Early Hospital Readmission (EHR) in kidney transplantation: a review article

Influence of physical function and frailty on unplanned readmission in middle-aged and older patients discharged from a hospital: a follow-up study

BACKGROUND

Unplanned readmissions are associated with increased mortality among older patients. This study investigated the effects of changes in physical function and frailty on unplanned readmissions in middle-aged and older patients after discharge.

METHODS

This longitudinal study recruited participants through convenience sampling from the general wards of a medical center in northern Taiwan. They were aged 50 years or older and identified as being at high risk for readmission or mortality following discharge. Baseline data were collected through interviews conducted the day before discharged, while follow-up data were obtained through interviews at 1, 2, and 3 months post-discharge. Generalized estimating equation (GEE) was used for statistical analysis, incorporating all tracked variables, including physical function and frailty.

RESULTS

A total of 230 participants were recruited, each followed three times after discharge. The unplanned readmission rates at 1, 2, and 3 months post-discharge were 2%, 8%, and 14%, respectively. Participants with poorer physical function (odds ratio [OR] = 1.60 [1.27-2.02]) and more severe frailty symptoms (OR = 3.16 [1.45-6.83]) had significantly higher odds of unplanned readmission. The interaction between the time and frailty indicated a significantly lower likelihood of unplanned readmission over time (OR = 0.73 [0.54-0.98]).

CONCLUSIONS

Declining physical function and frailty are key risk factors for unplanned readmission in older patients. Effective strategies to reduce this risk include monitoring physical function and frailty symptoms and providing supportive care services.

Twenty-Five Years of Evolution and Hurdles in Electronic Health Records and Interoperability in Medical Research: Comprehensive Review

BACKGROUND

Electronic health records (EHRs) facilitate the accessibility and sharing of patient data among various health care providers, contributing to more coordinated and efficient care.

OBJECTIVE

This study aimed to summarize the evolution of secondary use of EHRs and their interoperability in medical research over the past 25 years.

METHODS

We conducted an extensive literature search in the PubMed, Scopus, and Web of Science databases using the keywords Electronic health record and Electronic medical record in the title or abstract and Medical research in all fields from 2000 to 2024. Specific terms were applied to different time periods.

RESULTS

The review yielded 2212 studies, all of which were then screened and processed in a structured manner. Of these 2212 studies, 2102 (93.03%) were included in the review analysis, of which 1079 (51.33%) studies were from 2000 to 2009, 582 (27.69%) were from 2010 to 2019, 251 (11.94%) were from 2020 to 2023, and 190 (9.04%) were from 2024.

CONCLUSIONS

The evolution of EHRs marks an important milestone in health care's journey toward integrating technology and medicine. From early documentation practices to the sophisticated use of artificial intelligence and big data analytics today, EHRs have become central to improving patient care, enhancing public health surveillance, and advancing medical research.

The Burden of ABO-Incompatible Kidney Transplantation: Readmission Rates and Complications, a Twenty-Year Analysis

Background/Objectives: ABO-incompatible live-donor kidney transplantation (ABOi-LDKT) has become an established treatment for end-stage renal disease. Non-inferiority in the long-term graft function compared to ABO-compatible live-donor kidney transplantations (ABOc-LDKTs) has been shown. However, the assumed burden due to complications owing to increased immunosuppression inherent to ABOi-LDKTs has not yet been quantified. The aim of this study was to determine if ABOi-LDKT recipients suffer from additional morbidity and whether the resulting burden is justified. Methods: We retrospectively analyzed 45 matched pairs of ABOi-LDKTs and ABOc-LDKTs transplanted over a twenty-year period from January 2000 to March 2020. The number and duration of postoperative readmissions, surgical complication rates according to Clavien-Dindo and its comprehensive complication index (CCI), kidney function, occurrence of new-onset diabetes, and infections as well as tumor incidence were analyzed. Results: Patient and graft survival, as well as graft function, were comparable between the two groups. There were no significant differences in terms of complications, readmission rates, and length of readmission, as well as infection and rejection rates. The median CCIs for ABOi-LDKTs and ABOc-LDKTs at primary discharge and 3, 6, 12, and >12 months were 20.9 vs. 20.9 (p = 0.363), 31.4 vs. 33.7 (p = 0.438), 33.7 vs. 33.7 (p = 0.875), 20.9 vs. 33.1 (p = 0.25), and 27.1 vs. 31.9 (p = 0.163), respectively. Conclusions: ABOi-LDKT seems safe, with comparable outcome, complication, and readmission rates to ABOc-LDKT. In recipients with ABOi living donors, transplantation should not be delayed solely due to concerns over increased perioperative risks.

Suspicious of Acute Kidney Graft Rejection: Tacrolimus Pharmacokinetics Under Methylprednisolone Therapy

BACKGROUND

Acute rejection remains one of the main complications in the first months after transplantation and may influence long-term outcomes. Tacrolimus has proven its usefulness in solid organ transplants and its monitoring through the application of pharmacokinetic concepts to optimize individual drug therapy.

OBJECTIVE

This research proposes to evaluate the tacrolimus pharmacokinetic parameters in patients suspected of acute kidney graft rejection under methylprednisolone pulse therapy.

METHODS

Eleven adult tacrolimus-treated renal recipients were selected from a prospective, single-arm, single-center cohort study, with suspicion of acute rejection although in use of methylprednisolone pulses therapy. They were followed up for three months posttransplantation, being tacrolimus trough serum concentrations determined using a chemiluminescent magnetic immunoassay, and pharmacokinetic parameters were estimated by using a nonlinear mixed-effects model implemented by Monolix 2020R1. A tacrolimus trough serum concentration range of 8 to 12 ng.mL-1 was considered therapeutic.

RESULTS

Six patients showed acute cellular rejection, and two of them in addition had an antibody- mediated rejection. Tacrolimus trough serum concentration was below the reference range in eight patients. Most patients showed a high tacrolimus concentration intrapatient and pharmacokinetic parameters variability.

CONCLUSION

The obtained pharmacokinetics parameters helped in understanding the kidney recipient patients' tacrolimus behavior, assisting in the improvement of individual drug therapy and reducing the risk of acute rejection episodes.

Outcomes of early hospital readmission after kidney transplantation: Perspectives from a Canadian transplant centre

BACKGROUND

Early hospital readmissions (EHRs) after kidney transplantation range in incidence from 18%-47% and are important and substantial healthcare quality indicators. EHR can adversely impact clinical outcomes such as graft function and patient mortality as well as healthcare costs. EHRs have been extensively studied in American healthcare systems, but these associations have not been explored within a Canadian setting. Due to significant differences in the delivery of healthcare and patient outcomes, results from American studies cannot be readily applicable to Canadian populations. A better understanding of EHR can facilitate improved discharge planning and long-term outpatient management post kidney transplant.

AIM

To explore the burden of EHR on kidney transplant recipients (KTRs) and the Canadian healthcare system in a large transplant centre.

METHODS

This single centre cohort study included 1564 KTRs recruited from January 1, 2009 to December 31, 2017, with a 1-year follow-up. We defined EHR as hospitalizations within 30 d or 90 d of transplant discharge, excluding elective procedures. Multivariable Cox and linear regression models were used to examine EHR, late hospital readmissions (defined as hospitalizations within 31-365 d for 30-d EHR and within 91-365 d for 90-d EHR), and outcomes including graft function and patient mortality.

RESULTS

In this study, 307 (22.4%) and 394 (29.6%) KTRs had 30-d and 90-d EHRs, respectively. Factors such as having previous cases of rejection, being transplanted in more recent years, having a longer duration of dialysis pretransplant, and having an expanded criteria donor were associated with EHR post-transplant. The cumulative probability of death censored graft failure, as well as total graft failure, was higher among the 90-d EHR group as compared to patients with no EHR. While multivariable models found no significant association between EHR and patient mortality, patients with EHR were at an increased risk of late hospital readmissions, poorer kidney function throughout the 1st year post-transplant, and higher hospital-based care costs within the 1st year of follow-up.

CONCLUSION

EHRs are associated with suboptimal outcomes after kidney transplant and increased financial burden on the healthcare system. The results warrant the need for effective strategies to reduce post-transplant EHR.

Incidence and Causes of Early Hospital Readmissions After Living-Donor Renal Transplant at King Abdulaziz Medical City, Riyadh

BACKGROUND

 Living-donor organ transplant has a higher long-term survival rate compared to deceased-donor organ transplant, with kidney transplantation being the optimal treatment for most kidney failure patients. However, early hospital readmission within 30 days of discharge can occur due to various factors and can negatively affect long-term outcomes. Effective communication with patients pre-and post-transplant is crucial for a better quality of life and for reducing readmissions. Chronic kidney disease and co-morbid conditions must also be addressed for better long-term outcomes. The incidence and causes of early hospital readmission vary depending on local characteristics and other factors.

METHODS

 A retrospective cohort study of outcomes in patients who underwent living-donor renal transplantation at King Abdulaziz Medical City (KAMC) between 2015 and 2022. Data were collected by chart review using the BestCare system. The data collected included patients' demographics, comorbidities, surgery-related data, and the outcome of transplantation. The categorical data were presented using percentages and frequencies, while the numerical data were presented as mean and standard deviation. The Chi-square test was used for inferential statistics to find the association between categorical variables.

RESULTS

 Regarding sociodemographic characteristics, the majority of patients were male, aged 19-50 years, and either overweight or had obesity class 1. The incidence of complications, graft failure, and mortality after renal transplant was low, with only a small percentage of patients experiencing these outcomes within one year of transplant. There is no significant association between gender, age, BMI, and the likelihood of readmission after renal transplantation. Patients with comorbidities such as hypertension, diabetes, and coronary artery disease had a higher likelihood of readmission after renal transplantation. The study provides an association between readmission after renal transplantation and various factors such as surgical complications, previous transplant, age at transplant, graft failure, and mortality. Out of the 107 readmitted patients, 2.8% had surgical complications, and 5.6% had a previous transplant, but the association was not statistically significant.

CONCLUSION

 Early hospital readmission within 30 days of discharge can be a concern for patients undergoing renal transplants. While the incidence of complications, graft failure, and mortality after renal transplant was low, patients with comorbidities such as hypertension, diabetes, and coronary artery disease had a higher likelihood of readmission after renal transplantation. Although the association between surgical complications and readmission was not statistically significant, it is important to continue monitoring this factor in future studies. Effective communication with patients pre-and post-transplant can play a crucial role in reducing readmissions and improving long-term outcomes.

Predicting hospital readmission risk in patients with COVID-19: A machine learning approach

Introduction

The Coronavirus 2019 (COVID-19) epidemic stunned the health systems with severe scarcities in hospital resources. In this critical situation, decreasing COVID-19 readmissions could potentially sustain hospital capacity. This study aimed to select the most affecting features of COVID-19 readmission and compare the capability of Machine Learning (ML) algorithms to predict COVID-19 readmission based on the selected features.

Material and methods

The data of 5791 hospitalized patients with COVID-19 were retrospectively recruited from a hospital registry system. The LASSO feature selection algorithm was used to select the most important features related to COVID-19 readmission. HistGradientBoosting classifier (HGB), Bagging classifier, Multi-Layered Perceptron (MLP), Support Vector Machine ((SVM) kernel = linear), SVM (kernel = RBF), and Extreme Gradient Boosting (XGBoost) classifiers were used for prediction. We evaluated the performance of ML algorithms with a 10-fold cross-validation method using six performance evaluation metrics.

Results

Out of the 42 features, 14 were identified as the most relevant predictors. The XGBoost classifier outperformed the other six ML models with an average accuracy of 91.7%, specificity of 91.3%, the sensitivity of 91.6%, F-measure of 91.8%, and AUC of 0.91%.

Conclusion

The experimental results prove that ML models can satisfactorily predict COVID-19 readmission. Besides considering the risk factors prioritized in this work, categorizing cases with a high risk of reinfection can make the patient triaging procedure and hospital resource utilization more effective.

Nursing Care for Kidney Transplant Patients: A Scoping Review

Objectives: Mapping nursing care in kidney transplant patients. Materials and method: A scoping review was conducted according to the recommendations of the Joanna Briggs Institute Reviewers’ Manual. Data were collected through 13 national and international databases from December 2020 to January 2021, following scientific rigor in the selection of the material. The pre-selection was made by reading the title, abstract and introductory text in advance; the materials included in this stage were read in full to define the content for the study. Results: Fifteen studies were included. Of these, 60% are articles; dissertations, manuals, protocols, guidelines and bulletins totaled 40% of the material studied. 86.6% of the material has a quantitative approach. Regarding the methodological design, 73.3% were descriptive/transversal character studies. Regarding the mapping of nursing care, it was possible to divide them into two categories: nursing care after kidney transplantation (immediate, mediated and late) and nursing care after kidney transplantation in primary health/extra-hospital care. Conclusions: It is concluded that the study allowed mapping nursing care to kidney transplant patients in the immediate, late and primary health care periods.