Risk Groups Research Articles

Feasibility of virtual non-iodine coronary calcium scoring on dual source photon-counting coronary CT angiography: a dynamic phantom study.

The aim of our current systematic dynamic phantom study was first, to optimize reconstruction parameters of coronary CTA (CCTA) acquired on photon counting CT (PCCT) for coronary artery calcium (CAC) scoring, and second, to assess the feasibility of calculating CAC scores from CCTA, in comparison to reference calcium scoring CT (CSCT) scans. In this phantom study, an artificial coronary artery was translated at velocities corresponding to 0, < 60, and 60-75 beats per minute (bpm) within an anthropomorphic phantom. The density of calcifications was 100 (very low), 200 (low), 400 (medium), and 800 (high) mgHA/cm3, respectively. CCTA was reconstructed with the following parameters: virtual non-iodine (VNI), with and without iterative reconstruction (QIR level 2, QIR off, respectively); kernels Qr36 and Qr44f; slice thickness/increment 3.0/1.5 mm and 0.4/0.2 mm. The agreement in risk group classification between CACCCTA and CACCSCT scoring was measured using Cohen weighted linear κ with 95% CI. For CCTA reconstructed with 0.4 mm slice thickness, calcium detectability was perfect (100%). At < 60 bpm, CACCCTA of low, and medium density calcification was underestimated by 53%, and 15%, respectively. However, CACCCTA was not significantly different from CACCSCT of very low, and high-density calcifications. The best risk agreement was achieved when CCTA was reconstructed with QIR off, Qr44f, and 0.4 mm slice thickness (κ = 0.762, 95% CI 0.671-0.853). In this dynamic phantom study, the detection of calcifications with different densities was excellent with CCTA on PCCT using thin-slice VNI reconstruction. Agatston scores were underestimated compared to CSCT but agreement in risk classification was substantial. Photon counting CT may enable the implementation of coronary artery calcium scoring from coronary CTA in daily clinical practice. Photon-counting CTA allows for excellent detectability of low-density calcifications at all heart rates. Coronary artery calcium scoring from coronary CTA acquired on photon counting CT is feasible, although improvement is needed. Adoption of the standard acquisition and reconstruction protocol for calcium scoring is needed for improved quantification of coronary artery calcium to fully employ the potential of photon counting CT.

Prediction of recurrence risk in endometrial cancer with multimodal deep learning.

Predicting distant recurrence of endometrial cancer (EC) is crucial for personalized adjuvant treatment. The current gold standard of combined pathological and molecular profiling is costly, hampering implementation. Here we developed HECTOR (histopathology-based endometrial cancer tailored outcome risk), a multimodal deep learning prognostic model using hematoxylin and eosin-stained, whole-slide images and tumor stage as input, on 2,072 patients from eight EC cohorts including the PORTEC-1/-2/-3 randomized trials. HECTOR demonstrated C-indices in internal (n = 353) and two external (n = 160 and n = 151) test sets of 0.789, 0.828 and 0.815, respectively, outperforming the current gold standard, and identified patients with markedly different outcomes (10-year distant recurrence-free probabilities of 97.0%, 77.7% and 58.1% for HECTOR low-, intermediate- and high-risk groups, respectively, by Kaplan-Meier analysis). HECTOR also predicted adjuvant chemotherapy benefit better than current methods. Morphological and genomic feature extraction identified correlates of HECTOR risk groups, some with therapeutic potential. HECTOR improves on the current gold standard and may help delivery of personalized treatment in EC.

Cost-effectiveness of atrial fibrillation detection with insertable cardiac monitors in large-artery or small-vessel disease stroke in the United Kingdom

Abstract Background The randomised STROKE-AF trial demonstrated clinical effectiveness of continuous cardiac monitoring to detect atrial fibrillation (AF) with insertable cardiac monitors (ICMs) for patients with ischemic stroke attributed to large-artery or small-vessel disease (LAD/SVD). ICMs were ten-fold more effective at detecting AF compared to the standard of care (SoC). However, cost-effectiveness of this monitoring strategy is unknown. Purpose The aim of this economic evaluation was to assess the cost-effectiveness of long-term continuous cardiac monitoring via ICMs, for detection of AF (and, in event of AF diagnosis, subsequent anticoagulation), in patients with ischemic stroke attributed to large-or-small vessel disease compared to the SoC of conventional follow up in the United Kingdom. Methods We constructed a Markov model with a cycle length of three months and a lifetime horizon to conduct the cost-effectiveness analysis, from the National Health Service (NHS) perspective. Costs and health-related benefits were discounted at an annual rate of 3.5%. We expressed outcomes in terms of quality-adjusted life-years (QALYs). Patient characteristics in the analysis and detection probabilities were based on the STROKE-AF trial. Detection of AF resulted in a switch in treatment from antiplatelet to direct oral anticoagulant (DOAC). Risk of cerebrovascular events were dependent on a patient’s AF detection status and subsequent treatment. Scenario, deterministic, and probabilistic sensitivity analyses were conducted to test the robustness of the base-case incremental cost-effectiveness ratio (ICER) and account for uncertainties in the model. We stratified patients into risk groups based on CHA2DS2-VASc scores and risk of AF detection. Results The base case incremental cost-effectiveness ratio of the implantation of an ICM was £15,485 per QALY, substantially under the NICE willingness-to-pay threshold of £20,000-£30,000 per QALY. ICM implantations resulted in 0.139 QALYs gained per patient at an incremental cost of £2,147. There were 0.054 fewer stroke events per patient in the ICM arm versus SoC. Results were robust under sensitivity analysis. Conclusion ICMs were cost-effective compared to SoC for detection of AF in patients with LAD/SVD stroke in the United Kingdom driven largely by more stroke events avoided. Subgroup analysis showed that ICMs were more cost-effective in patients with higher CHA2DS2-VASc scores and those with a higher individual risk of AF.Markov Model SchematicSummary ICER Results and Events avoided

Prevalence and Treatment Outcomes of Childhood Acute Lymphoblastic Leukemia in Kosovo

Advances in research, including novel biomarker identification and patient stratification, have significantly improved the therapy for childhood acute lymphoblastic leukemia (ALL), though access to improved healthcare services varies across geographical regions. In an effort to evaluate the advances in therapeutic approaches, we performed a retrospective analysis of childhood ALL in Kosovo. Our retrospective analysis included 225 cases diagnosed between 2008 and 2023, representing 52% of 429 diagnosed childhood cancers. The average annual incidence was 14, with a median age diagnosis of seven years, and a male predominance (59.54%). Patients were categorized into risk groups, with the majority (43%) in the standard-risk category. We identified five different treatment protocols for this study period. Over 61% of patients achieved remission after the first chemotherapy cycle and we observed a 20% mortality rate. Survival analysis showed that 55% and 40% of patients achieved 2-year and 5-year event-free survival (EFS), respectively, with significant differences across risk groups. Treatment advancements significantly correlated with improved survival rates, achieving a 5-year overall survival (OS) of 88% in the currently used standardized AIEOP-BFM-2009 protocol. Our study emphasizes the need for continued research and customized care strategies to enhance clinical outcomes.

#1584 Development and validation of risk prediction models according to different clinical settings of IgA nephropathy: nationwide multicenter cohort study

Abstract Background and Aims IgA nephropathy (IgAN) is the most common glomerulonephritis with a high risk of progression to end-stage renal disease (ESRD). Because machine learning models developed for research have limited use in clinical settings, this study developed and validated prediction models for IgAN according to different clinical settings. Method In this study, we analyzed data from 1,174 patients in the Japanese Nationwide Retrospective Cohort Study in IgAN, focusing on a 10-year observation period. We defined the derivation data from January 2002 to April 2004, and temporal validation data from May 2004 to December 2004. The composite renal outcome was defined as a 1.5-fold increase in creatinine or progression to ESRD. We developed and evaluated the three prediction models according to the different clinical settings: the primary care model for general physicians in primary care settings, the tertiary care model for specialists in tertiary care hospitals, and the research institute model, a machine learning-based approach for academic research institute settings. Results After excluding 82 patients for missing data, 114 and 14 patients experienced the composite renal outcome in the derivation (n = 874) and validation (n = 218) cohorts, respectively. The primary care model identified three variables—eGFR &amp;lt;45 mL/min/1.73 m², proteinuria ≥0.5 g/day, and non-use of corticosteroids—as significant predictors (C-statistic: 0.796; 95% CI: 0.686-0.895). The tertiary care model composed of three variables including glomerular number, histological severity and tubular/interstitial severity showed a slightly higher C-statistic (0.807; 95% CI: 0.713-0.886). When stratifying patients into risk groups, the primary care model showed a higher incidence of composite renal events in high-risk patients, and the tertiary care model effectively discriminated outcomes in all groups. The research institute model, which included 38 variables including proteinuria level, hypertension, eGFR, and non-use of corticosteroids as key predictors, showed comparable performance (C-statistic: 0.808; 95% CI: 0.689-0.886). Conclusion The primary care and tertiary care models provide simple yet effective predictive tools, competitive with the machine learning-based research institution model. These models are critical for predicting renal outcomes in patients with IgA nephropathy and for patient management according to different clinical settings.

#2302 Bleeding risk stratification following kidney biopsy using “MAJOR BLEEDING RISK SCORE”

Abstract Background and Aims Kidney biopsy (KB) is the gold standard in diagnosing the majority of kidney diseases. While generally KB is a safe procedure, a complication rate of 6-8% has been reported, mainly bleeding. Halimi et al. proposed “The Major Bleeding Risk Score” (MBRS) identifying 11 risk factors (out of a maximum of 41 points) associated with the likelihood of major complications (such bleeding requiring transfusion, arteriography, nephrectomy or death). Method In this retrospective study, we analyzed 358 native KB conducted between 2017 and 2022 by the interventional nephrology team in a tertiary hospital. Following the application of the MBRS, 273 KB were finally included to validate the score within our cohort. Results We analyzed 273 KB, 46.5% were male, with a mean age of 53.6 ± 18.5 years. The majority of KB were performed on the left kidney (82.4%), with an average of 2.1 ± 0.7 cylinders and 12.33 ± 6.27 glomeruli. The MBRS stratified patients into three risk groups: G1 for scores from 0 to 9 points (36.6% KB), G2 for scores between 10 to 19 points (38.8% KB) and G3 for scores from 20 to 29 points (24.5% KB). Eleven patients (4%) had major complications (0.3% in G1, 1.5% in G2 and 2.2% in G3). The risk of bleeding increased proportionally with risk stage (G1 1% vs G2 3.8% vs G3 9%, p=0.037). Patients who experienced a complication after KB had a significantly higher MBRS than patients who did not develop complications (19 ± 5.23 points vs 13 ± 7.19 points, p=0,01). Patients who developed complications associated anaemia, thrombopenia and lower BMI more frequently than patients who did not develop complications (23.6 ± 5.9 vs. 27.3 ± 5.4, p=0.03). The pathology with the highest bleeding was thrombotic microangiopathy [OR 10,54 (2,39-46,51)]. Conclusion The MBRS adequately stratifies patients according to bleeding risk and could be a valuable tool in the clinical practice guiding the decision to proceed with the kidney biopsy.

Carbapenem-resistant gram-negative bacterial infections and risk factors for acquisition in a Kenyan intensive care unit

BackgroundCarbapenem-resistant Gram-negative bacteria (CR-GNB) are a critical public health threat globally; however, there are inadequate surveillance data, especially in intensive care units (ICU), to inform infection prevention and control in many resource-constrained settings. Here, we assessed the prevalence of CR-GNB infections and risk factors for acquisition in a Kenyan ICU.MethodsA hospital-based cross-sectional study design was adopted, recruiting 162 patients clinically presenting with bacterial infection after 48 h of ICU admission, from January to October 2022 at the Nairobi West Hospital, Kenya. Demographics and clinical data were collected by case report form. The type of sample collected, including blood, tracheal aspirate, ascitic tap, urine, stool, and sputum depended on the patient’s clinical presentation and were transported to the hospital Microbiology laboratory in a cool box for processing within 2 h. The samples were analyzed by cultured and BD Phoenix system used for isolates’ identity and antimicrobial susceptibility.ResultsCR-GNB infections prevalence was 25.9% (42/162), with Klebsiella pneumoniae (35.7%, 15/42) and Pseudomonas aeruginosa (26.2%, 11/42) predominating. All isolates were multidrug-resistant (MDR). P. aeruginosa and A. baumannii were 100% colistin-resistant, while K. pneumoniae (33.3%) was tigecycline-resistant. History of antibiotics (aOR = 3.40, p = 0.005) and nasogastric tube (NGT) use (aOR = 5.84, p = < 0.001) were the risk factors for infection.ConclusionOur study highlights high MDR- and CR-GNB infections in ICU, with prior antibiotic exposure and NGT use as risk factors, and diminishing clinical value of colistin and tigecycline. In this study setting and beyond, strict implementation of antimicrobial stewardship programs and adherence to infection prevention and control through monitoring, evaluation and feedback are warranted to curb CR-GNB infections, especially among the risk groups.

#1716 IgA nephropathy: our center's experience

Abstract Background and Aims IgA Nephropathy (IgAN) is the most common primary glomerulopathy worldwide. In the last years, significant advances have been made in understanding its pathophysiology and developing newer promising treatments. The accuracy of the International Risk-Prediction Tool in IgAN (IRP-IgAN) was already validated. Herein, we retrospectively analysed the relation of this risk score and the kidney outcomes. Method We performed a single center retrospective observational cross-sectional study of patients with histological diagnosis of IgAN between 2015 and 2023 in Centro Hospitalar de Setúbal, aiming to describe the demography, clinical presentation, histological characteristics, treatment and follow up of our cohort. The International Risk-Prediction Tool in IgAN was applied for patient stratification. Results Twenty-eight patients were diagnosed with IgAN in this eight-year period. Mean age was 46 years-old (SD ±12.2) and 71.4% were male. The majority were Caucasian (n = 26) with only two patients of Asian e African descent, respectively. The mean calculated Charlson Comorbidity Index was 1.43 (SD ±1.5). Eighteen patients (64.3%) had known arterial hypertension, diabetes was seen only in 2 patients, obesity in 4 patients, and hepatitis B in 2 patients. No cardiovascular disease or cancer was documented. On presentation, 71.4% (n = 20) had hypertension, 14.3% (n = 4) presented with rapidly progressive renal insufficiency, and 14.3% (n = 4) presented with nephrotic syndrome. Two patients (7.1%) required dialysis on presentation. Also, the mean glomerular filtration rate (GFR) was 55.3 ml/min (SD ±31.9) and mean proteinuria level (protein-to-creatinine ratio) was 2.42g/g (SD ±2.41). Most patients had hematuria (82.1%), C3 consumption was seen in only one patient while 10 patients had isolated higher levels of IgA. Mean time between the first symptoms or documented clinical features and dedicated Nephrology consultation was 2.9 years (SD ±3.78). Regarding the histological data and considering de MEST-C score, 71.4% had mesangial hypercellularity in more than 50% of the glomerulus (M1), 25% had endocapillary hypercellularity (E1), 17% had segmental glomerulosclerosis of at least one glomerulus (S1), 7% had interstitial fibrosis or cortical atrophy in 25-50% of the cortical area (T1) and 11% in more than 50% (T2), 17.9% had crescents in less than 25% of the glomerulus (C1) and 2.6% in more than 25% (C2). Fibrinoid necrosis was noticed in 7.1% of the patients. The presence of IgA in the mesangium on IF was universal and 18 patients (64.3%) had C3 co-stain. Approximately half of the patients (46.4%) were already on angiotensin converting enzyme inhibitor (ACEI) or angiotensin receptor blockers (ARB) by the time of clinical presentation and nearly all (92.9%) by the time the diagnosis was established. SGTL-2 inhibitors were started in 42.9% of the patients. Eight patients (28.6%) started immunosuppression therapy, within a mean time from histological diagnosis of 0.7 years (SD ±1.03). Of those, all of them were on corticosteroids, one patient was additionally under oral cyclophosphamide and another one under mofetil mycophenolate. According to the IRP-IgAN, patients were stratified in low (35.7%), intermediate (10%) and high risk (8%) of kidney disease progression (GFR decline &amp;gt;50%) or ESKD. In a mean time of 0.53 (SD ±0.34) years of follow-up after diagnosis, 8 patients (28.6%) required renal replacement therapy, with 7 choosing hemodialysis and 1 peritoneal dialysis. Six patients lost follow-up. Three patients died a mean time of 1.2 years after diagnosis, one from immunosuppression-related adverse events. We also found an association between higher risk group and progression to ESKD (p &amp;lt; 0.001). Conclusion The IRP-IgAN tool is a useful tool for prediction of kidney disease progression and the need for renal replacement therapy. The supportive care in IgAN even with antiproteinuric approach could be insufficient for patients with high and intermediate risk. The risk progression to ESKD is indeed heterogeneous, and close follow-up of these patients should be guaranteed.

#699 Diagnostic accuracy of the Modified Renal Angina Index (mRAI) for predicting acute kidney injury among critically ill Filipino adults

Abstract Background and Aims The proposed mRAI (modified renal angina index) (Fig. 1) predicts moderate to severe AKI within the first 7 days of ICU stay which outperforms serum creatinine and urine output. The use of the mRAI in AKI may be warranted to improve predicted performance of AKI biomarkers. The study aims to evaluate the diagnostic accuracy of modified renal angina index in predicting Acute Kidney Injury (AKI) among Critically ill Adult Filipino patient in a Tertiary Institution and its association with in hospital MAKE (Major Adverse Kidney Events). Method A retrospective cohort study including all adult critically ill patients, they were dichotomized into “low” (&amp;lt;10) or “high risk” (&amp;gt;10) based on the mRAI score upon the 1st ICU admission (Day 0-24 hr) during the hospital stay. Inclusion criteria: age &amp;gt;18 years old, ICU patients between 2019-2022. Exclusion criteria: Chronic Kidney Disease (Egfr &amp;lt;30 ml/min), Transplant recipients, HIV/Cancer, &amp;lt;48 hrs ICU stay, little changes in creatinine (&amp;lt;2x from baseline between Day 0-24 hr ICU admission). The composite outcome is achieved if at least one is met during the index of hospitalization: All-cause mortality prior to discharge or after ICU admission, New onset of renal replacement therapy (RRT), persistent renal dysfunction. The sensitivity, specificity, predictive values and area under the curve is used to determine diagnostic accuracy of the mRAI Scoring and its association with in Hospital MAKE. Simple and multiple logistic regression analysis is used to control the effect of confounders in determining the association of mRAI to AKI. SPSS version 20 will be used in the analysis. Results Using a cut off score of 10, the mRAI show 84.29% sensitivity, 76.06% specificity, 77.63%, PPV 83.08% NPV 80.14% and AUC 80.14% in predicting moderate to severe AKI (Fig. 2). A mRAI of &amp;gt;10 is associated with in hospital MAKE showing a 97.14% sensitivity, 67.61% specificity, 74.73% PPV, 96.0% NPV, and AUC 82.27% (Fig. 3). Among the high risk group there were 68 (97.1%) who had MAKE, 62 (88.6%) new onset RRT, 12% (17.1%) died within 7 days of ICU admission, 64 (91.4%) persistent renal dysfunction (Fig. 4). Conclusion The proposed score can be applied among critically ill adult Filipino patients which is an easy bedside tool for identification of moderate to severe AKI. mRAI constitutes a sensitive test with a high negative predictive, affirming its capability being a screening test, complementary to laboratory parameters and clinical judgement. We also found out that a mRAI score of &amp;gt;10 is associated with In-Hospital Major Adverse Kidney Events.

#2257 Kidney outcomes in ANCA-associated vasculitis—application of Berden's Classification and ANCA Renal Risk Score in a single centre cohort

Abstract Background and Aims Anti-neutrophil cytoplasmic antibody (ANCA) -associated vasculitis is the most common cause of rapidly progressive glomerulonephritis and is a life-threatening condition. The course of the disease is variable and disease prognostication remains challenging. Histological and clinical scores have been developed to predict kidney outcomes, to tailor treatment. The aim of this study is to apply Berden´s histopathological classification (BHC) and ANCA renal risk score (ARRS), proposed by Brix and co-workers, in a cohort of patients with ANCA-associated vasculitis and to analyse their performance in renal outcomes prediction. Method In this retrospective observational study, we included patients with biopsy proven ANCA-associated vasculitis, diagnosed at our centre between March 2011 and March 2023. We consulted the clinical records and the kidney biopsy reports. Biopsies were categorized according to both scores. Follow up time was up to 48 months since the date of diagnosis. In BHC patients were divided into 4 groups (focal, crescentic, sclerotic and mixed) according to normal glomeruli, cellular crescents and globally sclerosed glomeruli proportion. When applying the ARRS, patients were divided into 3 groups: low, medium or high risk. This is a histopathological and biochemical score that combines normal glomeruli and tubular atrophy and interstitial fibrosis (IFTA) percentages with estimated glomerular filtration rate (eGFR) at time of diagnosis. Factors related to renal survival were evaluated by Spearman Rank Correlation, Binary Logistic Regression analysis and Kaplan-Meier curves were used for assessing time between diagnosis and end stage kidney disease (ESKD). Results Our study included 31 patients, 54.8% were male, median age at diagnosis was 62 (IQR, 53-69) years, with a median eGFR of 8.3 (IQR, 6.2-13.3) mL/min/1.73 m2 and a median urine albumin to creatinine ratio (uACR) of 1.5 (IQR, 0.88-2.2) g/g. 19 patients (61.3%) were positive for myeloperoxidase and 5 (16.1%) were proteinase 3 positive. Median follow up time was 36 (IQR, 9-48) months. 10 patients (32%) developed ESKD and 9 patients (29%) died. Regarding BHC, 4 patients (13%) presented a focal class, 18 (58%) crescentic, 7 (23%) mixed and 2 (6%) sclerotic. Progression to ESKD occurred in 7 patients with crescentic class (38.9%), 2 patients with mixed (28.6%) and 1 patient with sclerotic (50%). None of the patients with focal class developed ESKD. There were no significant differences in kidney survival curves by BHC class (Log Rank p = 0.47) (Fig. 1a). In ARRS, 1 patient (3%) was in the low-risk group, 19 patients (61%) in the medium risk and 11 patients (35%) in the high risk. Characteristics of the population by ARRS score group and detailed score discrimination are specified in Table 1. Progression to ESKD, occurred in 5 patients of medium risk group (26.3%) and also in 5 patients in the high-risk group which represented 45.5% of this group. Kidney survival curves by ARRS score group had no statistic difference (Log Rank p = 0.46) (Fig. 1b). ESKD was positively associated with serum creatinine (sCr) at admission (p = 0.02), highest sCr (p = 0.001) and leukocyturia (p = 0.05). By multivariate analysis adjusted to gender, age, sCr at admission, leukocyturia and BHC or ARRS, the only factor associated with ESKD was sCr at admission (OR 1.45, CI 1.03-2.06, p = 0.05). Conclusion In our cohort of patients, sCr at patient hospital admission was the best predictor for progression to ESKD. By ARRS, just one patient had low risk, and as expected, kidney survival was higher in the medium risk group (68.5%) than in the high-risk group (53%), although not reaching statistical significance. BHC also had no association with kidney outcomes, although kidney survival was 100% in focal class and sclerotic class had the lowest survival (50%), yet crescentic class revealed a worse kidney survival (57.1%) than mixed class (71.4%). The small number of patients, overall and in each group, and the short follow up period can be pointed as limitations of this study.

#1751 Validation of the ReDO Death Score in a Portuguese cohort

Abstract Background and Aims Mortality within the first year after dialysis start is estimated to be 20-30%, and it is mostly due to cardiovascular disease. Prognostic assessment after starting hemodialysis is challenging. Clark et al. developed the Recovery and Death Outcome risk score, which accurately predicted the likelihood of renal recovery to dialysis independence and of death within 1 year after discharge from in-hospital dialysis initiation. These models can be used at discharge or soon after patients start outpatient dialysis. We aimed to validate the Death Outcome risk score to predict one-year mortality after dialysis start in our population. Method .Retrospective analysis of hospitalized patients who initiated hemodialysis in a tertiary care hospital (Unidade Local de Saúde Santa Maria), from January 1st of 2016 to December 31st of 2019, and were discharged to outpatient dialysis. The risk of death within one year of discharge was calculated according to the ReDO score. We evaluated all-cause mortality within one year of hospital discharge. We classified patients into death outcome risk groups (labeled D1 to D4) according to the ReDO predictive score. Cox regression method was used to determine if the risk score was predictive of mortality within the first year after discharge. The discriminatory ability for the ReDO score to predict mortality was determined using the receiver operating characteristic (ROC) curve. Results 369 patients were included, with a mean age of 71.1 ± 14.3 years. The majority were male (59.9%, n = 221) and 87% were Caucasian (n = 321). The median Charlson score was 7 ± 3. The mortality rate within one year after discharge was 22.2% (n = 82). The one-year survival was significantly lower in patients with the highest probability of death (D4 = 61.3% vs. D3 = 67.6% vs. D2 = 81.3% vs. D4 = 97.3%, p &amp;lt; 0.001). The ReDO Death score accurately predicted the one-year risk of mortality, with an area under the ROC curve of 0.741, [95% CI (0.687–0.794), p &amp;lt; 0.001] (Fig. 1). The optimal REDO Death risk cut-off was &amp;gt;30%, with a hazard ratio of 6.57 [95% CI (3.48–12.2), p &amp;lt; 0.001] for one year risk of death, with a sensitivity of 78.0% and specificity of 60.6%. Conclusion We validated the ReDO score for 1-year mortality prediction after starting hemodialysis during hospitalization in a Portuguese population. This score can be used as a tool to inform goals of care discussion at the time of transition to out-of-hospital care, involving the in-hospital nephrology care team, the patient, and, if applicable, the future care team, as it can enlighten clinical decisions and, in some cases, lead to better end-of-life planning.

#1543 Risk factors of obstructive sleep apnea-hypopnea syndrome in patients with chronic kidney disease

Abstract Background and Aims Both obstructive sleep apnea-hypopnea syndrome (OSAHS) and chronic kidney disease (CKD) are common disease. Patients with OSAHS were evidenced to have oxidative stress, increased albuminuria and renal injury. Previous reports show high prevalence of OSAHS among CKD patients, while its risk factors are hardly investigated. The objective of this study is to assess the risk factors of OSAHS in patients with CKD. Method We selected 181 patients with CKD who were hospitalized in department of Nephrology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital from September 2020 to February 2023. All participants underwent full-night standard nocturnal polysomnography (PSG) monitoring in the sleep center using Alice 4, 5 or 6 devices. An apnea hypopnea index (AHI)&amp;gt;5 events/h was consistent with the diagnosis of OSA. The 181 Patients are divided into three groups based on the level of AHI to studied the differences of clinical and biochemical characteristics. According to Kidney Disease Improving Global Outcomes (KDIGO) risk categories, all patients are divided into non very high risk and very high risk group, logistic regression is used for analyzing risk factors of OSAHS in patients with CKD. Results The prevalence of OSAHS was 86.7% (157 of 181), with 29.8% mild, 30.9% moderate and 25.9% severe respectively. The urea nitrogen (P=0.039) and cystatin C (P = 0.030) levels in patients of severe OSAHS group were significantly higher than those within non or mild OSAHS group. The eGFR in non or mild OSAHS group was significantly higher than moderate OSAHS group (P = 0.036). Pearson correlation analysis showed a significant negative correlation between AHI (p = 0.022), ODI (p = 0.033), and hypopnea index (p = 0.004) of sleep parameters and eGFR, while a significant positive correlation was found between LaSO2 (p = 0.005), MaSO2 (p = 0.030), and eGFR. Stepwise linear regression analysis showed that the hypopnea index was an independent risk factor for eGFR (p = 0.033, R2: 0.215), and CT90 was an independent risk factor for UACR (p &amp;lt; 0.001, R2: 0.105). Logistic regression analysis revealed that hypopnea index (OR = 1.058) was significantly correlated with very high risk in KDIGO risk categories (p &amp;lt; 0.05). Conclusion OSAHS is high prevalence in patients with CKD. Regression analysis shows that hypopnea index is not only an independent risk factor for eGFR but also a significant predictor associated with very high risk according to KDIGO risk category.

#1604 LACE index as predictors of 30 day rehospitalisation among patients on maintenance hemodialysis, cohort study

Abstract Background and Aims Over 35% of patients on maintenance dialysis are readmitted to the hospital within 30 days of hospital discharge. Validated risk assessment tools such as the LACE index (Length of stay, Acuity of admission, Co-morbidities, and Emergency department visits) have been developed to identify patients at high risk of hospital readmission in non-dialysis patients but have not been tested in dialysis patients. Method Data was collected from electronic medical records of patients on maintenance hemodialysis in Diaverum outpatient clinics hospitalized during 2023. Data included Age, gender, duration of hospital stay, Charlson comorbidity index (CCS), urgent or planned, and cause of Hospitalization. Multivariable logistic regression models with 30-day readmission for the same reason as the dependent outcome were used to identify readmission risk factors and whether the LACE score validly predicts 30-day rehospitalization among our cohort. Results Among (4829) patients received dialysis in Diaverum Saudi Arabia during 2023. (1487) episodes of hospitalization were reported due to various reasons rate of hospitalization was 0.54 Episodes per patient-years at risk, and 372(25%) of hospitalized patients were re-hospitalized for the same reason within 30 days. The proportion of patients with 30 days of rehospitalization for the same reason was higher in patients with post-initial discharge LACE index ≥10 in comparison to patients with LACE index&amp;lt;10, 348(32.6%) &amp; 24(5.7) respectively P-VALUE&amp;lt;0.001. also significantly higher in patients ≥65years old than those younger 163(27.7%) &amp;209(23.3%) respectively P-VALUE&amp;lt;0.05, those in high risk group (defined as those with higher comorbidity index ≥6 and/or lower Individual Patient Performance Score&amp;lt;75) than those who are not in high risk group 215(35%) &amp; 157(17.9%) respectively P-VALUE&amp;lt;0.001. Multivariate logistic regression including covariates significantly associated with higher 30-day rehospitalization to avoid confounder effect with model including ( age, gender, dialysis duration, body mass index, comorbidity index, diabetes, vascular access, cause of hospitalization and inclusion in high-risk group ) showed significantly higher rehospitalization in patients with post-initial discharge LACE index ≥10 in comparison to patients with LACE index&amp;lt;10 ODDS RATIO (95%CI) 7.95(5.1-12.5) P-VALUE&amp;lt;0.001. independent of other covariates in the model Conclusion LACE index at discharge is an independent predictor of (30) days re-hospitalization in patients on maintenance Hemodialysis. Further analysis needed for a specific model for HD patients taking into consideration the unique characteristics of this cohort of patients.

#2546 CKD-PC risk model for CKD progression: validation and association with outcomes in the FIDELITY population

Abstract Background and Aims The Chronic Kidney Disease Prognosis Consortium (CKD-PC) recently developed risk models to predict the 3-year risk of a ≥40% decrease in estimated glomerular filtration rate (eGFR) or to predict kidney failure in the general population. Unlike the kidney failure risk equation, the CKD-PC model is valid for all levels of eGFR (above and below 60 mL/min/1.73 m2) and includes chronic kidney disease (CKD) progression risk factors besides age, sex, eGFR and albuminuria; namely: systolic blood pressure, antihypertensive medication use, history of heart failure, coronary heart disease, atrial fibrillation, smoking status, body mass index, glycated hemoglobin, insulin use, and oral diabetes medication use [1]. We evaluated whether the CKD-PC model, developed using electronic health record data, is valid for use in a contemporary clinical population using the FIDELITY pooled dataset from international randomized clinical trials of finerenone [2]. Additionally, to inform clinical practice, we evaluated the efficacy of finerenone using categories of 3-year CKD progression risk as predicted by the model. Method FIDELITY was an individual, patient-level, prespecified, pooled efficacy and safety analysis of the phase III FIDELIO-DKD and FIGARO-DKD trials of patients with CKD and type 2 diabetes (T2D), randomized 1:1 to finerenone or placebo. The 3-year CKD progression risk of these patients was predicted and the validity of the CKD-PC model was evaluated using area under the curve (AUC) score (with higher scores indicating better risk prediction), Brier score (lower scores indicating better prediction), and by calibration plots of observed versus predicted risk by deciles of 3-year CKD progression risk. To evaluate the efficacy of finerenone, 3-year risk was categorized in quartiles and the effect of finerenone versus placebo on a kidney composite outcome, defined as kidney failure, a sustained ≥40% decrease in eGFR from baseline over ≥4 weeks, or renal death, was assessed. Results The FIDELITY population comprised 13,026 individuals with a mean eGFR of 58 mL/min/1.73 m2 and urine albumin-to-creatinine ratio of 515 mg/g. The median follow-up was 3 years and there were 1849 total kidney outcome events. Of 12,968 patients analyzed, the median 3-year risk of kidney failure was 15% (Q1–Q3: 9–24%). Overall, the model demonstrated good discrimination to predict a ≥40% kidney composite outcome for patients with CKD and T2D in FIDELITY: AUC score 0.726 (95% confidence interval [CI] 0.712–0.739) and Brier score 0.100 (95% CI 0.097–0.103). The predicted 3-year risk was generally slightly higher than the observed risk (Fig. 1). Finerenone was effective in preventing CKD progression across the risk quartiles (p-interaction = 0.094) with a trend towards greater efficacy in the higher risk quartiles (3-year risk of CKD progression ≥10%) (Fig. 2). All risk groups showed benefit with finerenone compared to placebo regarding eGFR decline in the chronic phase. Conclusion The CKD-PC risk model for CKD progression performed well in a large global clinical trial population of patients with CKD and T2D. Finerenone was effective across the range of baseline risk of CKD progression.

Analysis of prognostic value of lactate metabolism-related genes in ovarian cancer based on bioinformatics

BackgroundRecent studies have provided evidence supporting the functional role and mechanism of lactate in suppressing anticancer immunity. However, there is no systematic analysis of lactate metabolism-related genes (LMRGs) and ovarian cancer (OV) prognosis.ResultsSix genes (CCL18, CCND1, MXRA5, NRBP2, OLFML2B and THY1) were selected as prognostic genes and a prognostic model was utilized. Kaplan-Meier (K-M) and Receiver Operating Characteristic (ROC) analyses were further performed and indicated that the prognostic model was effective. Subsequently, the neoplasm_cancer_status and RiskScore were determined as independent prognostic factors, and a nomogram was established with relatively accurate forecasting ability. Additionally, 2 types of immune cells (Central memory CD8 T cell and Immature B cell), 4 types of immune functions (APC co inhibition, DCs, Tfh and Th1 cells), 9 immune checkpoints (BTLA, CTLA4, IDO1, LAG3, VTCN1, CXCL10, CXCL9, IFNG, CD27) and tumor immune dysfunction and exclusion (TIDE) scores were significantly different between risk groups. The expression of 6 genes were verified by quantitative Real-Time Polymerase Chain Reaction (qRT-PCR) and the expression of 6 genes were higher in the high-grade serous carcinoma (HGSC) samples.ConclusionA prognostic model related to lactate metabolism was established for OV based on six genes (CCL18, CCND1, MXRA5, NRBP2, OLFML2B and THY1) that could provide new insights into therapy.

Supported nano-sized precious metal catalysts for oxidation of catalytic volatile organic compounds.

Volatile organic compounds (VOCs) are common contaminants found as indoor as well as outdoor pollutants, which can induce acute or chronic health hazards to the human physiological system. The catalytic oxidation method is widely considered as one of the effective methods for removing VOCs, and the development of highly effective catalysts is highly urgent for booming this interesting field. This review focuses on the recent progress of VOC oxidation catalyzed by supported nano-sized precious metal catalysts, and discusses the effects of metal composition, supports, size, and morphology on the catalytic activity. In addition, the roles played by both nano-sized precious metals and supports in enhancing the performance of catalytic VOCs are also systematically discussed, which will guide the further development of more advanced VOC catalysts.

Anoikis-related gene signatures in colorectal cancer: implications for cell differentiation, immune infiltration, and prognostic prediction

Colorectal cancer (CRC) is a malignant tumor originating from epithelial cells of the colon or rectum, and its invasion and metastasis could be regulated by anoikis. However, the key genes and pathways regulating anoikis in CRC are still unclear and require further research. The single cell transcriptome dataset GSE221575 of GEO database was downloaded and applied to cell subpopulation type identification, intercellular communication, pseudo time cell trajectory analysis, and receptor ligand expression analysis of CRC. Meanwhile, the RNA transcriptome dataset of TCGA, the GSE39582, GSE17536, and GSE17537 datasets of GEO were downloaded and merged into one bulk transcriptome dataset. The differentially expressed genes (DEGs) related to anoikis were extracted from these data sets, and key marker genes were obtained after feature selection. A clinical prognosis prediction model was constructed based on the marker genes and the predictive effect was analyzed. Subsequently, gene pathway analysis, immune infiltration analysis, immunosuppressive point analysis, drug sensitivity analysis, and immunotherapy efficacy based on the key marker genes were conducted for the model. In this study, we used single cell datasets to determine the anoikis activity of cells and analyzed the DEGs of cells based on the score to identify the genes involved in anoikis and extracted DEGs related to the disease from the transcriptome dataset. After dimensionality reduction selection, 7 marker genes were obtained, including TIMP1, VEGFA, MYC, MSLN, EPHA2, ABHD2, and CD24. The prognostic risk model scoring system built by these 7 genes, along with patient clinical data (age, tumor stage, grade), were incorporated to create a nomogram, which predicted the 1-, 3-, and 5-years survival of CRC with accuracy of 0.818, 0.821, and 0.824. By using the scoring system, the CRC samples were divided into high/low anoikis-related prognosis risk groups, there are significant differences in immune infiltration, distribution of immune checkpoints, sensitivity to chemotherapy drugs, and efficacy of immunotherapy between these two risk groups. Anoikis genes participate in the differentiation of colorectal cancer tumor cells, promote tumor development, and could predict the prognosis of colorectal cancer.

Modelling respiratory syncytial virus age-specific risk of hospitalisation in term and preterm infants

BackgroundRespiratory syncytial virus (RSV) is the most common cause of acute lower respiratory infections in children worldwide. The highest incidence of severe disease is in the first 6 months of life, with infants born preterm at greatest risk for severe RSV infections. The licensure of new RSV therapeutics (a long-acting monoclonal antibody and a maternal vaccine) in Europe, USA, UK and most recently in Australia, has driven the need for strategic decision making on the implementation of RSV immunisation programs. Data driven approaches, considering the local RSV epidemiology, are critical to advise on the optimal use of these therapeutics for effective RSV control.MethodsWe developed a dynamic compartmental model of RSV transmission fitted to individually-linked population-based laboratory, perinatal and hospitalisation data for 2000–2012 from metropolitan Western Australia (WA), stratified by age and prior exposure. We account for the differential risk of RSV-hospitalisation in full-term and preterm infants (defined as < 37 weeks gestation). We formulated a function relating age, RSV exposure history, and preterm status to the risk of RSV-hospitalisation given infection.ResultsThe age-to-risk function shows that risk of hospitalisation, given RSV infection, declines quickly in the first 12 months of life for all infants and is 2.6 times higher in preterm compared with term infants. The hospitalisation risk, given infection, declines to < 10% of the risk at birth by age 7 months for term infants and by 9 months for preterm infants.ConclusionsThe dynamic model, using the age-to-risk function, characterises RSV epidemiology for metropolitan WA and can now be extended to predict the impact of prevention measures. The stratification of the model by preterm status will enable the comparative assessment of potential strategies in the extended model that target this RSV risk group relative to all-population approaches. Furthermore, the age-to-risk function developed in this work has wider relevance to the epidemiological characterisation of RSV.

The role of PSMA PET/CT in predicting downgrading in patients with Gleason score 4+4 prostate cancer in prostate biopsy

BackgroundTo investigate the predictable parameters associated with downgrading in patients with a Gleason score (GS) 8 (4+4) in prostate biopsy after radical prostatectomy.MethodsWe retrospectively analyzed 62 patients with a GS of 4+4 on prostate biopsy who underwent robotic radical prostatectomy between 2017 and 2022.Results38 of 62 (61.2%) were downgraded. In multivariable logistic regression model, Ga-68 prostate-specific membrane antigen (PSMA) positron-emission tomography (PET)/computed tomography (CT) SUV max was independent predictor of downgrading (OR 0.904; p = 0.011) and a Logistic Regression model was constructed using the following formula: Y = 1.465–0.95 (PSMA PET/CT SUV max). The model using this variable correctly predicted the downgrading in 72.6% of patients. The AUC for PSMA PET/CT SUV max was 0.709 the cut off being 8.8.A subgroup analysis was performed in 37 patients who had no other European Association of Urology (EAU) high risk features. 25 out of 37 (67.5%) were downgraded, and 21 of these 25 had organ confined disease. Low PSMA SUV max (<8.1) and percentage of GS 4+4 biopsy cores to cancer bearing cores (45.0%) were independently associated with downgrading to GS 7.ConclusionPSMA PET/CT can be used to predict downgrading in patients with GS 4+4 PCa. Patients with GS 4+4 disease, but no other EAU high risk features, low percentage of GS 4+4 biopsy cores to cancer bearing cores, and a low PSMA PET/CT SUV max are associated with a high likelihood of the cancer reclassification to intermediate risk group.

Monetary value of health-a practical decision-making framework combining equity considerations and WTP.

We estimate the first monetary value of a health gain in Croatia to inform the debate about the appropriate "demand-side" cost-effectiveness thresholds in Croatia but also Central and Eastern Europe, where such debates are still uncommon. We test the empirical support for two equity considerations: age and severity operationalized as proportional shortfall (PS), and propose a pragmatic framework for combining equity considerations with the monetary value of health into a single threshold. We used the contingent valuation method to elicit the willingness to pay per Quality-Adjusted Life Year (QALY) in Croatia, using a representative sample of the population (N = 1,500, online survey). 29 EQ-5D health states were valued using payment scales and open-ended question as payment vehicles. To test the hypotheses, we used both parametric tests and non-parametric tests. Multilinear regression was employed to test the theoretical validity of the results. The monetary value of a health gain in Croatia is equivalent to 1.15 of GDP per capita (equaling €17,000). Age of patients seems to be an important equity-related characteristic. The WTP per QALY in the age-neutral risk group (€11,900) was nearly equivalent to the WTP per QALY in the adult (neutral) risk group (€11,700) but lower by 16% compared to the WTP per QALY estimated in children (€14,200; p = 0.00). WTP estimates are theoretically valid and to, a small degree, scale sensitive. There is a positive association between the level of proportional shortfall and willingness to pay. To increase the usefulness of our results for the policy-makers, we combine the elicited preferences into a single decision-making framework and construct several cost-effectiveness thresholds based on willingness to pay and equity-related preferences. Based on empirical results, cost-effectiveness thresholds could range up to €20,308 for the most severe health conditions in children or could be lowered to €16,777 for less severe health conditions. In Central and Eastern Europe, in spite of a growing understanding of the importance of further developing value-based assessment frameworks there has been very little empirical research to guide, inform and promote this development. Countries in this region use mainly GDP-based thresholds without empirical evidence to support such important decisions. This may lead to thresholds that are too high, with detrimental consequence for the pricing and reimbursement systems.