Independent Predictors Of Readmission Research Articles

Assessing the impact of socioeconomic distress on hospital readmissions after cardiac surgery

BackgroundThe impact of socioeconomic distress on readmission rates following cardiac surgery has not been studied. We hypothesized that patients living in distressed communities would have a higher 30-day readmission rate after cardiac surgery compared to those living in less distressed communities. MethodsPatients undergoing isolated coronary artery bypass grafting (CABG) between 2016 and 2023 within a regional collaborative were identified. The Distressed Communities Index (DCI) and Area Deprivation Index (ADI) were used to measure socioeconomic distress. Two logistic regression models were performed to evaluate 30-day readmission rates: one incorporating ADI and the other including DCI. Models were adjusted for the Society of Thoracic Surgeons (STS) Predicted Risk of Mortality (PROM) score, postoperative complications, length of stay (LOS), year of surgery, and discharge disposition. ResultsA total of 16,369 patients were included, of whom 10% were readmitted within 30 days of discharge. Readmitted patients were more likely to be female (32% vs 23.3%) and to develop postoperative complications (47% vs 35%) and less likely to be discharged to home (70.6% vs 83.5%; P < .001 for all). On multivariable analysis, STS PROM score, postoperative complications, prolonged LOS, and discharge to a facility or leaving against medical advice were predictive of higher readmission rates. Socioeconomic distress was not an independent predictor of readmission in the model that used DCI (odds ratio [OR], 0.93; 95% confidence interval [CI], 0.76-1.15) or in the model that used ADI (OR, 1.17; 95% CI, 0.83-1.64). ConclusionsIn patients undergoing CABG, increasing socioeconomic distress does not predict higher 30-day readmission rate. Other factors, such as discharge location, have a greater impact on readmission rate.

The effect of social deprivation on hospital utilization following shoulder arthroplasty

BackgroundDisparities in social determinants of health have been linked to worse patient-reported outcomes and higher rates of hospital readmission following shoulder arthroplasty. Identification of perioperative predictors of increased healthcare utilization is of particular interest to surgeons to improve outcomes and mitigate the total cost of care. The effect of social deprivation on healthcare utilization has not been fully characterized in the context of shoulder arthroplasty. MethodsA retrospective review was performed from of a single institution’s experience with primary shoulder arthroplasty between 2012 and 2020. Demographic variables (age, race, and legal sex) and healthcare utilization (hospital readmission, emergency department (ED) visits, follow-up visits, and telephone calls) were recorded within 90 days of surgery. The Area Deprivation Index was recorded, and patients were separated into terciles according to their relative level of social deprivation. Outcomes were then stratified based on Area Deprivation Index tercile and compared. ResultsA total of 780 patients were included. The least, intermediate, and most deprived groups consisted of 195, 371, and 214 patients, respectively. The level of social deprivation was not a predictor of increased healthcare utilization through readmission, the ED, or the outpatient clinic. Identifying as Black or African American was an independent predictor of readmission and ED visitation. Female sex was an independent predictor of increased postoperative telephone calls. ConclusionPatients undergoing shoulder arthroplasty have similar use of hospital resources regardless of their level of social deprivation. We hope these results can be used to guide clinical decision-making, increase transparency, and manage patient outcomes following shoulder arthroplasty surgery.

The 5-factor modified frailty index (mFI-5) predicts adverse outcomes after elective anterior cervical discectomy and fusion (ACDF)

BackgroundAnterior cervical discectomy and fusion (ACDF) is a reliable procedure commonly performed in older patients with degenerative diseases of the cervical spine. Over 130,000 procedures are performed every year with an annual increase of 5%, and overall morbidity rates can reach as high as 19.3%, indicating a need for surgeons to gauge their patients’ risk for adverse outcomes. Frailty is an age-associated decline in functioning of multiple organ systems and has been shown to predict adverse outcomes following various spine procedures. There have been several proposed frailty indices of various factors including the 11-factor modified frailty index (mFI-11), which has been shown to be an effective tool for predicting complications in patients undergoing ACDF. However, there is a paucity of literature assessing the utility of the 5-factor modified frailty index (mFI-5) as a risk stratification tool for patients undergoing ACDF. The purpose of this study was to analyze the predictive capability of the mFI-5 score for 30-day postoperative adverse events following elective ACDF. MethodsA retrospective review was performed using the National Surgical Quality Improvement Program (NSQIP) database from 2010 through 2019. Patients older than 50 years of age who underwent elective ACDF were identified using Current Procedural Terminology ([CPT] codes 22554, 22551, 22552, and 63075). Exclusion criteria removed patients under the age of 51, as well as those with fractures, sepsis, disseminated cancer, a prior operation in the last 30 days, ascites, wound infection, or an emergency surgery. Patients were grouped using mFI scores of 1, 2, and 3+. Univariate analysis, using chi-squared and one-way analysis of variance (ANOVA) tests, was conducted to compare demographics, comorbidities, and postoperative complications across the varying cohorts based on mFI-5 scores. Multivariate logistic regression, including patient demographics and preoperative comorbidities as covariates, was performed to evaluate if mFI-5 scores were independent predictors of 30-day postoperative adverse events. Covariates including race, BMI, sex, ASA, and comorbidities were included in regression models. ResultsThe 45,991 patients were identified and allocated in cohorts based on mFI-5 score. Rates for superficial surgical site infection (SSI), organ/deep space SSI, pneumonia, progressive renal insufficiency, acute renal failure (ARF), urinary tract infection (UTI), stroke/cardiovascular accident (CVA), cardiac arrest requiring cardiopulmonary resuscitation (CPR), myocardial infarction, bleeding requiring transfusions, deep vein thrombosis/thrombophlebitis, sepsis, septic shock, readmissions, reoperation, and mortality incrementally increased with mFI-5 scores from 0 to 3+. Multivariate regression analysis revealed that mFI-5 scores 1 to 3+ increased the odds, in a stepwise manner, of total complications, cardiac arrest requiring CPR, pneumonia and mortality. MFI-5 scores of 2 and 3+ were independent predictors of readmission (2: OR=1.5, p<.001; 3+: OR=2.0, p<.001) and myocardial infarction (2: OR=3.4, p=.001; 3+: OR=6.9, p<.001). A score of 3+ increased the odds of ARF (OR=9.7, p=.022), septic shock (OR=3.6, p=.036), UTI (OR=2.1, p=.007), bleeding requiring transfusions (OR=2.1, p=.016), and reoperations (OR=1.7, p=.004). ConclusionmFI-5 score is a quick and viable option for surgeons to use as an assessment tool to stratify high risk patients undergoing elective ACDF, as increasing mFI-5 scores showed significantly higher rates of all adverse outcomes accounted for in this study, except for deep incisional SSI, wound disruption, and PE. Additionally, moderate to severe mFI-5 scores of 2 or 3+ were independent predictors for 30-day postoperative ARF, UTI, MI, bleeding requiring transfusions, septic shock, reoperation, and readmissions following elective ACDF surgery in adults over 50 years old.

Predictors of Readmission and Reoperation Following Shoulder Arthroplasty in Patients Under 45 Years of Age.

The use of shoulder arthroplasty has increased among all age groups, albeit most prominently in older patients. While previous studies have investigated predictors of short-term readmission and reoperation in the general population, there is a paucity of literature available on these in patients under 45 years of age. This study aimed to identify the predictors of 30-day readmission and reoperation following shoulder arthroplasty in patients under 45 years of age. A retrospective query in the American College of Surgeons National Surgical Quality Improvement Program database from 2011 to 2019 was used to identify patients who underwent primary reverse and anatomic total shoulder arthroplasty and hemiarthroplasty. Multivariate logistic regression was used to identify predictors of 30-day readmission and reoperation. A total of 530 patients were included. Multivariate regression revealed that Black race and Hispanic ethnicity were independent predictors of readmission. Functional dependence, hypertension requiring medication, and prolonged length of stay predicted reoperation. Finally, low hematocrit and prolonged length of stay predicted morbidity. Identifying and accounting for these risk factors for poor outcomes may help improve perioperative risk stratification. As a result, these findings have the potential to reduce healthcare costs associated with readmission and reoperation following shoulder arthroplasty in young patients. Our results also highlight the underlying disparities in healthcare outcomes among racial and ethnic groups that must be considered.

Understanding the role of frailty in local and systemic complications and healthcare resource utilization in acute pancreatitis: Findings from a national cohort

BackgroundAcute pancreatitis (AP) is a significant gastrointestinal cause of hospitalization with increasing incidence. Risk stratification is crucial for determining AP outcomes, but the association between frailty and AP outcomes is poorly understood. Moreover, age disparities in severity indices for AP complicate risk assessment. This study investigates frailty's impact on local and systemic complications in AP, readmission rates, and healthcare resource utilization. MethodsUsing the National Readmission Database from 2016 to 2019, we identified adult AP patients and assessed frailty using the Frailty Risk Score. Our analysis included local and systemic complications, resource utilization, readmission rates, procedures performed, and hospitalization outcomes. Multivariate regression was employed, and statistical significance was set at P < 0.05 using Stata version 14.2. ResultsAmong 1,134,738 AP patients, 6.94 % (78,750) were classified as frail, with a mean age of 63.42 years and 49.71 % being female. Frail patients experienced higher rates of local complications (e.g., pseudocyst, acute pancreatic necrosis, walled-off necrosis) and systemic complications (e.g., pleural effusion, acute respiratory distress syndrome, sepsis, abdominal compartment syndrome) compared to non-frail patients. Frailty was associated with increased readmission rates and served as an independent predictor of readmission. Frail patients had higher inpatient mortality (7.11 % vs. 1.60 %), longer hospital stays, and greater hospitalization costs. ConclusionFrailty in AP patients is linked to elevated rates of local and systemic complications, increased mortality, and higher healthcare costs. Assessing frailty is crucial in AP management as it provides a valuable tool for risk stratification and identifying high-risk patients, thereby improving overall outcomes.

Impact of Center Procedural Volume on Mortality and Readmission Rates Following Pericardiectomy in the United States

Our study aimed to explore the national trends in the rates of perioperative complications, in-hospital mortality, and readmissions after pericardiectomy and the impact of center volume on these outcomes. Using the Nationwide Readmission Database, we identified patients who underwent isolated pericardiectomy from 2010 to 2019. In-hospital mortality and readmission rates were assessed using orthogonal polynomial contrasts, with the linear and nonlinear trends evaluated as needed. Multivariable logistic regression models were constructed to identify the independent predictors of mortality and readmission. All analyses accounted for the Nationwide Readmission Database sampling design and were performed using SAS version 9.4 (SAS Institute Inc. Cary, NC.) with p <0.05 used to indicate statistical significance. A total of 26,169 hospitalizations for pericardiectomy were identified during the study period. The median age was 59years and 44% were female. In-hospital mortality was 5.2%, and the median length of stay was 7days. Advanced age, higher co-morbidity index, and lower annual facility pericardiectomy volume were independent predictors of in-hospital mortality. The 30- and 90-day readmission rates after pericardiectomy were 18% and 28%, respectively. Previous cardiac surgery, diagnosis of constrictive pericarditis, and greater co-morbidity score were independent predictors of readmission. In conclusion, isolated pericardiectomy rates have remained mostly constant, with relatively small changes in in-hospital mortality and 30- and 90-day readmission rates over the last decade. Advanced age, lower facility pericardiectomy volume, and higher Elixhauser co-morbidity index are independent predictors of surgical mortality.

Efficacy and safety analysis of angiotensin receptor neprilysin inhibition(ARNI)in patients with heart failure: a real-world retrospective study

BackgroundIn a large randomized controlled trial (PARADIGM-HF), ARNI has been shown to significantly reduce cardiovascular mortality and hospitalization for patients with reduced ejection fraction in heart failure. This study analyzed the efficacy and safety of ARNI on the basis of various types of heart failure patients in southwestern Sichuan Province.MethodsThis study included patients with heart failure who were treated at the Affiliated Hospital of North Sichuan Medical College from July 2017 to June 2021. This study analyzed the efficacy and safety of ARNI in the treatment of heart failure, and analyzed the risk factors for readmission after ARNI treatment.ResultsAfter propensity score matching, a total of 778 patients were included in the study. The readmission rate for heart failure in patients treated with ARNI (8.7%) was significantly lower than that in the standard treatment group (14.5%) (P = 0.023). Both the proportion of patients with increased LVEF and with decreased LVEF were higher in the ARNI treatment group than in the conventional therapy group. Compared with receiving standard medical treatment, combined ARNI treatment resulted in a greater reduction in SBP (-10.00, 95%CI: -24.00-1.50 vs. -7.00, 95%CI: -20.00-4.14; P = 0.016) in HF patients. Combination ARNI therapy did not increase the risk of adverse events. The study found that age (> 65 vs. ≤65 years) (OR = 4.038, 95%CI: 1.360-13.641, P = 0.013) and HFrEF (OR = 3.162, 95%CI: 1.028–9.724, P = 0.045) were independent predictors of readmission in HF patients treated with ARNI.ConclusionPatients with heart failure treated with ARNI can improve clinical symptoms and reduce the risk of readmitted hospital admission. Age > ~ 65 years and HFrEF were independent predictors of readmission in HF patients treated in ARNI group.

Screening for Media Use in the Emergency Department Among Young Australians: Cross-sectional Study.

Research on problematic internet use has largely adhered to addiction paradigms, possibly impeding the identification of specific internet behaviors related to psychopathology. This study presents a novel approach to screening for specific problematic internet behaviors by using a new measure, the emergency department media use screener (EDMUS). The purpose of this study was to identify patterns of internet use in young people presenting with mental health concerns to the emergency department (ED), ascertain associations with their mental health, and evaluate whether the EDMUS can be used to predict subsequent ED presentations within 3 months. This cross-sectional retrospective study of Australian young people (N=149, aged 11-25 years; female: n=92, 61.7%) sought to use the EDMUS, a 24-item questionnaire, to identify problematic internet behaviors, including accessing or posting prosuicidal or proeating disorder content, cyberbullying, and inappropriate digital content. Data on each person's mental health were extracted from electronic medical records to look for associations with EDMUS responses and ED re-presentation over 3 months. EDMUS items were grouped into clusters for analysis using chi-square tests, binary logistic regression, and path analyses. Sharing suicidal digital content was the most common problematic internet use pattern identified by the EDMUS. However, this did not correlate with having a prior mental health diagnosis or predict readmission. Most participants had families with a concern for their internet use; however, this was less likely in participants with a diagnosis of personality disorder. Diagnoses of personality disorder or posttraumatic stress disorder were independent predictors of readmission (P=.003; P=.048). Although a history of complex psychopathology increases the likelihood of subsequent ED presentations, its links to internet use-related behaviors are still unclear. The EDMUS has potential for identifying young people who are most vulnerable to problematic internet behaviors and offers the opportunity for early intervention and potential prevention of more entrenched difficulties.

Racial disparities in readmission rates following surgical treatment of pediatric developmental dysplasia of the hip.

Across orthopedic subspecialties, significant racial disparities have been identified with regard to postoperative outcomes. Despite these findings among adult patients, the literature assessing these disparities within pediatric orthopedics is limited. The purpose of this study was to determine the independent predictors for unplanned readmission following surgical treatment of developmental dysplasia of the hip. Pediatric patients undergoing hip dysplasia surgery from 2012 to 2019 were identified in the National Surgical Quality Improvement Program-Pediatric database. Two patient groups were defined: patients who had unplanned hospital readmission within 30days of surgery and patients who were not readmitted. Clinical characteristics assessed included gender, race, and American Society of Anesthesiologists (ASA) class. Risk factors for complications were assessed using bivariate and multivariate analysis. Of 6561 pediatric patients undergoing surgical treatment for hip dysplasia, 540 (8.2%) had unplanned readmission. On bivariate analysis, non-white race (Black, Asian, Hispanic, American Indian, and Native Hawaiian), an ASA class of III, IV, or V, pulmonary, renal, neurological, and gastrointestinal comorbidities, as well as immune disease, steroid use, and nutritional support were significantly associated with unplanned readmission (p < 0.05 for all). After controlling for confounding variables on multivariate analysis, non-white race (OR 1.46; p = 0.042) and ASA class of III-V (OR 2.21; p = 0.002) were found to be independent predictors for readmission. Clinicians should be advised of the increased readmission rates observed in non-white patients and those of higher ASA scores. Further work is needed to combat existing disparities within pediatric orthopedics.

Myocardial Strain to Predict Mid-term Mortality and Re-hospitalization in Patients With Heart Failure and Reduced Ejection Fraction

Background: Heart failure (HF) is a severe clinical syndrome caused by diversed etiologies. Classically left ventricle ejection fraction (LVEF) has been used as a diagnostic marker as well as to subdivide HF into 3 groups (HFpEF, HFmEF and HFrEF). However, the prognostic value of this index is not consistent in comparison to LV strain (GLS, GCS) which are not only able to detect heart failure at a very early stage (precede to EF change) but also to predict the primary outcome including HF readmission and death. The prognostic role of LV strain is independent and incremental to conventional echocardiographic parameters.&#x0D; Methods: 67 patients diagnosed with chronic HFrEF (EF &lt; 40%) in Vietnam National Heart Institute were consecutively enrolled in our study from January 2016 to September 2016. Clinical data were comprehensively evaluated and conventional echocardiographic parameters and two LV strain indices (GLS &amp; GCS) were measured using speckle-tracking. All patients were followed-up for all-cause 12-month readmission or death after discharge. The relation between echocardiographic parameters and clinical events was analyzed in Cox proportional hazard model.&#x0D; Results: GLS had a prognostic value of composite events after being adjusted with age, sex, heart rate, SBP, DBP, NT-ProBNP, renal clearance, LVEF and LVDd. GLS (cut-off = -7.5%; AUC = 0.738; p = 0.003) was a stronger predictor of composite event compared to LVEF (AUC= 0.66, p = 0.042) LVDd (AUC = 0.637; p = 0.025), LA diameter (AUC = 0.614, p = 0.03), NT-ProBNP (AUC = 0.663; p = 0.04) and hs-Troponin T (AUC = 0.592; p = 0.039).&#x0D; Conclusion: Global longitudinal strain is and strong and independent predictor of readmission and death in patients with heart failure with reduced ejection fraction.

Abstract WP205: Principal Diagnosis And Independent Predictors For 30-day Readmissions In Cryptogenic Stroke

Background: Cryptogenic stroke is defined as cerebral infraction that can’t be attributed to large artery atherosclerosis, small artery disease, or cardio-embolism, despite a standard cardiovascular and serologic workup. Our objective was to identify rates and causes for readmissions of cryptogenic stroke. Methods: A retrospective analysis was conducted using National Readmission Database 2018 with ICD-10 codes. Readmission rate and principal diagnosis for 30-day readmission for cryptogenic stroke were primary outcomes. Secondary outcomes were in-hospital mortality, and independent predictors of readmission. Multivariate logistic regression analysis was used for assessment. Results: Within 30 days, 21,418 out of 206,627 patients were readmitted, giving a 30-day readmission rate of 10.4%. For the index admissions, 49.9% were females, and mean age was 70 years. The in-hospital mortality rate for index admissions was 2.4% while it was 4.9% for the readmissions. The ten most common principal diagnosis for 30-day readmissions were subsequent admission for cryptogenic stroke (10.5%), sepsis (7.1%), acute kidney injury (3.2%), transient ischemic attack (1.9%), urinary tract infection (1.8%), aspiration pneumonitis (1.7%), hypertensive heart and chronic kidney disease (HHD/CKD) with heart failure (1.6%), left carotid artery stenosis/occlusion (1.5%), non-specific cerebral infarction (1.3%), and HHD with heart failure (1.2%). The independent predictors for readmission were heart failure, ischemic heart disease, ventricular arrhythmia, infective endocarditis, peripheral artery disease, venous thromboembolism, pulmonary embolism, and diabetes mellitus. Conclusions: Readmission rate for cryptogenic stroke is 10.4% within 30 days and is associated with higher mortality and costs. Most common principal diagnosis for readmission are cryptogenic stroke, sepsis, acute kidney injury, transient ischemic attack, urinary tract infection, and aspiration pneumonitis. The independent predictors for readmission are heart failure, ischemic heart disease, ventricular arrhythmia, infective endocarditis, peripheral artery disease, venous thromboembolism, pulmonary embolism, and diabetes mellitus.

Association of protein intake during hospitalization with readmission in older adult patients with heart failure at risk of malnutrition.

The influence of protein intake during hospitalization on postdischarge readmission in patients with heart failure (HF) is still unclear. This study aimed to investigate the relationship between protein intake and readmission in older adult patients with HF at risk of malnutrition. This retrospective observational study was conducted at a single acute care hospital. Patients were diagnosed with HF between April 2017 and March 2019, aged ≥65 years, and had a body mass index <35 and Geriatric Nutritional Risk Index <92 were included in the analysis. The primary outcome was HF-related readmission within 1 year after discharge. The Cox proportional hazards model was used to determine whether protein intake was an independent predictor of readmission within 1 year. Ultimately, 165 patients were included in the analysis: 105 patients did not require readmission, and 60 required readmission because of HF-related events. Multivariate analysis showed that protein intake <1.2 g/kg/day was an independent contributor to readmission in either model (model 1: hazard ratio [HR] = 2.07 [95% CI, 1.07-4.01], P = 0.030; model 2: HR = 2.24 [95% CI, 1.15-4.37], P = 0.018; model 3: HR = 2.70 [95% CI, 1.23-5.94], P = 0.013; and model 4: HR = 2.88 [95% CI, 1.28-6.51], P = 0.011). Low protein intake during hospitalization in older adult patients with HF at risk of malnutrition may increase the rate of readmission within 1 year after discharge. Nutrition intervention should be provided to these patients early during their hospitalization to ensure sufficient protein intake to maintain and improve their nutrition status and activity level.

Etiologies and Predictors of 30-Day Readmission in Heart Failure: An Updated Analysis.

Readmissions in heart failure (HF), historically reported as 20%, contribute to significant patient morbidity and high financial cost to the healthcare system. The changing population landscape and risk factor dynamics mandate periodic epidemiologic reassessment of HF readmissions. National Readmission Database (NRD, 2019) was used to identify HF-related hospitalizations and evaluated for demographic, admission characteristics, and comorbidity differences between patients readmitted vs. those not readmitted at 30-days. Causes of readmission and predictors of all-cause, HF-specific, and non-HF-related readmissions were analyzed. Of 48,971 HF patients, the readmitted cohort was younger (mean 67.4 vs. 68.9 years, p≤0.001), had higher proportion of males (56.3% vs. 53.7%), lowest income quartiles (33.3% vs. 28.9%), Charlson comorbidity index (CCI) ≥3 (61.7% vs. 52.8%), resource utilization including large bed-size hospitalizations, Medicaid enrollees, mean length of stay (6.2 vs. 5.4 days), and disposition to other facilities (23.9% vs. 20%) than non-readmitted. Readmission (30-day) rate was 21.2% (10,370) with cardiovascular causes in 50.3% (HF being the most common: 39%), and non-cardiac in 49.7%. Independent predictors for readmission were male sex, lower socioeconomic status, nonelective admissions, atrial fibrillation, chronic obstructive pulmonary disease, chronic kidney disease, anemia, and CCI ≥3. HF-specific readmissions were significantly associated with prior coronary artery disease and Medicaid enrollment. Our analysis revealed cardiac and noncardiac causes of readmission were equally common for 30-day readmissions in HF patients with HF itself being the most common etiology highlighting the importance of addressing the comorbidities, both cardiac and non-cardiac, to mitigate the risk of readmission.

An evaluation of risk factors for readmission in patients receiving outpatient parenteral antimicrobial therapy.

Outpatient parenteral antimicrobial therapy (OPAT), when required, is beneficial to patients and healthcare systems by reducing hospital length-of-stay, providing cost savings, and improving patient satisfaction. The purpose of this study is to determine readmission rates and associated risk factors in patients receiving OPAT at home. This retrospective study included hospitalized patients 15 years and older who were discharged on intravenous antimicrobial therapy via OPAT at home between January 2018 and December 2019. Patients receiving antimicrobials at a skilled nursing facility, long-term acute care, or dialysis center, and those who began OPAT at home directly from the outpatient setting were excluded. The primary outcome of this study was all-cause 30-day readmission rate. Secondary outcomes included 90-day readmission rate, rates of complications related to OPAT, emergency department visits during OPAT, and predictors of all-cause 30-day readmission through a logistic regression analysis. Two hundred individual patients were included in the analysis; 60% were male and the mean age was 49 years. The most common indications for OPAT at home were bone and joint infection (52%) and bacteremia (26%). Forty patients (20%) experienced an unplanned, all-cause 30-day readmission, with a total of 48 readmission events. Of the 40 patients who were readmitted within 30 days, 20 (50%) were due to non-OPAT related reasons. Sixty patients (30%) experienced an OPAT-related complication, and chronic kidney disease was found to be an independent predictor of readmission (OR: 2.8, 95% CI: 1.0-7.6). Patients receiving OPAT at home are at increased risk for early hospital readmission, but it is often due to reasons not associated with OPAT. Patients with chronic kidney disease beginning OPAT at home should be closely monitored after discharge.

Predictors of 30-Day Re-admission in Cardiac Patients at Heart Hospital, Qatar.

Cardiovascular disease patients are more likely to be readmitted within 30 days of being discharged alive. This causes an enormous burden on health-care systems in terms of poor care of patients and misutilization of resources. This study aims to find out the risk factors associated with 30-day readmission in cardiac patients at Heart Hospital, Qatar. A total of 10,550 cardiac patients who were discharged alive within 30 days at the heart hospital in Doha, Qatar, from January 2015 and December 2019 were analyzed. The bootstrap method, an internal validation statistical technique, was applied to present representative estimates for the population. Out of the 10,550 cardiac patients, there were 8418 (79.8%) index admissions and 2132 (20.2%) re-admitted at least once within 30 days after the index admission. The re-admissions group was older than the index admission group (65.6 ± 13.2 vs. 56.0 ± 13.5, P = 0.001). Multinomial regression analysis showed that females were 30% more likely to be re-admitted than males (adjusted odds ratio [aOR] 1.30, 95% confidence interval [CI]: 1.11-1.50, P = 0.001). Diabetes (aOR 1.36, 95% CI: 1.20-1.53, P = 0.001), chronic renal failure (aOR 1.93, 95% CI: 1.66-2.24, P = 0.001), previous MI (aOR 3.22, 95% CI: 2.85-3.64, P = 0.001), atrial fibrillation (aOR 2.17, 95% C.I. : 1.10-2.67, P = 0.01), cardiomyopathy (aOR 1.72, 95% CI 1.47-2.02, P = 0.001), and chronic heart failure (aOR 1.56, 95% C.I.: 1.33-1.82, P = 0.001) were also independent predictors for re-admission in the regression model. C-statistics showed these variables could predict 82% accurately hospital readmissions within 30 days after being discharged alive. The model was more than 80% accurate in predicting 30-day readmission after being discharged alive. The presence of five or more risk factors was found to be crucial for readmissions within 30 days. The study may help design interventions that may result in better outcomes with fewer resources in the population.

Incidence, Burden, and Predictors of Readmission for Acute Alcoholic Pancreatitis: A National Analysis over 11Months.

Data regarding incidence, health-care burden, and predictors for readmission in patients with acute alcoholic pancreatitis (AAP) is scarce. We aim to identify incidence, health-care burden, and predictors of readmission over an 11-month period. Retrospective cohort study using the 2016 National Readmission Database of adult patients admitted with a principal diagnosis of AAP in January and 11-month readmission follow up for all-cause readmission. Incidence of all-cause readmission, mortality rate, morbidity, length of stay (LOS), total hospitalization charges and costs were evaluated. Independent risk factors for all-cause readmission were identified using a Cox multivariate logistic regression analysis. A total of 6633 patients were included in the study. The mean age was 45.7years and 28.9% of patients were female. 73.1% of patients had a modified BISAP score of 0. The 11-month readmission rate was 43.1%. The main cause of readmission was another episode of AAP. The mortality rate of readmission was 0.5% and the mortality rate during the index admission (IA) was 1.1% (P = 0.03). The mean LOS, total hospitalization charges and costs for readmission were 4.5days, $34,307 and $8958, respectively. Independent predictors of readmission were Charlson Comorbidity Index score of ≥ 3, associated chronic alcoholic pancreatitis, and chronic pancreatitis (CP) from other causes. Among patients admitted with AAP, the 11-month readmission rate was 43.1%. Over one-third of readmissions were due to another episode of AAP. Readmission associated with significant resource utilization. Special attention should be placed in patients with underlying CP due to the increased risk of readmission.

RF24 | PSUN108 Inpatient and Readmission Outcomes Following Endoscopic Gastrectomy Versus Gastrojejunostomy in Patients with Morbid Obesity: A Nationwide Retrospective Analysis

Abstract The prevalence of obesity has increased worldwide leading to an increase in associated comorbidities and mortality. Endoscopic procedures are emerging treatments for obesity. We aimed to compare the outcomes of two of these procedures. This was a retrospective cohort study involving adults above 18 years old with morbid obesity admitted for either endoscopic vertical sleeve gastrectomy (EVSG) or endoscopic gastrojejunostomy (EGJ) in the US in 2019. We extracted data from the Nationwide Readmissions Database (NRD) in 2019, coding done with the International Classification of Diseases Tenth Revision, Clinical Modification (ICD10-CM). The study included hospitalizations with morbid obesity as the principal discharge diagnosis for index admission using ICD code E6601 excluding December hospitalizations and trauma admissions. This group was divided into EVSG (ICD: 0DB64Z3) and EGJ (ICD: 0D164ZA). Using unique identifiers, we obtained the index hospitalization and one subsequent hospitalization involving the same patient within 30 days as readmission. Outcomes included inpatient mortality, length of stay (LOS), and total hospital costs (THC) of the index hospitalization. We compared the 30-day all-cause readmission rate (ACR), the top 10 reasons for readmission, and independent predictors of readmission. We used multivariate Cox regression analysis to calculate the adjusted hazard ratio (aHR) to identify the independent predictors of readmission. The threshold for statistical significance was a p-value of &amp;lt;0.05. The study included 162,670 hospitalizations, 70.6% EVSG, and 29.4% EGJ. The mean age in the EVSG group was 43.8 ±12.8, compared to 45.1 ±12.3 years. The mean Charlson Comorbidity Index (CCI) was higher in the EGJ group (0.9 vs 0.7, p&amp;lt;0.001). Hospitalizations for EVSG had a higher proportion in the highest income quartile (20.5 vs 16.3%). Inpatient mortality rate was 0.02%, EGJ had higher adjusted odds ratio (aOR) (0.05 vs 0.01%, aOR: 5.07, 95% CI: 2.08–12.35, p&amp;lt;0.001) adjusted for age groups and sex. The EGJ group also had a longer LOS (1.9 vs 1.6 days, p&amp;lt;0.001) and higher THC (15,199 vs 12,408 USD, p&amp;lt;0.001). The overall 30 ACR rate was 3.0%, with a higher rate following EGJ (4.5 vs 2.4%). "Other complications of bariatric procedure" was the top reason for readmission (11.1%), followed by dehydration (5.2%), sepsis from unspecified organism (3.2%). EGJ patients had a higher adjusted hazard ratio for readmission (aHR: 1.81, p&amp;lt;0.001). Independent predictors of readmission included private insurance compared to Medicare (aHR: 0.59, p&amp;lt;0.001), large bed-size compared to small (aHR: 0.61, p=0.002), comorbid CHF (aHR: 1.50, p &amp;lt;0.001), PVD (aHR: 1.49, p=0.007), COPD (aHR: 1.13, p=0.014), DM (aHR: 1.12, p=0.009), and CKD (aHR: 1.20, p&amp;lt;0.001). EGJ is associated with more mortality, THC, and LOS in the index admission and more 30-day all-cause readmission rates compared to EVSG. Presentation: Sunday, June 12, 2022 12:30 p.m. - 2:30 p.m., Sunday, June 12, 2022 12:42 p.m. - 12:47 p.m.

Plastic Surgeon Involvement and Post-operative Complication Risk Factors During Soft Tissue Sarcoma Resection

PURPOSE: Given the invasiveness of margin negative radical resection for soft tissue sarcoma (STS), some plastic surgeons and orthopaedic oncologists have opted for a multidisciplinary approach to index resection dubbed ‘orthoplasty’ that includes plastics assistance during complex wound closure.[1,2] This study assesses risk factors of STS index resection complications at a single institution to determine the impact that plastic surgeon involvement during such procedures has on patient outcomes. METHOD: Adult patients that underwent index STS resection between January 2005 and December 2018 were queried from an institutional database using CPT codes. Cases were excluded if the patient underwent head or neck malignancy resection or previous same-site resection at our institution. Primary outcomes analyzed include same-site reoperation, any-cause readmission, and wound healing complications, all assessed within 90-days post-resection. Predictor variables including gender, age, tumor size, operative time, ASA classification, hospital LOS, BMI, smoking, diabetes, radiation, and plastic surgeon involvement. Outcomes were verified with chart review. Univariate logistic regression was used to identify risk factors for complications, with multivariate logistic regression used to assess significant univariate predictors. Patients were then split into two cohorts: those with and without plastic surgeon involvement. Chi-squared and unpaired t-tests were used to compare categorical and continuous variables, respectively. RESULTS: 234 patients were included in the final analysis. Univariate regression suggested the following risk factors for readmission: operative time (p<0.001) and hospital LOS (p=0.002); reoperation: operative time (p=0.009) and hospital LOS (p=0.004); and wound complications: operative time (p<0.001) and hospital LOS (p<0.001). Multivariate regression demonstrated the following independent predictors for readmission: operative time (p=0.039); reoperation: hospital LOS (p=0.036); and wound-healing complications: operative time (p=0.009) and hospital LOS (p=0.006). Upon separation into two cohorts based on plastic surgeon involvement, patients whose resection included a plastic surgeon (104 vs. 130 patients) experienced statistically similar rates of all primary outcomes despite patients with plastics involvement having expectedly longer operative times (219 vs. 107 minutes, p<0.001) and hospital LOS (3.96 vs. 1.33 days, p <0.001)–both independent predictors of complications. CONCLUSION: Operative time and hospital LOS emerged via multivariate logistic regression as independent predictors of short term readmission (operative time), reoperation (hospital LOS), and wound healing complications (both). In our analysis of plastic surgeon involvement in STS index resection cases, patients whose cases included a plastic surgeon achieved statistically similar complication rates in all categories relative to patients without plastics involvement. Similar complication rates for plastic surgery patients were achieved despite significantly longer operative time and hospital LOS, both identified as independent risk factors for complications. As the partnership between plastic surgeons and orthopaedic oncologists evolves, risk factor analysis and patient selection will become increasingly central to limiting complications and promoting healthy outcomes. REFERENCES: 1. Angelini A, Tiengo C, Sonda R, Berizzi A, Bassetto F, Ruggieri P. One-Stage Soft Tissue Reconstruction Following Sarcoma Excision: A Personalized Multidisciplinary Approach Called ‘Orthoplasty’. J Pers Med. 2020;10. 2. Frobert P, Vaucher R, Vaz G, Gouin F, Meeus P, Delay E. The role of reconstructive surgery after soft tissue sarcoma resection. Ann Chir Plast Esthet. 2020;65:394-422.

Rates, Reasons, and Independent Predictors of Readmissions in Portal Venous Thrombosis Hospitalizations in the USA.

Portal vein thrombosis (PVT), generally considered rare, is becoming increasingly recognized with advanced imaging. Limited data exist regarding readmissions in PVT and its burden on the overall healthcare cost. This study aimed to outline the burden of PVT readmissions and identify the modifiable predictors of readmissions. The National Readmission Database (NRD) was used to identify PVT admissions from 2016 to 2019. Using the patient demographic and hospital-specific variables within the NRD, we grouped patient encounters into two cohorts, 30- and 90-day readmission cohorts. We assessed comorbidities using the validated Elixhauser comorbidity index. We obtained inpatient mortality rates, mean length of hospital stay (LOS), total hospital cost (THC), and causes of readmissions in both 30- and 90-day readmission cohorts. Using a multivariate Cox regression analysis, we identified the independent predictors of 30-day readmissions. We identified 17,971 unique index hospitalizations, of which 2,971 (16.5%) were readmitted within 30 days. The top five causes of readmissions in both 30-day and 90-day readmission cohorts were PVT, sepsis, hepatocellular cancer, liver failure, and alcoholic liver cirrhosis. The following independent predictors of 30-day readmission were identified: discharge against medical advice (AMA) (adjusted hazard ratio (aHR) 1.86; P = 0.002); renal failure (aHR 1.44, P = 0.014), metastatic cancer (aHR 1.31, P = 0.016), fluid and electrolyte disorders (aHR 1.20, P = 0.004), diabetes mellitus (aHR 1.31, P = 0.001) and alcohol abuse (aHR 1.31, P ≤ 0.001). The readmission rate identified in this study was higher than the national average and targeted interventions addressing these factors may help reduce the overall health care costs.

S866 Malnutrition and Opioid Use Disorder Are Associated With Higher 30-Day Readmission Rates in Patients Initially Admitted for Ulcerative Colitis

Introduction: Ulcerative colitis (UC) is a chronic disorder that predisposes patients to multiple complications. Readmissions to the hospital pose a burden to patients and health-care systems. Preventing readmissions is important for quality of care and quality of life of patients with UC. We aim to identify the incidence of 30-day readmissions and its predictors. Methods: Retrospective review of the 2018 National Readmission Database (NRD) of adult patients readmitted after an index admission of UC. ICD-10CM/PCS codes were used to identify UC, other comorbidities and procedures. We identified the most common causes for readmission and independent risk factors for readmission were identified using Cox regression analysis. Results: A total of 68,889 index admission (IA) patients were identified, out of which 16.5% (n=11,411) were readmitted within 30-days of discharge. 8.3% of readmissions were secondary to sepsis. Readmitted patients had higher rates of in-hospital mortality (3.4% vs. 2.1%; P< 0.01). Readmitted patients were less likely to be female (50.5% vs 52.8%; P< 0.01), to have private insurance (34.4% vs 40.3%; P< 0.01), to undergo colonoscopy (10.8% vs 17.7%; P< 0.01) and to be from the highest quartile of income (21.9% vs 23.3%; P=0.01). They were more likely to be older (54.0 vs 53.2 years; P< 0.01), to have a Charlson Comorbidity Index (CCI) score of ≥3 (34.1 vs 24.1; P< 0.01), to be from large metropolitan areas with at least 1 million residents (61.1 vs 59.9; P< 0.01), to require parenteral nutrition (3.2% vs 1.5%; P< 0.01), to be malnourished (20.3% vs 11.8%; P< 0.01), to have concomitant Clostridium difficile (6.9% vs. 5.7%; P< 0.01), primary sclerosing cholangitis (0.5% vs 0.2%; P< 0.01) and opioid use disorder (OUD) (3.5% vs 2.4%; P< 0.01). Independent predictors of readmission were CCI of ≥ 3 (aHR 1.95; 95% CI [1.78- 2.13]), undergoing ileostomy during IA (aHR 1.39; 95% CI [1.06-1.82]), increasing LOS (aHR 1.00; 95% CI [1.00-1.01), malnutrition (aHR 1.29; 95% CI [1.17-1.43]) and OUD (aHR 1.45; 95% CI [1.26-1.68]). Private insurance (aHR 0.78; 95% CI [0.72-0.85]), female gender (aHR 0.92; 95% CI [0.87-0.98]) and younger age (aHR 0.99; 95% CI [0.99-0.99]) were associated with less odds of early readmission. (Figure) (Table) Conclusion: The 30-day readmission rate for UC in 2018 was 16.5%. Readmission is associated with higher mortality and are associated with risk factors such as malnutrition and OUD. Early readmissions in UC continues to pose a high burden to patients and our health-care system.Figure 1.: Kaplan Meier graph of 30-day readmission Table 1. - Independent Predictors of 30-day readmission Variable Adjusted odds ratio (95% confidence interval) P value Female 0.92 (0.87-0.98) < 0.01 Age 0.99 (0.99-0.99) < 0.01 Length of stay 1.00 (1.00-1.01) < 0.01 Insurance Provider Medicare Reference Reference Medicaid 0.96 (0.87-1.06) 0.48 Private 0.78 (0.72-0.85) < 0.01 Uninsured 0.81 (0.69-0.96) 0.01 Charlson Comorbidity Index Score 0 1 Reference Reference 2 1.12 (1.03-1.22) < 0.01 ≥3 1.37 (1.24-1.51) < 0.01 Patient residence Large metropolitan area with at least 1 million residents Reference Reference Small metropolitan areas with less than 1 million residents 0.98 (0.92-1.05) 0.75 Micropolitan areas 0.94 (0.79-1.12) 0.53 Not metropolitan or micropolitan (nonurban residual) 0.75 (0.55-1.04) 0.08 In-Hospital Procedures Partial Colectomy 0.91 (0.62-1.32) 0.63 Total colectomy 0.92 (0.70-1.22) 0.58 Ileostomy 1.39 (1.06- 1.82) 0.01 Colonoscopy 1.04 (0.89-1.23) 0.57 Parenteral nutrition 1.19 (0.97-1.46) 0.09 Other Comorbidities Malnutrition 1.29 (1.17-1.43) < 0.01 Obesity 1.00 (0.92-1.08) 0.95 PSC 1.44 (0.98-2.11) 0.06 Alcohol use disorder 1.05 (0.92-1.19) 0.42 Opioid use disorder 1.45 (1.26-1.68) < 0.01 Cannabis use disorder 0.87 (0.72-1.06) 0.18 Diabetes type 1 1.49 (0.98-2.26) 0.06 Diabetes type 2 1.01 (0.93-1.09) 0.74 Shock 1.09 (0.87-1.38) 0.41 Teaching bed size Small Reference Medium 0.96 (0.87-1.06) 0.45 Large 1.06 (0.97-1.15) 0.16