Outcomes in Arthroplasty Procedures Performed for Femoral Neck Fractures Does Approach Affect Outcome?

BACKGROUND: The surgical approach used for arthroplasty in the setting of hip fracture has traditionally been decided based on surgeon preference. This study analyzed the ef-fect of the surgical approach on hospital quality measures, complications, and mortality in patients treated with hip arthroplasty for fracture fixation. METHODS: A cohort of consecutive acute hip fracture pa-tients who were 60 years of age or older and who underwent hemiarthroplasty (HA) or total hip arthroplasty (THA) at one academic medical center between January 2014 and January 2018 was included. Patient demographics, length of stay (LOS), surgery details, complications, ambulation at dis-charge, discharge location, readmission, and mortality were recorded. Two cohorts were included based on the surgical approach: the anterior-based cohort included the direct an-terior and anterolateral approaches and the posterior-based cohort included direct lateral and posterior approaches. RESULTS: Two hundred five patients were included: 146 underwent HA (81 anterior-based and 65 posterior-based) and 79 underwent THA (37 anterior-based and 42 posterior-based). The mean age of the HA and THA cohorts was 84.1 ± 7.5 and 73.7 ± 8.0 years, respectively. There was no dif-ference in LOS, time to surgery, or surgical time between the two cohorts for HA and THA. There were no differences in perioperative complications, including dislocation, ob-served based on surgical approach. No difference was found between readmission rates and mortality. CONCLUSION: In this cohort of hip fracture arthroplasty patients, there was no difference observed in hospital quality measures, readmission, or mortality in patients based on sur-gical approach. These results are in contrast with literature in elective arthroplasty patients supporting the use of an anterior approach for potential improved short-term outcomes.

Is Electronic Information Exchange Associated With Lower 30-Day Readmission Charges Among Medicare Beneficiaries?

OBJECTIVE: Fragmented readmissions, when admission and readmission occur at different hospitals, are associated with increased charges compared with nonfragmented readmissions. We assessed if hospital participation in health information exchange (HIE) was associated with differences in total charges in fragmented readmissions. DATA SOURCE: Medicare Fee-for-Service Data, 2018. STUDY DESIGN: We used generalized linear models with hospital referral region and readmission month fixed effects to assess relationships between information sharing (same HIE, different HIEs, and no HIE available) and total charges of 30-day readmissions among fragmented readmissions; analyses were adjusted for patient-level clinical/demographic characteristics and hospital-level characteristics. DATA EXTRACTION METHODS: We included beneficiaries with a hospitalization for acute myocardial infarction, congestive heart failure, chronic obstructive pulmonary disease, syncope, urinary tract infection, dehydration, or behavioral issues with a 30-day readmission for any reason. PRINCIPAL FINDINGS: In all, 279,729 admission-readmission pairs were included, 27% of which were fragmented (n=75,438); average charges of fragmented readmissions were $64,897-$71,606. Compared with fragmented readmissions where no HIE was available, the average marginal effects of same-HIE and different-HIE admission-readmission pairs were -$2329.55 (95% CI: -7333.73, 2674.62) and -$3905.20 (95% CI: -7592.85, -307.54), respectively. While the average marginal effects of different-HIE pairs were lower than those for no-HIE fragmented readmissions, the average marginal effects of same-HIE and different-HIE pairs were not significantly different from each other. CONCLUSIONS: There were no statistical differences in charges between fragmented readmissions to hospitals that share an HIE or that do not share an HIE compared with hospitals with no HIE available.

Association between immigration status and total knee arthroplasty outcomes in Ontario, Canada: a population-based matched cohort study.

BACKGROUND: Immigrants and refugees face unique challenges navigating the health care system to manage severe arthritis, because of unfamiliarity, lack of awareness of surgical options, or access. The purpose of this study was to assess total knee arthroplasty (TKA) uptake, surgical outcomes, and hospital utilization among immigrants and refugees compared with Canadian-born patients. METHODS: We included all adults undergoing primary TKA from January 2011 to December 2020 in Ontario. Cohorts were defined as Canadian-born or immigrants and refugees. We assessed change in yearly TKA utilization for trend. We compared differences in 1-year revision, infection rates, 30-day venous thromboembolism (VTE), presentation to emergency department, and hospital readmission between matched Canadian-born and immigrant and refugee groups. RESULTS: We included 158 031 TKA procedures. A total of 11 973 (7.6%) patients were in the immigrant and refugee group, and 146 058 (92.4%) patients were in the Canadian-born group. The proportion of TKAs in Ontario performed among immigrants and refugees nearly doubled over the 10-year study period (p < 0.001). After matching, immigrants were at relatively lower risk of 1-year revision (0.9% v. 1.6%, p < 0.001), infection (p < 0.001), death (p = 0.004), and surgical complications (p < 0.001). No differences were observed in rates of 30-day VTE or length of hospital stay. Immigrants were more likely to be discharged to rehabilitation (p < 0.001) and less likely to present to the emergency department (p < 0.001) than Canadian-born patients. CONCLUSION: Compared with Canadian-born patients, immigrants and refugees have favourable surgical outcomes and similar rates of resource utilization after TKA. We observed an underutilization of these procedures in Ontario relative to their proportion of the population. This may reflect differences in perceptions of chronic pain or barriers accessing arthroplasty.

Hospital Readmission Rates for Patients Receiving In-Person vs. Telemedicine Discharge Follow-Up Care.

INTRODUCTION: Unplanned readmissions can be avoided by standardizing and improving the coordination of care after discharge. Telemedicine has been increasingly utilized; however, the quality of this care has not been well studied. Standardized measures can provide an objective comparison of care quality. The purpose of our study was to compare quality performance transitions of care management in the office vs telemedicine. METHODS: The Epic SlicerDicer tool was used to compare the percentage of encounters that were completed via telemedicine (video visits); or via in-person for comparison, Chi-squared tests were used. RESULTS: A total of 13,891 patients met the inclusion criteria during the study time frame. There were 12,846 patients in the office and 1,048 in the telemedicine cohort. The office readmission rate was 11.9% with 1,533 patients out of 12,846 compared with telemedicine with the rate of readmission at 12.1% with 126 patients out of 1,045 patients. The P-value for the Chi-squared test between the prepandemic and study time frame was 0.15 and 0.95, respectively. Demographic comparability was seen. DISCUSSION: Our study found a comparable readmission rate between patients seen via in-office and telemedicine for Transitions of Care Management (TCM) encounters. The findings of this study support the growing body of evidence that telemedicine augments quality performance while reducing cost and improving access without negatively impacting HEDIS performance in health care systems. CONCLUSION: Telemedicine poses little threat of negatively impacting HEDIS performance and might be as effective as posthospitalization traditional office care transitions of care management.

Influence of hospital-level and surgeon factors on the outcomes after ileo-anal pouch surgery for inflammatory bowel disease: systematic review.

BACKGROUND: Ileal pouch-anal anastomosis ('pouch surgery') provides a chance to avoid permanent ileostomy after proctocolectomy, but can be associated with poor outcomes. The relationship between hospital-level/surgeon factors (including volume) and outcomes after pouch surgery is of increasing interest given arguments for increasing centralization of these complex procedures. The aim of this systematic review was to appraise the literature describing the influence of hospital-level and surgeon factors on outcomes after pouch surgery for inflammatory bowel disease. METHODS: A systematic review was performed of studies reporting outcomes after pouch surgery for inflammatory bowel disease. The MEDLINE (Ovid), Embase (Ovid), and Cochrane CENTRAL databases were searched (1978-2022). Data on outcomes, including mortality, morbidity, readmission, operative approach, reconstruction, postoperative parameters, and pouch-specific outcomes (failure), were extracted. Associations between hospital-level/surgeon factors and these outcomes were summarized. This systematic review was prospectively registered in PROSPERO, the international prospective register of systematic reviews (CRD42022352851). RESULTS: A total of 29 studies, describing 41 344 patients who underwent a pouch procedure, were included; 3 studies demonstrated higher rates of pouch failure in lower-volume centres, 4 studies demonstrated higher reconstruction rates in higher-volume centres, 2 studies reported an inverse association between annual hospital pouch volume and readmission rates, and 4 studies reported a significant association between complication rates and surgeon experience. CONCLUSION: This review summarizes the growing body of evidence that supports centralization of pouch surgery to specialist high-volume inflammatory bowel disease units. Centralization of this technically demanding surgery that requires dedicated perioperative medical and nursing support should facilitate improved patient outcomes and help train the next generation of pouch surgeons.

Prognostic Nutritional Index and Instant Nutritional Assessement Are Associated with Clinical Outcomes in a Geriatric Cohort of Acutely Inpatients.

BACKGROUND: Among elderly inpatients, malnutrition is one of the most important predictive factors affecting length of stay (LOS), mortality, and risk of re-hospitalization. METHODS: We conducted an observational, retrospective study on a cohort of 2206 acutely inpatients. Serum albumin and lymphocytes were evaluated. Instant Nutritional Assessment (INA) and the Prognostic Nutritional Index (PNI) were calculated to predict in-hospital mortality, LOS, and risk of rehospitalization. RESULTS: An inverse relationship between LOS, serum albumin, and PNI were found. Deceased patients had lower albumin levels, lower PNI values, and third- and fourth-degree INA scores. An accurate predictor of mortality was PNI (AUC = 0.785) after ROC curve analysis; both lower PNI values (HR = 3.56) and third- and fourth-degree INA scores (HR = 3.12) could be independent risk factors for mortality during hospitalization after Cox regression analysis. Moreover, among 309 subjects with a lower PNI value or third- and fourth-class INA, hospitalization was re-hospitalization. CONCLUSIONS: PNI and INA are two simple and quick-to-calculate tools that can help in classifying the condition of hospitalized elderly patients also based on their nutritional status, or in assessing their mortality risk. A poor nutritional status at the time of discharge may represent an important risk factor for rehospitalization in the following thirty days. This study confirms the importance of evaluating nutritional status at the time of hospitalization, especially in older patients. This study also confirms the importance for adequate training of doctors and nurses regarding the importance of maintaining a good nutritional status as an integral part of the therapeutic process of hospitalization in acute departments.

Developing and validating prediction models for severe exacerbations and readmissions in patients hospitalised for COPD exacerbation (SERCO) in China: a prospective observational study.

BACKGROUND: There is a lack of individualised prediction models for patients hospitalised with chronic obstructive pulmonary disease (COPD) for clinical practice. We developed and validated prediction models of severe exacerbations and readmissions in patients hospitalised for COPD exacerbation (SERCO). METHODS: Data were obtained from the Acute Exacerbations of Chronic Obstructive Pulmonary Disease Inpatient Registry study (NCT02657525) in China. Cause-specific hazard models were used to estimate coefficients. C-statistic was used to evaluate the discrimination. Slope and intercept were used to evaluate the calibration and used for model adjustment. Models were validated internally by 10-fold cross-validation and externally using data from different regions. Risk-stratified scoring scales and nomograms were provided. The discrimination ability of the SERCO model was compared with the exacerbation history in the previous year. RESULTS: Two sets with 2196 and 1869 patients from different geographical regions were used for model development and external validation. The 12-month severe exacerbations cumulative incidence rates were 11.55% (95% CI 10.06% to 13.16%) in development cohorts and 12.30% (95% CI 10.67% to 14.05%) in validation cohorts. The COPD-specific readmission incidence rates were 11.31% (95% CI 9.83% to 12.91%) and 12.26% (95% CI 10.63% to 14.02%), respectively. Demographic characteristics, medical history, comorbidities, drug usage, Global Initiative for Chronic Obstructive Lung Disease stage and interactions were included as predictors. C-indexes for severe exacerbations were 77.3 (95% CI 70.7 to 83.9), 76.5 (95% CI 72.6 to 80.4) and 74.7 (95% CI 71.2 to 78.2) at 1, 6 and 12 months. The corresponding values for readmissions were 77.1 (95% CI 70.1 to 84.0), 76.3 (95% CI 72.3 to 80.4) and 74.5 (95% CI 71.0 to 78.0). The SERCO model was consistently discriminative and accurate with C-indexes in the derivation and internal validation groups. In external validation, the C-indexes were relatively lower at 60-70 levels. The SERCO model discriminated outcomes better than prior severe exacerbation history. The slope and intercept after adjustment showed close agreement between predicted and observed risks. However, in external validation, the models may overestimate the risk in higher-risk groups. The model-driven risk groups showed significant disparities in prognosis. CONCLUSION: The SERCO model provides individual predictions for severe exacerbation and COPD-specific readmission risk, which enables identifying high-risk patients and implementing personalised preventive intervention for patients with COPD.

Interpretable (not just posthoc-explainable) medical claims modeling for discharge placement to reduce preventable all-cause readmissions or death.

We developed an inherently interpretable multilevel Bayesian framework for representing variation in regression coefficients that mimics the piecewise linearity of ReLU-activated deep neural networks. We used the framework to formulate a survival model for using medical claims to predict hospital readmission and death that focuses on discharge placement, adjusting for confounding in estimating causal local average treatment effects. We trained the model on a 5% sample of Medicare beneficiaries from 2008 and 2011, based on their 2009-2011 inpatient episodes (approximately 1.2 million), and then tested the model on 2012 episodes (approximately 400 thousand). The model scored an out-of-sample AUROC of approximately 0.75 on predicting all-cause readmissions-defined using official Centers for Medicare and Medicaid Services (CMS) methodology-or death within 30-days of discharge, being competitive against XGBoost and a Bayesian deep neural network, demonstrating that one need-not sacrifice interpretability for accuracy. Crucially, as a regression model, it provides what blackboxes cannot-its exact gold-standard global interpretation, explicitly defining how the model performs its internal "reasoning" for mapping the input data features to predictions. In doing so, we identify relative risk factors and quantify the effect of discharge placement. We also show that the posthoc explainer SHAP provides explanations that are inconsistent with the ground truth model reasoning that our model readily admits.

Preoperative prediction model for risk of readmission after total joint replacement surgery: a random forest approach leveraging NLP and unfairness mitigation for improved patient care and cost-effectiveness.

BACKGROUND: The Center for Medicare and Medicaid Services (CMS) imposes payment penalties for readmissions following total joint replacement surgeries. This study focuses on total hip, knee, and shoulder arthroplasty procedures as they account for most joint replacement surgeries. Apart from being a burden to healthcare systems, readmissions are also troublesome for patients. There are several studies which only utilized structured data from Electronic Health Records (EHR) without considering any gender and payor bias adjustments. METHODS: For this study, dataset of 38,581 total knee, hip, and shoulder replacement surgeries performed from 2015 to 2021 at Novant Health was gathered. This data was used to train a random forest machine learning model to predict the combined endpoint of emergency department (ED) visit or unplanned readmissions within 30 days of discharge or discharge to Skilled Nursing Facility (SNF) following the surgery. 98 features of laboratory results, diagnoses, vitals, medications, and utilization history were extracted. A natural language processing (NLP) model finetuned from Clinical BERT was used to generate an NLP risk score feature for each patient based on their clinical notes. To address societal biases, a feature bias analysis was performed in conjunction with propensity score matching. A threshold optimization algorithm from the Fairlearn toolkit was used to mitigate gender and payor biases to promote fairness in predictions. RESULTS: The model achieved an Area Under the Receiver Operating characteristic Curve (AUROC) of 0.738 (95% confidence interval, 0.724 to 0.754) and an Area Under the Precision-Recall Curve (AUPRC) of 0.406 (95% confidence interval, 0.384 to 0.433). Considering an outcome prevalence of 16%, these metrics indicate the model's ability to accurately discriminate between readmission and non-readmission cases within the context of total arthroplasty surgeries while adjusting patient scores in the model to mitigate bias based on patient gender and payor. CONCLUSION: This work culminated in a model that identifies the most predictive and protective features associated with the combined endpoint. This model serves as a tool to empower healthcare providers to proactively intervene based on these influential factors without introducing bias towards protected patient classes, effectively mitigating the risk of negative outcomes and ultimately improving quality of care regardless of socioeconomic factors.

Machine learning models on a web application to predict short-term postoperative outcomes following anterior cervical discectomy and fusion.

BACKGROUND: The frequency of anterior cervical discectomy and fusion (ACDF) has increased up to 400% since 2011, underscoring the need to preoperatively anticipate adverse postoperative outcomes given the procedure's expanding use. Our study aims to accomplish two goals: firstly, to develop a suite of explainable machine learning (ML) models capable of predicting adverse postoperative outcomes following ACDF surgery, and secondly, to embed these models in a user-friendly web application, demonstrating their potential utility. METHODS: We utilized data from the National Surgical Quality Improvement Program database to identify patients who underwent ACDF surgery. The outcomes of interest were four short-term postoperative adverse outcomes: prolonged length of stay (LOS), non-home discharges, 30-day readmissions, and major complications. We utilized five ML algorithms - TabPFN, TabNET, XGBoost, LightGBM, and Random Forest - coupled with the Optuna optimization library for hyperparameter tuning. To bolster the interpretability of our models, we employed SHapley Additive exPlanations (SHAP) for evaluating predictor variables' relative importance and used partial dependence plots to illustrate the impact of individual variables on the predictions generated by our top-performing models. We visualized model performance using receiver operating characteristic (ROC) curves and precision-recall curves (PRC). Quantitative metrics calculated were the area under the ROC curve (AUROC), balanced accuracy, weighted area under the PRC (AUPRC), weighted precision, and weighted recall. Models with the highest AUROC values were selected for inclusion in a web application. RESULTS: The analysis included 57,760 patients for prolonged LOS [11.1% with prolonged LOS], 57,780 for non-home discharges [3.3% non-home discharges], 57,790 for 30-day readmissions [2.9% readmitted], and 57,800 for major complications [1.4% with major complications]. The top-performing models, which were the ones built with the Random Forest algorithm, yielded mean AUROCs of 0.776, 0.846, 0.775, and 0.747 for predicting prolonged LOS, non-home discharges, readmissions, and complications, respectively. CONCLUSIONS: Our study employs advanced ML methodologies to enhance the prediction of adverse postoperative outcomes following ACDF. We designed an accessible web application to integrate these models into clinical practice. Our findings affirm that ML tools serve as vital supplements in risk stratification, facilitating the prediction of diverse outcomes and enhancing patient counseling for ACDF.

The patient experience of a postpartum readmission for hypertension: a qualitative study.

BACKGROUND: Hypertensive disorders of pregnancy (HDP) are the most common cause of postpartum readmission. Prior research led to clinical guidelines for postpartum management; however, the patient experience is often missing from this work. The objective of this study is to understand the perspective of patients readmitted for postpartum hypertension. METHODS: This was a qualitative study with data generated through semi-structured interviews. Patients readmitted with postpartum HDP at an urban academic medical center from February to December 2022 were approached and consented for an interview. The same researcher conducted all interviews and patient recruitment continued until thematic saturation was reached (n = 9). Two coders coded all interviews using Nvivo software with both deductive and inductive coding processes. Discrepancies were discussed and resolved with consensus among the two coders. Themes were identified through an initial a priori template of codes which were expanded upon using grounded theory, and researchers were reflexive in their thematic generation. RESULTS: Six themes were generated: every pregnancy is different, symptoms of preeclampsia are easily dismissed or minimized by both patient and providers, miscommunication regarding medical changes can increase the risk of readmissions, postpartum care coordination and readmission logistics at our hospital could be improved to facilitate caring for a newborn, postpartum care is often considered separately from the rest of pregnancy, and patient well-being improved when conversations acknowledged the struggles of readmission. CONCLUSIONS: This qualitative research study revealed patient-identified gaps in care that may have led to readmission for hypertensive disorders of pregnancy. The specific recommendations that emerge from these themes include addressing barriers to blood pressure management prior to discharge, improving postpartum discharge follow-up, providing newborn care coordination, and improving counseling on the risk of postpartum preeclampsia during discharge. Incorporating these patient perspectives in hospital discharge policy can be helpful in creating patient-centered systems of care and may help reduce rates of readmission.

Health mediation does not reduce the readmission rate of frequent users of emergency departments living in precarious conditions: what lessons can be learned from this randomised controlled trial?

BACKGROUND: Severe overcrowding of emergency departments (EDs) affects the quality of healthcare. One factor of overcrowding is precariousness, but it has rarely been considered a key factor in designing interventions to improve ED care. Health mediation (HM) aims to facilitate access to rights, prevention, and care for the most vulnerable persons and to raise awareness among healthcare providers about obstacles in accessing healthcare. The primary aim was to determine whether HM intervention for frequent users of EDs (FUED) living in precarious conditions could reduce the readmission rate at 90 days. METHODS: Between February 2019 and May 2022, we enrolled and interviewed 726 FUED in four EDs of southeastern France in this randomised controlled trial. The HM intervention started in the ED and lasted 90 days. In addition to the primary endpoint (first readmission at 90 days), secondary endpoints (readmission at 30 and 180 days, number of hospitalisations at 30, 90, 180 days, admissions for the same reasons as the first admission) were also studied. The outcomes were measured in the ED information systems. Statistical methods included an intention-to-treat analysis and a per-protocol analysis. Comparisons were adjusted for gender, age, ED, and health mediator. RESULTS: 46% of patients reported attending the ED because they felt their life was in danger, and 42% had been referred to the ED by the emergency medical dispatch centre or their GP; 40% of patients were considered to be in a serious condition by ED physicians. The proportion of patients who were readmitted at 90 days was high but did not differ between the control and the HM intervention groups (31.7% vs. 36.3%, p = 0.23). There was no significant difference in any of the secondary outcome measures between the control and HM intervention groups. Per-protocol analysis also showed no significant difference for the primary and secondary endpoints. CONCLUSIONS: This randomised controlled trial did not show that our health mediation intervention was effective in reducing the use of emergency services by FUED living in precarious conditions. Some limitations are discussed: the duration of the intervention (90 days), the long-term effects (> 6 months), the involvement of the ED staff. TRIAL REGISTRATION: Registered on clinicaltrials.gov as NCT03660215 on 4th September 2018.

Factors Associated with the Treatment Costs within the First Year after Pacemaker Implantation or Pulse Generator Replacement. / Fatores Associados aos Custos do Tratamento no Primeiro Ano após Implantes Iniciais ou Trocas de Geradores de Pulsos de Marca-passos Cardíacos.

BACKGROUND: The use of artificial cardiac pacemakers has grown steadily in line with the aging population. OBJECTIVES: To determine the rates of hospital readmissions and complications after pacemaker implantation or pulse generator replacement and to assess the impact of these events on annual treatment costs from the perspective of the Unified Health System (SUS). METHODS: A prospective registry, with data derived from clinical practice, collected during index hospitalization and during the first 12 months after the surgical procedure. The cost of index hospitalization, the procedure, and clinical follow-up were estimated according to the values reimbursed by SUS and analyzed at the patient level. Generalized linear models were used to study factors associated with the total annual treatment cost, adopting a significance level of 5%. RESULTS: A total of 1,223 consecutive patients underwent initial implantation (n=634) or pulse generator replacement (n=589). Seventy episodes of complication were observed in 63 patients (5.1%). The incidence of hospital readmissions within one year was 16.4% (95% CI 13.7% - 19.6%) after initial implants and 10.6% (95% CI 8.3% - 13.4%) after generator replacements. Chronic kidney disease, history of stroke, length of hospital stays, need for postoperative intensive care, complications, and hospital readmissions showed a significant impact on the total annual treatment cost. CONCLUSIONS: The results confirm the influence of age, comorbidities, postoperative complications, and hospital readmissions as factors associated with increased total annual treatment cost for patients with pacemakers.

FUNDAMENTO: O uso de marca-passos cardíacos artificiais tem crescido constantemente, acompanhando o envelhecimento populacional. OBJETIVOS: Determinar as taxas de readmissões hospitalares e complicações após implante de marca-passo ou troca de gerador de pulsos e avaliar o impacto desses eventos nos custos anuais do tratamento sob a perspectiva do Sistema Único de Saúde (SUS). MÉTODOS: Registro prospectivo, com dados derivados da prática clínica assistencial, coletados na hospitalização índice e durante os primeiros 12 meses após o procedimento cirúrgico. O custo da hospitalização índice, do procedimento e do seguimento clínico foram estimados de acordo com os valores reembolsados pelo SUS e analisados ao nível do paciente. Modelos lineares generalizados foram utilizados para estudar fatores associados ao custo total anual do tratamento, adotando-se um nível de significância de 5%. RESULTADOS: No total, 1.223 pacientes consecutivos foram submetidos a implante inicial (n= 634) ou troca do gerador de pulsos (n= 589). Foram observados 70 episódios de complicação em 63 pacientes (5,1%). A incidência de readmissões hospitalares em um ano foi de 16,4% (IC 95% 13,7% - 19,6%) após implantes iniciais e 10,6% (IC 95% 8,3% - 13,4%) após trocas de geradores. Doença renal crônica, histórico de acidente vascular encefálico, tempo de permanência hospitalar, necessidade de cuidados intensivos pós-operatórios, complicações e readmissões hospitalares mostraram um impacto significativo sobre o custo anual total do tratamento. CONCLUSÕES: Os resultados confirmam a influência da idade, comorbidades, complicações pós-operatórias e readmissões hospitalares como fatores associados ao incremento do custo total anual do tratamento de pacientes com marca-passo.

Hospital at home for elderly acute patients: a study protocol for a randomised controlled trial.

INTRODUCTION: The increasing elderly population has led to a growing demand for healthcare services. A hospital at home treatment model offers an alternative to standard hospital admission, with the potential to reduce readmission and healthcare consumption while improving patients' quality of life. However, there is little evidence regarding hospital at home treatment in a Danish setting. This article describes the protocol for a randomised controlled trial (RCT) comparing standard hospital admission to hospital at home treatment. The main aim of the intervention is to reduce 30-day acute readmission after discharge and improve the quality of life of elderly acute patients. METHODS AND ANALYSIS: A total of 849 elderly acute patients will be randomised in a 1:2 ratio to either the control or intervention group in the trial. The control group will receive standard hospital treatment in a hospital emergency department while the intervention group will receive treatment at home. The primary outcomes of the trial are the rate of 30-day acute readmission and quality of life, assessed using the European Quality of Life-5 Dimensions-5-Level instrument. Primary analyses are based on the intention-to-treat principle. Secondary outcomes are basic functional mobility, resource use in healthcare, primary and secondary healthcare cost, incremental cost-effectiveness ratio, and the mortality rate 3 months after discharge. ETHICS AND DISSEMINATION: The RCT was approved by the Ethical Committee, Central Denmark Region (no. 1-10-72-67-20). Results will be presented at relevant national and international meetings and conferences and will be published in international peer-reviewed journals. Furthermore, we plan to communicate the results to relevant stakeholders in the Danish healthcare system. TRIAL REGISTRATION NUMBER: NCT05360914.

Transcatheter Mitral Valve Repair With the MitraClip Device for Prior Mitral Valve Repair Failure: Insights From the GIOTTO-FAILS Study.

BACKGROUND: Minimally invasive mitral valve repair has a favorable risk-benefit profile in patients with significant de novo mitral regurgitation. Its role in patients with prior mitral valve repair is uncertain. We aimed to appraise the outcome of patients undergoing transcatheter edge-to-edge repair (TEER) with prior transcatheter or surgical mitral valve repair (SMVR). METHODS AND RESULTS: We queried the Italian multicenter registry on TEER with MitraClip, distinguishing naïve patients from those with prior TEER or (SMVR). Inhospital and long-term clinical/echocardiographic outcomes were appraised. The primary outcome was the occurrence of death or rehospitalization for heart failure. A total of 2238 patients were included, with 2169 (96.9%) who were naïve to any mitral intervention, 29 (1.3%) with prior TEER, and 40 (1.8%) with prior SMVR. Several significant differences were found in baseline clinical and imaging features. Respectively, device success was obtained in 2120 (97.7%), 28 (96.6%), and 38 (95.0%, P=0.261) patients; procedural success in 2080 (95.9%), 25 (86.2%), and 38 (95.0%; P=0.047); and inhospital death in 61 (2.8%), 1 (3.5%), and no (P=0.558) patients. Clinical follow-up after a mean of 14 months showed similar rates of death, cardiac death, rehospitalization, rehospitalization for heart failure, and their composite (all P>0.05). Propensity score-adjusted analysis confirmed unadjusted analysis, with lower procedural success for the prior TEER group (odds ratio, 0.28 [95% CI, 0.09-0.81]; P=0.019) but similar odds ratios and hazard ratios for all other outcomes in the naïve, TEER, and SMVR groups (all P>0.05). CONCLUSIONS: In carefully selected patients, TEER can be performed using the MitraClip device even after prior TEER or SMVR.

Charlson and Elixhauser Comorbidity Indices for Prediction of Mortality and Hospital Readmission in Patients With Acute Pulmonary Embolism.

Several risk stratification systems aid clinicians in classifying pulmonary embolism (PE) severity and prognosis. We compared 2 clinical PE scoring systems, the PESI and sPESI scores, with 2 comorbidity indices, the Charlson Comorbidity Index (CCI) and the val Walraven Elixhauser Comorbidity Index (ECI), to determine the utility of each in predicting mortality and hospital readmission. Information was collected from 436 patients presenting with PE via retrospective chart review. The PESI, sPESI, CCI, and ECI scores were calculated for each patient. Multivariate analysis was used to determine each system's ability to predict in-hospital mortality, 90-day mortality, overall mortality, and all-cause hospital readmission. The impact of various demographic and clinical characteristics of each patient on these outcomes was also assessed. The PESI score was found to be an independent predictor of in-hospital mortality and 90-day mortality. The PESI score and the CCI were able to independently predict overall mortality. None of the 4 risk scores independently predicted hospital readmission. Other factors including hypoalbuminemia, serum BNP, coagulopathy, anemia, and diabetes were associated with increased mortality and readmission at various endpoints. The PESI score was the best tool for predicting mortality at any endpoint. The CCI may have utility in predicting long-term outcomes. Further work is needed to better determine the roles of the CCI and ECI in predicting patient outcomes in PE. The potential prognostic implications of low serum albumin and anemia at the time of PE also warrant further investigation.

Clinical and health care utilization variables can predict 90-day hospital re-admission in adults with Crohn's disease for point of care risk evaluation.

BACKGROUND: Hospital re-admission for persons with Crohn's disease (CD) is a significant contributor to morbidity and healthcare costs. We derived prediction models of risk of 90-day re-hospitalization among persons with CD that could be applied at hospital discharge to target outpatient interventions mitigating this risk. METHODS: We performed a retrospective study in persons with CD admitted between 2009 and 2016 for an acute CD-related indication. Demographic, clinical, and health services predictor variables were ascertained through chart review and linkage to administrative health databases. We derived and internally validated a multivariable logistic regression model of 90-day CD-related re-hospitalization. We selected the optimal probability cut-point to maximize Youden's index. RESULTS: There were 524 CD hospitalizations and 57 (10.9%) CD re-hospitalizations within 90 days of discharge. Our final model included hospitalization within the prior year (adjusted odds ratio [aOR] 3.27, 95% confidence interval [CI] 1.76-6.08), gastroenterologist consultation within the prior year (aOR 0.185, 95% CI 0.0950-0.360), intra-abdominal surgery during index hospitalization (aOR 0.216, 95% CI 0.0500-0.934), and new diagnosis of CD during index hospitalization (aOR 0.327, 95% CI 0.0950-1.13). The model demonstrated good discrimination (optimism-corrected c-statistic value 0.726) and excellent calibration (Hosmer-Lemeshow goodness-of-fit p-value 0.990). The optimal model probability cut point allowed for a sensitivity of 71.9% and specificity of 70.9% for identifying 90-day re-hospitalization, at a false positivity rate of 29.1% and false negativity rate of 28.1%. CONCLUSIONS: Demographic, clinical, and health services variables can help discriminate persons with CD at risk of early re-hospitalization, which could permit targeted post-discharge intervention.

Rethinking postoperative care: same-day ileostomy closure discharge improves patient outcomes.

BACKGROUND: The evolution of enhanced recovery pathways (ERPs) in colon and rectal surgery has led to the development of same-day discharge (SDD) procedures for selected patients. Early discharge after diverting loop ileostomy (DLI) closure was first described in 2003. However, its widespread adoption remains limited, with SDD accounting for only 3.2% of all DLI closures in 2005-2006, according to the American College of Surgeons National Surgical Quality Improvement Program database, and rising to just 4.1% by 2016. This study aimed to compare the outcomes of SDD DLI closure with those of DLI closure after the standard ERP. METHODS: A retrospective case-matched study compared 125 patients undergoing SDD DLI closure with 250 patients undergoing DLI closure after the standard ERP based on age (±1 year), sex, American Society of Anesthesiologists score, body mass index, surgery date (±2 months), underlying disease, and hospital site. The primary outcome was comparative 30-day complication rates. RESULTS: Patients in the traditional ERP group received more intraoperative fluids (1221.1 ± 416.6 vs 1039.0 ± 368.3 mL, P < .001) but had similar estimated blood loss. Ten patients (8%) in the SDD-ERP group failed SDD. The 30-day postoperative complication rate was significantly lower in the SDD group (14.8%) than the standard ERP group (25.7%, P = .025). This difference was primarily driven by a lower incidence of ileus in the SDD group (9.6% vs 14.8%, P = .034). There were no significant differences in readmission rate (9.6% of SDD-ERP vs 9.2% of standard ERP, P = .900) and reoperation rates (3.2% of SDD-ERP vs 2.4% of standard ERP, P = .650). CONCLUSION: SDD ileostomy closure is a safe, feasible, and effective procedure associated with fewer complications than the present study's standard ERP. This could represent a new standard of care. Further prospective trials are required to confirm the findings of this study.

The principles of enhanced recovery after percutaneous endoscopic gastrostomy (ERaPEG): a UK tertiary center experience.

PURPOSE: Enhanced recovery after surgery (ERAS) pathways have been shown to improve surgical outcomes and patient satisfaction. The aim of the study was to assess whether the implementation of a perioperative enhanced recovery after percutaneous endoscopic gastrostomy (ERaPEG) pathway based on ERAS principles was safe, satisfactory to parents and improved outcomes. METHODS: Following a quality improvement project, a multimodal ERaPEG pathway was introduced as standard practice within the department and children undergoing elective same-day admission percutaneous endoscopic gastrostomy (PEG) at a single UK tertiary center were prospectively enrolled. Exclusion criteria were patients undergoing other concurrent procedures and those who underwent a laparoscopic assisted/open procedure. Data included patient demographics, underlying diagnosis, indication, length of stay (LOS) and 30-day readmission. Parental experience and satisfaction were determined using a questionnaire including 5-point Likert scales. A retrospective cohort was used for comparison. Data were analyzed using Chi-Square test and Mann-Whitney U tests. RESULTS: Ninety-five patients met the inclusion criteria: 50 pre and 45 post the implementation of ERaPEG. Median age was 3 and 2 years, respectively. Neurodisability was the underlying diagnosis in most patients (84%-pre-ERaPEG; 76%-post-ERaPEG). Most common PEG indication was medication/nutritional supplementation (52%-pre-ERaPEG; 51%-post-ERaPEG). The LOS significantly decreased from a median of 51.5 h (pre-ERaPEG) to 32 h (post-ERaPEG) (p < 0.001). Thirty-day readmission rates were similar (6% vs 11%). Most parents felt that the educational material was easy to access and understand. Post-operatively the majority of parents (≥ 80%) were confident in managing the gastrostomy device, setting up/giving the feeds and also felt that the LOS was appropriate. CONCLUSION: This study shows that the implementation of an ERaPEG pathway significantly reduced LOS following PEG. In addition, the pathway was satisfactory to parents and offered the benefit of improved resource utilization.