Preoperative preparation of children with upper respiratory tract infection: a focussed narrative review.

This review summarises the current evidence for the perioperative preparation in children with upper respiratory tract infections (URTI), including COVID-19 infection. URTI, including COVID-19 infection, are common and frequent in children who present for elective surgery. Children with URTI are at increased risk of perioperative respiratory adverse events. Perioperative respiratory adverse events are among the most serious and impactful consequences of paediatric anaesthesia, including cardiorespiratory arrest, and therefore present a significant challenge for the paediatric anaesthetist. This review addresses the pathophysiology and time course of URTI, including COVID-19. The evidence-based patient, anaesthetic, and surgical risk factors for perioperative respiratory adverse events are summarised. These risk factors work synergistically to determine individual patient risk and allow for risk stratification both clinically and with validated scoring systems. Evidence-based optimisation of modifiable respiratory risk factors can reduce the risk of perioperative bronchospasm. The evidence for the anaesthesia management options, including the timing and setting of surgery, experience of the paediatric anaesthetist, premedication, choice of airway device, choice of agent for induction and maintenance of anaesthesia, and deep vs awake tracheal extubation techniques along with a risk stratification framework are discussed.

Integrating oxidative-stress biomarkers into a precision oncology risk-stratification model for bladder cancer prognosis and therapy.

Introduction: Bladder cancer is a common malignant tumor with significant heterogeneity, making personalized risk stratification crucial for optimizing treatment and prognosis. This study aimed to develop a prognostic model based on oxidative stress-related genes to guide risk assessment in bladder cancer. Methods: Differentially expressed oxidative stress-related genes were identified using the GEO database. Functional enrichment and survival analyses were performed on these genes. A risk-scoring model was built and tested for prognostic value and therapeutic response prediction. Expression of key genes was validated by qRT-PCR in samples from two muscle-invasive and two non-muscle-invasive bladder cancer patients. Results: Several oxidative stress-related genes were identified as significantly associated with survival. The risk-scoring model stratified patients into high- and low-risk groups, accurately predicting prognosis and therapeutic responses. qRT-PCR confirmed the differential expression of key genes in patient samples. Discussion: The study provides a concise risk stratification model based on oxidative stress-related genes, offering a practical tool for improving personalized treatment in bladder cancer. Further validation is required for broader clinical application.

Advancing gastrointestinal stromal tumor management: The role of imagomics features in precision risk assessment.

BACKGROUND: Gastrointestinal stromal tumors (GISTs) vary widely in prognosis, and traditional pathological assessments often lack precision in risk stratification. Advanced imaging techniques, especially magnetic resonance imaging (MRI), offer potential improvements. This study investigates how MRI imagomics can enhance risk assessment and support personalized treatment for GIST patients. AIM: To assess the effectiveness of MRI imagomics in improving GIST risk stratification, addressing the limitations of traditional pathological assessments. METHODS: Analyzed clinical and MRI data from 132 GIST patients, categorizing them by tumor specifics and dividing into risk groups. Employed dimension reduction for optimal imagomics feature selection from diffusion-weighted imaging (DWI), T1-weighted imaging (T1WI), and contrast enhanced T1WI with fat saturation (CE-T1WI) fat suppress (fs) sequences. RESULTS: Age, lesion diameter, and mitotic figures significantly correlated with GIST risk, with DWI sequence features like sphericity and regional entropy showing high predictive accuracy. The combined T1WI and CE-T1WI fs model had the best predictive efficacy. In the test group, the DWI sequence model demonstrated an area under the curve (AUC) value of 0.960 with a sensitivity of 80.0% and a specificity of 100.0%. On the other hand, the combined performance of the T1WI and CE-T1WI fs models in the test group was the most robust, exhibiting an AUC value of 0.834, a sensitivity of 70.4%, and a specificity of 85.2%. CONCLUSION: MRI imagomics, particularly DWI and combined T1WI/CE-T1WI fs models, significantly enhance GIST risk stratification, supporting precise preoperative patient assessment and personalized treatment plans. The clinical implications are profound, enabling more accurate surgical strategy formulation and optimized treatment selection, thereby improving patient outcomes. Future research should focus on multicenter studies to validate these findings, integrate advanced imaging technologies like PET/MRI, and incorporate genetic factors to achieve a more comprehensive risk assessment.

MicroRΝΑ analysis in patients with myelodysplastic neoplasms. Possible implications in risk stratification.

MiRNAs have been identified as participants in leukemogenesis by controlling several cellular functions, such as differentiation, proliferation, and apoptosis. Their role in myelodysplastic neoplasms (MDS) pathogenesis is researched due to implementations in early identification, classification, and therapeutical options. IPSS-R, being the most widely used MDS classification, underestimates early biological events that can alter the disease's prognosis. The purpose of this study is to determine whether miRNA levels are aligned to MDS risk stratification groups and can therefore be used as diagnostic biomarkers. To evaluate miRNAs as possible biomarkers, we measured the levels of miR-181a-2-3p, miR-124-3p, miR-550a-3p, miR-155-5p, miR-151a-3p, and miR-125b-5p by a quantitative real-time PCR in bone marrow samples of 41 MDS patients. In conclusion, in myeloid malignancies, genomic characteristics may provide a wider apprehension of its clinical course and prognosis. MiRNAs constitute a possible diagnostic biomarker and therapeutic target, allowing intermediate-risk patients that express high levels of specific miRNAs to be re-classified and receive more advanced therapeutic agents. In our study, an association between high levels of miRNAs and worsening outcomes is established, supporting the need for further incorporation of molecular data into currently used classification systems.

A machine learning algorithm-based risk prediction score for in-hospital/30 day mortality after adult cardiac surgery.

OBJECTIVES: A study of the performance of in-hospital/30 day mortality risk prediction models using an alterantive machine learning algorithm(XGBoost) in adults undergoing cardiac surgery. METHODS: Retrospective analyses of prospectively routinely collected data on adult patients undergoing cardiac surgery in the UK(UK) from January 2012 to March 2019.Data was temporally split 70:30 into training and validation subsets. Independent mortality prediction models were created using sequential backward floating selection(SBFS) starting with 61 variables. Assessments of discrimination, calibration and clinical utility of the resultant XGBoost model with 23 variables were then conducted. RESULTS: 224,318 adults underwent cardiac surgery during the study period with a 2.76%(N = 6,100) mortality. In the testing cohort, there was good discrimination(AUC 0.846, F1 0.277) and calibration(especially in high-risk patients). Decision curve analysis showed XGBoost-23 had a greater net benefit till a threshold probability of 60%.The most important variables were the type of operation, age, creatinine clearance, urgency of the procedure and the New York Heart Association score. CONCLUSIONS: Feature-selected XGBoost showed good discrimination, calibration and clinical benefit when predicting mortality post-cardiac surgery. Prospective external validation of a XGBoost-derived model performance is warranted.

Development of a Mitochondrial Membrane Permeability Transition Prognosis System in Colon Adenocarcinoma: Risk Stratification and Therapeutic Target Identification.

AIMS: Explore the role of mitochondrial membrane permeability transition (MPT) in colon adenocarcinoma (COAD). BACKGROUND: Further exploration of risk stratification for COAD prognostic assessment has important clinical value. MPT-related pathways play a key role in the pathogenesis of many human diseases, including tumorigenesis. Its impact on COAD is still unknown. OBJECTIVE: Bioinformatics analysis was conducted by analyzing the GEO database and TCGA database, and the bioinformatics results were verified by in vitro experiments. METHOD: Through the analysis of the transcriptome data of 1008 COAD samples in the GEO database and TCGA database, the differential expressions of MPT-related genes in COAD were explored, followed by molecular subtype analysis based on MPT characteristics by univariate Cox algorithm analysis and the consensus clustering algorithm. The gene signature associated with MPT molecular subtypes was further identified and the MPT scoring system was established by the LASSO-univariate Cox analysis algorithm. After evaluating the prognostic value of the MPT scoring system in COAD patients via nomogram establishment, the clinical value of the MPT scoring system was comprehensively analyzed through somatic mutation characteristics analysis, immunotherapy response analysis, immunoinfiltration analysis, and drug sensitivity analysis. CCK-8, WB, PCR, colony formation method, and Transwell method were used to verify the effect of the screened target on the proliferation and invasion of COAD cells. RESULT: We successfully established a scoring system related to MPT and validated the prognostic value of COAD patients. The potential clinical value of the MPT scoring system was also analyzed. VSIG4 was selected for further in vitro experiments to verify the effect of the screened targets on the proliferation and invasion ability of COAD cells. CONCLUSIONS: We established an MPT scoring system for effective risk stratification of COAD patients, demonstrating the impact of MPT on the development of COAD and its potential value as an intervention factor.

A simplified and robust risk stratification model for stem cell transplantation in pediatric acute myeloid leukemia.

The efficacy of stem cell transplantation (SCT) in pediatric acute myeloid leukemia (pAML) remains unsatisfactory due to the limitations of existing prognostic models in predicting efficacy and selecting suitable candidates. This study aims to develop a cytomolecular risk stratification-independent prognostic model for SCT in pAML patients at CR1 stage. The pAML SCT model, based on age, KMT2A rearrangement (KMT2A-r), and minimal residual disease at end of course 1 (MRD1), effectively classifies patients into low-, intermediate-, and high-risk groups. We validate the effectiveness in an internal validation cohort and in four external validation cohorts, consisting of different graft sources and donors. Moreover, by incorporating the FMS-like tyrosine kinase 3/internal tandem duplication (FLT3/ITD) allelic ratio, the pAML SCT model is refined, enhancing its ability to effectively select suitable candidates. We develop a simple and robust risk stratification model for pAML patients undergoing SCT, to aid in risk stratification and inform pretransplant decision-making at CR1 stage.

Fragmented QRS in patients with preeclampsia.

PURPOSE: This study aims to investigate the prevalence, clinical correlates, and prognostic implications of fragmented QRS complexes (fQRS) in pregnant women with preeclampsia (PE), shedding light on the potential role of electrocardiographic markers in identifying cardiac involvement in hypertensive disorders of pregnancy. METHODS: Patients with PE and age-matched low-risk control patients were recruited at a tertiary hospital between January 2015 and January 2023. A comprehensive assessment, including heart rate, PR duration, QRS duration, corrected QT duration, and fragmented QRS, was conducted by 12-lead electrocardiography. Baseline clinical characteristics, laboratory parameters, and electrocardiographic findings were compared between the study groups. RESULT: 128 preeclampsia patients and 122 age- and comorbidity-matched controls were included in the study. The prevalence of fQRS was significantly higher in preeclamptic women compared to normotensive controls (14.1% vs. 3.3%, p = 0.04). ALT levels of pregnant women with preeclampsia and without preeclampsia groups were 43,77 (35.25-48.22) and 23,18 (13.75-33.00) (p: 0.038), respectively. In univariate regression analyses, Na and fragmented QRS were found to be associated with preeclampsia. (p: 0.016 and 0.009, respectively). After multivariable adjustment for variables, Na and fragmented QRS remained strongly associated with preeclampsia (OR: 4.787 (1.556-14.720), p: 0.06; 0.941 (0.893-0.992), p: 0.023, respectively). CONCLUSION: This study provides compelling evidence of an association between preeclampsia and fragmented QRS complexes, implicating electrolyte imbalances and hemodynamic stress as potential contributors to myocardial electrical instability in hypertensive disorders of pregnancy. Further research is warranted to validate these findings and improve risk stratification and clinical outcomes in affected women. Number: 2023/4705 Retrospectively Registered.

Prognostic factors and risk-stratification model of recurrent or metastatic head and neck squamous cell carcinoma treated with cetuximab containing regimen.

BACKGROUND: In recent years, the addition of cetuximab to chemotherapy has improved treatment outcomes for patients with recurrent/metastatic head and neck squamous cell carcinoma (R/M HNSCC). In this study, we present the real-world survival data of R/M HNSCC patients who received cetuximab-containing regimens from thirteen medical centers in Taiwan, as well as a three-level risk stratification model for this patient population. METHODS: This study enrolled R/M HNSCC patients from thirteen medical centers in Taiwan who received cetuximab-containing regimens from January 1, 2017 to June 6, 2022. The cases were divided into a training cohort and a validation cohort based on the start of treatment. Overall survival (OS) was evaluated in both cohorts and exploratory analysis was performed to identify associated adverse clinical and laboratory factors. The results of the exploratory analysis were used to construct a three-level risk stratification prediction model for OS. RESULTS: A total of 1434 patients with R/M HNSCC were enrolled in this study and received cetuximab-containing regimens. The overall population had a median OS of 8.57 months (95% CI: 8.07 - 9.08). Multivariate analysis of the training cohort identified poor ECOG performance status, heavy alcohol consumption, and prior adjuvant CCRT or lack of prior RT as adverse prognostic factors. Comparison of laboratory data between patients with OS≦6 and OS > 6 also revealed unfavorable factors, including increased white blood cell count, decreased hemoglobin level, increased platelet count, increased absolute neutrophil count, decreased absolute lymphocyte count, and increased neutrophil-to-lymphocyte ratio. Using forward prediction, a three-level risk stratification prediction model was constructed using the variables of ECOG performance status, alcohol consumption, skin metastasis, modality of radiation therapy, hemoglobin level, and neutrophil-to-lymphocyte ratio. The median OS in the low-risk, intermediate-risk, and high-risk groups were 12.02 months (95% CI 10.44-13.61), 7.5 months (95% CI 7.33-8.17), and 4.01 months (95% CI 3.94-4.08), respectively, with a log-rank test p-value < 0.001. CONCLUSION: This study presents a three-level risk stratification model with strong prediction ability for OS in R/M HNSCC patients who received cetuximab-containing regimens. The results are based on real-world data and may provide valuable information for clinicians in treatment planning and future drug development.

Artificial intelligence based real-time prediction of imminent heart failure hospitalisation in patients undergoing non-invasive telemedicine.

Background: Remote patient management may improve prognosis in heart failure. Daily review of transmitted data for early recognition of patients at risk requires substantial resources that represent a major barrier to wide implementation. An automated analysis of incoming data for detection of risk for imminent events would allow focusing on patients requiring prompt medical intervention. Methods: We analysed data of the Telemedical Interventional Management in Heart Failure II (TIM-HF2) randomized trial that were collected during quarterly in-patient visits and daily transmissions from non-invasive monitoring devices. By application of machine learning, we developed and internally validated a risk score for heart failure hospitalisation within seven days following data transmission as estimate of short-term patient risk for adverse heart failure events. Score performance was assessed by the area under the receiver-operating characteristic (ROCAUC) and compared with a conventional algorithm, a heuristic rule set originally applied in the randomized trial. Results: The machine learning model significantly outperformed the conventional algorithm (ROCAUC 0.855 vs. 0.727, p < 0.001). On average, the machine learning risk score increased continuously in the three weeks preceding heart failure hospitalisations, indicating potential for early detection of risk. In a simulated one-year scenario, daily review of only the one third of patients with the highest machine learning risk score would have led to detection of 95% of HF hospitalisations occurring within the following seven days. Conclusions: A machine learning model allowed automated analysis of incoming remote monitoring data and reliable identification of patients at risk of heart failure hospitalisation requiring immediate medical intervention. This approach may significantly reduce the need for manual data review.

Lymphocyte to high density lipoprotein ratio can predict the short-term prognosis of hepatitis B virus-related acute-on-chronic liver failure patients.

Background: Acute-on-chronic liver failure (ACLF) is a syndrome characterized by systemic inflammation, leading to high short-term mortality. The lymphocyte to high-density lipoprotein ratio (LHR) has been introduced as a novel marker of inflammation. However, its role as a prognostic inflammatory biomarker in the context of hepatitis B virus-related acute-on-chronic liver failure (HBV-ACLF) has received limited attention. Methods: We retrospectively included 272 patients with HBV-ACLF who met the definition of APALC. Data on clinical features and laboratory tests were collected from medical records within 24 h. Logistic regression was used to identify risk factors for poor short-term prognosis, and LHR-based prediction (LHRB) models were constructed based on risk factors. Furthermore, the accuracy of the LHRB model was validated through rigorous testing. Results: In the survival and death groups, there were statistical differences in their CTP, MELD, MELD-Na, COSSH-ACLF II scores, and LHR. Multivariate logistic regression identified seven predictors significantly associated with 28-day mortality. Furthermore, statistically significant differences in short-term mortality and certain clinical laboratory tests for poor prognosis were observed between the high and low LHR groups. To assess the predictive performance of various models in terms of short-term mortality, the area under the receiver operating characteristic curve (AUROC) was calculated. The AUROC values for the CTP, MELD, MELD-Na, COSSH-ACLF II, and LHRB models were found to be 0.725, 0.788, 0.772, 0.871, and 0.877, respectively. The results in the validation group were similar to those in the training group, and the validation results suggested excellent performance of the LHRB model. Conclusion: LHR levels have the potential to serve as indicators for the prognosis of HBV-ACLF. Additionally, the recently developed LHRB model offers an accessible risk assessment tool.

A multiparametric heart failure score at baseline is associated with long-term outcome in patients with remotely monitored implantable cardioverter-defibrillators: A pooled analysis of nine clinical trials.

BACKGROUND: To predict worsening heart failure hospitalizations (WHFHs), the HeartInsight multiparametric algorithm calculates a Heart Failure (HF) Score based on temporal trends of physiologic parameters obtained through automatic daily remote monitoring of implantable cardioverter-defibrillators (ICDs). OBJECTIVE: We studied the association of the baseline HF Score (BHFScore), determined at algorithm activation, with long-term patient outcomes. METHODS: Data from nine clinical trials were pooled, including 1,841 ICD patients with a pre-implant ejection fraction ≤35%, NYHA class II/III, and no long-standing atrial fibrillation. Primary endpoint was a composite of death or WHFH. RESULTS: After a median follow-up of 631 days (interquartile range, 385-865), there were 243 WHFHs in 173 patients (9.4%) and 122 deaths (6.6%), 52 of which (42.6%) were cardiovascular. Primary endpoint occurred in 265 patients (14.4%). A multivariable time-to-first event analysis showed that a high BHFScore (>23, as determined by a time-dependent receiver operating characteristics curve analysis) was significantly associated with the occurrence of primary endpoint (adjusted hazard ratio [HR], 2.05; 95%-confidence interval [CI], 1.54-2.71; p<0.0001), all-cause death (HR, 2.37; CI, 1.56-3.58; p<0.0001), cardiovascular death (HR, 2.19; CI, 1.14-4.22; p=0.019), and WHFH (HR, 1.91; CI, 1.35-2.71; p=0.0003). In a hierarchical event analysis of all-cause death as the outcome with highest priority and WHFHs as repeated-event outcomes, the win-ratio was 2.47 (CI, 1.89-3.24; p<0.0001). CONCLUSIONS: Based on a retrospective analysis of clinical trial data with adjudicated events, baseline HF Score derived from device-monitored variables was able to stratify patients at higher long-term risk of death or WHFH.

High-Risk HLA-DQ Mismatches Are Associated With Adverse Outcomes After Lung Transplantation.

Human leukocyte antigen (HLA) mismatches (MM) between donor and recipient lead to eplet MM (epMM) in lung transplantation (LTX), which can induce the development of de-novo donor-specific HLA-antibodies (dnDSA), particularly HLA-DQ-dnDSA. Aim of our study was to identify risk factors for HLA-DQ-dnDSA development. We included all patients undergoing LTX between 2012 and 2020. All recipients/donors were typed for HLA 11-loci. Development of dnDSA was monitored 1-year post-LTX. EpMM were calculated using HLAMatchmaker. Differences in proportions and means were compared using Chi2-test and Students' t-test. We used Kaplan-Meier curves with LogRank test and multivariate Cox regression to compare acute cellular rejection (ACR), chronic lung allograft dysfunction (CLAD) and survival. Out of 183 patients, 22.9% patients developed HLA-DQ-dnDSA. HLA-DQ-homozygous patients were more likely to develop HLA-DQ-dnDSA than HLA-DQ-heterozygous patients (p = 0.03). Patients homozygous for HLA-DQ1 appeared to have a higher risk of developing HLA-DQ-dnDSA if they received a donor with HLA-DQB1*03:01. Several DQ-eplets were significantly associated with HLA-DQ-dnDSA development. In the multivariate analysis HLA-DQ-dnDSA was significantly associated with ACR (p = 0.03) and CLAD (p = 0.01). HLA-DQ-homozygosity, several high-risk DQ combinations and high-risk epMM result in a higher risk for HLA-DQ-dnDSA development which negatively impact clinical outcomes. Implementation in clinical practice could improve immunological compatibility and graft outcomes.

Cost-effective identification of Barrett's esophagus in the community: A first step towards screening.

BACKGROUND AND AIM: The first step towards developing a screening strategy for Barrett's esophagus (BE) is the identification of individuals in the community. Currently available tools include endoscopy, less-invasive non-endoscopic devices, and non-invasive risk stratification models. We evaluated the cost of potential strategies for identification of BE as a first step towards screening. METHODS: Two hypothetical cohorts of the general population aged ≥ 50 years with BE prevalence rates of 1.9% and 6.8% were modeled. Four potential screening tools were evaluated: (i) risk stratification based on non-weighted clinical factors according to US/European guidelines, (ii) weighted risk stratification using algorithmic models, (iii) less-invasive devices such as Cytosponge + trefoil factor 3 (TFF3), and (iv) endoscopy. Using a decision-analytic model, the cost per BE case identified and the cost-effectiveness were compared for six potential BE screening strategies based on combinations of the four screening tools; (i) + (iv), (ii) + (iv), (iii) + (iv), (i) + (iii) + (iv), (ii) + (iii) + (iv), and only (iv). RESULTS: The cost per BE case identified was lowest for the weighted risk stratification followed by Cytosponge-TFF3 then endoscopy strategy at both 1.9% and 6.8% BE prevalences (US$9282 and US$3406, respectively) although it was sensitive to the cost of less-invasive devices. This strategy was also most cost-effective for a BE prevalence of 1.9%. At BE prevalence of 6.8%, the Cytosponge-TFF3 followed by endoscopy strategy was most cost-effective. CONCLUSIONS: Incorporating weighted risk stratification and less-invasive devices such as Cytosponge-TFF3 into BE screening strategies has a potential to cost-effectively identify BE in the community although device cost and the community prevalence of BE will impact the optimal strategy.

Automated Breast Arterial Calcification Score Is Associated With Cardiovascular Outcomes and Mortality.

Background: Breast arterial calcification (BAC) on mammograms has emerged as a biomarker of women's cardiovascular disease (CVD) risk, but there is a lack of quantification tools and clinical outcomes studies. Objectives: This study assessed the association of BAC (both presence and quantity) with CVD outcomes. Methods: This single-center, retrospective study included women with a screening mammogram from 2007 to 2016. BAC was quantified using an artificial intelligence-generated score, which was assessed as both a binary and continuous variable. Regression analyses evaluated the association between BAC and mortality and a composite of acute myocardial infarction, heart failure, stroke, and mortality. Analyses were adjusted for age, race, diabetes, smoking, blood pressure, cholesterol, and history of CVD and chronic kidney disease. Results: A total of 18,092 women were included in this study (mean age 56.8 ± 11.0 years; diabetes [13%], hypertension [36%], hyperlipidemia [40%], and smoking [5%]). BAC was present in 4,223 (23%). Over a median follow-up of 6 years, death occurred in 7.8% and 2.3% of women with and without BAC, respectively. The composite occurred in 12.4% and 4.3% of women with and without BAC, respectively. Compared to those without, women with BAC had adjusted HRs of 1.49 (95% CI: 1.33-1.67) for mortality and 1.56 (95% CI: 1.41-1.72) for the composite. Each 10-point increase in the BAC score was associated with higher risk of mortality (HR: 1.08 [95% CI: 1.06-1.11]) and the composite (HR: 1.08 [95% CI: 1.06-1.10]). BAC was especially predictive of future events among younger women. Conclusions: BAC is independently associated with mortality and CVD, especially among younger women. Measurement of BAC beyond presence adds incremental risk stratification. Quantifying BAC using an artificial intelligence algorithm is feasible, clinically relevant, and may improve personalized CVD risk stratification.

Transition of care from pediatric to adult nephrology post-renal transplant: a review.

Pediatric renal transplant recipients (RTRs) face heightened risks when they transition from a childhood nephrologist to an adult-centered one. The transition of care usually occurs when an individual is between ages 18 and 21 years, although some change providers earlier or later depending on varying circumstances. Turbulence during this shift can significantly impact daily life and, in severe cases, lead to graft loss. Several modern studies have explored the transition from pediatric to adult-centered nephrology care post-renal transplant. In this review, we first provide an overview of the differences between pediatric and adult renal transplant, highlighting unique challenges faced by pediatric patients such as donor-recipient size disparity, growth impairment, and need for additional immunizations. We then emphasize the criticality of a well-planned transition process, identifying factors that can hinder a smooth transition-such as medical and medication nonadherence, lack of health literacy, patient psychosocial challenges, and systemic shortcomings in coordination between care teams. Furthermore, this review outlines existing protocols and risk assessment tools, in addition to highlighting recent advancements aimed at facilitating smoother transitions such as the RISE protocol, readiness assessment, and the use of multidisciplinary teams. Proper implementation of coordinated, evidence-based transition protocols can improve patient outcomes, promote medication and appointment adherence, and reduce graft rejection rates. Efforts from multidisciplinary teams utilizing technology, risk stratification tools, and open communication between providers and patients are key to optimizing the transition process for pediatric RTRs as they transfer to adult-centered care.

Simplified rapid hydration and contrast-associated acute kidney injury among CKD patients stratified by Mehran score: sub-analysis from the TIME Trial.

Simplified rapid hydration has been proven to be non-inferior to standard hydration in preventing contrast-associated acute kidney injury among chronic kidney disease patients undergoing coronary angiography. The current investigation aimed to further confirm the feasibility and safety of the newly proposed hydration method-simplified rapid hydration (SH) in each risk stratification by Mehran risk score (MRS). Eligible patients (n = 954) randomized to the SH group and standard hydration group were allocated into 2 groups based on MRS: low to moderate-risk and high to very high-risk groups. Primary endpoints were the incidence of contrast-associated acute kidney injury (CA-AKI) and acute heart failure (AHF) (SH vs standard hydration). Secondary endpoints included serum creatinine (Scr), blood urea nitrogen (BUN), cystatin-C (Cys-C), and C-reactive protein (CRP) at 24 h, 48 h, and 72 h after PCI procedure, and the incidence of major adverse cardiac events (MACE). MRS was associated with a higher incidence of CA-AKI (OR = 1.101, 95%CI 1.049-1.156, P < 0.001). In the low to moderate-risk and high to very-high-risk groups, the incidence of CA-AKI in the SH and standard hydration group was 3.3% versus 4.9% (P = 0.5342), 10% versus 12% (P = 0.6392), respectively. Meanwhile, there might be subtle differences in renal function indexes and inflammatory indicators between SH and the control group at different time points. The preventive effect of SH in CA-AKI was similar to standard hydration regardless of MRS-guided risk stratification.