Frailty impacts outcomes in critical Acute Myocardial Infarction (AMI). This study evaluates three Hospital Frailty Risk Measure (HFRM) formats-continuous score, 8 risk groups, and binary classification-for predicting clinical outcomes.

Using 2129 critical AMI patients' data from MIMIC-IV, logistic and COX regression models assessed associations between HFRM formats and outcomes (ICU mortality, in-hospital mortality, discharge with nursing support, one-year mortality), adjusted for age, gender, smoking, and NSTEMI.

All HFRM formats consistently predicted adverse outcomes. The continuous score showed increased adjusted odds/hazard ratios for ICU mortality (OR 1.289, 95 % CI:1.065-1.516), in-hospital mortality (OR 1.343, 95 % CI:1.161-1.554), nursing support discharge (2.389, 95 % CI: 1.960-2.912), and one-year mortality (1.709, 95 % CI:1.533-1.904). The binary measure (groups 4-8 as frail) demonstrated higher adjusted risks for all outcomes except ICU mortality.

HFRM effectively predicts adverse outcomes in critical AMI. The binary classification offers robust risk stratification, underscoring frailty assessment's role in personalized care planning.

Satralizumab showed a comparable safety profile versus placebo in 2 pivotal neuromyelitis optica spectrum disorder (NMOSD) studies. We analyzed infection rates with long-term satralizumab treatment in the open-label study, SAkuraMoon, and in a post-marketing setting (PMS), comparing frequencies with US-based health claims real-world data (US-RWD). Incidence rates of infection per 100 patient-years (IR/100 PY) were analyzed in the SAkura studies (clinical cut-off date: 31 January 2023). Reported rates of infection ( %) in a PMS using Periodic Benefit-Risk Evaluation Reports (2020-2023), and cumulative incidence of infections ( %) from the US PharMetrics claims data in NMOSD patients (2017-2022) were analyzed. 166 patients (SAkura studies), 2951 patients (PMS) and 2872 patients (US-RWD) were included. In the SAkura studies, the incidence rates of infection, serious infection, and sepsis were lower versus the double-blind period (IR/100 PY [95 % confidence intervals (Tur, C. et al.)] infection 91.7 [85.5-98.3] vs 113.0 [98.6-129.0]; serious infection 2.6 [1.7-3.9] vs 4.1 [1.8-8.1]; sepsis 0.6 [0.2-1.3] vs 1.0 [0.1-3.7], respectively). In a PMS, reported rates of infection, serious infection, and sepsis were 7.3 %, 3.8 %, and 0.6 %, respectively. In the US-RWD, cumulative incidence of infection, serious infection, and sepsis in NMOSD were 67.3 %, 8.4 %, and 4.9 %, respectively. Concomitant IST use, comorbidities, Expanded Disability Status Scale score ≥4.0, and age >65 years were potential confounders of sepsis. US-RWD indicated infection is a major comorbidity in NMOSD, independent of satralizumab treatment. Infection rates were consistently lower in satralizumab-treated patients compared with US-RWD. Trial Registration: NCT04660539(SAkuraMoon), NCT02028884(SAkuraSky), NCT02073279(SAkuraStar).

Frailty is a common symptom in Multiple Sclerosis (MS), yet its precise mechanism remains elusive, and the clinical implications of frailty in MS are uncertain. Moreover, inflammation is closely linked to frailty. This study aims to assess serum cytokine levels in individuals with MS and explore their correlation with frailty.

A case-control study included 83 primary MS patients and 100 healthy individuals undergoing health check-ups. Serum cytokine levels were measured, and MS severity was determined using the Expanded Disability Status Scale (EDSS) score. Additionally, a comprehensive frailty index (FI) was calculated based on health deficits from various domains following standardized procedures.

Serum IL-6 and TNF-α levels were significantly higher in the frail group than in the non-frail group, with a statistically significant difference (P < 0.05). After adjusting for disease duration, sex, age, BMI, SBP, and DBP, serum IL-6 independently correlated with frailty in MS patients (OR = 1.46; 95 % CI = 1.02-1.93; P = 0.003). Moreover, increased serum IL-6 levels were associated positively with the frailty index (β = 0.123, P = 0.008).

Our initial findings suggest elevated levels of pro-inflammatory cytokines in MS patients with frailty, with IL-6 showing a positive correlation with frail indices. These results underscore the potential impact of inflammatory responses on frailty development in MS.

BackgroundIntensive care unit (ICU) hospitalizations of very old patients with acute respiratory infection have risen. The decision-making process for ICU admission is multifaceted, and the prediction of long-term survival outcome is an important component. We hypothesized that data-driven algorithms could build long-term prediction by examining massive real-life data. Our objective was to assess machine learning (ML) algorithms to predict the 1-y survival of very old patients with severe respiratory infections.MethodsA national 2011-2020 study of ICU patients ≥80 y with respiratory infection was carried out, using French hospital discharge databases. Data for the training cohort were collected from 2013 to 2016 to build the models, and the data of patients extracted in 2017 were used for external validation. Our proposed models were developed using random forest, logistic regression (LR), and XGBoost. The optimal model was selected based on its accuracy, sensitivity, specificity, Matthews coefficient correlation (MCC), receiver-operating characteristic curve (AUROC), and decision curve analysis (DCA). The local interpretable model-agnostic explanation (LIME) algorithm was used to analyze the contribution of individual features.ResultsA total of 24,270 very old patients were hospitalized in the ICU for respiratory infection (2013-2017) with a known vital status at 1 y. The 1-y survival rate was 41.3% (median survival: 3 mo [2.7-3.3]). Of the 3 ML models tested, LR exhibited promising performance with an accuracy, sensitivity, specificity, MCC, and AUROC (95% confidence interval) of 0.65, 0.76, 0.60, 0.27, and 0.70 (0.69-0.72), respectively. LR achieved an AUROC of 0.70 (0.68-0.71) in external validation by temporal splitting. LR demonstrated higher net benefits across a range of threshold probability values in DCA. The LIME algorithm identified the 10 most influential features at an individual scale.ConclusionsWe demonstrated that a ML model has the potential to predict long-term outcomes for very old patients with acute respiratory infections. As a proof of concept, we proposed a program that acts as an "explainer" for the ML model. This work represents a step forward in translating ML models into practical, transparent, and reliable clinical tools to support medical decision making.HighlightsThe decision to admit a very old patient to the ICU is one of the most complex challenges faced by intensivists, often relying on subjective judgment.In this study, we evaluated the efficacy of machine learning algorithms in predicting the 1-y survival rate of critically ill very old patients (≥80 y) with severe respiratory infections, using data available prior to the admission decision.Our findings demonstrate that machine learning can effectively predict long-term outcomes in very old patients. We used an innovative approach that aims to support medical decision making about admission in ICU.

Delirium is common in the older hospital population and is often precipitated by acute illness. Delirium is associated with poor outcomes including subsequent cognitive decline and dementia and may therefore be a modifiable risk factor for dementia. However, the mechanisms underpinning the delirium-dementia relationship and the role of coexisting acute illness factors remain uncertain. Current biomarker studies of delirium have limitations including lack of detailed delirium characterisation with few studies on neurodegenerative or neuroimaging biomarkers especially in the acute setting. The Oxford and Reading Cognitive Health After Recovery from acute illness and Delirium-Prospective Study (ORCHARD-PS) aims to elucidate the pathophysiology of delirium and subsequent cognitive decline after acute illness in older adults, through acquisition of multimodal biomarkers for deep phenotyping of delirium and acute illness, and follow-up for incident dementia.

ORCHARD-PS is a bi-centre, prospective cohort study. Consecutive eligible patients requiring acute hospital admission or assessment are identified by the relevant acute clinical care team. All patients age >65 years without advanced dementia, nursing home residence, end-stage frailty or terminal illness are eligible. Details of potential participants are communicated to the research team and written informed consent or consultee agreement is obtained. Participants are interviewed as soon as possible after admission/assessment using a structured proforma.Data are collected on demographics, diagnosis and comorbidities, social and functional background. Delirium is assessed using the 4A's test, Confusion Assessment Method (long-form), Observational Scale of Level of Arousal, Richmond Agitation-Sedation Scale and Memorial Delirium Assessment Scale and diagnosed using the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition criteria. Delirium is categorised by time of onset (prevalent vs incident), dementia status, motoric subtype, severity and duration. Cognitive tests include the 10-point Abbreviated Mental Test and Montreal Cognitive Assessment. Participants are reassessed every 48-72 hours if remaining in hospital. Informant questionnaire data and interview are supplemented by hand searching of medical records and linkage to electronic patient records for nursing risk assessments, vital observations, laboratory results and International Classification of Diseases, Tenth Revision diagnostic and procedure codes.In-person follow-up with more detailed cognitive testing and informant interview is undertaken at 3 months, and 1 and 3 years supplemented with indirect follow-up using medical records. Blood banking is performed at baseline and all follow-ups for future biomarker analyses. CT-brain and MRI-brain imaging acquired as part of standard care is obtained for quantification of brain atrophy and white matter disease/stroke supplemented by research CT-brain imaging. Outcomes include length of hospitalisation, change in care needs, institutionalisation, mortality, readmission, longitudinal changes in cognitive and functional status and incident dementia. Biomarker associations with delirium, and with incident dementia on follow-up, will be determined using logistic or Cox regression as appropriate, unadjusted and adjusted for covariates including demographics, baseline cognition, frailty, comorbidity and apolipoprotein E genotype.

ORCHARD-PS is approved by the South Central-Berkshire Research Ethics Committee (REC Reference: 23/SC/0199). Results will be disseminated through peer-reviewed publications and conference presentations.

ISRCTN24171810.

Understanding the impact of frailty risk on outcomes after hydrocephalus surgery in older adults is critical for improving prognosis and guiding tailored treatment strategies. This study evaluated the effect of frailty risk on postoperative activities of daily living (ADL) and in-hospital events in older patients with hydrocephalus, using a nationwide Japanese database.

A retrospective study was conducted on older patients who underwent cerebrospinal fluid shunt surgery. Frailty risk was assessed using the Hospital Frailty Risk Score (HFRS) based on ICD-10 codes. Patients were categorized into low (<5 points) and moderate-to-high (≥5 points) frailty risk groups. Outcomes included the Barthel Index (BI) at discharge, BI gain, BI efficiency, and incidences of dysphagia and delirium. Propensity score-based inverse probability weighting was applied to adjust for confounding.

Among 3075 patients, 1539 were at low risk and 1526 were at moderate-to-high risk of frailty. Moderate-to-high frailty risk significantly reduced BI at discharge (β = -0.10, P < 0.001), BI gain (β = -0.07, P < 0.001), and BI efficiency (β = -0.07, P < 0.001). Frailty risk also increased the odds of dysphagia (odds ratio = 1.86, P = 0.017) and delirium (odds ratio = 31.07, P < 0.001).

Moderate-to-high frailty risk negatively impacts postoperative ADL recovery and increases dysphagia and delirium risk in older patients with hydrocephalus. These findings highlight the need for early frailty assessment and tailored interventions to improve surgical outcomes. Geriatr Gerontol Int 2025; ••: ••-••.

Atrial fibrillation (AF) that is first diagnosed during hospitalization for other causes can subside with resolution of the inciting stressor.

To describe the risk for stroke after newly diagnosed AF during hospitalization for other causes.

Population-based retrospective cohort study.

Ontario, Canada.

Patients aged 66 years or older discharged alive from the hospital between April 2013 and March 2023 with a first diagnosis of AF.

Newly diagnosed AF during hospitalization for other causes, categorized into cardiac medical, noncardiac medical, cardiac surgical, and noncardiac surgical.

The primary outcome was hospitalization for stroke. The cumulative incidence function was used to estimate crude incidence, censoring on anticoagulant dispensation. Inverse probability of censoring weights were used to account for informative censoring.

Atrial fibrillation was diagnosed in 20 639 patients (mean age, 77.1 years; 58.1% male) while hospitalized for other causes: 8340 (40.4%) for noncardiac medical, 7097 (34.4%) for cardiac surgical, 3553 (17.2%) for noncardiac surgical, and 1649 (8.0%) for cardiac medical diagnoses. At 1 year, anticoagulants were being dispensed to 26.4% of patients with CHA2DS2-VA scores of 1 to 4 and 35.2% of those with CHA2DS2-VA scores of 5 to 8. The 1-year risk for stroke without anticoagulation was 1.3% (95% CI, 0.7% to 2.3%) for cardiac medical, 1.2% (CI, 0.9% to 1.5%) for noncardiac medical, 1.1% (CI, 0.8% to 1.7%) for noncardiac surgical, and 1.0% (CI, 0.7% to 1.3%) for cardiac surgical patients. Patients with CHA2DS2-VA scores of 1 to 4 had a 1-year stroke risk of 0.7% (CI, 0.6% to 1.0%) without anticoagulation, compared with 1.8% (CI, 1.4% to 2.2%) at CHA2DS2-VA scores of 5 to 8.

Long-standing AF may have been misclassified as newly diagnosed, leading to overestimation of stroke risk.

Among patients with newly diagnosed AF during hospitalization for other causes, a substantial proportion with low CHA2DS2-VA scores receive anticoagulation, with modest increases in this proportion at higher scores. The stroke risk in patients with CHA2DS2-VA scores greater than 4 approximated the 2% threshold commonly used to initiate anticoagulation in AF.

Canadian Cardiovascular Society.

The COVID-19 pandemic had a profound impact on the management and delivery of acute healthcare. To tackle the pandemic, hospitals redesigned their organisational models to provide a rapid increase in acute care assessment and treatment capacity for patients with COVID-19 whilst also trying to maintain delivery of care for patients with non-COVID-19 healthcare needs. This capacity to adjust and recover after COVID-19 might be shaped by both measures taken by acute hospitals and wider hospital pre-pandemic characteristics. The aim of this study is to examine how hospital characteristics in acute care are associated with recovery of elective activity after the height of the COVID-19 pandemic compared to pre-pandemic levels. Using patient-level data from Hospital Episode Statistics aggregated at monthly-trust level for all English National Health Service (NHS) acute hospital trusts in 2019 and 2021, we estimate the associations between hospital recovery rate and hospital pre-pandemic characteristics by employing linear regressions of the proportional change over time in elective activity against a set of explanatory variables related to supply factors (e.g., hospital size, workforce, type of hospital, regional location), demand factors (e.g., population need, patient case-mix) and time factors. On average, English NHS acute hospital trusts did not fully recover from the COVID-19 pandemic in 2021. The results show that the explanatory variables are not systematically associated with hospital recovery rate, excepting regional differences. Hospital trusts not located in London, especially in the North of England, are associated with a lower recovery (less resilience) of total elective activity and orthopaedic and vascular surgical elective activity. The implication for policy development is that the evolution of hospital recovery rates in elective activity varied across English regions, especially for high-volume and high-risk elective specialties, with better recovery in London than elsewhere.

Although frailty has been recognized to adversely influence outcomes of emergency general surgery, there are limited data comparing the performance of frailty instruments among this population. We compared the discriminatory power of 4 risk prediction models across a national cohort of patients who underwent emergency general surgery to assess outcomes of interest.

Adults undergoing emergency general surgery (large bowel resection, small bowel resection, repair of perforated ulcer, cholecystectomy, appendectomy, lysis of adhesions, or laparotomy) were identified in 2016-2021 Nationwide Readmissions Database. Patients were grouped into frail and non-frail cohorts on the basis of various frailty instruments: Hospital Frailty Risk Score, Modified 5-factor Frailty Index, Modified 11-factor Frailty Index, and Johns Hopkins Adjusted Clinical Groups index. Multivariable regressions were developed to assess independent associations between frailty instruments and in-hospital mortality as well as a composite of perioperative complications.

Of 1,385,505 hospitalizations for emergency general surgery, 57.0%, 29.9%, 26.6%, and 10.5% were identified as frail by mFI-11, Hospital Frailty Risk Score, Modified 5-factor Frailty Index, and Adjusted Clinical Groups, respectively. After multivariable adjustment, Hospital Frailty Risk Score demonstrated the greatest discriminatory power for predicting in-hospital mortality and perioperative complications when compared with other frailty indices. Subjects classified as frail using the Hospital Frailty Risk Score were associated with the greatest risk of mortality (adjusted odds ratio, 7.8; 95% confidence interval, 7.4-8.3) and composite complications (adjusted odds ratio, 8.4; 95% confidence interval, 9.3-8.5) compared with other indices across all frailty levels.

Among patients undergoing emergency general surgery, Hospital Frailty Risk Score demonstrated the greatest discrimination in predicting mortality and composite complications. Risk-stratification efforts should prioritize Hospital Frailty Risk Score in elderly patients undergoing emergency general surgery to optimize clinical outcomes and resource allocation.

The global annual incidence of hip fractures is projected to double over the next 20 to 30 years. The rates and risk factors for new persistent opioid use after hip fracture surgery remain poorly quantified.

To describe trajectories, rates, and risk factors for new persistent opioid use after hip fracture surgery in Australia.

A retrospective population-based cohort study was conducted using linked administrative health data in Australia. Adults aged ≥30 years discharged from hospital after a first hip fracture surgery between July 2012 and June 2017, opioid-naïve on admission, and alive 12 months postdischarge were included. Group-based trajectory modelling was utilised to determine trajectories and rates of opioid use 12 months postdischarge. Multivariate multinomial logistic regression analysis was performed to identify risk factors for persistent opioid use.

Among 10,309 opioid-naïve patients who had first hip fracture surgery, 5305 (51.5%) used opioids postdischarge. Opioid users were categorised as 58.9% (3127/5305) nonpersistent, 12.6% (670/5305) fluctuating, 12.1% (641/5305) late discontinuation, and 16.3% (867/5305) persistent. Key risk factors for persistent use were total oral morphine equivalent >600 mg in first 30 days postdischarge (relative risk [RR] 13.61, 95% confidence interval [CI] 9.34-19.83), transdermal opioid in the first 30 days postdischarge (RR 7.64, 95% CI 5.61-10.39), and hospital length of stay >60 days (RR 4.31, 95% CI 3.02-6.15).

Among opioid-naïve patients, 16.3% were persistent opioid users at 12 months posthospital discharge. Future research should focus on targeted interventions to address modifiable risk factors to reduce new persistent opioid use in older and vulnerable populations.

The aim of this study was to compare the risk of seizure, recurrent stroke, fall or fracture, and mortality in individuals prescribed different antiseizure medications (ASMs) following an ischemic stroke.

We identified all patients admitted to a Victorian public or private hospital with a principal diagnosis of an incident ischemic stroke between 2013 and 2017 and dispensed an ASM within 12 months of discharge. Cox proportional hazards regression was used to estimate the risk of cause-specific rehospitalization or emergency department visits (seizure, fall or fracture, recurrent stroke) and all-cause mortality over a 2-year period. Inverse probability of treatment weighting was applied to each model to adjust for baseline covariates.

Of 19 601 individuals hospitalized for incident ischemic stroke, 897 initiated ASM treatment within 12 months. More than three quarters were initiated on a non-enzyme-inducing ASM (78.0%). Levetiracetam (41.9%), valproate (28.4%), and carbamazepine (11.4%) were commonly dispensed initial ASMs. Non-enzyme-inducing ASMs demonstrated similar risk of seizure (hazard ratio [HR] = .93, 95% confidence interval [CI] = .63-1.37), fall or fracture (HR = 1.47, 95% CI = .92-2.34), stroke (HR = .83; 95% CI = .52-1.33), and mortality (HR = .96; 95% CI = .69-1.32) compared to enzyme-inducing ASMs. However, when valproate was grouped as a separate class, non-enzyme-inducing ASMs (HR = 1.67, 95% CI = 1.04-2.71) showed higher risk of fall or fracture compared to enzyme-inducing ASMs.

At a population level, ASMs of different types showed no significant differences in the risk of hospitalization or emergency department presentation for seizure, fall or fracture, stroke, and mortality within 2 years of an incident stroke presentation, suggesting similar short-term health outcomes in a real-world setting. Future research should investigate decision-making around ASM choice for stroke survivors and examine the impact of long-term ASM exposure on health outcomes.

Parallel to demographic trends, an increase of multimorbid patients in emergency and acute medicine is prominent. To define easily applicable criteria for the necessity of inpatient admission, a hierarchical cluster analysis was performed.

In a retrospective, single-center study data of n = 35,249 emergency cases (01/2016-05/2018) were statistically analyzed. Multimorbidity (MM) was defined by at least five ICD-10-GM diagnoses resulting from treatment. A hierarchical cluster analysis was performed for those diagnoses initially summarized into 112 diagnosis subclusters to determine specific clusters of in- and outpatient cases.

Hospital admission was determined in 81.2% of all ED patients (n = 28,633); 54.7% of inpatients (n = 15,652) and 0.97% of outpatient cases (n = 64) met the criteria for multimorbidity and the age difference between them was highly significant (68.7/60.8 years; p < 0.001). Using a hierarchical cluster analysis, 13 clusters with different diagnoses were identified for inpatient multimorbid patients (MP) and 7 clusters with primarily hematological malignancies for outpatient MP. The length of stay in the ED of inpatient MP was more than twice as long (max. 8.3 h) as for outpatient MP (max. 3.2 h.).

The combination of diagnoses typical for MM were characterized as clusters in this study. In contrast to single or combined single diagnoses, the statistically determined characterization of clusters allows for a significantly more accurate prediction of ED patients' disposition as well as for economic process allocation.

Enhanced recovery pathways (ERPs) are designed to improve patient outcomes after elective surgery. Our primary aim was to examine whether shorter hospital stay, as a surrogate ERP outcome, was associated with higher 30-day emergency readmission rates for colonic and rectal surgery in England. A secondary aim was to assess how hospital trust compliance with a specific postoperative care bundle, drinking, eating, and mobilising (DrEaMing) within 24 h, relates to outcomes.

This was a retrospective analysis of observational data from the Hospital Episode Statistics dataset for England. All patients aged ≥17 yr undergoing elective colonic or rectal surgery for cancer between April 1, 2014, and March 31, 2024, were included.

Shorter hospital stays were significantly associated with a lower rate of 30-day emergency readmission among 124 580 colonic and 87 036 rectal surgery patients. Comparing the first (reference) and fourth quartile of length of stay, the odds of 30-day emergency readmission increased by 2.16 (95% confidence interval [CI] 2.04-2.30) and 2.41 (95% CI 2.26-2.57) for colonic and rectal surgery, respectively. Increased hospital trust DrEaMing compliance was associated with a reduction in the number of patients with extended length of stay (colonic surgery: X2=24.885, P<0.001; rectal surgery: X2=61.670, P<0.001) and was not associated with 30-day emergency readmission.

We found no evidence that shorter length of stay, or greater DrEaMing compliance, were associated with higher emergency admission rates. These findings should not be interpreted as causal.

Cirrhosis-related inpatient hospitalizations have increased dramatically over the past decade. We used a longitudinal dataset capturing a large metropolitan area in the United States from 2011 to 2021 to evaluate contemporary hospitalization rates and risk factors among frail patients with cirrhosis.

We conducted a retrospective, longitudinal cohort study using the Chicago Area Patient-Centered Outcomes Research Network (CAPriCORN) database, an electronic health record repository that aggregates de-duplicated data across 7 health care systems in the Chicago metropolitan area, from 2011 to 2021. The primary outcome of our study was the rate of hospitalization encounters. Frailty was defined by the Hospital Frailty Risk Score. Hospitalization rates were reported per 100 patients per year, and a multivariable logistic regression analysis identified predictors of annual hospitalization probability.

During the study period, of 36,971 patients, 16,265 patients (44%) were hospitalized (compensated, 18.4%; decompensated, 81.6%). Hospitalization rates were highest in patients with decompensated cirrhosis, reaching nearly 77.3 hospitalizations/100 patients per year. Hospitalization rates among patients with compensated cirrhosis were also high (14.2 vs 77.3 hospitalization/100 patients per year), with odds of annual hospitalization 3 times (odds ratio, 3.1; 95% confidence interval, 2.9-3.4) as high among compensated patients with intermediate frailty and 5 times (odds ratio, 5.2; 95% confidence interval, 4.5-6.0) as high among those with severe frailty (compared with compensated patients with low frailty).

Compensated and decompensated cirrhosis patients with intermediate to severe frailty face a substantially increased odds of annual hospitalizations compared with those with low frailty. Future work should focus on targeted interventions to incorporate routine frailty screenings into cirrhosis care and to ultimately minimize high hospitalization rates.

As the trajectory of very old critically-ill patients becomes an increasingly significant global challenge, these patients are often referred to intermediate care units. Intermediate care units provide a level of care that is less intensive than the intensive care unit (ICU) but more advanced than standard hospital wards. We aimed to assess the nationwide utilization of intermediate care units for critically ill patients aged 80 years or older (≥ 80 y.o.) and to examine their characteristics and long-term mortality outcomes.

From the overall adult population (aged 18 years and older) hospitalized in France (French Hospital Discharge Database) from January 1, 2014, to December 31, 2022, patients ≥ 80 y.o. were included. We examined trends in the utilization of medical intermediate care units for critically ill patients ≥ 80 y.o and reported patient characteristics, including the Charlson comorbidity index and Hospital Frailty Risk Score. Readmission rates (hospital or rehabilitation unit) and mortality rates were calculated during a one-year follow-up period after the end of hospital stay.

The proportion of patients ≥ 80 y.o. in intermediate care units was 31% whereas it was 17% in ICU. Patients with greater comorbidities and severity were more frequently hospitalized in polyvalent intermediate care units (10% of them receiving acute organ support) compared to specialized intermediate care units. Admission to intermediate care units was associated with a 14% mortality rate during the stay, 28% at one year. Additionally, 58% of intermediate care units patients were rehospitalized within the year following discharge (6% in critical care units).

One-third of the patients hospitalized in the intermediate care units in France are aged 80 years or older.

Frailty increases vulnerability for adverse outcomes in older adults. Characterizing the prevalence and distribution of frailty can help guide healthcare service decision-making and policy.

This study evaluated the association between frailty and healthcare utilization and interactions by demographic characteristics.

Using electronic health records (2018-2022), we conducted a retrospective cohort study with 355,266 patients ≥65 years of age who had ≥2 ambulatory office visits in separate years in the 4-year baseline period (2018-2021). The Gilbert Frailty Index (GFI) was calculated (low vs. intermediate vs. high) using ICD-10 codes. One-year utilization outcomes in 2022 included high outpatient clinic utilizations (OCU), inpatient (IP), emergency department (ED), and nursing home (NH) admissions. Fully adjusted log-binomial regression models were calculated overall and by race (White vs. Black), age groups, and gender.

The sample was 74.5(±7.5) years of age, 57.7 % female, 89.2 % White, and 13.5 % categorized as GFI high. After adjustment for covariates, GFI high had the highest risk for all outcomes (RR=3.31 for IP; 2.77 for ED; 4.26 for NH; 1.60 for high OCU). We observed significant interactions by race, gender, and age for some outcomes. Effects of GFI high vs. low were larger for White (IP, ED, & high OCU), female patients (ED & high OCU), and younger patients (IP). Conversely, the effects of GFI high vs. low were strongest in older patients for ED, IP and high OCU.

Monitoring frailty and paying attention to patient's demographic characteristics is needed to best estimate associations between frailty and healthcare utilization.

This study evaluates the combined effects of frailty, anemia, and malnutrition on outcomes in spinal metastases patients.

We conducted a retrospective cohort study using the 2011-2022 NSQIP database. Adult patients undergoing spinal surgery for spinal metastases were identified using CPT and ICD codes and stratified based on Risk Analysis Index-revised (RAI-rev) frailty status; frail patients were subdivided based on anemia and malnutrition status. Our primary outcomes were extended hospital length of stay (LOS), 30-day adverse events (AEs), non-routine discharge (NRD), and 30-day mortality. For each outcome, we fitted four nested multivariable logistic regression models (RAI-rev + anemia + malnutrition, RAI-rev + anemia, RAI-rev + malnutrition, and RAI-rev alone) and compared the incremental discrimination of each model using receiver operating characteristic (ROC) analysis.

1530 patients were stratified accordingly: 355 Frail Alone, 540 Frail + Anemic, 85 Frail + Malnourished, 407 Frail + Anemic + Malnourished, and 143 Not Frail. RAI-rev and malnourishment were risk factors for extended LOS ((RAI-rev: aOR 1.04, 95% CI 1.01-1.08; malnourishment: aOR 1.98, 95% CI 1.44-2.73)) and mortality (RAI-rev: aOR: 1.07, 95% CI 1.03-1.11; malnourishment: aOR: 2.37, 95% CI 1.50-3.75). RAI-rev (aOR 1.02, 95% CI 1.00-1.03) and anemia (aOR 2.06, 95% CI 1.50-2.84) independently predicted AEs and malnourishment predicted NRD (aOR 1.56, 95% CI 1.15-2.13). On ROC analysis, RAI-rev + anemic + malnourished superiorly predicted extended LOS (p = 0.021), AEs (p = 0.035), and mortality (p = 0.023) compared to RAI-rev. RAI-rev + malnourished outperformed RAI-rev in predicting extended LOS (p = 0.035) and mortality (p = 0.020). RAI-rev + anemic outperformed RAI-rev in predicting AEs (p = 0.032).

Our study suggests that RAI-rev-defined frailty combined with anemia and malnutrition is a superior predictor of outcomes in spinal metastases patients.

Some East Asian (EA) guidelines recommend lower doses of direct oral anticoagulants (DOACs) for atrial fibrillation (AF) than in North America and Europe.

Investigate the association of immigration from EA with DOAC dosing and outcomes in AF.

Population-based cohort study using administrative databases of Ontario immigrants with AF aged ≥66 years who were dispensed DOAC prescriptions from 2012-2019. Birth country was classified as EA or not. We used multivariable logistic regression to assess the association of EA birth with DOAC dose and cause-specific hazards regression for the association of EA birth and DOAC dose with stroke/bleeding/death. Interaction between EA birth and DOAC dosing was studied for each outcome.

Among 14,421 immigrants, 3958 (27.4%) were born in EA. EA immigrants had lower odds of receiving full-dose DOACs versus non-EA immigrants (OR 0.64, 95%CI 0.58-0.69, p<0.001). EA birth was not associated with a composite of hospitalization for stroke/bleeding (HR 0.97, 95%CI 0.84-1.12, p= 0.67) nor hospitalization for stroke (HR 0.86, 95%CI 0.71-1.04, p= 0.13), but was associated with higher bleeding hazard (HR 1.15, 95%CI 1.02-1.30, p= 0.02) and lower mortality (HR 0.91, 95%CI 0.84-0.99, p= 0.04). There was no significant interaction between EA birth and DOAC dosing for stroke (p=0.41), bleeding (p=0.27), or death (p=0.33).

EA immigrants were less likely to receive full-dose DOACs and had a higher bleeding hazard, similar stroke hazard, and lower mortality risk than non-EA immigrants. There was no evidence that DOAC dosing had a differential treatment effect in EA immigrants.

Accurate in-hospital length of stay prediction is a vital quality metric for hospital leaders and health policy decision-makers. It assists with decision-making and informs hospital operations involving factors such as patient flow, elective cases, and human resources allocation, while also informing quality of care and risk considerations. The aim of the research reported in this paper is to use survival analysis to model General Internal Medicine (GIM) length of stay, and to use Shapley value to support interpretation of the resulting model. Survival analysis aims to predict the time until a specific event occurs. In our study, we predict the duration from patient admission to discharge to home, i.e., in-hospital length of stay. In addition to discussing the modeling results, we also talk about how survival analysis of hospital length of stay can be used to guide improvements in the efficiency of hospital operations and support the development of quality metrics.

The aim of this scoping review was to examine the scope and characteristics of the published literature related to the Electronic Frailty Index (eFI).

Scoping review.

Original studies related to the eFI in older adults.

Six databases were searched for articles published between March 2016 and August 2024: PubMed, Web of Science, Cochrane Library, Scopus, China National Knowledge Infrastructure (CNKI), and Wanfang Database. Data extracted included the publication year, country, sample size, data sources for developing an eFI, number of items included in the eFI, performance of the eFI, and application of the eFI.

Of the 424 articles initially retrieved, this scoping review included 50 studies for analysis. Thirty-nine (78%) of these studies were conducted after the year 2019. Moreover, we identified 8 distinct eFIs. Twelve studies assessed the performance of eFIs, whereas 30 studies used them. The eFIs covered 4 key domains: diseases, functional information, laboratory tests and measures, and symptoms and signs. The most common outcome examined was mortality. Furthermore, the eFIs were applied for diverse purposes, including exploring the relationship between frailty and health outcomes.

This scoping review revealed that eFIs can be developed using various electronic health care data sources, and they have been extensively employed for various population-level purposes. The observed associations between the eFIs, existing frailty assessment tools, and health outcomes highlight their utility in evaluating the care needs of an aging population.

Complete lead extraction is strongly recommended for managing cardiac implantable electronic device (CIED) infections. However, actual practices and associated patient outcomes in real-world settings are not well documented. This study aims to quantify use of lead extraction among Australian patients with CIED infections. In this retrospective cohort study, we analyzed linked hospital and mortality data from New South Wales (July 2008 to September 2022). We included patients aged ≥18 years diagnosed with CIED infections, identified using diagnosis codes T82.71 (from July 2017 onwards) and T82.7 with relevant supplementary codes prior to July 2017. We quantified the association between lead extraction and 1-year mortality using time-varying Cox proportional hazards regression models. We included 2,339 patients (mean age 72.5 years, 31.5% female) who were hospitalized with CIED infections, of which 24.0% (n = 561) underwent lead extraction within 30 days. The likelihood of lead extraction was higher among those with sepsis, endocarditis, Staphylococcus aureus infection, prior revision/replacement CIED procedures, and patients admitted to private hospitals. In contrast, older patients (aged 75+ years), female patients, and those with chronic kidney disease were less likely to undergo lead extraction. Lead extraction was associated with reduced 1-year mortality rate (adjusted-HR = 0.64, 95% CI: 0.51 to 0.81), with evidence of greater survival benefit in patients with sepsis and lesser benefit in older patients and females. In conclusion, utilization of lead extraction was limited among patients with CIED infections. Lead extraction was linked to significantly reduced mortality rate, highlighting the importance of improving adherence to recommended management for patients with CIED infections.

The global cancer burden is rapidly increasing, with 20 million new cases estimated in 2022. The world population aged ≥65 years is also increasing, projected to reach 15.9% by 2050, making cancer control for older patients urgent. Surgical resection is important for cancer treatment; however, predicting postoperative disability and mortality in older patients is crucial for surgical decision-making, considering the quality of life and care burden. Currently, no model directly predicts postoperative functional disability in this population.

We aimed to develop and validate machine-learning models to predict postoperative functional disability (≥5-point decrease in the Barthel Index) or in-hospital death in patients with cancer aged ≥ 65 years.

This retrospective cohort study included patients aged ≥65 years who underwent surgery for major cancers (lung, stomach, colorectal, liver, pancreatic, breast, or prostate cancer) between April 2016 and March 2023 in 70 Japanese hospitals across 6 regional groups. One group was randomly selected for external validation, while the remaining 5 groups were randomly divided into training (70%) and internal validation (30%) sets. Predictor variables were selected from 37 routinely available preoperative factors through electronic medical records (age, sex, income, comorbidities, laboratory values, and vital signs) using crude odds ratios (P<.1) and the least absolute shrinkage and selection operator method. We developed 6 machine-learning models, including category boosting (CatBoost), extreme gradient boosting (XGBoost), logistic regression, neural networks, random forest, and support vector machine. Model predictive performance was evaluated using the area under the receiver operating characteristic curve (AUC) with 95% CI. We used the Shapley additive explanations (SHAP) method to evaluate contribution to the predictive performance for each predictor variable.

This study included 33,355 patients in the training, 14,294 in the internal validation, and 6711 in the external validation sets. In the training set, 1406/33,355 (4.2%) patients experienced worse discharge. A total of 24 predictor variables were selected for the final models. CatBoost and XGBoost achieved the largest AUCs among the 6 models: 0.81 (95% CI 0.80-0.82) and 0.81 (95% CI 0.80-0.82), respectively. In the top 15 influential factors based on the mean absolute SHAP value, both models shared the same 14 factors such as dementia, age ≥85 years, and gastrointestinal cancer. The CatBoost model showed the largest AUCs in both internal (0.77, 95% CI 0.75-0.79) and external validation (0.72, 95% CI 0.68-0.75).

The CatBoost model demonstrated good performance in predicting postoperative outcomes for older patients with cancer using routinely available preoperative factors. The robustness of these findings was supported by the identical top influential factors between the CatBoost and XGBoost models. This model could support surgical decision-making while considering postoperative quality of life and care burden, with potential for implementation through electronic health records.

To analyse the concordance between theoretical and actual stratification of people living with HIV infection attending a pharmaceutical care outpatient clinic in a tertiary regional hospital.

Observational, retrospective, analytical, cross-sectional and single-centre study in people living with HIV infection. Study period: April 2024. Inclusion criteria: patients with HIV infection aged over 18 years who had been receiving active antiretroviral therapy (ART) for at least two years prior to inclusion. The 2022 version of the pharmaceutical care stratification model for people living with HIV infection was used. Reliability was evaluated from a qualitative perspective using Cohen's Kappa coefficient.

Of the 199 patients attended during the study period, 100 were consecutively selected, of whom 93 were ultimately stratified. Men accounted for 77.41% of the cohort, with a mean age of 47.81 ± 12.53 years. The obtained stratification percentages were: Priority 1: 7.52%; Priority 2: 26.88%; Priority 3: 65.59%. Quantitative analysis of concordance between the models yielded a Cohen Kappa value of K=0.866.

There is a good concordance between the distribution percentages of the theoretical stratification and the actual one obtained in our study.

To validate the Hospital Frailty Risk Score (HFRS) in Chinese hospital settings, describing how patients are allocated to frailty risk groups and how frailty risk is associated with length of stay (LoS) and hospital costs.

Retrospective observational study.

Forty-eight hospitals in Lvliang City, Shanxi Province, China.

Patients aged 75 years or older hospitalised between 1 January 2022 and 31 December 2023 (n = 34,731).

A logistic regression model examined the association between long length of stay (LoS) and frailty risk. A generalised linear model assessed the association between hospital costs and frailty risk. Subgroup analyses of age group, sex, and hospital tiers were conducted.

22.2% of patients were categorised as having zero risk, 62.4% as low risk, 15.3% as intermediate risk, and 0.08% as high risk. Compared to the zero risk group: for those with low risk, the probability of long LoS was 1.92 (95% CI 1.79-2.06) times higher and hospital costs were ¥1926 (95% CI 1655-2197) higher; for those with intermediate risk, the probability of long LoS was 2.7 (95% CI 2.49-2.96) times higher and hospital costs were ¥4284 (95% CI 3916-4653) higher; and for those with high risk, the probability of long LoS was 6.7 (95% CI 3.06-14.43) times higher and hospital costs were ¥16,613 (95% CI 12,827-20,399) higher. The explanatory power of the HFRS held across subgroups.

Compared to patients aged 75 + elsewhere, those in China had lower frailty risk scores, likely reflecting a younger age structure and recording of fewer diagnosis codes. Even so, the HFRS is a powerful predictor of long length of stay and hospital costs in China.

Nonvariceal upper gastrointestinal bleeding (NVUGIB) is a common cause of hospitalization in the United States, with approximately 400 000 admissions annually and a 5%-10% mortality rate. This study aimed to evaluate frailty's impact on NVUGIB outcomes.

We utilized the 2019 National Readmission Database (NRD) to identify adult patients (≥ 18 years) admitted with a principal diagnosis of NVUGIB using ICD-10-CM codes. NVUGIB hospitalizations were stratified by frailty using the hospital frailty risk score (HFRS) of 5 or more as the cut-off for frailty. Multivariate regression analyses were conducted to analyze the outcomes. STATA 14.2 was used for statistical testing.

Among 218 647 NVUGIB admissions, 99 892 (45.69%) were frail. Frail patients were older, more often female, and had higher comorbidity burdens. They showed significantly greater in-hospital mortality (adjusted odds ratio [aOR] 5.64, 95% CI 4.94-6.44; p < 0.001), acute kidney injury (5.85), respiratory failure (6.93), septic shock (40.94), hemorrhagic shock (2.64), vasopressor use (4.36), mechanical ventilation (6.04), and ICU admission (5.41). Although frail patients had higher odds of esophagogastroduodenoscopy (EGD) with intervention (1.04; p < 0.001), they were less likely to receive EGD within 24 h (0.75; p < 0.001). They also had higher odds of rebleeding (1.18; p < 0.001) and radioembolization (2.69; p < 0.001). Length of stay increased by 2.30 days, total charges rose by $28 518, discharge to rehabilitation was more frequent (3.12; p < 0.01), and 30-day readmission was higher (15.24% vs. 11.43%, HR 1.16; p < 0.001).

Frailty independently predicts worse clinical outcomes and increased resource use in NVUGIB. Recognizing frailty may improve risk stratification and guide more tailored management strategies for this high-risk population.

BackgroundAlthough artificial hip and knee arthroplasty has been widely used, the incidence of perioperative complications remains relatively high due to factors such as long operation time and large surgical incisions. However, the Hospital Frailty Risk Score (HFRS) clinical value for patients undergoing artificial hip and knee arthroplasty in China is not yet clear. This study aims to explore its clinical value in this population.ObjectiveTo explore predictive value of the HFRS in perioperative complications of artificial hip and knee arthroplasty in elderly patients.MethodsElderly patients who underwent artificial hip and knee arthroplasty in our hospital from March 2020 to March 2022 were selected as the study subjects. The patients were divided into the non-frail risk group (HFRS <5 points) and the frail risk group (HFRS ≥5 points) on the basis of the literature grading method. 5-factor modified frailty index (mFI-5) and Charlson Comorbidity Index (CCI) scores were assessed. General data including age, sex, ASA classification, preoperative course, and surgical time were collected through the electronic medical record system. The occurrence of postoperative deep venous thrombosis, periprosthetic infection, hematoma, anemia, and overall complications was recorded. Hospitalization days, surgical costs, and total treatment costs were also calculated for all patients.ResultsThere were no significant differences in age, sex, ASA classification, preoperative course, or surgical time between the two groups (p > 0.05). The frail risk group had significantly higher mFI-5 and CCI scores (p < 0.05). This group also had a higher incidence of deep venous thrombosis and overall complications (p < 0.05), but similar rates of periprosthetic infection, hematoma, and anemia (p > 0.05). ROC analysis showed HFRS had the highest predictive value for postoperative complications (AUC = 0.851) compared to mFI-5 (0.786) and CCI (0.739). Surgical costs were similar (p > 0.05), but the frail group had longer hospital stays and higher total treatment costs (p < 0.05).ConclusionHFRS has better predictive value for perioperative complications in elderly patients undergoing artificial hip and knee arthroplasty compared to mFI-5 and CCI scores, and it can be used for predicting perioperative complications in elderly patients with this surgery.

Background: Older patients with peripheral artery disease (PAD) encounter an increased risk of in-hospital mortality. Accurate risk scoring methods are crucial for assessing the likelihood of cardiovascular events in these patients. However, a comprehensive comparison of these scoring methods for predicting in-hospital mortality in PAD patients has not yet been conducted. Patients and methods: This study analyzed 173,075 patients hospitalized with PAD in the year 2020 from a German nationwide registry. We assessed five risk scores: the Elixhauser Comorbidity Index, the Charlson Comorbidity Index, the CHA2DS2-VA Score, the EuroSCORE, and the Hospital Frailty Risk Score (HFRS). The average patient age was 72 ± 10.94 years, with 36.82% female and 35.27% also diagnosed with diabetes mellitus. The overall in-hospital mortality rate was 2.68%. Mean scores were 7.12±6.55 for the Elixhauser Comorbidity Index, 2.66±1.72 for the Charlson Comorbidity Index, 3.85±1.43 for the CHA2DS2-VA Score, 8.96%±8.85% for the EuroSCORE, and 3.53±5 for the HFRS. The HFRS showed the highest predictive potential for in-hospital mortality with an area under the curve (AUC) of 0.86 (95% confidence interval (CI): 0.86-0.87) but had the worst calibration for high-risk patients. The CHA2DS2-VA Score had the lowest AUC 0.69 (95% CI: 0.68-0.70) but was the most consistent prediction model regarding calibration. Conclusions: HFRS was the most effective overall predictor of in-hospital mortality, but did not detect those patients with a very high risk of mortality. The CHA2DS2-VA Score was the most robust predictor of increasing score points but had the lowest sensitivity. Therefore, use of the HFRS combined with application of the CHA2DS2-VA Score appears to be most appropriate in identifying older PAD patients at risk of in-hospital mortality.

Providing equitable health care to rural stroke patients is challenging and associated with less intervention and poorer outcomes. We assessed how several distinct patient-related geographic classifications influenced stroke care and outcomes in Scotland, United Kingdom.

We conducted a population-level data-linkage study of ischemic stroke patients admitted to the hospital (2010-2018). Geographic classifications included 2 binary (urban versus rural; accessible versus remote) and 1 six-category classification encompassing both rurality and accessibility (large urban areas, other urban areas, accessible small towns, remote small towns, accessible rural areas, and remote rural areas). Process outcomes included achievement of a stroke care bundle and thrombolysis administration. Clinical outcomes included 30-day discharge from hospital care, 90-day home time, inpatient and 1-year all-cause mortality.

We included 42 917 ischemic stroke patients (35 766 urban and 7151 rural). Binary classifications of rurality or accessibility missed important differences in stroke care and outcomes revealed using 6-category classification. Using the latter, compared with large urban areas, patients in accessible rural areas were more likely to receive a complete stroke care bundle (adjusted odds ratio, 1.21 [95% CI, 1.12-1.31]); patients in remote rural areas were less likely (adjusted odds ratio, 0.85 [95% CI, 0.78-0.93]). Compared with large urban areas, 30-day discharge from hospital care was more likely for patients residing elsewhere (eg, remote rural areas adjusted subdistribution hazards ratio, 1.11 [95% CI, 1.05-1.17]); home time within 90 days was higher for other urban areas (adjusted incidence rate ratio, 1.05 [95% CI, 1.03-1.07]) and accessible rural areas (adjusted incidence rate ratio, 1.03 [95% CI, 1.01-1.06]); and 1-year mortality was less likely in other urban areas (adjusted hazard ratio, 0.93 [95% CI, 0.88-0.98]) and remote small towns (adjusted hazard ratio, 0.89 [95% CI, 0.80-0.99]).

When considering geographic disparities in stroke care and outcomes across Scotland, it is important to account for both home location and accessibility of care. Despite patients residing in remote rural areas being less likely to achieve a complete stroke care bundle, this did not translate into poorer outcomes.

The epidemiology of infective endocarditis (IE) is evolving, driven by an aging population and increased use of endovascular devices, and is associated with significant morbidity and mortality. This study aims to evaluate changes in microbiological trends and clinical outcomes in patients with IE over the past decade in Switzerland.

This nationwide cohort study analyzed in-hospital claims data from patients hospitalized with IE in Switzerland between 2012 and 2021. We assessed incidence rates per 100 000 hospitalizations, categorizing them by common pathogens. The outcomes included in-hospital and 6-month mortality, admission to the intensive care unit, and length of hospital stay.

Among 15 255 hospitalizations with IE, the annual number of cases increased from 1361 in 2012 to 1636 in 2021. The most frequently diagnosed pathogens were Staphylococcus aureus (increasing from 19.8% to 30.0%, Ptrend < .01) and Streptococcus species (from 17.6% to 24.4%, Ptrend < .01). Infective endocarditis caused by Staphylococcus aureus was associated with the highest in-hospital (19.9%) and 6-month mortality (30.3%), and intensive care unit admission rates (44.2%), with no relevant changes over time. The longest length of hospital stay was observed in hospitalizations with IE caused by Enterococcus species (mean 23.9 days) and S. aureus (23.8 days).

This nationwide cohort study showed an increase in IE hospitalizations from 2012 to 2021, primarily from S. aureus and Streptococcus species. Predominantly, S. aureus was associated with adverse outcomes that remained consistently high over time compared to other or unidentified pathogens.

Introduction: Frailty is increasingly recognized as a critical predictor of adverse outcomes in older adults, particularly those with cancer. However, the role of frailty-distinct from comorbidity burden-has not been fully characterized in older adults hospitalized with cholangiocarcinoma (CCA), a rare but aggressive malignancy with rising incidence in the aging population. Methodology: A retrospective cross-sectional analysis of the Nationwide Inpatient Sample (NIS) 2019-2022 was performed. Adult inpatients aged ≥ 65 with CCA-related ICD-10 codes were identified. Patients were stratified into frailty categories based on the Hospital Frailty Risk Score (HFRS). Multivariable regression models were used to assess associations with in-hospital mortality, length of stay (LOS), and hospital charges. Results: Among 18,785 hospitalizations, the in-hospital mortality rate was 7.18%. High frailty conferred an eight-fold increased risk of mortality, a 70% longer LOS, and 52% higher charges compared to low frailty. Elixhauser comorbidity scores were not significantly associated with outcomes. Discussion: These findings support the use of frailty screening to guide inpatient care planning and optimize outcomes in older adults with CCA.

During the 2023-2024 respiratory syncytial virus (RSV) season, vaccination was recommended for adults ≥60 years based on shared clinical decision-making with their healthcare providers. We examined RSV vaccine uptake and characteristics associated with uptake among age-eligible Kaiser Permanente Southern California (KPSC) patients. Our study cohort included all patients ≥60 years from September 23, 2023 (i.e., date RSV vaccination first became available at KPSC; N = 1,003,132) to April 9, 2024 (i.e., end of local RSV season). To identify sociodemographic and clinical characteristics associated with RSV vaccination, we used multivariable robust Poisson regression to estimate the adjusted relative risk (aRR) and 95 % CI. Overall, 7.6 % of patients were vaccinated for RSV. In multivariable regression analyses, those aged 70-79.9 years (aRR: 1.36; 95 % CI: 1.34-1.39) and aged ≥80 years (aRR: 1.35; 95 % CI: 1.32-1.38) were more likely to be vaccinated, compared with those aged 60-69.9 years. Compared with Non-Hispanic White patients, Asian (aRR: 0.95; 95 % CI: 0.93-0.97), Hispanic (aRR: 0.52; 95 % CI: 0.51-0.54), Non-Hispanic Black (aRR: 0.69; 95 % CI: 0.67-0.71), Pacific Islander (aRR: 0.91; 95 % CI: 0.84-0.98), and Native American or Alaska Native (aRR: 0.80; 95 % CI: 0.70-0.92) patients were less likely to be vaccinated. Those in higher neighborhood deprivation quartiles were less likely to be vaccinated (Q2: aRR: 0.86; 95 % CI: 0.85-0.88; Q3: aRR: 0.77; 95 % CI: 0.76-0.79; and Q4: aRR: 0.67; 95 % CI: 0.65-0.68), compared with those in the lowest deprivation quartile. We found low vaccination uptake and identified disparities in vaccination that might exacerbate existing disparities in RSV infection and severe RSV disease among certain populations. CDC's ACIP recently updated their recommendations for all adults 75+ years, and this might begin to address these disparities.

Cardiogenic shock (CS) is a common complication of acute coronary syndrome (ACS) and is associated with significant morbidity and mortality. Revascularization has been shown to reduce mortality in ACS-CS. Patients with cancer are at high risk of ACS and CS. However, patients with cancer are often undertreated with invasive procedures and outcomes of patients with cancer and ACS-CS have not been thoroughly characterized.

Patients with ACS-CS from 2014 to 2020 with and without cancer were identified using the National Readmission Database (NRD). Primary outcome was death at 90-days. Secondary outcomes were 90-day cardiovascular (CV) and bleeding readmissions, and index hospitalization major bleeding and thrombotic complications. Patients with cancer were compared to patients without cancer using multivariable logistic and Cox proportional hazards regression. Temporal trends in revascularization among patients with and without cancer were examined. Effect of revascularization among patients with cancer and ACS-CS was assessed using propensity score weighting (PSW).

A total of 140,205 patients were identified, of whom 6118 (4.4 %) with cancer were identified. Patients with cancer were less likely to undergo percutaneous coronary intervention (45.5 % vs 53.5 %) or be managed with mechanical circulatory support (36.6 % vs 46.0 %). After multivariable logistic regression, there was no difference in primary outcome (adjusted OR 0.98, 95 % CI 0.92-1.06) but patients with cancer had higher risk of 90-day CV (HR 1.11, 95 % CI 1.01-1.22) and bleeding readmissions (HR 1.39, 95 % CI 1.10-1.76). Among patients with cancer and ACS-CS, revascularization was associated with lower primary outcome (OR 0.54, 95 % CI 0.50-0.58) and 90-day CV readmission (HR 0.68, 95 % CI 0.59-0.77) after PSW.

Among patients with ACS-CS, patients with cancer have similar 90-day death but higher risk of 90-day CV and bleeding readmissions. Additionally, revascularization was associated with improved outcomes among patients with cancer and ACS-CS. Further studies are needed to optimize patient selection for invasive management among patients with cancer.

Guidelines recommend combining macrolides with β-lactam antibiotics for moderate-to-high severity community-acquired pneumonia (CAP); however, macrolides pose risks of adverse events and anti-microbial resistance.

We analyzed electronic health data from 8872 adults hospitalized with CAP in Oxfordshire, UK (2016-2024), initially treated with amoxicillin or co-amoxiclav. Using inverse probability treatment weighting, we examined the effects of adjunctive macrolides on 30-day all-cause mortality, time to hospital discharge, and changes in Sequential Organ Failure Assessment (SOFA) score.

There was no evidence of an association between adjunctive macrolides and 30-day mortality (marginal odds ratio 1.05 [95% CI 0.75-1.47] for amoxicillin with vs. without macrolide; 1.12 [0.93-1.34] for co-amoxiclav with vs. without macrolide); and no evidence of a difference in time to discharge (restricted mean days lost +1.76 days [-1.66, +5.19] for amoxicillin, +0.44 days [-1.63, +2.51] for co-amoxiclav). Macrolide use was not associated with SOFA score decreases. Results were consistent across severity sub-groups and sensitivity analyses with missing covariates imputed.

At a population level, the addition of macrolides was not associated with improved clinical outcomes for patients with CAP. The potential benefits of additional macrolides should be weighed against the risks of adverse effects and anti-microbial resistance.

The Rib Fracture Frailty (RFF) Index is an internally validated machine learning-based risk assessment tool for adult patients with rib fractures that requires minimal provider entry. Existing frailty risk scores have yet to undergo head-to-head performance comparison with age, a widely used proxy for frailty in clinical practice. Our aim was to externally validate the RFF Index in a small-scale implementation feasibility study.

Prospective observational cohort study conducted across five ACS COT-verified trauma centers. Participants included ≥18-year-old adults presenting January 1, 2021, to December 31, 2021, with traumatic rib fractures. The primary outcome was a composite outcome score comprised of three clinical factors: hospitalization ≥5 days, discharge disposition, and inpatient mortality. Proportional odds logistic regression evaluated associations of age model or RFF Index score model with composite outcome scores. Models were compared using standard discrimination and calibration metrics. Secondary analysis delineated predictive performance among patients with lower (Injury Severity Score < 15) and higher Injury Severity Score ≥ 15) injury burden.

Of 849 participants, 546 (64%) were male and median age was 62 years (interquartile range, 46-76 years). A one-point increase in RFF score was associated with 6% increased odds of higher composite outcome score (odds ratio [OR], 1.06; 95% confidence interval [95% CI], 1.04-1.08), while a 1-year increase in age did not show statistically significant association (OR, 1.10; 95% CI, 0.75-1.61). The RFF score had higher discrimination (OR, 0.09; 95% CI, 0.08-0.11 vs. OR, 0.06; 95% CI, 0.04-0.08; p = 0.04) and calibration performance compared with age, but on secondary analysis, higher predictive performance was limited to patients with lower injury burden. Both RFF Index and age had poor calibration for predicting patients discharged to home after hospitalization ≥5 days.

This prospective external validation study found RFF Index may be a better alternative to age for predicting adverse outcomes among patients with traumatic rib fractures and lower overall injury burden. Staged implementation studies in accordance with clinical prediction model implementation guidelines are required to evaluate the RFF Index's clinical efficacy and guide potential adoption.

Prognostic; Level II.

Altered mental status (AMS) is a common cause of hospitalization among older adults, with a wide range of potential etiologies. However, the diagnostic and therapeutic yield of routine laboratory testing in such patients is unknown.

In a retrospective cohort of inpatient hospital admissions to a large academic medical center from 2017 to 2022 of patients 65 years and older for whom the admitting diagnosis was AMS, we assessed laboratory testing for thyroid stimulating hormone (TSH), syphilis, vitamin B12, folate, vitamin C, vitamin D, zinc, niacin, and thiamine. We calculated the frequency of testing, rate of abnormal results, and rate of follow-up treatment.

Of the 3169 patients, 2312 (73 %) received at least one designated lab, and overall, 12 % of labs were abnormal. Labs varied in frequency of use (0.2 % for niacin-66 % for TSH) and rate of abnormality (0 % for niacin-71 % for zinc). 16 % of abnormal index labs led to a new prescription at discharge. The most common tests - TSH, folate, and B12- were of relatively low diagnostic and therapeutic utility. Tests that were less common-zinc, vitamin D, and vitamin C-were more commonly abnormal. 3.8 % of patients tested for syphilis had abnormal results, and 72 % of patients with an abnormal result received treatment with penicillin during the index hospitalization.

These analyses suggest that commonly obtained labs in the workup of AMS have varied diagnostic and therapeutic utility. The contribution of observed laboratory abnormalities to a patients' AMS warrants further study to improve the delivery of high-value care.

Frailty has been associated with a greater risk of complications and higher treatment costs for various medical conditions and surgical procedures. The Modified Frailty Index, which analyzes five or six medical comorbidities, helps grade the severity of a patient's frailty. Patients with frailty, as recognized by this index, are more likely to face adverse medical and surgical events after total shoulder arthroplasty (TSA). However, these modified indices often do not consider less common medical conditions that contribute to frailty. As such, we believe that patients may be more readily misdiagnosed as not having frailty. A more comprehensive frailty score that more accurately recognizes frailty in a wider patient population is necessary.

After analyzing for any possible differences due to confounding variables such as age, gender, socioeconomic variables, and insurance provider, we asked: (1) Was frailty, defined as a score of ≥ 5 on the Hospital Frailty Risk Score (HFRS), associated with a higher risk of reoperation or readmission within 30 days of primary TSA? (2) Was frailty associated with an increased risk of major medical or surgical complications after TSA? (3) Was frailty associated with higher hospital costs (assessed by insurance charge-to-cost ratio per admission) and length of stay for patients after TSA?

This study examined the Nationwide Readmissions Database, which includes patients from 28 states, representing 60% of all US residents and 60% of all US hospitalizations. We identified adult patients who were discharged after both anatomic and reverse TSA for primary osteoarthritis between January and November of 2017 to 2019 (patients who underwent TSA in December of each year were excluded). The HFRS was calculated for each patient based on 109 differently weighted ICD-10 Clinical Modification codes as validated in previous studies. Patients with an HFRS of ≥ 5 were considered as having frailty. Of the 107,774 patients who underwent TSA and were recorded in this database, 15% (16,210) were classified as patients with frailty. Patients over age 65 years comprised a larger portion of patients with frailty than patients without frailty (81% [13,130 of 16,210] of patients with frailty versus 74% [67,757 of 91,564] of patients without frailty; p < 0.01). Women comprised a larger portion of patients with frailty than patients without frailty (62% [10,050 of 16,210] women with frailty versus 53% [48,528 of 91,564] women without frailty; p < 0.01). Patients paying with Medicare comprised a larger portion of patients with frailty than patients without frailty (80% [12,968 of 16,210] Medicare payers with frailty versus 72% [65,926 of 91,564] Medicare payers without frailty; p < 0.01). We used the Student t-test to compare demographics and complication risk. After analysis of these confounders and controlling for them, we used multivariate logistic regression to analyze 30-day readmissions and negative binomial regression to analyze length of stay and hospital costs (as estimated by insurance charge-to-cost ratios per patient admission). Length of stay was expressed as an incidence rate ratio (IRR) because it was recorded and analyzed as a continuous variable. The Student t-test was used to compare demographics and risk of major surgical and medical complications of similar severity.

After controlling for confounding variables such as age, gender, socioeconomic status, and insurance provider, we found that frailty was associated with increased odds of reoperation within 30 days (OR 1.61 [95% CI 1.22 to 2.09]; p < 0.001) and increased 30-day readmissions (OR 1.79 [95% CI 1.63 to 1.97]; p < 0.001). We also found that frailty was associated with higher 30-day major surgical complication risk (0.4% [70 of 16,210] versus 0.3% [266 of 91,564]; p < 0.01) and 30-day major medical complication risk (2.6% [421 of 16,210] versus 1.1% [1007 of 91,564]; p < 0.01). We also found that frailty was associated with greater hospitalization costs (IRR 1.09 [95% CI 1.09 to 1.10]; p < 0.001) and longer lengths of hospital stay (IRR 1.46 [95% CI 1.44 to 1.47]; p < 0.001).

Frailty, as measured by the HFRS, is associated with increased postoperative events and estimated hospitalizations costs after TSA. The HFRS is derived from routinely collected administrative data and could help clinicians quickly identify patients at risk of complications without increased cost. Once patients with frailty are identified, clinicians may be able to provide additional counseling regarding patients' increased risk for postoperative complications and costs. An automatically calculated, robust scoring tool such as the HFRS can also aid clinicians in operative decision-making, as patients with severe frailty may be advised against undergoing TSA if the procedure is not absolutely necessary.

Level III, therapeutic study.

The frailty index, based on laboratory assessments, helps identify individuals at risk for adverse health outcomes. However, its relationship with overall mortality in acute pancreatitis patients in ICUs remains unclear. This study aims to investigate the association between the frailty index and all-cause mortality and assess its prognostic value for these patients.

We carried out a retrospective observational investigation utilizing data from the Medical Information Mart for Intensive Care IV (MIMIC-IV 2.2) database. Extract data from the database for all ICU patients (first-time ICU admissions, age ≥ 18 years) who meet the diagnostic criteria for acute pancreatitis. The frailty index derived from laboratory tests (FI-lab) encompassed three vital sign indicators and 30 laboratory test indicators. Patients were categorized into four groups based on quartiles of the FI-lab score. To assess the differences in 28-day all-cause mortality among these groups, we employed Kaplan-Meier analysis, whereas the relationship between FI-lab scores and 28-day mortality was explored through Cox proportional hazards analysis. In addition, we applied Harrell's C statistic, Integrated Discrimination Improvement (IDI), and Net Reclassification Improvement (NRI) to assess the additional predictive capability of FI-lab scores compare to traditional disease severity metrics.

The study included a total of 741 patients (all age ≥ 18 years, 19.84% age > 75 years, 41.16% Female). The Kaplan-Meier analysis demonstrated that individuals with elevated FI-lab scores exhibited a significantly heightened risk of all-cause mortality (log-rank p < 0.0001). The multivariate Cox regression analysis suggested that treating FI-lab as a continuous variable (per 0.01 increment) was linked to an increased risk of 28-day all-cause mortality [hazard ratio (HR) 1.072, 95% confidence interval (CI) (1.055-1.089), p < 0.001]. Moreover, when FI-lab was analyzed as a categorical variable, patients in the fourth quartile of FI-lab had a notably greater risk of 28-day all-cause mortality in comparison to those in the first quartile [HR 9.933, 95% CI (4.676-21.104), p < 0.001]. Additionally, the integration of FI-lab scores with conventional disease severity scores improved the predictive performance for 28-day mortality.

In patients in the ICU who have been diagnosed with acute pancreatitis, the FI-lab score functions as a reliable indicator of short-term mortality. Early detection of patients at high risk for acute pancreatitis through the implementation of the FI-lab score, along with prompt interventions, is essential for enhancing these individuals' prognoses.

A poor prognosis within 1 year of discharge is important when making decisions affecting postoperative geriatric inpatients. Comprehensive geriatric assessment (CGA) plays an important role in guiding holistic assessment-based interventions. However, current prognostic models derived from CGA and clinical data are limited and have unsatisfactory performance. We aimed to develop an accurate 1-year mortality prediction model for patients discharged from the geriatric ward using CGA and clinical data.

This longitudinal cohort study analysed data from 816 consecutively assessed geriatric patients between January 1, 2018 and December 31, 2019. Models were constructed using Cox proportional hazards regression and their validity was assessed by analysing discrimination, calibration, and decision curves. The robustness of the model was determined using sensitivity analysis. A nomogram was developed to predict the 1-year probability of mortality, and the model was validated using C-statistics, Brier scores, and calibration curves.

During 644 patient-years of follow-up, 57 (11·7%) patients died. Clinical variables included in the final prediction model were activities of daily living, serum albumin level, Charlson Comorbidity Index, FRAIL scale, and Mini-Nutrition Assessment-Short Form scores. A C-statistic value of 0·911, a Brier score of 0·058, and a calibration curve validated the model.

Our risk stratification model can accurately predict prospective mortality risk among patients discharged from the geriatric ward. The functionality of this tool facilitates objective palliative care.

Background/objectives: Depression is a common complication of cancer and is associated with distress and reduced participation in medical care. The prevalence is still uncertain in advanced cancer due to methodological problems. Our aim was to study depression in the last year of life and related variables. Methods: We used an administrative database and analyzed clinically verified diagnoses of depression during the last year of life for 27,343 persons (nursing home residents excluded) and related the data to age, sex, socioeconomic status on an area level (Mosaic system), and frailty risk as calculated by the Hospital Frailty Risk Score (HFRS). T-tests, chi-2 tests, and binary logistic regression models were used. Results: During the last year of life, a clinical diagnosis of depression was found in 1168/27,343 (4.3%) cases and more frequently seen in women (4.8% vs. 3.8%, p = 0.001), in the elderly aged 80 years or more, p = 0.03, and especially in persons with a frailty risk according to the HFRS, with rates of 3.3%, 5.3% and 7.8% in the low-risk, intermediate and high-risk groups, respectively (p < 0.001), whereas no differences were found based on socioeconomic status. In a multiple logistic regression model, being female (aOR 1.30, 95% CI 1.16-1.46) or having an intermediate (1.66, 1.46-1.88) or high frailty risk (2.57, 2.10-3.14) retained the predictive value (p < 0.001, respectively). Conclusions: Depression is more common in women and, above all, in people with multimorbidity. Depression affects the amount of health care needed, including the need for psychiatric care. Therefore, it should be included in clinical decision-making, especially as depression is associated with poorer prognosis in cancer.