Hospital Readmission Research Articles

Observation-first versus angioembolization-first approach in stable patients with blunt liver trauma: A WTA multicenter study.

Prior studies evaluating observation versus angioembolization (AE) for blunt liver injuries (BLT) with contrast extravasation (CE) on computed tomography imaging have yielded inconsistent conclusions, primarily due to limitations in single-center and/or retrospective study design. Therefore, this multicenter study aims to compare an observation versus AE-first approach for BLT, hypothesizing decreased liver-related complications (LRCs) with observation. We conducted a post hoc analysis of a multicenter, prospective observational study (2019-2021) across 23 centers. Adult patients with BLT + CE undergoing observation or AE within 8 hours of arrival were included. The primary outcome was LRCs, defined as perihepatic fluid collection, bile leak/biloma, pseudoaneurysm, hepatic necrosis, and/or hepatic abscess. A multivariable logistic regression analysis was used to evaluate risk factors associated with LRCs. From 128 patients presenting with BLT + CE on imaging, 71 (55.5%) underwent observation-first and 57 (45.5%) AE-first management. Both groups were comparable in age, vitals, mechanism of injury, and shock index (all p > 0.05), however the AE group had increased frequency of American Association for the Surgery of Trauma Grade IV injuries (51.0% vs. 22.0%, p = 0.002). The AE cohort demonstrated increased rates of in-hospital LRCs (36.8% vs. 12.7%, p = 0.038), emergency department representation (25.0% vs. 10.0%, p = 0.025), and hospital readmission for LRCs (12.3% vs. 1.4%, p = 0.012). However, the two cohorts had similar mortality rates (5.7% vs. 5.3%, p = 0.912). After adjusting for age, ISS, and grade of liver injury, an AE-first approach had a similar associated risk of LRCs compared with observation-first management (odds ratio, 1.949; 95% confidence interval, 0.673-5.643; p = 0.219). Patients with blunt liver injury and CE undergoing an observation-first approach were associated with a similar adjusted risk of LRCs and rate of mortality compared with AE-first approach. Overall, this calls for reevaluation of the role of routine AE in blunt liver trauma patients with CE. Future prospective randomized trials are needed to confirm these findings. Therapeutic/Care Management, Level IV.

Effects of the Strong Hearts program at two years post program completion.

This is a follow-up to the original published article, Effects of the Strong Hearts Program after a Major Cardiovascular Event in Patients with Cardiovascular Disease. This study evaluated the long-term efficacy of the Strong Hearts program up to 2 years after program completion. All study participants who initially completed the Strong Hearts program between 2020 and 2021 (n=128) were contacted at 12months and 24months following the date of program completion. A phone survey was conducted to see if any significant post-cardiovascular events or readmissions to the hospital occurred, and self-reported dates of any occurrences were recorded. Hospital readmissions and cardiac-related procedures were cross-referenced with the hospital's electronic medical record. A chi-square goodness-of-fit analysis was utilized to compare the observed rates of categorical outcomes vs. expected rates yielded from the empirical literature. The rate of all-cause readmission at 6months post-program completion was 2/120 (1.7 %), compared to the expected rate of 50 %, χ2(1) = 112.13, p<0.001. The readmission rate at 1 year post-program completion was 17/120 (14.2 %), vs. the expected rate of 45 %, χ2(1) = 46.09, p<0.001, and at 2 years post-program completion, the readmission rate was 24/120 (20.0 %) compared to the expected rate of 53.8 %, χ2(1) = 56.43, p<0.001. Ten participants (8.3 %) had a subsequent cardiac procedure within 2 years of completing the program, including two requiring percutaneous coronary intervention (1.7 %) and eight requiring coronary artery bypass grafting (CABG, 6.7 %), compared to the expected rates of 13.4 and 57.74 %, χ2(1)=153.08, p<0.001, respectively. Mortality at 2 years post-program completion was 2/128 (1.6 %), compared to 23.4 %, χ2(1)=34.13, p<0.001. Efficacy of the Strong Hearts program continued at 6months, 1 year, and 2 years post-program completion in terms of all-cause readmission, subsequent cardiac event, and all-cause mortality.

Sex differences in cardiovascular-related hospital readmissions, adverse events and interventions within 1 year after ST-elevation myocardial infarction

Abstract Introduction Reducing cardiovascular (CV)-related hospital readmissions as well as adverse events following ST- elevation myocardial infarction (STEMI) is a critical goal to improve outcomes as well as quality of life and reduce healthcare costs. We aimed to study the rates of CV-related readmissions, adverse events and interventions after STEMI in women and men. Methods We included STEMI patients from the Acute Myocardial Infarction in Switzerland (AMIS) Plus registry, who underwent percutaneous coronary intervention (PCI) between 2013 and 2022 and participated in a telephone-based follow-up (FU) interview 1-year after hospital admission. Patients were asked if they had hospital readmissions (if yes: planned/emergency/both) during FU for any CV reason, if they suffered a reinfarction or stroke and if they had any or several of the following interventions: PCI, coronary artery bypass graft, pacemaker and/or defibrillator implantation. These self-reported data were analysed using descriptive statistics and logistic regression models were used to study the relationship between patient characteristics and hospital readmissions. Results Of 4388 PCI-treated STEMI patients contacted for FU, 275 (6.3%) were unreachable, 118 (2.7%) died, and 223 (5.1%) had no data on readmissions; therefore 3772 patients (78.4% men, 21.6% women) were analysed. Women were older (mean (SD) age at event: 68.4 (12.0) vs. 62.5 (11.5) years) while the Charlson Comorbidity Index (CCI) was similar (CCI&amp;gt;1: 14.0% vs. 12.1%, n.s.). The mean rate of patients readmitted for CV reasons was 22.1%; 20.4% for women and 22.6% for men (p=0.198). Overall, 8.8% had at least one emergency and 13.9% at least one planned readmission. The occurrence of a planned readmission was significantly lower in women (11.1% vs. 14.7%, p=0.008). Patients with a readmission had during the index hospitalisation higher rates of in-hospital complications (18% vs. 14%), heart failure (NYHA III+IV) (2.2% vs. 0.8%), diabetes (18% vs. 14%) and peripheral arterial disease (3.9% vs. 2.5%). A multivariable adjusted model that included these factors together with age and sex identified heart failure (OR: 2.5, CI 1.34-4.66, p=0.004) and in-hospital complications (OR:1.4, CI 1.12-1.70, p=0.003) as independent predictors of hospital readmission. The rates of the analysed adverse events and interventions were similar between sexes except that women had less often a PCI during the FU period (13.2% vs. 16.6%, p=0.026). Conclusion Over the last 10 years, on average 1 in 5 patients had at least one CV-related readmission within 1 year after PCI-treated STEMI, while no overall sex-difference was found. Heart failure and in-hospital complications were independent predictors of readmission. Women had less often planned hospital readmissions and additional PCIs.

Predicting hospital readmission in multimorbid patients with the use of AI: A systematic review

Abstract Background Multimorbid patients are at higher risk of hospital readmission due to the complex nature of their conditions. Identifying those who may be at particularly high risk would allow us to intervene early and potentially delay or prevent such readmissions occurring, thus reducing healthcare costs. We conducted a systematic review investigating the use of machine learning models in predicting 30-days unplanned hospital readmission of multimorbid patients. Methods This review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Guidelines, and was registered with PROSPERO (CRD42022373937). We searched MEDLINE, Embase, Web of Science and Cumulative Index to Nursing and Allied Health Literature (CINAHL). Included studies developed an AI model for prediction of 30-days hospital readmission for adult patients with two or more health conditions. The CHARM and PROBAST checklists for data extraction and bias assessment were used. The quality of included studies was assessed with the CASP checklist. Results Eighteen papers were eligible for inclusion. A total of 669 predictors were reported with an average of 37 used per model. Predictors were classified as modifiable and non-modifiable with the most common modifiable predictors being hospital length of stay, hypertension, anaemia and obesity. Average sensitivity and specificity of the models was reported to be 72% in 13 studies and 79.2 in 11 studies, respectively. Area under the curve (AUC) was reported in 13 studies, five of which were considered to have good discrimination power (AUC&amp;gt;0.8). Conclusions Machine learning models are capable of accurately predicting 30-days hospital readmission of multimorbid patients. Identifying modifiable predictors with highest weight allows for better planning and resource allocation to potentially reduce the risk of 30-days readmissions. An important area for future work would be the implementation of these high performance models in practice. Key messages • Hospital readmissions are preventable and identifying those at higher risk allows us to intervene early. • Machine learning models are capable of predicting 30-days readmission of multimorbid patients.

Explainable machine learning and multi-modal data for predicting readmission in patients with heart failure

Abstract Background Cardiovascular diseases (CVDs) are among the leading causes of mortality and morbidity globally, with an estimated 1 million hospital admissions for CVD in England in 2019/20, leading to 5.5 million bed days. In addition, patients with CVDs have a notably high rate of hospital readmission, with approximately one in four patients experiencing heart failure (HF) being readmitted within one month of discharge. We explored whether machine learning models trained on electrocardiogram (ECG) and patient electronic health records (EHRs) can support decision-making and risk management and ultimately improve health outcomes for HF patients. Purpose The project aims to develop a machine learning model to predict health outcomes for HF patients. To test the hypothesis, we trained and tested an explainable machine learning model to predict the risk of mortality and hospital readmission rate for HF patients. Methods We used EHR data and tabulated ECG records to train an XGBoost model to predict the risk of 30-day mortality and 30-day hospital readmission for HF patients. EHR data from a cohort of 2,868 patients with their ECG records were used for model development. We extracted a total of 78 features from the ECG data, such as heart rate variability (HRV), P-wave durations, and QT intervals. These ECG features were combined with coded and free-text EHR data (e.g., demographic information, diagnosis, medication history, and lab results) and used as tabular inputs to the XGBoost model. Of the 2,868 patients, an internal set of 574 patients stratified by age, sex, and health outcomes (30-day mortality and 30-day hospital readmission) were held out for testing. Results Among 2,868 HF patients with 10-year follow-up, 1065 patients were reported for mortality or hospital readmission within 30 days of discharge. When the machine learning model was trained on ECG data in addition to EHR data, the model was able to predict patient mortality and hospital readmission rate in the test set with an area under the curve (AUC) of 0.91 and 0.70, respectively. For mortality prediction, the model achieved a sensitivity and specificity of 0.81 and 0.82, respectively, when employing an operating point with minimum difference between the sensitivity and specificity. When the threshold was adjusted to favor sensitivity at 0.91, the model specificity decreased to 0.74. The machine learning model also identified high sensitive troponin levels, QT dispersion, and lactate dehydrogenase levels as features of high importance for predicting the outcomes for HF patients. Conclusions Our developed machine learning model was able to predict mortality and readmission risks in HF patients using multi-modal data. Upon further validation, the machine learning model has the potential to be tested for supporting clinical decision-making and risk management for HF patients.ROC CurveFeature Importance

Outcomes of bariatric surgery in obese patients with heart failure:a meta-analysis

Abstract Background Patients with heart failure possess an increased risk for adverse outcomes with noncardiac surgery (1). While bariatric surgery is frequently performed in patients with obesity, there remains a limited understanding of the impact of bariatric surgery in obese patients with heart failure. Purpose The purpose of this study was to compare outcomes of bariatric surgery versus nonsurgical management in obese patients with heart failure. Methods We searched PubMed, EMBASE, and the Cochrane Library, through February 2024, for studies evaluating outcomes in obese patients with heart failure who underwent bariatric surgery compared to nonsurgical management. Outcomes assessed were postoperative atrial fibrillation, all-cause mortality, and hospital readmission. We used a fixed-effect model to calculate hazard ratios (HR) with 95% confidence intervals (CI) in R studio for outcomes assessed. In outcomes where significant heterogeneity was found (P&amp;lt; 0.05 and I2 &amp;gt; 60%), a random effects model was used. Results A total of 3 studies were identified, consisting of 260,186 patients. Compared to nonsurgical management, bariatric surgery was associated with a significant reduction in postoperative atrial fibrillation (HR 0.72; 95% CI: 0.62-0.84), all-cause mortality (HR 0.50; 95%CI 0.35-0.72), and hospital readmission (HR 0.73; 95% CI 0.69-0.78) in obese patients with heart failure. Conclusion Our study suggests that bariatric surgery significantly reduces post-operative atrial fibrillation, mortality, and hospital readmission among obese patients with heart failure.Our findings demonstrate that bariatric surgery should be considered as a viable intervention in obese patients with heart failure. Further studies are warranted to confirm our findings.Forest Plots of Outcomes Assessed

SINAVE’s quality: completeness for Meningococcal Disease – Northern Portugal, 2020-2022

Abstract Due to Meningococcal’s Disease (MD) severity and impact in public health, in Portugal it is mandatory to notify the suspicious cases to implement effective control measures. MD cases are notified in the National Surveillance System (SINAVE), which triggers epidemiological investigation, risk assessment and community intervention. The quality of SINAVE is defined by various attributes, being their evaluation crucial to improve and guarantee quality standards. Our goal is to evaluate the external and internal completeness of SINAVE for MD in northern Portugal from 2020 to 2022. We have conducted a cross-sectional study, using MD cases from 2020 to 2022. External Completeness was estimated using a two-source capture-recapture method, with data from SINAVE and Diagnostic-Related Group (DRG) cases. Hospital readmissions’, duplicates and cases from other regions were excluded. Internal completeness of SINAVE was accessed for each case and for each non-mandatory variable. For external completeness (EC) analysis, 21 of the 23 DRG cases were eligible for matching. Out of 31 SINAVE confirmed cases, 20 were eligible for matching. EC of SINAVE was 66,7%. For internal completeness (IC) analysis, we excluded 7 cases that did not meet the criteria for inclusion. The mean IC was 73,5% (min 38,5%, max 85,7%) when analysing by case. When assessing each of the 30 non-mandatory variables of the reports, 7 (23,3%) had an IC of 100% and 13 (43,3%) had an IC of 0%, the mean value was 49,7%. SINAVE assessment, as a routine, is crucial to identify the need for improvement. Completeness is fundamental to ensure an effective public health response. Our results confirm under-reporting and incomplete report of MD. There is a need to strengthen the improvement of data quality of SINAVE. Future studies may be important to estimate true incidence of MD and compare the results for other diseases in order to improve public health actions. Key messages • Meningococcal disease requires timely public health intervention. • valuation of the surveillance system is crucial, with completeness playing an important role for data quality and prompt response.

Healthcare utilization following acute myocardial infarction findings from RECORD MI registry

Abstract Background As therapeutic options and epidemiology have evolved rapidly, the contemporary healthcare utilization following acute myocardial infarction (MI) is not well known. Methods All patients admitted with MI between 01/2015 and 12/2021 in the Baylor Scott &amp; White health system were studied. Patient characteristics and outcomes including hospital readmissions, cardiovascular (CV)-related hospital readmissions, emergency department (ED) encounters, and outpatient visits were studied. Results Of 6804 patients, 6556 were discharged alive. Median age was 69 years, 60% were male, and 77% had non-ST elevation MI (NSTEMI); 1172 (22%) had an LVEF &amp;lt;40%, 493 (7.5%) were revascularized within 3 months of discharge, and 1090 (17%) had multivessel disease. The number of unique patients with first hospital readmission within 30-days, 3-months, and 12-months were 844 (13%), 1372 (21%) and 2306 (35%), respectively, with a higher risk in patients with NSTEMI, prior heart failure (HF), new HF, and LVEF &amp;lt;40%. ED visits at 12 months for any cause were 2401 (37%) and for CV cause were 1321 (20%), with a higher risk in patients with prior HF. Patients with at least 1 primary care visit within 12 months of discharge were captured for 4102 (63%), CV specialty visits for 5009 (76%), and non-CV visits for 3860 patients (59%), with similar distribution across subgroups (Table). Conclusions Post-MI patients had a high risk of readmissions, and ED and outpatient visits, especially amongst those with a prior or new HF diagnosis.

Selenium, selenoprotein P and autoantibodies to selenium transport proteins in Swedish heart failure patients - a pilot study in preparation for a randomized supplementation trial

Abstract Background Severe selenium (Se) deficiency, as in Keshan disease, is associated with a fatal form of heart failure (HF), preventable and reversible with Se supplementation. Recent studies have identified Se deficiency as highly prevalent, up to 70%, among patients with HF, and associated with a poorer prognosis. Observational data suggest that Se concentrations &amp;lt;100 μg/L in HF patients and selenoprotein P (SELENOP) concentrations &amp;lt;4.1 mg/L are associated with increased mortality and hospital readmissions. Further, in recent studies, natural autoantibodies (aAb) towards SELENOP have been detected with the potential to disrupt transportation mechanisms. While the evidence does not yet support Se supplementation for HF patients in clinical practice, it does justify the initiation of large, well-designed randomized controlled trials (RCTs). Purpose To assess and confirm the previously reported high prevalence of Se deficiency, measured by both Se and SELENOP concentrations in HF patients and exploring the prevalence of aAb to SELENOP. This will provide a rationale for further, adequately powered and designed, studies of Se supplementation in HF patients. Methods A total of 527 blood samples were obtained from a nationwide Swedish HF biobank, sourced from various hospitals. In those samples; serum Se concentrations in 455 samples using mass spectrometry, SELENOP concentrations in 520 samples using an immunoassay, and prevalence of aAb to SELENOP in 513 samples using an immunoluminometric assay were analyzed. In addition, SELENOP concentrations in 320 HF patients from a Swedish single-center study were analysed. Results The study population had a mean age of 70.3 (±11.8) years (30.5% women). Prevalence of Se deficiency was higher than previously reported. In the national HF registry, the median Se concentration was 75 µg/L and Se concentrations below 100 μg/L were found in 426 (93%) samples. SELENOP concentrations had a median of 3.5 mg/L, corresponding to ~80 μg/L Se, with 80.5% of subjects below SELENOP-concentration of 4.3 mg/L (corresponding to ~100 μg/L Se). In the confirmatory single-center study, the SELENOP median concentration was 3.1 mg/L, corresponding to Se concentrations of ~70 µg/L and SELENOP -concentrations below 4.3 mg/L (corresponding to approximately 100 μg/L Se) were observed in 89.4% of the study population. Further, aAb to SELENOP were prevalent in 9.7% of the population, compared to approximately 1% in healthy subjects. Conclusion This pilot study demonstrates a high prevalence of suboptimal Selenium status in Swedish HF patients which further underscores the need for suitably designed intervention studies to address the efficacy and safety of Se supplementation which can possibly constitute an inexpensive, safe and readily available treatment option for HF patients.

Long-term outcomes of cardiogenic shock survivors: a contemporary retrospective analysis from a tertiary center

Abstract Background Cardiogenic shock (CS) is a complex syndrome that still portends a dismal short-term prognosis. However, in patients that survive the initial admission and are later discharged, the long-term prognosis remains ill-characterized. Aim We aimed to describe the long-term morbidity and mortality outcomes of patients surviving the index admission for CS. Methods Retrospective analysis of all consecutive patients admitted to a cardiac intensive care unit (CICU) between December 2016 and December 2022 with a diagnosis of CS. All etiologies were included and further categorized as: acute myocardial infarction (AMI-CS), acute-on-chronic heart failure (HF-CS) and secondary causes [(S-CS): myocarditis, arrhythmic storm, acute pulmonary embolism, among others]. Our primary endpoint was defined as all-cause death, conditional to being discharged alive. Secondary endpoints comprised heart transplant, durable left ventricular assist device (LVAD) implantation, implantable cardioverter-defibrillator (ICD) insertion and hospital readmission during follow-up. Results A total of 208 patients were included [median age 68 years (IQR 57-80), 66% males, mean Charlson comorbidity index 4±3], of whom 52% (n=108) had AMI-CS, 27% (n=56) HF-CS and 21% (n=44) S-CS. During the index admission, mean SAPS II score was 49±18 and most patients were in SCAI-C (66%, n=137) stage. Organ support in the form of invasive mechanical ventilation, renal replacement therapy or temporary mechanical circulatory assist devices was necessary in 62% (n=129), 27% (n=56) and 26% (n=55) of patients, respectively. 53% of patients (n=110) survived the index admission [median CICU length of stay 8 (IQR 3-15) days; median hospital length of stay 13 (IQR 4-25) days]. At discharge, mean left ventricular ejection fraction was 38±16% and 28% (n=26) of patients underwent ICD implantation. Median follow-up after discharge was 679 (IQR 373-1056) days, with 4 (4%) patients lost to follow-up. Overall mortality was 22% (n=24) and was numerically higher for AMI-CS when compared to HF-CS and S-CS (9% vs 7% vs 6% respectively, p=0.640). Secondary endpoint analysis showed that 10% (n=11) had a heart transplant, 2% (n=2) received a durable LVAD, 9% (n=10) received an ICD and 26% (n=28) were re-hospitalized during that period. Conclusions Although the long-term mortality of patients discharged alive after the index admission for CS is not overwhelming, one in every four will be readmitted and a small proportion will be eligible for advanced heart failure therapies. Healthcare strategies to improve the morbidity and mortality of many CS survivors should be devised.

Readmission and mortality during the first year after an acute stroke: A prospective cohort study from Cameroon.

Hospital readmission after discharge for stroke is associated with high morbidity and mortality. There is a paucity of data on the burden of stroke readmission in most sub-Saharan African countries. We aimed to determine the rate, reasons and predictors of hospital readmission and the mortality rate within 12 months of discharge among stroke survivors in Cameroon. This prospective cohort included patients who survived hospitalization for an acute stroke and who were discharged from two referral hospitals in the capital city of Cameroon between January 2013 and December 2013.We performed logistic regression analysis to identify demographic and clinical factors associated with readmission within 1 year of discharge and causes of readmission. Of the 254 consecutive patients admitted for acute stroke, 198 were discharged alive. There were 107 (54%) males, and their mean age (SD) was 61.7 (13.9) years (range: 10 to 95 years). A total of 30 (15.2%) patients were readmitted following discharge from the index admission over a mean follow-up time of 286.9 (127.6) days. Of these, 14 (46.7%) were discharged and 16 (53.3%) died after readmission. Thirty percent (30%) of readmissions occurred within the first month. The most frequent causes of readmissions were infections (30%) and recurrent stroke (26.7%). Factors associated with readmission in bivariate analysis were initial admission temperature > 37.5°C (risk ratio [RR]: 1.3, p = 0.021) and initial admission Glasgow Coma Score < 14 (RR: p = 1.23, p = 0.019). After stratified adjustment for age and sex, temperature > 37.5°C (adjusted RR: 1.3, 95% CI: 1-1.7, p = 0.036) and GCS <14 (adjusted RR: 1.23, 95% CI: 1-1.6, p = 0.041) were associated with readmission. Readmission after discharge for stroke was common with nearly one third occurring within the first month and more than half dying following readmission. The most common causes of readmission were infections and recurrent stroke.

Revascularization strategies in elderly patients with acute coronary syndromes and multivessel disease: comparative analysis of culprit-only vs complete revascularization

Abstract Background Acute coronary syndromes (ACS) are more challenging in elderly patients, particularly when related to multivessel disease (MVD). Concerns about outcomes, and the lack of evidence, lead to more conservative treatment. While benefits of complete revascularization are well established among the youngest, doubts persist in older patients. Despite FIRE trial having showed superiority of complete revascularization with coronary physiology, in older patients with ACS and MVD, more evidence is needed. Methods Multicenter retrospective cohort of 629 patients, older than 75 years, with ACS and MVD, was divided into complete or culprit-only revascularization groups. In-hospital outcome of death and major adverse cardiovascular events (MACE) and follow-up outcome of death and cardiovascular hospital admission were assessed. Results From the 629 patients, 383 (61%) were submitted to PCI, of which 66% (n=254) were submitted to culprit-only revascularization and 34% (n=129) to complete revascularization. Culprit-only group's mean age was 83±5 years and median age in complete revascularization group was 81 (IQ 78-84) years. There was similar number of female patients in both groups (42% and 37%, p=0,26), and the culprit only group was significantly older (p=0,006). There were more ST-segment elevation myocardial infarctions in culprit- only group (p&amp;lt;0,001). Regarding diabetes, previous ACS, Killip classification, heart failure, stroke, peripheral artery disease, and chronic kidney disease, there were no statistically significant differences between groups (p&amp;gt;0,05). Complete revascularization was associated with lower in-hospital events, with 36% against 48% in culprit-only (p=0,025 OR 0,62 [0,4-0,9]), mainly due to lower in-hospital deaths, with 3% against 13% (p&amp;lt;0,01 OR 0,3 [0,15-0,67]) but also due to lower in-hospital MACE with 29% against 27% (p=0,02 OR 0,6 [0,4-0,9]). The mean follow-up was 13±7 months, during which, in complete revascularization group, there was non-statistically significant decrease of deaths, with 13% against 15% (p=0,4), hospital readmissions, with 21,8%, in comparison with 24,9% (p=0,2), and composite outcome, with 35% and 40% (p=0,16) of composite events in the culprit-only group There was a non-statistically significant decrease of the mean for survival time for culprit only group which was 10±8 months comparing with complete group of 13±8 months (p=0,16). Conclusion In older patients with ACS and MVD the ideal strategy is yet to be determined. Still complete revascularization strategy showed a statistically significant decrease of in-hospital death and MACE, and non-statistically significant decrease in follow-up mortality and readmissions. This study suggests, like FIRE trial, that when clinically and anatomically feasible, it seems legit to attempt complete revascularization in elderly patients with ACS and MVD.

Prognostic impact of myocarditis as aetiology compared with dilated cardiomyopathy and ischaemic heart disease in heart failure

Abstract Background A subgroup of myocarditis can lead to heart failure. However, whether prognosis of myocarditis-induced heart failure differs from other heart failure remains largely unknown. Aim This study aimed to investigate the prognostic impact of myocarditis induced heart failure compared with heart failure with dilated cardiomyopathy and ischaemic heart disease as causes respectively in the overall population and a propensity score-matched cohort, based on patient-level data from the Swedish Heart Failure Registry (SwedeHF). Methods Patients with heart failure (HF) were enrolled from the SwedeHF (2003-2020) linked with the National Patient Register, and the Swedish Cause of Death Register. Endpoints were all-cause mortality, cardiovascular death, and hospital re-admissions, followed up from the index date until censoring or event. Results Of 54416 patients identified through the SwedeHF with HF, 418 hade myocarditis as aetiology (MC-HF), 6,871 with dilated cardiomyopathy (DCM-HF) and 47127 with ischemic heart diseases (IHD-HF). In general patients with MC-HF have shorter disease duration and less comorbidities compared with DCM-HF and IHD-HF, but older than DCM-HF and younger than IHD-HF. Compared with DCM-HF, MC-HF are associated with 29% higher risk for all cause mortality [(1.29 (1.07 - 1.55), p=0.0079] and 40% higher risk for cardiovascular death [ 1.40 (1.09 - 1.80), p=0.0088], and 19 % higher risk for heart failure rehospitalization [1.19 (1.03 - 1.37), p=0.018] and even higher risk by censoring within one-year . However, compared with IHD-HF, patients with MC-HF have similar risk for all cause mortality [0.95 (0.80 - 1.13), p=0.54], cardiovascular death [0.95 (0.75 - 1.20), p=0.65], and heart failure rehospitalization [0.93 (0.81 - 1.06), p=0.29]. Similar results were obtained from a propensity 1:2 matched cohort. No significant interactions were found regardless of age (&amp;lt; and &amp;lt; 70 years) , sex, LVEF (≥50%, 40-49%, 30-39% and &amp;lt; 30%) for all cause mortality comparing MC-HF vs DCM-HF, and MC-HF vs IHD-HF. Conclusion Patients with myocarditis-induced heart failure have worse outcome than heart failure due to dilated cardiomyopathy, with even higher risk during one year. This finding highlights the importance of early and more effective customized management of patients with myocarditis in particular those with high risk to develope heart failure.

Evaluating an integrated clinical pharmacy service model in an ambulatory cardiac clinic- a single centre study

Abstract Background Evidence suggests that multidisciplinary cardiology clinics improve patient outcomes. Currently, there is limited data on the type of pharmacist-led interventions occurring in cardiac ambulatory clinics in the Australian setting. Purpose The primary aim of this pilot audit is to examine the frequency and type of pharmacist-led interventions in the ambulatory clinics of this specialist hospital. The secondary aim is to assess factors associated with hospital readmissions within 30 days of Pharmacists' reviews. Methods A retrospective pilot audit was conducted for patients who attended an integrated multidisciplinary Heart Failure (HF) and Hypertension (HTN) clinic from April 2023 to February 2024. Patients’ demographics, Charlson comorbidity index (CCI), and the number and types of pharmacist interventions and readmission data 30 days post clinic review were recorded. Descriptive statistics were used to evaluate patient characteristics and logistic regression for hospital readmissions. Results A total of 398 patients were reviewed by pharmacists, with 300 (75%) from the HF clinics and 98 (25%) from the HTN clinics. Patients’ median age was 63± 14.8 years and median CCI was 4± 3.7. Pharmacists documented medication histories for all patients (100%) and provided 355 recommendations, of which 213 (60%) were actioned by the cardiologist. Pharmacists had a face-to-face consultation and provided education and counselling to 175 (44%) patients. The most common types of interventions were related to guideline-directed prescribing and deprescribing (68, 39%), followed by up-titration of current therapies (61, 35%). Pharmacists also provided education on medication adherence and lifestyle modifications (28, 16%) as well as optimizing medications related to other comorbidities (18, 10%). A total of 8 patients (2%) were re-admitted l within 30 days of clinic review from either heart failure exacerbation or hypertensive crisis. Patients who had a face-to-face consultation and education with a pharmacist were less likely to be readmitted within 30 days (P=0.048). However, none of the other predictors tested for readmission such as age (P= 0.572), gender (0.296), history of non-compliance (0.834), CCI (0.984) or a diagnosis of HF or HTN (0.473) were predictors for readmission within 30 days of clinic review. Conclusion Pharmacists play an integral role in the cardiac ambulatory setting by providing expert medication advice and patient education to optimize patients’ outcomes. This study demonstrates that the activities performed by pharmacists working in Australian cardiac clinics are consistent with other international ambulatory clinics. The study also identified opportunities to develop a similar service for other ambulatory clinics at this hospital such as lipid and atrial fibrillation clinics. Additionally, further research is required to assess long term benefit of pharmacist led interventions on cardiac patients.

Influence of process-focused patient care on clinical outcomes among hospitalized heart failure patients in the cardiology ward

Abstract Background The implementation of a process-oriented organizational structure in patient care allows for a comprehensive and optimized approach. In the context of heart failure (HF), it remains uncertain whether the establishment of a specialized hospitalisation team can contribute to improved major clinical outcomes. Purpose To analyse the rates of all-cause hospitalisation, cardiovascular hospitalization, HF hospitalization and overall mortality at 180 days among patients admitted to the Cardiology ward for HF, both prior to and after the implementation of a specialized HF hospitalisation team. Methods The study included all patients discharged from the Cardiology department with HF as the primary diagnosis and subsequent outpatient follow-up by the Community HF Unit in both 2019 and 2022. Clinical outcomes were compared between two distinct periods: the pre-implementation year of 2019 and the subsequent year of 2022, characterized by process-oriented HF care. Statistical analyses were performed using Kaplan-Meier and adjusted Cox proportional-hazards models. Results A total of 140 patients were enrolled in the study, comprising 55 individuals receiving care from a conventional ward team in 2019 and 85 under the specialized HF team in 2022. The mean age of the cohort was 69.4 years (+/-11.8), with a mean LVEF of 40.6%. The pre-implementation group showed a higher percentage of male patients (73% vs. 47%; p=0.003) and LVEF was lower in the HF team period (38.9% vs. 43.4%; p=0.045), with no statistically significant differences in other baseline variables. As shown in figure 1, over 180 days of follow-up, 15 patients (27.6%) were admitted to hospital in the conventional ward team period and 13 (15.3%) in the HF team period (hazard ratio [HR] 0.44; 95% confidence interval [CI] 0.19 to 0.99; P=0.047). Of these hospitalisations, 13 patients (23.6%) in pre-implementation period and 10 (11.8%) in post-implementation period were attributed to cardiovascular events (HR 0.40; 95% CI 0.16 to 0.99; P=0.049). Additionally, there was a reduction in the rate of heart failure admissions in the post-implementation period compared to the pre-implementation time (HR 0.30; 95% CI 0.09 to 0.94; P=0.039). Furthermore, a significant decline in all-cause of death was observed in patients treated by HF-team in 2022 compared to patients receiving care from the conventional ward team (log-rank test, p=0.015). Conclusions The implementation of a process-oriented organizational model within the Cardiology unit consisting in the provision of patient care by a team specialized in HF management, is associated with a statistically significant reduction in major clinical outcomes such as all-cause hospitalization, cardiovascular hospitalization and HF readmission, alongside a reduction in overall mortality rates at 180 days.

AI-Powered Post-Discharge Monitoring to Prevent Patients Readmissions and Reduce Workforce Burden

Abstract Background Patient readmission poses a significant burden on healthcare systems, straining resources, negatively impacting patient treatment, and it is often a Public Health problem. Traditional post-discharge follow-up methods, such as phone calls, often lack efficiency and personalization. Artificial intelligence (e.g., Machine Learning (ML)) offers a transformative approach that can potentially improve post-discharge care. Methods This scoping review aimed to map existing research on AI-powered solutions for post-discharge monitoring, focusing on their application in risk stratification and their potential for reducing hospital readmissions within a public health framework. Following PRISMA-ScR guidelines, a search was conducted across four databases using keywords related to AI, post-discharge, and risk stratification. Results Studies published between 2018 and January 2024 were included if they described the development and application of an ML model in a post-discharge setting for risk stratification. Sixteen studies met the inclusion criteria. Tree-based algorithms, particularly XGBoost, were the predominant ML approach, with promising performance metrics for readmission risk prediction. Conclusions However, limitations were identified, including restricted generalizability due to data source limitations and a lack of real-time implementation in many studies. This review highlights the potential of AI in post-discharge monitoring, particularly the use of ML for risk stratification, as a promising tool for public health contact tracing. While challenges remain regarding generalizability and real-world implementation, the findings suggest AI holds immense promise for improving post-discharge care, potentially reducing readmissions, and optimizing resource allocation. Future research with broader datasets and real-time applications can further solidify the role of AI in revolutionizing post-discharge care within public health systems. Key messages • This study shows the potential of AI and risk stratification in post-discharge monitoring, improving public health outcomes by reducing hospital readmissions and optimizing the healthcare workforce. • This review highlights the value of AI in public health, particularly for improving post-discharge care through effective prediction of high-risk readmissions.

Cardiovascular mortality with oral potassium-binders in patients with CKD and heart failure

Abstract Introduction Hyperkalemia is an inherent consequence of advancing chronic kidney disease (CKD) as a result of the kidney’s decreased ability to excrete potassium. Heart failure patients with concomitant CKD may not tolerate maximum doses of guideline-directed medical therapies (GDMT) like ACE inhibitors (ACEi), angiotensin receptor blockers (ARB), angiotensin receptor/neprilysin inhibitors (ARNI) and mineralocorticoid receptor antagonists (MRA) due to dose-limiting hyperkalemia. Many randomized controlled trials in heart failure exclude patients with advanced CKD. Two oral therapies exist to manage hyperkalemia - patiromer sorbitex calcium and sodium zirconium cyclosilicate. This study aims to identify the potassium-binder with better outcomes as defined by less readmissions, hyperkalemia episodes, and death. Purpose This project was undertaken to better understand the impact of using potassium-binders in CKD patients with heart failure. Improved management of hyperkalemia will be an avenue for optimization of GDMT in this population. Methods and materials The TriNetX research network was used for this study. Two cohorts of patients were created by using International Classification of Disease 10 (ICD-10) codes and CPT codes. Both cohorts consisted of patients with no prior history of hyperkalemia within 30 days of hospital discharge at which time one cohort was prescribed patiromer and the other received sodium zirconium cyclosilicate. Each cohort was prohibited from exposure to the other medication. The cohorts were balanced by propensity score matching and the greedy nearest neighbor algorithm for age, race, gender, ethnicity. They were also balanced for systolic and diastolic heart failure diagnoses, and for each individual stage of CKD (1 through 5 and end stage). They were also balanced for use of ACEi, ARBs, and MRAs. This resulted in 8,921 patients in each arm. They were then evaluated for the outcomes of hospital readmission, hyperkalemia episodes (&amp;gt;6.1 mmol/L), and death within 12 months. Results Patients treated with patiromer were more likely to be hospitalized over the following twelve months (44% vs 40%, RR 1.11, 95% CI (1.07,1.15), p value &amp;lt;0.0001). They were also more likely to experience hyperkalemia (11.7% vs 9.2%, RR 1.27, 95% CI (1.16,1.38), p value &amp;lt;0.0001). Patiromer was also associated with slightly greater all cause mortality (27% vs 25%, RR 1.08, 95% CI (1.03,1.13), p value 0.0021). Discussion This study demonstrates patiromer has more readmissions and hyperkalemia episodes along with greater mortality. In conclusion, sodium zirconium cyclosilicate was found to have better outcomes compared to that of patiromer. Further studies are necessary to better understand the utility of using sodium zirconium cyclosilicate as maintenance therapy for hyperkalemia in order to maximize GDMT in CKD patients with heart failure.

Multimorbidity patterns in adults admitted to hospital with heart failure: an analysis of 175 million hospitalisation episodes

Abstract Background The prevalence of heart failure (HF) is increasing as a result of population ageing, improved survival following myocardial infarction and the widespread uptake of evidence-based HF treatments. Greater understanding of multimorbidity patterns in patients with HF may enable the development of treatment strategies that target multiple, related long-term conditions (LTCs), producing synergistic benefits. Purpose To characterise multimorbidity patterns in patients with HF and compare these to a matched population without HF. Methods A retrospective matched cohort study was conducted using the United States National Readmission Database (NRD), 2010–2020. International Classification of Disease (ICD) codes were used to identify HF and 92 other common LTCs. The most frequent combinations of LTCs were identified for individuals with HF and a control cohort of individuals of the same age and sex, with a non-HF-related hospital admission in the same year (matched in a 1:5 ratio). Multivariable regression analysis (adjusted for age, sex, socioeconomic status, tobacco use, year of hospitalisation, and hospital characteristics) was used to evaluate the association between multimorbidity burden, length of stay (LOS; negative binomial regression) and 30-day readmission (logistic regression). Results From a total of 175,388,410 hospitalisation episodes, 3,913,924 individuals with an HF-related hospitalisation were identified and matched to 19,552,954 controls (Figure 1a). The median (interquartile range, IQR) age of a patient admitted with HF was 74 (63–85) years; 1,856,268 (47.5%) were female. The most common comorbidities in those with HF were hypertension (87.2 vs. 72.8% in matched controls), chronic kidney disease (CKD; 55.3 vs. 34.6%), coronary artery disease (CAD; 53.7 vs. 31.0%), dyslipidaemia (46.9 vs. 39.7%), diabetes (46.6 vs. 33.9%), atrial fibrillation (AF; 43.0 vs. 23.0%) and anaemia (33.2 vs. 30.1%; p all &amp;lt; 0.001). Patients with HF had a greater number of LTCs compared with matched controls (median [IQR] 7 [5–9] vs. 6 [4–8]; p &amp;lt; 0.001). From 2010–2020, the number of LTCs in those with an HF admission increased (from 6 [4–8] in 2020, to 8 [6–10] in 2020; Figure 1b). The most common multimorbidity patterns in those with HF are presented in Figure 2. In the HF cohort, a greater multimorbidity burden was associated with a longer LOS (+6% for each additional LTC; 95% confidence interval [CI] 5–7%; p&amp;lt;0.001) and greater risk of 30-day readmission (adjusted odds ratio [aOR] for 6 vs. 0 LTCs: 1.15, 95% CI 1.08–1.22; aOR for ≥12 vs. 0 LTCs: 1.54, 95% CI 1.45–1.64). Conclusions Patients admitted to hospital with HF have a significant burden of multimorbidity, which has increased over time and is associated with increased length of stay and unplanned hospital re-admission. The high prevalence of multiple LTCs warrants the development of novel treatment strategies that target common multimorbidity patterns observed in HF.

Risk Factors for Unplanned Readmissions in Paediatric Neurosurgery: A Systematic Review

Abstract Background Unplanned hospital readmission (UHR) after paediatric neurosurgery is an important indicator of surgical outcomes. As this field deals with complex cases, there is an increased likelihood of potential complications and the subsequent need for readmission. Hence, the study aims to identify factors contributing to 30-day and 90-day UHR rates in children undergoing neurosurgical procedures. Methods A systematic review (Prospero CRD 42023455779) was conducted, which included studies from Embase, Medline, CINAHL, and Global Index Medicus databases that reported unplanned readmissions within 30-/90-days of an index neurosurgical procedure. Quality and risk of bias assessment was done using the Newcastle-Ottawa scale. Data extraction and narrative synthesis were performed to identify significant factors associated with UHR. Results 2593 titles were identified following the search strategy. 52 studies were included after screening and quality appraisal. Most studies were from the United States and are retrospective cohort in nature. Majority were cranial procedures (n = 30), with common ones being shunt procedures for hydrocephalus and cranial tumour resections. Aetiology-related, procedural complexities, and age emerged as the three most common significant risk factors. Age is a significant predictor (9/52), with younger children facing higher odds compared to their older counterparts across different procedures. While early readmissions can be due to disease progression, some are linked to preventable causes. The included studies also exhibited significant heterogeneity. Variations in definitions and examined variables, as well as the inclusion of studies from both national databases and single institutions, contributed to this heterogeneity. Conclusions Overall, findings from this study contribute to a collective understanding of factors affecting unplanned readmissions in paediatric neurosurgery. Key messages • Identified risk factors can help guide creating and refining surgical protocols for post-operative monitoring and follow-up. • UHRs reflect the interplay among surgical complexity, patient characteristics such as age, and disease aetiology.

Prognostic value of soluble urokinase plasminogen activator receptor (suPAR) in patients admitted with acute heart failure

Abstract Introduction The inflammatory marker, soluble urokinase plasminogen activator receptor (suPAR), has emerged as a promising prognostic biomarker of heart failure (HF). Higher levels of suPAR in plasma are indicative of hospital readmissions and mortality. Currently little is known about suPAR-values upon admission in patients with acute heart failure (AHF). Purpose This study investigates the prevalence of elevated suPAR and prognostic value in patients hospitalized with AHF. Methods In this prospective cohort study, all patients ≥ 18 years old admitted at the Emergency Department at a large University Hospital in Denmark, were consecutively included from March 10, 2020, to March 31, 2022. The follow-up period was 365 days. The biomarker suPAR was measured in all patients upon admission (median time from admission to suPAR measurement was two hours (IQR 3: 3,9-6,9)). Patient data was extracted from the electronic patient record system, and a cardiologist adjudicated whether the patients had AHF. Patients were stratified according to validated cut-off values of suPAR above or below 6 ng/mL. Kaplan-Meier survival analysis and Cox Regression were used to assess the association between suPAR levels and one-year mortality outcomes. Results A total of 408 (5%) AHF patients, from a total population of 6,715, were included in the study. 40 patients were excluded due to missing suPAR-values and the final analysis comprised of 368 AHF patients. Among AHF patients upon admission, the mean suPAR value was 6.2 ng/mL (standard deviation [SD] = 4.8 ng/mL), and non-AHF patients had a mean value of 4.5 ng/mL (SD = 3.1 ng/mL). A suPAR level above 6 ng/mL was significantly associated with mortality (figure 1), log-rank test p-value &amp;lt; 0.0001. Furthermore, Cox regression analysis demonstrated that elevated suPAR levels were independently associated with increased risk of mortality with a hazard ratio (HR): 2.09 (95% CI: 1.59-2.90), p-value &amp;lt; 0.001 after adjusting for potential confounders: age, sex, atrial fibrillation, Chronic Obstructive Pulmonary Disease, and Creatinine levels. Conclusion The inflammatory biomarker suPAR measured upon hospital admission in AHF patients is significantly associated with one-year mortality in patients admitted with AHF. The potential of suPAR as a valuable prognostic marker in AHF is offering clinicians a tool to identify high-risk patients and tailor management strategies, accordingly, thereby improving patient outcomes.Figure 1 - 1 year mortality