Higher Readmission Rates Research Articles

Analyzing Gait Dynamics and Recovery Trajectory in Lower Extremity Fractures Using Linear Mixed Models and Gait Analysis Variables

In a prospective study, we examined the recovery trajectory of patients with lower extremity fractures to better understand the healing process in the absence of complications. Using a chest-mounted inertial measurement unit (IMU) device for gait analysis and collecting patient-reported outcome measures, we focused on 12 key gait variables, including Mean Leg Lift Acceleration, Stance Time, and Body Orientation. We employed a linear mixed model (LMM) to analyze these variables over time, incorporating both fixed and random effects to account for individual differences and the time since injury. This model also adjusted for varying intervals between assessments. Our study provided insights into gait recovery across different fracture types using data from 318 patients who experienced no complications or readmissions during their recovery. Through LMM analysis, we found that Tibia-Distal fractures demonstrated the fastest recovery, particularly in terms of mobility and strength. Tibia-Proximal fractures showed balanced improvements in both mobility and stability, suggesting that rehabilitation should target both strength and balance. Femur fractures exhibited varied recovery, with Diaphyseal fractures showing clear improvements in stability, while Distal fractures reflected gains in limb strength but with some variability in stability. To examine patients with readmissions, we conducted a Chi-squared test of independence to determine whether there was a relationship between fracture type and readmission rates, revealing a significant association (p < 0.001). Pelvis fractures had the highest readmission rates, while Tibia-Diaphyseal and Tibia-Distal fractures were more prone to infections, highlighting the need for enhanced infection control strategies. Femur fractures showed moderate readmission and infection rates, indicating a mixed risk profile. In conclusion, our findings emphasize the importance of fracture-specific rehabilitation strategies, focusing on infection prevention and individualized treatment plans to optimize recovery outcomes.

Efficacy of the ECHOMANTRA online intervention to support recovery from anorexia nervosa in adult patients: study protocol of a randomized controlled multi-center trial

BackgroundPoor quality of life in adults with anorexia nervosa (AN) and persistent high rates of readmission highlight the necessity of developing interventions to optimize treatment outcomes. ECHOMANTRA is a novel online intervention based on interventions for carers (Experienced Carers Helping Others, ECHO) and patients (Maudsley Model of Anorexia Nervosa Treatment for Adults, MANTRA) with anorexia nervosa. The objective of this paper is to describe the study protocol of a randomized control trial (RCT) aimed at evaluating the efficacy of an adaptation of the ECHOMANTRA for adults AN inpatients and outpatients, and their carers, to be implemented as an add-on to treatment-as-usual (TAU).MethodsIn a multi − center pilot randomized controlled trial (RCT), 148 adult AN patients, and their carers, will be randomized to receive treatment as usual (TAU) or TAU plus ECHOMANTRA. Assessments will take place at baseline (T0), post-intervention (2-month) (T1), 6-month follow-up (T2), and 12-month follow-up (T3). Primary outcomes will be eating disorder psychopathology and psychological well-being. For carers, outcome variables will include psychological well-being, accommodation and enabling behaviors, expressed emotion, illness burden, quality of life and care skills.DiscussionThis study will provide evidence of the efficacy of this novel, online and protocolized intervention in facilitating the recovery of these patients.Trial registrationISRCTN registry (Identifier: 80253157 https://doi.org/10.1186/ISRCTN80253157).

A 5-Year Review of Characteristics and Outcomes of Trauma Surgery Patients Leaving Against Medical Advice.

The objective of this study was to characterize the demographic, social, economic, and clinical factors of trauma surgery patients leaving against medical advice (AMA). Data were retroactively obtained from a level-one trauma center in a medium-sized metropolitan area from January 2017 to December 2021. The sample population consisted of patients admitted or treated by the trauma surgical service. In the 5-year study period, 130 surgical patients left AMA and met the inclusion criteria for this study. The average patient was 38.8 years old. The majority were male (77.7%) and White (47.7%). It was found that 74.6% of patients had insurance, 23.6% were experiencing homelessness, and 6.2% required an interpreter. A large percentage of patients had a past medical history significant for depression (31.5%), anxiety disorders (25.4%), and substance use disorder (68.5%). Analysis of the hospital time course of this patient population indicated that patients were most often admitted to trauma surgery (70.0%) and most often required consults by neurosurgery (28.5%). Procedures were performed for 81.5% of patients and social services were consulted for 60.8% of patients. Only 50.8% of patients who left AMA were noted to receive discharge instructions. Nearly half (44.6%) of the patients returned to a hospital to receive additional care within 1 month of their initial AMA discharge date. A concerning number of trauma surgery patients left without discharge instructions, possibly leading to a high rate of 30-day hospital readmission. Future studies are needed to examine and further characterize the relationship between discharge protocol and outcomes of patients leaving AMA.

Identifying specific subgroups of older patients at risk of repeated hospital readmissions and death after discharge in a prospective multicentre cohort in France

ObjectiveTo identify specific subgroups of older patients at risk of repeated hospital readmissions and death.DesignProspective, multicentre, DAMAGE (Patient Outcomes After Hospitalization in Acute Geriatric Unit) cohort of adults aged 75...

Risk factors for readmission within one year after acute exacerbations of bronchiectasis in a Chinese tertiary hospital: a retrospective cohort study

BackgroundFrequent exacerbations of bronchiectasis lead to poor quality of life, impaired lung function, and higher mortality rates. This study aims to evaluate the risk factors associated with readmission within one year due to acute exacerbation of bronchiectasis (AEB).MethodsA retrospective cohort study was performed on 260 patients with bronchiectasis who were hospitalized in the respiratory and critical care department of a tertiary hospital in China. Univariate and multivariate Cox analyses were used to evaluate the risk factors for readmission within one year.ResultsReadmission within one year was found in 44.6% of 260 patients hospitalized with acute exacerbation of bronchiectasis. The risk factors associated with readmission included age over 65 years (HR = 3.66; 95% CI: 2.30 to 5.85), BMI < 18.5 kg/m2 (HR = 1.71; 95% CI: 1.16 to 2.51), respiratory intensive care unit (RICU) stay during admission (HR = 2.06, 95% CI: 1.16–3.67), involvement of 3 or more lobes on chest high-resolution computed tomography (HRCT) (HR = 1.85; 95% CI, 1.22 to 2.80), chronic Pseudomonas aeruginosa (PA) colonization (HR = 2.29; 95% CI: 1.54 to 3.38), and positive sputum culture results within 24 h after admission (HR = 1.93; 95% CI: 1.27 to 2.94). Long-term oral antibiotics use after discharge was associated with decreased hazard of readmission (HR = 0.34; 95% CI: 0.20 to 0.59).ConclusionsPatients with bronchiectasis have a high rate of readmission, which is linked to varieties of risk factors, and identifying these risk factors is importance for effectively managing patients with bronchiectasis.

Impact of general vs. regional anaesthesia on one-year clinical outcomes and healthcare utilisation after lower limb arthroplasty: a retrospective study.

General anaesthesia and regional anaesthesia are used for hip and knee arthroplasty but their impact on long-term outcomes remains unclear. This study aimed to compare one-year clinical outcomes and healthcare utilisation in patients receiving general or regional anaesthesia for hip or knee arthroplasty. Using data from the TriNetX Global Collaborative Network, we conducted a retrospective analysis of 247,142 patients aged 40-90 y who underwent hip or knee arthroplasty between 2010 and 2023. After propensity score matching, 12,558 patients were included in the general anaesthesia and regional anaesthesia cohorts. The primary outcome was one-year all-cause mortality. Secondary outcomes included one-year incidence of dementia; cerebral infarction; pneumonia; major depression; care provider dependency; and readmission rates. Subgroup analyses according to sex, age (40-70 y vs. > 70 y) and timeframe (2010-2016 vs. 2017-2023) were also performed. There was no significant difference in one-year mortality (hazard ratio 1.12, 95%CI 0.89-1.41, p = 0.322). General anaesthesia was associated with a lower incidence of major depression (hazard ratio 0.82, 95%CI 0.70-0.97, p = 0.021) and care provider dependency (hazard ratio 0.47, 95%CI 0.38-0.58, p < 0.001), but higher readmission rates (hazard ratio 1.22, 95%CI 1.16-1.29, p < 0.001) than regional anaesthesia. Subgroup analysis revealed that patient characteristics including sex and age, as well as evolving peri-operative care practices over time, may influence the comparative outcomes of general and regional anaesthesia in patients undergoing elective hip or knee arthroplasty. Although general anaesthesia and regional anaesthesia showed comparable one-year mortality, general anaesthesia was associated with lower risks of major depression and care provider dependency but higher readmission rates than regional anaesthesia. These findings suggest that the choice of anaesthesia may have important implications for long-term outcomes beyond mortality.

Predictive Modeling of Hospital Readmission of Schizophrenic Patients in a Spanish Region Combining Particle Swarm Optimization and Machine Learning Algorithms.

Readmissions are an indicator of hospital care quality; a high readmission rate is associated with adverse outcomes. This leads to an increase in healthcare costs and quality of life for patients. Developing predictive models for hospital readmissions provides opportunities to select treatments and implement preventive measures. The aim of this study is to develop predictive models for the readmission risk of patients with schizophrenia, combining the particle swarm optimization (PSO) algorithm with machine learning classification algorithms. The database used in the study includes a total of 6089 readmission records of patients with schizophrenia. These records were collected from 11 public hospitals in Castilla and León, Spain, in the period 2005-2015. The results of the study show that the Random Forest algorithm combined with PSO achieved the best results across the evaluated performance metrics: AUC = 0.860, recall = 0.959, accuracy = 0.844, and F1-score = 0.907. The development of these new models contributes to -improving patient care. Additionally, they enable preventive measures to reduce costs in healthcare systems.

Post-discharge telephone follow-up calls to patients with chronic obstructive pulmonary disease by primary care nurses: a best practice implementation project.

Chronic obstructive pulmonary disease (COPD) is a complex health problem, with important repercussions for patients and their families. Interventions need to be improved to prevent exacerbations and reduce high readmission and mortality rates. Evidence suggests that including a telephone follow-up (TFU) call in discharge plans could improve outcomes in patients with a chronic disease. This project aimed to improve how primary care nurses in Gran Canaria, Spain, followed up COPD patients after hospital discharge. This project was guided by the JBI Evidence Implementation Framework, which includes the JBI Practical Application of Clinical Evidence System (PACES) and the Getting Research into Practice (GRiP) method. The JBI approach uses audit, feedback, and re-audit to promote evidence-based health care. A baseline audit was conducted to compare current practices against best practices. Five barriers to best practices were identified and improvement strategies were developed. The follow-up audit revealed 100% compliance for Criteria 1 and 2, which related to COPD patients having a discharge plan and that plan including TFU. There was a 4.88% improvement for both Criteria 3 and 4, which involved the TFU being prompt and using a validated clinical questionnaire. Following project implementation, the 30-day readmission rate increased from 2.78% to 4.88% but the 30-day emergency room presentation rate decreased from 25% to 9.76%. The practice changes were partly achieved, but further strategies are needed to achieve full compliance. Educational programs are necessary when conducting improvement projects. Chances of success increase when decisions about hospital discharge involve both the hospital and the primary care service. http://links.lww.com/IJEBH/A296.

Assessment of the Effect of Telephonic Follow-up on Readmissions and Mortality Rate of the Patients with Acute Coronary Syndrome and Acute Heart Failure in Rashid Hospital

Background: Acute coronary syndrome (ACS) and acute heart failure (AHF) are severe medical conditions that are closely associated with higher rates of readmissions and mortality in hospitals. These conditions pose an exponential challenge to the healthcare system and increase patient burden. Objectives: This study aims to identify the effect of telephonic follow-up on readmission and mortality rates in Rashid Hospital due to ACS and AHF. Methods: In 2022, we conducted a prospective study. We divided 805 patients admitted with ACS and AHF in Rashid Hospital into two groups and compared the readmission and mortality rates of patients who were followed up with those who were not. The data collection tool included a demographic questionnaire, which was then analyzed by statistical tests and SPSS software. Results: There were patients in the follow-up call group versus patients in the nonfollow- up call group. The patients with follow-up calls had a higher survival rate (98.3%) compared with the ones who had not been called (93.4%) (p = 0.003). Readmission rates for follow-up patients were (7.7%) versus (5.9%) for those without follow-up calls (p = 0.429). The study analyzed and investigated the individuals on various other factors; however, no statistically significant difference was observed between the two groups. Conclusion: The study provides insight into the various factors associated with patients’ outcomes. Even though the association of readmission rate to follow-up was unremarkable, the mortality rate of patients with follow-up was significantly lower.

Exploring the pharmacological mechanism of Qishen Yiqi dropping pills in treating chronic heart failure based on network pharmacology and molecular docking

Chronic heart failure (CHF) is a severe condition that affects millions of people worldwide. Despite standardized treatments, patients often face recurrent symptoms such as dyspnea, edema, and fatigue, which impair their quality of life and contribute to high mortality and hospital readmission rates. Traditional Chinese Medicine (TCM) offers alternative therapies, and Qishen Yiqi Dropping Pills (QYDP) has emerged as a potential treatment for CHF. QYDP is composed of Danshen, Huangqi, Jiangxiang, and Sanqi and is known for its ability to promote circulation, enhance Qi, and support cardiac health. Although clinical studies have suggested that QYDP can alleviate CHF symptoms, the underlying molecular mechanisms are not fully understood. In this study, network pharmacology and molecular docking were used to explore the pharmacological targets of QYDP for CHF treatment. Four core genes were identified: AKT1, HIF1A, STAT3, and MYC. Molecular docking confirmed the interactions between these genes and active compounds in QYDP, such as kaempferol, luteolin, quercetin, tanshinone IIa, and cryptotanshinone. These findings suggest that QYDP may treat CHF through a multitarget mechanism, offering new insights into its therapeutic potential and providing a basis for further clinical research.

Impact of alcohol use disorder on inpatient hospitalizations: A comparison of outcomes between urban and rural Veterans Affairs hospitals.

Alcohol use disorder (AUD) is a leading cause of morbidity and mortality that disproportionately affects rural residents and Veterans. To evaluate the burden of AUD in admissions at rural and urban hospitals within the Veterans Health Administration (VHA) comparing patient characteristics, clinical outcomes, and 1-, 3-, and 5-year mortality rates. Retrospective cross-sectional study of patients admitted to VHA hospitals from 2016 to 2020, with a primary or secondary diagnosis related to AUD. Follow-up mortality data was collected through September 30, 2023. From 2.9 million qualifying admissions, AUD-related diagnoses were present in 14.3% of admitted patients (427,375 admissions among 190,152 unique patients in 129 facilities). Rural hospitals (n = 22) had a significantly higher overall admission rate for AUD-related diagnoses (21.6% vs. 14.8%, p = .011), higher 30-day readmission rates (17.8% vs. 15.3%, p < .001), but lower hospital-level average length of stay (median = 4.3 vs. 5.6, p < .001). Mortality in rural hospitals was lower than urban at 1 year (9.6% vs. 11.4%, p < .001), 3 years (20.7% vs. 23.1%, p < .001), and 5 years (30.4% vs. 32.9%, p < .001). Rural VHA hospitals have a higher proportion of patients admitted with AUD-related diagnoses and higher readmission rates, but lower mortality rates. Approximately, one in three patients admitted with an AUD-related diagnosis died within the 5-year follow-up period. The mortality rates observed are extraordinary and deserve urgent attention. A comprehensive plan to address AUD in the Veteran population, including how we approach and engage patients in treatment during hospitalizations with any primary or secondary AUD diagnoses, is needed.

Time to surgery for acute uncomplicated appendicitis in an adult university teaching hospital.

Both patient and hospital-related factors determine the timing of appendicectomy for acute uncomplicated appendicitis. Recent literature suggests appendicectomy more than 24h after hospital admission is associated with increased morbidity in adults. Current guidelines from the World Society of Emergency Surgery (WSES) recommend surgery within this timeframe to reduce the risk of complications. The aim of this study was to determine the time to surgery for patients with acute uncomplicated appendicitis and to compare this to the current WSES recommendations. This study also aimed to identify potential reasons for any in-hospital delay. This study is a retrospective review of all patients who underwent appendicectomy for confirmed acute uncomplicated appendicitis at an adult university teaching hospital between September 2021 and September 2022. Patient demographics, clinical information, time of admission, time of surgery, time of discharge and surgical complication data were collected. A total of 229 appendicectomies were performed during the study period. 138 (60%) had a preoperative diagnosis of acute uncomplicated appendicitis. The median age was 36 years (range 17-93). Time to surgery was <24h in 80 (58%) patients and >24h in 58 (42%) patients. In patients with a delay of >24h, 28 (48%) had their surgery 24-36h after admission, 23 (40%) had their surgery between 36 and 48h, and 7 (12%) had their surgery >48h after admission. Patients who were operated >24h after admission had a higher rate of readmission, 4/58 (6.9%) compared to 1/80 (1.25%) in the less than 24h group (p=0.09). Delays in radiology, surgical ward beds and the lack of a dedicated emergency theatre may have contributed to extended waiting times. The results of this study show that the majority (58%) of patients within our cohort were operated on within the WSES guidelines. However, 42% of patients had their surgery in excess of these recommendations. Extended waiting periods may be related to delays in radiology, surgical ward beds and a lack of a dedicated emergency theatre. Patients who were operated on greater than 24h following their admission also had a higher rate of readmission.

The cost of readmissions in hospitals: the case of the Spanish public hospitals

BackgroundIn this paper, we propose a novel model that allows us to understand the effect of hospital readmissions on technology and costs. To do this, we consider that hospitals may experience heterogeneous discharges: on the one hand, discharges corresponding to patients who have completed their healing process in hospital and, on the other hand, discharges resulting from patients who have been discharged too early and are therefore required to be readmitted to hospital. In the first case, discharges involve more resources; in the second case, the patient returns implying an additional use of resources. In tandem, two new issues arise which need to be addressed: a) Does a trade-off exist between the decision to discharge at the finalisation of fully completed treatment or the decision to discharge taken at an earlier stage; b) Readmissions may prove endogenous and if so, their econometric treatment must be considered in order to obtain unbiased results. Our study contributes to the literature by proposing a novel model which estimates the marginal cost of readmissions, thus allowing us to understand the effect of readmission on technology and hospital costs.MethodsTo resolve the foregoing concerns, this paper proposes a theoretical and empirical model based on the dual theory, which combines cost and input-oriented distance functions to obtain the marginal cost of readmissions. Our empirical application uses a panel of Spanish public hospitals observed over the period 2002–2016.ResultsResults indicate that the treatment required by a patient who is readmitted proves more expensive than keeping the patient under observation for a few extra days in order to achieve a definitive discharge. Moreover, this additional cost follows an increasing temporal trend, especially in times of expansion when the availability of resources is greater.ConclusionsGiven that the results indicate that readmissions imply an additional cost for the hospital system, they must be contained. In fact, readmission rates are a significant component of current hospital sector activity improvement strategies. Therefore, knowing the cost which readmission implies is relevant for the design of policies that seek to penalize those hospitals with high readmission rates.

Characteristics and Readmission Risks Following Sepsis Discharges to Home.

To examine the characteristics and risk factors associated with 30-day readmissions, including the impact of home health care (HHC), among older sepsis survivors transitioning from hospital to home. Retrospective cohort study of the Medical Information Mart for Intensive Care (MIMIC)-IV data (2008-2019), using generalized estimating equations (GEE) models adjusting for patient sociodemographic and clinical characteristics. Sepsis admission episodes with in-hospital stays, aged over 65, and discharged home with or without HHC were included. The outcome was all-cause hospital readmission within 30 days following sepsis hospitalization. Covariates, including the primary predictor (HHC vs. Home discharges), were collected during hospital stays. Among 9115 sepsis admissions involving 6822 patients discharged home (66.8% HHC, 33.2% Home), HHC patients, compared with those discharged without services, were older, had more comorbidities, longer hospital stays, more prior hospitalizations, more intensive care unit admissions, and higher rates of septic shock diagnoses. Despite higher illness severity in the HHC discharges, both groups had high 30-day readmission rates (30.2% HHC, 25.2% Home). GEE analyses revealed 14% higher odds of 30-day readmission for HHC discharges after adjusting for risk factors (aOR: 1.14; 95% CI: 1.02-1.27; P=0.02). HHC discharges experienced higher 30-day readmission rates than those without, indicating the need for specialized care in HHC settings for sepsis survivors due to their complex health care needs. Attention to sepsis survivors, regardless of HHC receipt, is crucial given the high readmission rates in both groups. Further research is needed to optimize postacute care/interventions for older sepsis survivors.

Risk factors for readmission following esophagectomy and gastrectomy for cancer.

Hospital readmission after surgery is a key quality indicator. This nationwide cohort study aimed to assess readmission rates following esophagectomy and gastrectomy for cancer and identify associated risk factors. Data were extracted from the Dutch Upper GI Cancer Audit (DUCA) for patients with esophagogastric cancer who underwent esophagectomy or gastrectomy with curative intent between January 2011 and June 2016. Logistic regression analysis identified risk factors for 30-day readmission. In total, 5566 patients were included. Readmission within 30days occurred in 483 of 3488 (13.8%) patients after esophagectomy and 243 of 2078 patients (11.7%) after gastrectomy. Both minor (Clavien Dindo 1-2) and major (Clavien Dindo ≥3) postoperative complications were independent predictors of readmission after esophagectomy (OR 2.99; 95%CI 2.23-4.02; p< 0.001 and OR 5.20; 95%CI 3.82-7.09; p< 0.001). Specific complications included pulmonary (OR 1.49; 95%CI 1.20-1.85; p< 0.001), gastrointestinal (OR 2.43; 95%CI 1.94-3.05; p< 0.001), and infectious (OR 2.27; 95%CI 1.60-3.22; p< 0.001). Prolonged length of stay (pLOS) was associated with higher readmission rates in patients without complications following esophagectomy (OR 1.91 95% CI 1.19-3.07; p= 0.008), but lower rates in those with complications (OR 0.65 95% CI 0.51-0.83; p< 0.001). For gastrectomy, postoperative complications were also linked to readmission (OR 3.18; 95%CI 2.30-4.40; p< 0.001), particularly gastrointestinal (OR 2.16; 95%CI 1.40-3.32; p< 0.001), and infectious (OR 3.80; 95%CI 2.53-5.71; p< 0.001). Readmission after esophagogastric resection is common, particularly among patients with both minor and major postoperative complications. Prolonged stay after esophagectomy impacts readmission risk differently based on the presence of complications.

Using large administrative data for mining patients' trajectories for risk stratification: An example from urological diseases.

To identify latent clusters among urological patients by examining hospitalisation rate trajectories and their association with risk factors and outcome quality indicators. Victorian Admitted Episodes Dataset, containing information on all hospital admissions in Victoria from 2009 to 2019. The top twenty ICD-10 primary diagnosis codes in urology were used to select patients (n = 98,782) who were included in the study. Latent class trajectory modelling (LCTM) was used to cluster urological patient hospitalisation trajectories. Logistic regression was used to find baseline factors that influence cluster membership, the variables tested included comorbidities, baseline diagnosis codes, and socio-demographic factors. The analysis was further stratified into non-surgical procedures and surgical procedures. Five clusters of hospitalisation trajectories were identified based on clustering hospitalisation rates over time. Higher hospitalisation clusters were strongly associated with longer length of stay, higher readmission rates and higher complication rates. Higher-risk groups were strongly associated with comorbidities such as renal disease and diabetes. For surgical procedures, urological cancers (kidney, prostate and bladder cancer) and irradiation cystitis were associated with higher-risk groups. For non-surgical procedures, calculus of the bladder, urethral stricture and bladder neck obstruction were associated with higher-risk groups. For patients with two or more admissions, liver cardiovascular disease and being diagnosed with benign prostatic hyperplasia were also associated with higher risk groups. A novel statistical approach to cluster hospitalisation trajectories for urological patients was used to explore potential clusters of patient risks and their associations with outcome quality indicators. This study supports the observation that baseline comorbidities and diagnosis can be predictive of higher hospitalisation rates and, therefore, poorer health outcomes. This demonstrates that it is possible to identify patients at risk of developing complications, higher length of stay and readmissions by using baseline comorbidities and diagnosis from administrative data.

EGS SO34 - Idiopathic pancreatitis - a myth or a reality?

Abstract Background Acute pancreatitis is characterized by frequent episodes of inflammation in the pancreas.The most common causes are alcohol abuse and gallstones but approximately 30% of cases are defined as idiopathic because initial evaluation fails to detect the aetiology.This study aims to investigate the aetiology and the reasons for the incorrect labelling of patients with pancreatitis as idiopathic. Method This is a retrospective study and included patients with a diagnosis of idiopathic pancreatitis (IP) between 1 May 2019 and 31 April 2023.Cases were eligible for inclusion if they had been discharged as IP. Data were collected following review of patient notes into Microsoft Excel. Results A total of 129 patients were identified of whom the majority of patients did not find to have gallstones (88%), did not report alcohol use (91%), and did not experience trauma (87%). However, MRCP and EUS were not performed in all patients before they are labelled as idiopathic. Ultrasound was the most commonly performed diagnostic procedure (98%), while MRCP (40%) and EUS (8%) were less frequently utilized. Surprisingly, a quarter of patients underwent a laparoscopic cholecystectomy. Nutritional referrals were lacking in a significant portion of cases and the readmission rates were high (65%). Conclusion The most surprising elements in the data include the high incidence of unperformed diagnostic procedures to exclude the common causes of pancreatitis.Also,the underutilization of nutritional referrals and the high readmission rates suggest potential areas for improvement in the diagnostic workup and management of IP, as well as raising questions about the current clinical practices and their efficacy in this cohort.

Comparing Urethral Stricture Rates Following Bipolar and Monopolar Transurethral Resection of the Prostate: A Retrospective Study.

Aim The aim is to compare the incidence of urethral strictures and other complications following monopolar and bipolar transurethral resection of the prostate (TURP). Method We conducted a retrospective study to compare patients who underwent bipolar TURP with those who underwent monopolar TURP between 2017 and 2023. The collected data included demographics, age, history of urethral stricture, prostate size, operation duration, and postoperative complications, such as blood transfusion, transurethral resection (TUR) syndrome, and other relevant data points. Results The COVID-19 pandemic significantly affected the number of surgeries performed. A total of 572 patients who underwent TURP at our center during this period were identified, 302 of whom underwent monopolar TURP, and 270 underwent bipolar TURP. Bladder neck stenosis was more frequently identified in the monopolar group compared to the bipolar group (1.99% (6) vs. 0.7% (2)). In the monopolar group, 6.62% (20) of the patients had strictures compared to 4.07% (11) in the bipolar group; however, this difference is not statistically significant. The bipolar group had a higher incidence of urinary incontinence (5.6% (15) vs. 3.3% (10)), whereas the monopolar group had higher readmission rates (18.8% (57) vs. 13.7% (37)) and a higher frequency of delayed trial without catheter (TWOC) (84% (254) vs. 75.9% (205)). Conclusion We believe that our findings contribute towards resolving the debate between stricture complication rates in monopolar versus bipolar TURP. Our analysis revealed no statistically significant differences in stricture rates between the two groups. However, we noted differences in other complications, such as higher rates of urinary incontinence in the bipolar group, whereas the monopolar group had increased rates of readmission and bladder neck stenosis.

Abstract 4147608: Trends in Mortality and 30-Day Readmission Rates Among Heart Failure Patients Undergoing Cardiac Rehabilitation: A Nationwide Analysis from 2017 to 2020

Background: Heart failure (HF) is a significant public health concern, affecting approximately 6.2 million adults in the United States, with high mortality and readmission rates. Cardiac rehabilitation (CR) programs have been widely recognized as a crucial component of HF management, aiming to improve physical function, reduce symptoms, and enhance quality of life. Despite the established benefits of CR, there is a need to understand the trends in mortality and readmission rates among HF patients participating in these programs. We aim to analyze mortality and 30-day readmission rate trends among heart failure patients undergoing cardiac rehabilitation from 2017 to 2020 using NRD data. Hypothesis: We hypothesize a significant downward trend in mortality rates and significant yearly variation in 30-day readmission rates among heart failure patients undergoing cardiac rehabilitation. Methods: We analyzed NRD data from 2017 to 2020, including patients with ICD-10 codes I50 (heart failure) and Z5189 (cardiac rehabilitation). Trend analyses were performed using Ordinary Least Squares (OLS) regression for mortality rates and the Cochrane-Armitage test for binary data. Multivariate regression adjusted for age, sex, and comorbidities. Statistical analyses were conducted using STATA version 18. Results: From 2017 to 2020, annual mortality rates were 6.9% (95% CI: 0.95% to 12.85%), 5.5% (95% CI: 0.47% to 10.52%), 4.6% (95% CI: -0.51% to 9.68%), and 1.9% (95% CI: -1.90% to 5.74%), respectively. The mean age was 78 years, with 54% were female. OLS regression showed a significant downward trend in mortality (p = 0.025), while the Cochrane-Armitage test did not (p = 0.998). Multivariate regression also indicated a downward trend, though individual predictors were insignificant (p=0.576). For 30-day readmission rates from 2017 to 2020, annual margins were 21.5% (2017), 21.7% (2018), 18.0% (2019), and 34.3% (2020), showing significant yearly variation. Conclusion: Despite the varying range of 30-day readmission within the years of interest, there seems to be a significant downward trend in mortality for heart failure patients who underwent cardiac rehabilitation. Further studies are required to corroborate these findings as understanding CR program outcomes can help identify improvement areas, guide resource allocation, and inform healthcare policy decisions.

Impact of Data Pre-Processing Techniques on XGBoost Model Performance for Predicting All-Cause Readmission and Mortality Among Patients with Heart Failure

Background: Heart failure poses a significant global health challenge, with high rates of readmission and mortality. Accurate models to predict these outcomes are essential for effective patient management. This study investigates the impact of data pre-processing techniques on XGBoost model performance in predicting all-cause readmission and mortality among heart failure patients. Methods: A dataset of 168 features from 2008 heart failure patients was used. Pre-processing included handling missing values, categorical encoding, and standardization. Four imputation techniques were compared: Mean, Multivariate Imputation by Chained Equations (MICEs), k-nearest Neighbors (kNNs), and Random Forest (RF). XGBoost models were evaluated using accuracy, recall, F1-score, and Area Under the Curve (AUC). Robustness was assessed through 10-fold cross-validation. Results: The XGBoost model with kNN imputation, one-hot encoding, and standardization outperformed others, with an accuracy of 0.614, recall of 0.551, and F1-score of 0.476. The MICE-based model achieved the highest AUC (0.647) and mean AUC (0.65 ± 0.04) in cross-validation. All pre-processed models outperformed the default XGBoost model (AUC: 0.60). Conclusions: Data pre-processing, especially MICE with one-hot encoding and standardization, improves XGBoost performance in heart failure prediction. However, moderate AUC scores suggest further steps are needed to enhance predictive accuracy.