrition control score, intervention and treatment measures and other elderly patient information was collected. Logistic regression analysis was used to analyze the relevant factors that affect the severity of frailty and hospitalization costs.

Results

According to the (fr)AGILE scale score, the elderly patients were divided into groups to determine whether they were frail and the severity of the frailty. Among them, 164 patients were in the prefrailty stage, which accounted for 40.2%. There were 188 cases of mild frailty that accounted for 46.1%, and 56 cases of moderate to severe frailty that accounted for 13.7%. Decreased grip strength, elevated white blood cell levels, and low sodium and potassium are independent risk factors affecting the severity of frailty. As the severity of frailty increases, the proportion of sodium, potassium, albumin supplementation as well as anti-infection gradually increases.

Conclusion

Frailty is a common elderly syndrome with a high incidence among elderly patients in internal medicine departments. The main manifestations of frailty vary with different severity levels. Inflammation, anemia, and poor nutritional status can lead to an increase in the severity of frailty as well as blood hypercoagulability, myocardial damage, and additional supportive interventions. This ultimately leads to prolonged hospitalization and increased hospitalization costs.

Prevalence and outcomes of frailty in unplanned hospital admissions: a systematic review and meta-analysis of hospital-wide and general (internal) medicine cohorts

Background

Guidelines recommend routine frailty screening for all hospitalised older adults to inform care decisions, based mainly on studies in elective or speciality-specific settings. However, most hospital bed days are accounted for by acute non-elective admissions, in which the prevalence and prognostic value of frailty might differ, and uptake of screening is limited. We therefore did a systematic review and meta-analysis of frailty prevalence and outcomes in unplanned hospital admissions.

Methods

We searched MEDLINE, EMBASE and CINAHL up to 31/01/2023 and included observational studies using validated frailty measures in adult hospital-wide or general medicine admissions. Summary data on the prevalence of frailty and associated outcomes, measurement tools, study setting (hospital-wide vs general medicine), and design (prospective vs retrospective) were extracted and risk of bias assessed (modified Joanna Briggs Institute checklists). Unadjusted relative risks (RR; moderate/severe frailty vs no/mild) for mortality (within one year), length of stay (LOS), discharge destination and readmission were calculated and pooled, where appropriate, using random-effects models. PROSPERO CRD42021235663.

Findings

Among 45 cohorts (median/SD age = 80/5 years; n = 39,041,266 admissions, n = 22 measurement tools) moderate/severe frailty ranged from 14.3% to 79.6% overall (and in the 26 cohorts with low-moderate risk of bias) with considerable heterogeneity between studies (p_het < 0.001) preventing pooling of results but with rates <25% in only 3 cohorts. Moderate/severe vs no/mild frailty was associated with increased mortality (n = 19 cohorts; RR range = 1.08-3.70), more consistently among cohorts using clinically administered tools (n = 11; RR range = 1.63-3.70; p_het = 0.08; pooled RR = 2.53, 95% CI = 2.15-2.97) vs cohorts using (retrospective) administrative coding data (n = 8; RR range = 1.08-3.02; p_het < 0.001). Clinically administered tools also predicted increasing mortality across the full range of frailty severity in each of the six cohorts that allowed ordinal analysis (all p < 0.05). Moderate/severe vs no/mild frailty was also associated with a LOS >8 days (RR range = 2.14-3.04; n = 6) and discharge to a location other than home (RR range = 1.97-2.82; n = 4) but was inconsistently related to 30-day readmission (RR range = 0.83-1.94; n = 12). Associations remained clinically significant after adjustment for age, sex and comorbidity where reported.

Interpretation

Frailty is common in older patients with acute, non-elective hospital admission and remains predictive of mortality, LOS and discharge home with more severe frailty associated with greater risk, justifying more widespread implementation of screening using clinically administered tools.

Funding

None.

Machine learning for predicting readmission risk among the frail: Explainable AI for healthcare

Healthcare costs due to unplanned readmissions are high and negatively affect health and wellness of patients. Hospital readmission is an undesirable outcome for elderly patients. Here, we present readmission risk prediction using five machine learning approaches for predicting 30-day unplanned readmission for elderly patients (age ≥ 50 years). We use a comprehensive and curated set of variables that include frailty, comorbidities, high-risk medications, demographics, hospital, and insurance utilization to build these models. We conduct a large-scale study with electronic health record (her) data with over 145,000 observations from 76,000 patients. Findings indicate that the category boost (CatBoost) model outperforms other models with a mean area under the curve (AUC) of 0.79. We find that prior readmissions, discharge to a rehabilitation facility, length of stay, comorbidities, and frailty indicators were all strong predictors of 30-day readmission. We present in-depth insights using Shapley additive explanations (SHAP), the state of the art in machine learning explainability.

Understanding health-care outcomes of older people with cognitive impairment and/or dementia admitted to hospital: a mixed-methods study

Background

Cognitive impairment is common in older people admitted to hospital, but previous research has focused on single conditions.

Objective

This project sits in phase 0/1 of the Medical Research Council Framework for the Development and Evaluation of Complex Interventions. It aims to develop an understanding of current health-care outcomes. This will be used in the future development of a multidomain intervention for people with confusion (dementia and cognitive impairment) in general hospitals. The research was conducted from January 2015 to June 2018 and used data from people admitted between 2012 and 2013.

Design

For the review of outcomes, the systematic review identified peer-reviewed quantitative epidemiology measuring prevalence and associations with outcomes. Screening for duplication and relevance was followed by full-text review, quality assessment and a narrative review (141 papers). A survey sought opinion on the key outcomes for people with dementia and/or confusion and their carers in the acute hospital (n = 78). For the analysis of outcomes including cost, the prospective cohort study was in a medical admissions unit in an acute hospital in one Scottish health board covering 10% of the Scottish population. The participants (n = 6724) were older people (aged ≥ 65 years) with or without a cognitive spectrum disorder who were admitted as medical emergencies between January 2012 and December 2013 and who underwent a structured nurse assessment. ‘Cognitive spectrum disorder’ was defined as any combination of delirium, known dementia or an Abbreviated Mental Test score of < 8 out of 10 points. The main outcome measures were living at home 30 days after discharge, mortality within 2 years of admission, length of stay, re-admission within 2 years of admission and cost.

Data sources

Scottish Morbidity Records 01 was linked to the Older Persons Routine Acute Assessment data set.

Results

In the systematic review, methodological heterogeneity, especially concerning diagnostic criteria, means that there is significant overlap in conditions of patients presenting to general hospitals with confusion. Patients and their families expect that patients are discharged in the same or a better condition than they were in on admission or, failing that, that they have a satisfactory experience of their admission. Cognitive spectrum disorders were present in more than one-third of patients aged ≥ 65 years, and in over half of those aged ≥ 85 years. Outcomes were worse in those patients with cognitive spectrum disorders than in those without: length of stay 25.0 vs. 11.8 days, 30-day mortality 13.6% vs. 9.0%, 1-year mortality 40.0% vs. 26.0%, 1-year mortality or re-admission 62.4% vs. 51.5%, respectively (all p < 0.01). There was relatively little difference by cognitive spectrum disorder type; for example, the presence of any cognitive spectrum disorder was associated with an increased mortality over the entire period of follow-up, but with different temporal patterns depending on the type of cognitive spectrum disorder. The cost of admission was higher for those with cognitive spectrum disorders, but the average daily cost was lower.

Limitations

A lack of diagnosis and/or standardisation of diagnosis for dementia and/or delirium was a limitation for the systematic review, the quantitative study and the economic study. The economic study was limited to in-hospital costs as data for social or informal care costs were unavailable. The survey was conducted online, limiting its reach to older carers and those people with cognitive spectrum disorders.

Conclusions

Cognitive spectrum disorders are common in older inpatients and are associated with considerably worse health-care outcomes, with significant overlap between individual cognitive spectrum disorders. This suggests the need for health-care systems to systematically identify and develop care pathways for older people with cognitive spectrum disorders, and avoid focusing on only condition-specific pathways.

Future work

Development and evaluation of a multidomain intervention for the management of patients with cognitive spectrum disorders in hospital.

Study registration

This study is registered as PROSPERO CRD42015024492.

Funding

This project was funded by the National Institute for Health Research (NIHR) Health Services and Delivery Research programme and will be published in full in Health Services and Delivery Research; Vol. 9, No. 8. See the NIHR Journals Library website for further project information.

What do we know about frailty in the acute care setting? A scoping review

Background

The ability of acute care providers to cope with the influx of frail older patients is increasingly stressed, and changes need to be made to improve care provided to older adults. Our purpose was to conduct a scoping review to map and synthesize the literature addressing frailty in the acute care setting in order to understand how to tackle this challenge. We also aimed to highlight the current gaps in frailty research.

Methods

This scoping review included original research articles with acutely-ill Emergency Medical Services (EMS) or hospitalized older patients who were identified as frail by the authors. We searched Medline, CINAHL, Embase, PsycINFO, Eric, and Cochrane from January 2000 to September 2015.

Results

Our database search initially resulted in 8658 articles and 617 were eligible. In 67% of the articles the authors identified their participants as frail but did not report on how they measured frailty. Among the 204 articles that did measure frailty, the most common disciplines were geriatrics (14%), emergency department (14%), and general medicine (11%). In total, 89 measures were used. This included 13 established tools, used in 51% of the articles, and 35 non-frailty tools, used in 24% of the articles. The most commonly used tools were the Clinical Frailty Scale, the Frailty Index, and the Frailty Phenotype (12% each). Most often (44%) researchers used frailty tools to predict adverse health outcomes. In 74% of the cases frailty predicted the outcome examined, typically mortality and length of stay.

Conclusions

Most studies (83%) were conducted in non-geriatric disciplines and two thirds of the articles identified participants as frail without measuring frailty. There was great variability in tools used and more recently published studies were more likely to use established frailty tools. Overall, frailty appears to be a good predictor of adverse health outcomes. For frailty to be implemented in clinical practice frailty tools should help formulate the care plan and improve shared decision making. How this will happen has yet to be determined.

Electronic supplementary material

The online version of this article (10.1186/s12877-018-0823-2) contains supplementary material, which is available to authorized users.

Frailty status at admission to hospital predicts multiple adverse outcomes

Aims

frailty is proposed as a summative measure of health status and marker of individual vulnerability. We aimed to investigate the discriminative capacity of a frailty index (FI) derived from interRAI Comprehensive Geriatric Assessment for Acute Care (AC) in relation to multiple adverse inpatient outcomes.

Methods

in this prospective cohort study, an FI was derived for 1,418 patients ≥70 years across 11 hospitals in Australia. The interRAI-AC was administered at admission and discharge by trained nurses, who also screened patients daily for geriatric syndromes.

Results

in adjusted logistic regression models an increase of 0.1 in FI was significantly associated with increased likelihood of length of stay >28 days (odds ratio [OR]: 1.29 [1.10-1.52]), new discharge to residential aged care (OR: 1.31 [1.10-1.57]), in-hospital falls (OR: 1.29 [1.10-1.50]), delirium (OR: 2.34 [2.08-2.63]), pressure ulcer incidence (OR: 1.51 [1.23-1.87]) and inpatient mortality (OR: 2.01 [1.66-2.42]). For each of these adverse outcomes, the cut-point at which optimal sensitivity and specificity occurred was for an FI > 0.40. Specificity was higher than sensitivity with positive predictive values of 7-52% and negative predictive values of 88-98%. FI-AC was not significantly associated with readmissions to hospital.

Conclusions

the interRAI-AC can be used to derive a single score that predicts multiple adverse outcomes in older inpatients. A score of ≤0.40 can well discriminate patients who are unlikely to die or experience a geriatric syndrome. Whether the FI-AC can result in management decisions that improve outcomes requires further study.

Preoperative Hypoalbuminemia is a Risk Factor for Early and Late Mortality in Patients Undergoing Endovascular Juxtarenal and Thoracoabdominal Aortic Aneurysm Repair

BACKGROUND

Advances in endovascular aneurysm repair now allow surgeons to treat high-risk patients with complex aortic aneurysms. Stringent selection criteria for repair exist from an anatomic and technical perspective; however, there is a paucity of literature examining frailty in patients being evaluated for fenestrated and branched endovascular aortic repair (FEVAR). As a marker of frailty well supported in the literature, we hypothesized that preoperative hypoalbuminemia would increase risk for short-term mortality after endovascular juxtarenal and thoracoabdominal aortic aneurysm repair.

METHODS

One thousand eighty nine consecutive patients with juxtarenal and thoracoabdominal aortic aneurysms considered high risk for open surgery from a single institution who underwent FEVAR from 2001 to 2014 were included in the study. Risk factors for all-cause mortality were identified via a Cox regression model on time to death.

RESULTS

The patients with severe hypoalbuminemia (albumin <2.4 g/dL) had significantly increased 30-day mortality (P = 0.025, odds ratio [OR]: 4.967 (95% CI: 1.385-17.814, normal versus severe) and 2-year mortality P = 0.006, OR: 2.4, 95% CI: 1.05-5.73, normal versus severe), as well as increased 30-day complication rates P = 0.026, OR: 1.91, 95% CI: 0.9-4.17, normal versus severe). A univariate analysis for 30-day mortality revealed no significant difference in median age: 75.1 vs. 72.5 years (alive at 30 days (Q1, Q3: 69.8, 80.1) versus expired (Q1, Q3: 69.3, 77.8), P = 0.24.

CONCLUSIONS

Patients with hypoalbuminemia have significantly increased mortality risk. Albumin level is regulated by nutritional intake and inflammation due to chronic disease, which make it a useful part of a preoperative frailty assessment. Further studies are needed to identify whether optimizing nutrition status will affect albumin levels or decrease mortality.

Frailty Assessment in Hospitalized Older Adults Using the Electronic Health Record

INTRODUCTION

Frailty, a clinical syndrome of decreased physiologic reserve and dysregulation in multiple physiologic systems, is associated with increased risk for adverse outcomes.

PURPOSE

The aim of this retrospective, cross-sectional, correlational study was to characterize frailty in older adults admitted to a tertiary-care hospital using a biopsychosocial frailty assessment and to determine associations between frailty and time to in-hospital mortality and 30-day rehospitalization.

METHODS

The sample included 278 patients ≥55 years old admitted to medicine units. Frailty was determined using clinical data from the electronic health record (EHR) for symptoms, syndromes, and conditions and laboratory data for four serum biomarkers. A frailty risk score (FRS) was created from 16 risk factors, and relationships between the FRS and outcomes were examined.

RESULTS

The mean age of the sample was 70.2 years and mean FRS was 9.4 ( SD, 2.2). Increased FRS was significantly associated with increased risk of death (hazard ratio = 1.77-2.27 for 3 days ≤ length of stay (LOS) ≤7 days), but depended upon LOS ( p < .001). Frailty was marginally associated with rehospitalization for those who did not die in hospital (adjusted odds ratio = 1.18, p = .086, area under the curve [AUC] = 0.66, 95% confidence interval for AUC = [0.57, 0.76]).

DISCUSSION

Clinical data in the EHR can be used for frailty assessment. Informatics may facilitate data aggregation and decision support. Because frailty is potentially preventable and treatable, early detection is crucial to delivery of tailored interventions and optimal patient outcomes.