Risk Of Readmission Research Articles

Predictive Modeling of COVID-19 Readmissions: Insights from Machine Learning and Deep Learning Approaches.

This project employs artificial intelligence, including machine learning and deep learning, to assess COVID-19 readmission risk in Malaysia. It offers tools to mitigate healthcare resource strain and enhance patient outcomes. This study outlines a methodology for classifying COVID-19 readmissions. It starts with dataset description and pre-processing, while the data balancing was computed through Random Oversampling, Borderline SMOTE, and Adaptive Synthetic Sampling. Nine machine learning and ten deep learning techniques are applied, with five-fold cross-validation for evaluation. Optuna is used for hyperparameter selection, while the consistency in training hyperparameters is maintained. Evaluation metrics encompass accuracy, AUC, and training/inference times. Results were based on stratified five-fold cross-validation and different data-balancing methods. Notably, CatBoost consistently excelled in accuracy and AUC across all tables. Using ROS, CatBoost achieved the highest accuracy (0.9882 ± 0.0020) with an AUC of 1.0000 ± 0.0000. CatBoost maintained its superiority in BSMOTE and ADASYN as well. Deep learning approaches performed well, with SAINT leading in ROS and TabNet leading in BSMOTE and ADASYN. Decision Tree ensembles like Random Forest and XGBoost consistently showed strong performance.

Synergistic effects of social determinants of health and race-ethnicity on 30-day all-cause readmission disparities: a retrospective cohort study

ObjectiveThe objective of this study is to assess the effects of social determinants of health (SDOH) and race-ethnicity on readmission and to investigate the potential for geospatial clustering of patients...

Prevalence of malnutrition and impact on 30-day hospital readmission in adults receiving home care and ambulatory care: A descriptive cohort study.

Little is known about the prevalence of malnutrition among patients receiving home care (HC) and ambulatory care (AC) services. Further, the risk of hospital readmission in malnourished patients transitioning from hospital to HC or AC is also not well established. This study aims to address these two gaps. A descriptive cohort study of newly referred HC and AC patients between January and December 2019 was conducted. Nutrition status was assessed by clinicians using the Mini Nutritional Assessment-Short Form (MNA-SF). Prevalence of malnutrition and at risk of malnutrition (ARM) was calculated, and a log-binomial regression model was used to estimate the relative risk of hospital readmission within 30 days of discharge for those who were malnourished and referred from hospital. A total of 3704 MNA-SFs were returned, of which 2402 (65%) had complete data. The estimated prevalence of malnutrition and ARM among newly referred HC and AC patients was 21% (95% CI: 19%-22%) and 55% (95% CI: 53%-57%), respectively. The estimated risk of hospital readmission for malnourished patients was 2.7 times higher (95% CI: 1.9%-3.9%) and for ARM patients was 1.9 times higher (95% CI: 1.4%-2.8%) than that of patients with normal nutrition status. The prevalence of malnutrition and ARM among HC and AC patients is high. Malnutrition and ARM are correlated with an increased risk of hospital readmission 30 days posthospital discharge.

Age-adjusted Charlson Comorbidity Index as an effective tool for the choice between simultaneous or staged bilateral total knee arthroplasty.

The choice between simultaneous and staged bilateral total knee arthroplasty (BTKA) remains controversial. Age-adjusted Charlson Comorbidity Index(CCI) is a promising tool for risk-stratification. We aimed to compare the outcomes between patients who underwent simultaneous and staged BTKA, stratified by age-adjusted CCI scores. We conducted this retrospective, single-surgeon case series from 2010 to 2020. This study consisted of 1558 simultaneous BTKA and 786 staged BTKA procedures. The outcome domains included 30-day and 90-day readmission and 1-year reoperation events. We performed multivariate regression analysis to compare the risk of readmission and reoperation following simultaneous and staged BTKA. Other factors included age, sex, body mass index, diabetes mellitus, rheumatoid arthritis, smoking, receiving thromboprophylaxis and blood transfusion. The rates of 30-day, 90-day readmission and 1-year reoperation following simultaneous BTKA was 1.99%, 2.70% and 0.71%, respectively. The rates of 30-day, 90-day readmission and 1-year reoperation following staged BTKA was 0.89%, 1.78% and 0.89%, respectively. For patients with age-adjusted CCI ≥ 4 points, simultaneous BTKA was associated with a higher risk of 30-day (aOR:3.369, 95% CI:0.990-11.466) and 90-day readmission (aOR:2.310, 95% CI:0.942-5.668). In patients with age-adjusted CCI ≤ 3 points, the risk of readmission and reoperation was not different between simultaneous or staged BTKA. Simultaneous BTKA was associated with an increased risk of short-term readmissions in patients with age-adjusted CCI ≥ 4 points but not in those with age-adjusted CCI ≤ 3 points. Age-adjusted CCI can be an effective index for the choice between simultaneous and staged BTKA procedures.

Myocardial infarction with nonobstructive coronary arteries: a single-center retrospective study by sex and race.

In myocardial infarction with nonobstructive coronary arteries (MINOCA), there are limited patient-level data on outcomes by sex and race. The aim of this study was to assess baseline demographics and 3-year outcomes by sex and race for MINOCA patients. Patients admitted to a single center with acute myocardial infarction (MI) between 1 January 2012 and 31 December 2018, were identified by chart and angiographic review. The primary outcome was nonfatal MI with secondary outcomes including nonfatal cerebrovascular accident (CVA), chest pain readmission, and repeat coronary angiography. During the study period, 304 patients were admitted with MINOCA. The cohort was predominantly female (66.4%), and women were significantly older (64.6 vs. 59.2). One-sixth of the total population were Black patients, and nearly half of Black patients (47.2%) were male. Prior CVA (19.7%) and comorbid anxiety, depression, or post-traumatic stress disorder (41.1%) were common. Rates of nonfatal MI were 6.3% without difference by sex or race. For secondary outcomes, rates of CVA were 1.7%, chest pain readmission was 22.4%, and repeat angiography was 8.9%. Men were significantly more likely to have repeat angiography (13.7 vs. 6.4%), and Black patients were more likely to be readmitted for angina (34.0 vs. 19.1%). Over one-quarter of patients underwent repeat stress testing, with 8.9% ultimately undergoing repeat angiograms and low numbers (0.7%) undergoing revascularization. Men were more likely to be referred for a repeat angiogram (13.7 vs. 6.4%, P = 0.035). In multivariate analysis, Black race [odds ratio (OR), 2.31; 95% confidence interval (CI), 1.06-5.03] was associated with an increased risk of readmission for angina, while female sex was associated with decreased odds of repeat angiography (OR, 0.36; 95% CI, 0.14-0.90) and current smoking was associated with increased odds of repeat angiography (OR, 4.07; 95% CI, 1.02-16.29)] along with hyperlipidemia (OR, 4.65; 95% CI, 1.22-17.7). White women presented more frequently with MINOCA than White men, however, Black men are equally as affected as Black women. Rates of nonfatal MI were low without statistical differences by sex or race.

Using social risks to predict unplanned hospital readmission and emergency care among hospitalized Veterans.

(1) To estimate the association of social risk factors with unplanned readmission and emergency care after a hospital stay. (2) To create a social risk scoring index. We analyzed administrative data from the Department of Veterans Affairs (VA) Corporate Data Warehouse. Settings were VA medical centers that participated in a national social work staffing program. We grouped socially relevant diagnoses, screenings, assessments, and procedure codes into nine social risk domains. We used logistic regression to examine the extent to which domains predicted unplanned hospital readmission and emergency department (ED) use in 30 days after hospital discharge. Covariates were age, sex, and medical readmission risk score. We used model estimates to create a percentile score signaling Veterans' health-related social risk. We included 156,690 Veterans' admissions to a VA hospital with discharged to home from 1 October, 2016 to 30 September, 2022. The 30-day rate of unplanned readmission was 0.074 and of ED use was 0.240. After adjustment, the social risks with greatest probability of readmission were food insecurity (adjusted probability = 0.091 [95% confidence interval: 0.082, 0.101]), legal need (0.090 [0.079, 0.102]), and neighborhood deprivation (0.081 [0.081, 0.108]); versus no social risk (0.052). The greatest adjusted probabilities of ED use were among those who had experienced food insecurity (adjusted probability 0.28 [0.26, 0.30]), legal problems (0.28 [0.26, 0.30]), and violence (0.27 [0.25, 0.29]), versus no social risk (0.21). Veterans with social risk scores in the 95th percentile had greater rates of unplanned care than those with 95th percentile Care Assessment Needs score, a clinical prediction tool used in the VA. Veterans with social risks may need specialized interventions and targeted resources after a hospital stay. We propose a scoring method to rate social risk for use in clinical practice and future research.

Long-term effects of air quality on hospital readmission for heart failure in patients with acute myocardial infarction

BackgroundCardiovascular disease (CVD) is the leading cause of death worldwide, with air pollution posing significant risks to cardiovascular health. The effect of air quality on heart failure (HF) readmission in acute myocardial infarction (AMI) patients is unclear.The aim of this study was to evaluate the role of a single measure of air pollution exposure collected on the day of first hospitalization. MethodsWe retrospectively analyzed data from 12,857 acute coronary syndrome (ACS) patients (January 2015–March 2023). After multiple screenings, 4023 AMI patients were included. The air pollution data is updated by the automatic monitoring data of the national urban air quality monitoring stations in real time and synchronized to the China Environmental Monitoring Station. Cox proportional hazards regression assessed the impact of air quality indicators on admission and outcomes in 4013 AMI patients. A decision tree model identified the most susceptible groups. ResultsAfter adjusting for confounders, NO2 (HR 1.009, 95% CI 1.004–1.015, P = 0.00066) and PM10 (HR 1.006, 95% CI 1.002–1.011, P = 0.00751) increased the risk of HF readmission in ST-segment elevation myocardial infarction (STEMI) patients. No significant effect was observed in non-STEMI (NSTEMI) patients (P > 0.05). STEMI patients had a 2.8-fold higher risk of HF readmission with NO2 > 13 μg/m3 (HR 2.857, 95% CI 1.439–5.670, P = 0.00269) and a 1.65-fold higher risk with PM10 > 55 μg/m3 (HR 1.654, 95% CI 1.124–2.434, P = 0.01064). ConclusionNO2 and PM10 are linked to increased HF readmission risk in STEMI patients, particularly when NO2 exceeds 13 μg/m3 and PM10 exceeds 55 μg/m3. Younger, less symptomatic male STEMI patients with fewer underlying conditions are more vulnerable to these pollutants.

Early Postoperative Prediction of Complications and Readmission After Colorectal Cancer Surgery Using an Artificial Neural Network.

Early predictors of postoperative complications can risk-stratify patients undergoing colorectal cancer surgery. However, conventional regression models have limited power to identify complex nonlinear relationships among a large set of variables. We developed artificial neural network models to optimize the prediction of major postoperative complications and risk of readmission in patients undergoing colorectal cancer surgery. This study aimed to develop an artificial neural network model to predict postoperative complications using postoperative laboratory values and compare the accuracy of models to standard regression methods. This retrospective study included patients who underwent elective colorectal cancer resection between January 1, 2016, and July 31, 2021. Clinical data, cancer stage, and laboratory data from postoperative days 1 to 3 were collected. Complications and readmission risk models were created using multivariable logistic regression and single-layer neural networks. National Cancer Institute-Designated Comprehensive Cancer Center. Adult patients with colorectal cancer. The accuracy of predicting postoperative major complications, readmissions, and anastomotic leaks using the area under the receiver operating characteristic curve. Neural networks had larger areas under the curve for predicting major complications compared to regression models (neural network 0.811; regression model 0.724, p < 0.001). Neural networks also showed an advantage in predicting anastomotic leak ( p = 0.036) and readmission using postoperative day 1 to 2 values ( p = 0.014). Single-center, retrospective design limited to cancer operations. In this study, we generated a set of models for the early prediction of complications after colorectal surgery. The neural network models provided greater discrimination than the models based on traditional logistic regression. These models may allow for early detection of postoperative complications as early as postoperative day 2. See the Video Abstract . ANTECEDENTES:Los predictores tempranos de complicaciones postoperatorias pueden estratificar el riesgo de los pacientes sometidos a cirugía de cáncer colorrectal. Sin embargo, los modelos de regresión convencionales tienen un poder limitado para identificar relaciones no lineales complejas entre un gran conjunto de variables. Desarrollamos modelos de redes neuronales artificiales para optimizar la predicción de complicaciones postoperatorias importantes y riesgo de reingreso en pacientes sometidos a cirugía de cáncer colorrectal.OBJETIVO:El objetivo de este estudio fue desarrollar un modelo de red neuronal artificial para predecir complicaciones postoperatorias utilizando valores de laboratorio postoperatorios y comparar la precisión de estos modelos con los métodos de regresión estándar.DISEÑO:Este estudio retrospectivo incluyó a pacientes que se sometieron a resección electiva de cáncer colorrectal entre el 1 de enero de 2016 y el 31 de julio de 2021. Se recopilaron datos clínicos, estadio del cáncer y datos de laboratorio del día 1 al 3 posoperatorio. Se crearon modelos de complicaciones y riesgo de reingreso mediante regresión logística multivariable y redes neuronales de una sola capa.AJUSTE:Instituto Nacional del Cáncer designado Centro Oncológico Integral.PACIENTES:Pacientes adultos con cáncer colorrectal.PRINCIPALES MEDIDAS DE RESULTADO:Precisión de la predicción de complicaciones mayores postoperatorias, reingreso y fuga anastomótica utilizando el área bajo la curva característica operativa del receptor.RESULTADOS:Las redes neuronales tuvieron áreas bajo la curva más grandes para predecir complicaciones importantes en comparación con los modelos de regresión (red neuronal 0,811; modelo de regresión 0,724, p < 0,001). Las redes neuronales también mostraron una ventaja en la predicción de la fuga anastomótica ( p = 0,036) y el reingreso utilizando los valores del día 1-2 postoperatorio ( p = 0,014).LIMITACIONES:Diseño retrospectivo de un solo centro limitado a operaciones de cáncer.CONCLUSIONES:En este estudio, generamos un conjunto de modelos para la predicción temprana de complicaciones después de la cirugía colorrectal. Los modelos de redes neuronales proporcionaron una mayor discriminación que los modelos basados en regresión logística tradicional. Estos modelos pueden permitir la detección temprana de complicaciones posoperatorias tan pronto como el segundo día posoperatorio. (Traducción-Dr. Mauricio Santamaria ).

A collaborative pharmacist-led intervention to prevent hospital readmissions among elderly patients discharged from the emergency department: a retrospective cohort study

Unplanned hospital readmission is a safety and quality healthcare measure, conferring significant costs to the healthcare system. Elderly individuals, particularly, are at high risk of readmissions, often due to issues related to medication management. Pharmacists play a pivotal role in addressing medication-related concerns, which can potentially reduce readmissions. This retrospective single-centre cohort study, conducted from November 2022 to February 2023 in an emergency department, aimed to determine if integrating emergency medicine pharmacists into Emergency Department care models reduces unplanned hospital readmissions within 28 days and to identify the interventions they employ. The inclusion criteria included patients aged ≥ 65, taking ≥ 3 medications, and presenting with falls, cognition changes, or reduced mobility and were planned for discharge to home from the emergency department. Collaborating with the Emergency Department Aged Care Service Emergency Team, a pharmacist provided comprehensive medication management consultations, discharge liaison services, and other pharmacy related interventions to eligible participants whenever the pharmacist was available. Patients who met the eligibility criteria but did not receive pharmacist interventions due to the pharmacist's unavailability served as the control group. This method was chosen to ensure that the control group consisted of comparable patients who only differed in terms of receiving the pharmacist intervention. The study included 210 participants, with 120 receiving pharmacist interventions and 90 acting as controls. The results revealed a significant reduction in unplanned hospital readmissions among participants who received pharmacist interventions (10.0%, n = 12) compared to controls (22.2%, n = 20), with a notable difference of 12.2% (95% confidence interval 2.4–23.4%, p = 0.01). A total of 107 interventions were documented, emphasising medication selection recommendations (28.0%) and identification of adverse drug reactions/drug-drug interactions (21.5%) as primary areas of focus. These findings suggest that integrating skilled pharmacists into Emergency Department Aged Care Service Emergency Team (ASET) lowered the rate of unplanned hospital readmission within 28 days resulting in improved hospital performance metric outcomes. This highlights the potential role of pharmacists in addressing medication-related issues and enhancing the quality and safety of healthcare delivery, particularly for elderly patients transitioning from the ED to home care settings.

Risk Factors for Emergency Room Visits in Patients with Digestive Bleeding Associated with Direct-Acting Anticoagulants

Gastrointestinal bleeding is the main cause of admission to the emergency services of patients taking direct-acting oral anticoagulants (DOACs). Little is known about the effects of treatment modification on the risk of readmission, especially in elderly patients. This retrospective observational study included elderly patients with atrial fibrillation who were on DOACs and who were admitted to the emergency department due to gastrointestinal bleeding from 2018 to 2023. To evaluate the risk factors for readmission 90 days after discharge, a multivariate analysis was conducted, which included patient comorbidities, concomitant treatment, changes in anticoagulant treatment, and the prescription of DOACs at discharge. One hundred and thirty-nine patients were included. At discharge, anticoagulant therapy was modified in 44 (31.6%) patients, 16 (36.3%) patients were switched from one DOAC to another, 23 (52.2%) to heparins, and 5 (11.3%) to vitamin K antagonists. A total of 21 (15.1%) patients returned to the emergency department within 90 days after discharge due to new bleeding events. No significant differences were observed depending on the modification of treatment at discharge. The presence of cognitive impairment was the only factor associated with readmission at 90 days. Patients who undergo treatment with DOACs and have gastrointestinal bleeding at discharge are at risk of readmission to the emergency room due to new bleeding events. No benefit was observed in modifying anticoagulant treatment at discharge.

Postpartum Weight Change Association With Readmission and Blood Pressure Trend Among Individuals With Hypertensive Disorders of Pregnancy.

The aim of this study was to evaluate the association between early postpartum weight change and (1) hospital readmission and (2) 2-week blood pressure trajectory. This retrospective study cohort included 1365 individuals with a hypertensive disorder of pregnancy enrolled in a postpartum hypertension remote monitoring program. Exposure was percentage weight change from delivery to first weight recorded within 10 days postpartum. We first modeled likelihood of hospital readmission within 8 weeks postpartum using logistic regression adjusting for age, race, insurance, type of hypertensive disorder of pregnancy, early body mass index, gestational weight gain, mode of delivery, and any discharge antihypertensive medications. We then performed case-control analysis additionally matching in a 1:3 ratio on breastfeeding, early body mass index, discharge on antihypertensive medications, and days between weight measurements. Both analytic approaches were repeated, limiting to readmissions attributable to hypertension or heart failure. Finally, we compared blood pressure trajectories over first 2 weeks postpartum. Individuals who did not lose weight in the early postpartum period had more admissions compared with weight loss groups (group 3: 14.1% versus group 2: 5.8% versus group 1: 4.5%). These individuals had 4 times the odds of postpartum readmissions (adjusted odds ratio [aOR], 3.9 [95% CI, 1.8-8.6]) to 7 (aOR, 7.8 [95% CI, 2.3-26.5]) compared with those with the most weight loss. This association strengthened when limited to hypertension or heart failure readmissions. These individuals also had more adverse postpartum blood pressure trajectories, with significant differences by weight change group. Weight change is readily accessible and may identify individuals at high risk for postpartum readmission following a hypertensive disorder of pregnancy who could benefit from targeted interventions.

Examining Heart Failure Outcomes Amid Housing Insecurity

How housing insecurity might affect patients with heart failure (HF) is not well characterized. Housing insecurity increases risks related to both communicable and noncommunicable diseases. For patients with HF, housing insecurity is likely to increase the risk for worse outcomes and rehospitalizations. We analyzed hospitalizations due to HF in the United States by using the 2020 National Inpatient Sample and Nationwide Readmissions Database to evaluate the impacts of housing insecurity on HF outcomes and hospital use. Individuals were identified as having housing insecurity by using diagnostic International Classification of Disease (ICD)-10 codes. Demographics and comorbidities were compared between patients with HF with and without housing insecurity. An adjusted logistic regression was performed to evaluate the relationships between housing insecurity and socioeconomic status on in-hospital mortality. Using a Cox proportional hazards model, patients with HF and without housing insecurity were evaluated for the risk of all-cause and HF-specific readmissions over time. Of the 1,003,270 hospitalizations for HF in the U.S. in 2020, 16,150 were identified as having housing insecurity (1.6%), and 987,120 were identified as having no housing insecurity (98.4%). The median age of patients with housing insecurity who were hospitalized for HF was 57, as compared to 73 in the population with no housing insecurity. A higher proportion of patients in the housing-insecurity group were Black (35% vs 20.1%) or Hispanic (11.1% vs 7.3%). Patients with housing insecurity were more likely to carry a diagnosis of alcohol-use disorder (15.2% vs 3.3%) or substance-use disorder (70.2% vs 17.8%) but were less likely to use tobacco (18.3% vs 28.7%). Patients with housing insecurity were over 4.5 times more likely to have Medicaid (52.4% vs 11.3%). Median length of stay did not differ between patients with housing insecurity vs those without it. Patients with housing insecurity were more likely to discharge against medical advice (11.4% vs 2.03%). After adjusting for patients' characteristics, housing insecurity was associated with lower in-hospital mortality rates (OR 0.60, 95% CI 0.39-0.92). Housing insecurity was associated with a higher risk of all-cause readmissions at 180 days (HR 1.13, 95% CI 1.12-1.14). However, there was no significant difference in the risk of HF-specific readmissions at 180 days (HR 1.07, 95% CI 0.998-1.14) CONCLUSIONS: Patients with HF and housing insecurity have distinct demographic characteristics. They are also more likely to be readmitted after their initial hospitalization when compared to those without housing insecurity. Identifying and addressing specific comorbid conditions for patients with housing insecurity who are hospitalized for HF may allow clinicians to provide more focused care, with the goal of preventing morbidity, mortality and unnecessary readmissions.

Discharge against medical advice in trauma patients: Trends, risk factors, and implications for health care management strategies

ObjectiveGiven the nonelective nature of most trauma admissions, patients who experience trauma are at a particular risk of discharge against medical advice. Despite the risk of unplanned readmission and financial burden on the health care system, discharge against medical advice among hospitalized patients continues to rise. The present study aimed to assess evolving trends and outcomes associated in patients with discharge against medical advice among patients hospitalized for traumatic injury. MethodsThe 2016–2020 Nationwide Readmissions Database was queried to identify all hospitalizations for traumatic injuries. The patient cohort was stratified into those who had discharge against medical advice and those who did not. Temporal trends of discharge against medical advice and associated costs over time were evaluated using nonparametric tests. Multivariable regression models were developed to assess factors associated with discharge against medical advice. Associations of discharge against medical advice with length of stay, hospitalization costs, and unplanned 30-day readmission were subsequently evaluated. ResultsOf an estimated 4,969,717 patients, 65,354 (1.3%) had discharge against medical advice after hospitalization for traumatic injury. Over the study period, the incidence of discharge against medical advice increased (nptrend <0.001). After risk adjustment, older age (adjusted odds ratio, 0.98/per year; 95% confidence interval, 0.97–0.98), female sex (adjusted odds ratio, 0.65; 95% confidence interval, 0.64–0.67), and management at high-volume trauma center (adjusted odds ratio, 0.71; 95% confidence interval, 0.69–0.74) were associated with lower odds of discharge against medical advice. Compared with others, discharge against medical advice was associated with decrements in length of stay by 1.3 days (95% confidence interval, 1.1–1.5 days) and index hospitalization costs by $2,200 (5% confidence interval, $1,600–2,900), while having a greater risk of unplanned 30-day readmission (adjusted odds ratio, 2.21; 95% confidence interval, 2.06–2.36). ConclusionThe incidence of discharge against medical advice and its associated cost burden have increased in recent years. Community-level interventions and institutional efforts to mitigate discharge against medical advice may improve the quality of care and resource allocation for patients with traumatic injuries.

The impact of metabolic syndrome on short term radical cystectomy complications

PurposeRadical cystectomy is a highly morbid procedure with short term perioperative complications rates cited to be as high as 60%. Short term perioperative complications have been demonstrated to be more frequent in underweight and overweight patients. We sought to evaluate the impact of metabolic syndrome on surgical outcomes. Materials and methodsWe identified 19,071 eligible patients who underwent radical cystectomy for nonmetastatic bladder cancer using the American College of Surgeons National Surgical Quality Improvement Program database between the years 2014 to 2021. The primary exposure was the presence of metabolic syndrome (body mass index >30, hypertension, diabetes) and included 1,566 patients. Our primary outcome was the development of a post operative surgical complication with secondary outcomes of the impact on length of stay, return to operating room, readmission, and 30 day mortality. ResultsMetabolic syndrome was associated with an increased rate of complications following radical cystectomy (P < 0.001). Complications were demonstrated in 68% of patients with metabolic syndrome in comparison to 60% of those without. Following multivariable adjustment for relevant demographic, comorbidity, and treatment factors, compared to patients without metabolic syndrome, patients with metabolic syndrome were significantly more likely to experience a complication in the 30 days following cystectomy. Among the secondary outcomes, on multivariable analysis significant differences were found in the risk of readmission and extended length of stay. Critically, the risk of 30 day morbidity was associated with a 1.8 fold increase in those with metabolic syndrome. ConclusionsMetabolic syndrome demonstrates significantly worse perioperative outcomes following radical cystectomy for bladder cancer.

The inverted U-shaped association between blood fibrinogen and rehospitalization risk in patients with heart failure

Fibrinogen, a biomarker of thrombosis and inflammation, is related to a high risk for cardiovascular diseases. However, studies on the prognostic value of blood fibrinogen concentrations for heart failure (HF) patients are few and controversial. We performed a retrospective analysis among acute or deteriorating chronic HF patients admitted to a hospital in Sichuan, China, between 2016 and 2019, integrating electronic health care records and external outcome data (N = 1532). During 6 months of follow-up, 579 HF patients were readmitted within 6 months, and 46 of them died. Surprisingly, we found an inverted U-shaped association of blood fibrinogen levels with risk of readmission within 6 months but not with risk of death within 6 months. It was found that HF patients had the highest risk for readmission within 6 months after reaching the turning point for blood fibrinogen (2.4 g/L). In HF patients with low fibrinogen levels < 2.4 g/L, elevated fibrinogen concentrations were still significantly associated with a higher risk for readmission within 6 months [OR = 2.3, 95% CI (1.2, 4.6); P = 0.014] after controlling for relevant covariates. There was no significant association between blood fibrinogen and readmission within 6 months [(OR = 1.0, 95% CI (0.9, 1.1); P = 0.675] in HF patients with high fibrinogen (> 2.4 g/L). The effect difference for the two subgroups was significant (P = 0.014). However, we did not observe any association between blood fibrinogen and death within 6 months stratified by the turning point, and the effect difference for the stratification was not significant (P = 0.380). We observed an inverted U-shaped association between blood fibrinogen and rehospitalization risk in HF patients for the first time. Additionally, our results did not support that elevated blood fibrinogen was related to increased death risk after discharge.

Can prediction models for hospital readmission be improved by incorporating patient-reported outcome measures? A systematic review and narrative synthesis.

To investigate the roles, challenges, and implications of using patient-reported outcome measures (PROMs) in predicting the risk of hospital readmissions. We systematically searched four bibliometric databases for peer-reviewed studies published in English between 1 January 2000 and 15 June 2023 and used validated PROMs to predict readmission risks for adult populations. Reported studies were analysed and narratively synthesised in accordance with the CHARMS and PRISMA guidelines. Of the 2858 abstracts reviewed, 23 studies met predefined eligibility criteria, representing diverse geographic regions and medical specialties. Among those, 19 identified the positive contributions of PROMs in predicting readmission risks. Seven studies utilised generic PROMs exclusively, eleven used generic and condition-specific PROMs, while 5 focussed solely on condition-specific PROMs. Logistic regression was the most used modelling approach, with 13 studies aiming at predicting 30-day all-cause readmission risks. The c-statistic, ranging from 0.54 to 0.84, was reported in 22/23 studies as a measure of model discrimination. Nine studies reported model calibration in addition to c-statistic. Thirteen studies detailed their approaches to dealing with missing data. Our study highlights the potential of PROMs to enhance predictive accuracy in readmission models, while acknowledging the diversity in data collection methods, readmission definitions, and model evaluation approaches. Recognizing that PROMs serve various purposes beyond readmission reduction, our study supports routine data collection and strategic integration of PROMs in healthcare practices to improve patient outcomes. To facilitate comparative analysis and broaden the use of PROMs in the prediction framework, it is imperative to consider the methodological aspects involved.

Risk Factors for 90-Day Readmission Among Patients with Metastatic Spine Tumors in South Korea: A Nationwide Population-Based Study

Population-based studies on the cause of readmission within 90 days after surgery or radiotherapy for metastatic spine tumors are scarce. We aimed to investigate the risk factors for readmission within 90 days after initial surgical or radiation treatment for metastatic spine tumors. Patients who were diagnosed with metastatic spine tumors between 2012 and 2019 and underwent spinal magnetic resonance imaging within 1 year were classified according to treatment (surgical or radiotherapy groups), and the causes of the 90-day readmission and patient characteristics were compared. Overall, data from 15,815 patients (surgical group, 13,974 patients; radiotherapy group, 1,841 patients) were evaluated. Radiotherapy was preferred in younger and male patients with a high Charlson Comorbidity Index (CCI), whereas surgery was mainly performed in patients with lumbar metastasis. Radiotherapy, age of 30-69 years, male sex, and CCI > 1 increased the risk of 90-day readmission in patients with metastatic spine tumors. The main causes of 90-day readmission among patients with metastatic spine tumors who received radiotherapy included tumor recurrence, chemotherapy, radiotherapy, and treatment of other organ metastases with radiotherapy. These study findings offer a better understanding of the causes of readmission following radiotherapy or surgical treatment in patients with metastatic spine tumors, and these results can help reduce postoperative morbidity and medical costs among these patients.

Postoperative Care and Outcomes in Solid-Organ Transplant Patients Undergoing Lower Extremity Fracture Treatment.

To determine the postoperative outcomes in solid-organ transplant (SOT) patients undergoing operative treatment of lower extremity fractures. Retrospective comparative study. Academic Level 1 trauma center. Patients who underwent SOT and operative treatment of lower extremity fracture from 2013 to 2021 were identified, excluding pathologic fractures. Postoperative complications, length of stay, time to death, 90-day and 1-year readmission rates, readmission causes, discharge location, and immunosuppressive regiments. Sixty-one patients with an average age of 67 years (range 29-88) were included. The mortality rate was 37.7%. The average follow-up was 15.2 months (range of 2 weeks-10 years). The majority of patients (32.8%) had received a liver transplant, and femoral neck fractures constituted the largest fracture group. The average length of stay was 10 days, with the shortest being 1 day and the longest being 126 days (SD 18). The majority of patients (57.3%) were not discharged home. Only 2 suffered from a postoperative complication requiring another procedure: hardware removal and liner exchange for periprosthetic joint infection, respectively. There was a 27.9% 90-day readmission rate with 2 deaths within that period with the most common being altered mental status (29.4%), genitourinary infections (17.6%), repeat falls (11.8%), and low hemoglobin requiring transfusion (11.8%). The longest average time to death analyzed by transplant type was found among lung transplant patients (1076 days, 62.5% mortality), followed by liver transplant patients (949 days, 35.0% mortality), and then kidney transplant patients (834 days, 38.9% mortality). The shortest time to death was 71 days from index procedure. Family members of SOT patients undergoing operative treatment of lower extremity fractures should be made aware of the high risk for 90-day readmission postoperatively (27.9%) and overall mortality (12.5%). Providers should be aware of the need for multidisciplinary involvement for inpatient care, monitoring postoperative complications, and facilitating discharge planning. Therapeutic Level IV. See Instructions for Authors for a complete description of levels of evidence.

The impact of elevated C-reactive protein levels on long-term outcomes of patients undergoing transcatheter aortic valve replacement

BackgroundIn patients undergoing transcatheter aortic valve replacement (TAVR), elevated pre-procedural C-reactive protein (CRP) levels are frequently observed. Its impact on long-term results of TAVR is unclear. The aim of the study was to investigate the long-term (up to six years) clinical outcomes of TAVR patients with normal compared to elevated CRP levels before TAVR. MethodsConsecutive patients undergoing TAVR between August 2012 and January 2023 at a tertiary cardiology facility were included. Patients were divided into two cohorts based on the baseline CRP levels: normal CRP (≤ 5 mg/l) and elevated CRP (>5 mg/l). The cohorts were followed clinically for up to six years after TAVR. ResultsFrom a total of 1000 TAVR patients (mean age 81 ± 6 years), 268 patients (27 %) were found to have elevated baseline CRP (>5 mg/l). Such patients had significantly more co-morbidities (e.g. chronic obstructive pulmonary disease, atrial fibrillation, heart failure, concomitant valvopathies). They also developed periprocedural infections more frequently (3 % vs. 1 %, p = 0.007) and required more commonly repeat hospitalizations for infections during follow-up (HR 1.97, CI 1.47–2.64, p < 0.001). All-cause mortality and development of valve dysfunction did not significantly differ between patients with elevated and normal baseline CRP levels. ConclusionAlbeit long-term results of TAVR patients with elevated pre-procedural CRP levels seem favorable in terms of survival and development of valve dysfunction, they have an increased risk for periprocedural infections and re-admissions due to infections of any type during the follow-up period.

Risk Factors for Unplanned Readmission in Adult Liver Transplant Patients: A Retrospective Study

IntroductionUnplanned readmission is an important indicator for evaluating medical care quality. Adult liver transplant patients have high risk for readmission, which seriously affects their recovery. As there is currently a lack of research on risk factors for unplanned readmission of adult liver transplant patients in China, the purpose of this study was to elucidate such risk factors. MethodsData for patients undergoing liver transplantation surgery at a tertiary hospital in Zhejiang Province from March 2018 to July 2022 were retrospectively collected. Patients were divided into readmission and nonreadmission groups based on whether unplanned readmission occurred within 90 days. Univariate analysis and logistic regression were used to analyze risk factors for unplanned readmission. ResultsIn total, 123 adult liver transplant patients were included; 38 had unplanned readmission, for a rate of 30.8%. There was a statistically significant difference between the groups in terms of age, educational level, operation time, intraoperative bleeding volume, number of complications, postoperative hospital stay, and hemoglobin (P < .05). Logistic regression analysis showed that age [OR = 1.085, 95% CI (1.022, 1.152)], operation time [OR = 1.010, 95% CI (1.001, 1.020)], postoperative hospital stay [OR = 1.124, 95% CI (1.023, 1.235)], and number of complications [OR = 4.487, 95% CI (1.234, 16.319)] were independent risk factors for unplanned readmission in adult liver transplant patients (P < .05). ConclusionsThe current situation of unplanned readmission for adult liver transplant patients cannot be ignored, indicating that staff should identify risk factors for unplanned readmission as soon as possible and take targeted personalized measures and health education to reduce readmission risk.