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Medical screening is employed to detect early signs of diseases in asymptomatic populations, potentially improving patient outcomes through early intervention. However, the psychosocial impact of screenings remains a field of discussion. Inconsistent findings from studies, mainly originally from cancer research, are not easily transferable to the context of liver screening. This study aimed to identify predictors of psychosocial consequences in asymptomatic adults screened for early-stage liver cirrhosis, thereby contributing to the current knowledge on screening impact. We analyzed data from 487 participants who underwent a systematic liver disease screening in Germany from January 2018 to February 2021. The screening involved blood tests, advanced diagnostics, and potentially, liver biopsies. We used bootstrapped LASSO regression with 10-fold validation to evaluate the influence of various predictors on psychosocial outcomes measured by the Psychological Consequences of Screening Questionnaire (PCQ). The results show that severity of comorbidities (beta =  0.44-2.72), subjective social status (beta =  -0.30--0.86), and social support (beta =  -0.33--0.98) were consistent predictors across all psychosocial outcome measures by not covering zero in the confidence intervals. Older age (beta =  -0.03--0.08), the existence of a steady partnership (beta =  -1.08--0.48) and higher health literacy regarding the application of medical information (beta =  0.33-0.48) were associated with less psychosocial dysfunction, indicating their protective roles to prevent psychosocial burden of screening. The study underscores the importance of considering individual patient characteristics in predicting psychosocial consequences of medical screening. Medical practitioners should consider personalized communication strategies taking into account the individual context of patients. The protective role of social support and stable personal relationships suggests that integrating psychosocial support services within screening programs could mitigate negative outcomes. Furthermore, increasing patient health literacy might help to demystify the screening process and can reduce psychosocial burden even if patients come from a segment of lower subjective social status.

The G1 cell cycle inhibitors tissue inhibitor of metalloproteinase-2 (TIMP-2) and insulin-like growth factor-binding protein 7 (IGFBP7) have been identified as promising biomarkers for the prediction of adverse outcomes including renal replacement therapy (RRT) and mortality in critically ill adult patients who develop acute kidney injury (AKI). However, the prognostic value of urinary TIMP-2 and IGFBP7 in neonatal and pediatric AKI for adverse outcome has not been investigated yet. The product of the urinary concentration of TIMP-2 and IGFBP7 ([TIMP-2]•[IGFBP7]) was assessed by a commercially available immunoassay (NephroCheck™) in a prospective cohort study in 133 subjects aged 0-18 years including 46 patients with established AKI according to pRIFLE criteria, 27 patients without AKI (non-AKI group I) and 60 apparently healthy neonates and children (non-AKI group II). AKI etiologies were: dehydration/hypovolemia (n = 7), hemodynamic instability (n = 7), perinatal asphyxia (n = 9), septic shock (n = 7), typical hemolytic-uremic syndrome (HUS; n = 5), interstitial nephritis (n = 5), vasculitis (n = 4), nephrotoxic injury (n = 1) and renal vein thrombosis (n = 1). When AKI patients were classified into pRIFLE criteria, 6/46 (13%) patients fulfilled the criteria for the category \"Risk\", 13/46 (28%) for \"Injury\", 26/46 (57%) for \"Failure\" and 1/46 (2%) for \"Loss\". Patients in the \"Failure\" stage had a median 3.7-fold higher urinary [TIMP-2]•[IGFBP7] compared to non-AKI subjects (P<0.001). When analyzed for AKI etiology, highest [TIMP-2]•[IGFBP7] values were found in patients with septic shock (P<0.001 vs. non-AKI I+II). Receiver operating characteristic (ROC) curve analyses in the AKI group revealed good performance of [TIMP-2]•[IGFBP7] in predicting 30-day (area under the curve (AUC) 0.79; 95% CI, 0.61-0.97) and 3-month mortality (AUC 0.84; 95% CI, 0.67-0.99) and moderate performance in predicting RRT (AUC 0.67; 95% CI, 0.50-0.84). This study shows that urinary [TIMP-2]•[IGFBP7] has a good diagnostic performance in predicting adverse outcomes in neonatal and pediatric AKI of heterogeneous etiology.

Rejection remains the main cause of allograft failure in paediatric kidney transplantation and is driven by donor-recipient HLA mismatching. Modern computational algorithms enable assessment of HLA mismatch immunogenicity at the molecular level (molecular-mismatch, molMM). Whilst molMM has been shown to correlate with alloimmune outcomes, evidence demonstrating improved prediction performance against traditional antigen mismatching (antMM) is lacking. We analysed 177 patients from the CERTAIN registry (median follow-up 4.5 years). molMM scores included Amino-Acid-Mismatch-Score (AAMS), Electrostatic-Mismatch-Score (EMS3D) and netMHCIIpan (netMHC1k: peptide binding affinity ≤1000 nM; netMHC: binding affinity ≤500 nM plus rank <2%). We stratified patients into high/low-risk groups based on risk models of DSA development. Donor-specific HLA antibodies (DSA) predominantly targeted the highest scoring molMM donor antigen within each HLA locus. MolMM scores offered superior discrimination versus antMM in predicting DSA for all HLA loci; the EMS3D algorithm had particularly consistent performance (area under the receiver operating characteristic curve (AUC) >0.7 for all HLA loci vs. 0.52-0.70 for antMM). ABMR (but not TCMR) was associated with HLA-DQ molMM scores (AAMS, EMS3D and netMHC). Patients with high-risk HLA-DQ molMM had increased risk of graft function deterioration (50% reduction in baseline eGFR (eGFR50), adjusted HR: 3.5, 95% CI 1.6-8.2 high vs. low EMS3D). Multivariable modelling of the eGFR50 outcome using EMS3D HLA-DQ stratification showed better discrimination (AUC EMS3D vs. antMM at 2 years: 0.81 vs. 0.77, at 4.5 years: 0.72 vs. 0.64) and stratified more patients into the low-risk group, compared to traditional antMM. Molecular mismatching was superior to antigen mismatching in predicting humoral alloimmunity. Molecular HLA-DQ mismatching appears to be a significant prognostic factor for graft function deterioration in paediatric kidney transplantation.

The advancement of Artificial Intelligence, particularly Large Language Models (LLMs), is rapidly progressing. LLMs, such as OpenAI's GPT, are becoming vital in scientific and medical processes, including text production, knowledge synthesis, translation, patient communication and data analysis. However, the outcome quality needs to be evaluated to assess the full potential for usage in statistical applications. LLMs show potential for all research areas, including teaching. Integrating LLMs in research, education and medical care poses opportunities and challenges, depending on user competence, experience and attitudes. This project aims at exploring the use of LLMs in supporting statistical consulting by evaluating the utility, efficiency and satisfaction related to the use of LLMs in statistical consulting from both advisee and consultant perspective. Within this project, we will develop, execute and evaluate a training module for the use of LLMs in statistical consulting. In this context, we aim to identify the strengths, limitations and areas for potential improvement. Furthermore, we will explore experiences, attitudes, fears and current practices regarding the use of LLMs of the staff at the Medical Center and the University of Freiburg. This multimodal study includes four study parts using qualitative and quantitative methods to gather data. Study part (I) is designed as mixed mode study to explore the use of LLMs in supporting statistical consulting and to evaluate the utility, efficiency and satisfaction related to the use of LLMs. Study part (II) uses a standardized online questionnaire to evaluate the training module. Study part (III) evaluates the consulting sessions using LLMs from advisee perspective. Study part (IV) explores experiences, attitudes, fears and current practices regarding the use of LLMs of the staff at the Medical Center and the University of Freiburg. This study is registered at the Freiburg Registry of Clinical Studies under the ID: FRKS004971.

Delayed graft function (DGF) in pediatric kidney transplantation is a serious complication with negative impact on graft survival. Currently, there are no reliable methods available to assess the risk of DGF in children. We performed a retrospective analysis of data from the Cooperative European Paediatric Renal Transplant Initiative (CERTAIN) registry to develop a DGF risk assessment model for pediatric kidney transplantation, based on parameters available within the first 24 h post-transplant. The model was developed by forward selection and logistic regression. This study included n = 694 patients. The overall rate of DGF was 8.5%. The following key parameters were selected for the DGF risk assessment model: (i) occurrence of post-transplant surgical complications, (ii) immediate graft urine production, (iii) rate of change in recipient’s serum creatinine, (iv) initial calcineurin inhibitor therapy. The significance of these parameters was confirmed by calculating adjusted odds ratios. In the training cohort and the internal validation cohort the ROC-AUCs were 0.9043 and 0.878. This multivariable model based on early post-transplant parameters can predict the occurrence of DGF in pediatric kidney transplant recipients with high accuracy and may facilitate future interventional trials of targeted pharmacological strategies against ischemia-reperfusion injury in this population.

Early identification of patients with acute kidney injury (AKI) being at high risk for adverse outcome can influence medical treatment. This study compares urinary calprotectin, kidney injury molecule-1 (KIM-1), and neutrophil gelatinase-associated lipocalin (NGAL) for their performance in predicting mortality and need for renal replacement therapy (RRT) in pediatric AKI patients. Urinary biomarker concentrations were assessed prospectively in 141 subjects aged 0–18 years including 55 patients with established AKI according to pediatric Risk, Injury, Failure, Loss, and End-stage kidney disease (pRIFLE) criteria, 27 patients without AKI, and 59 healthy children. Within the AKI group, receiver operating characteristic (ROC) curve analysis revealed moderate to poor performance of calprotectin and KIM-1 in the prediction of 30-day mortality (calprotectin area under the curve (AUC) 0.55; KIM-1 AUC 0.55) and 3-month mortality (calprotectin AUC 0.61; KIM-1 AUC 0.60) and fair performance in the prediction of RRT requirement (calprotectin AUC 0.72; KIM-1 AUC 0.71). Urinary NGAL showed good performance in predicting 30-day (AUC 0.79) and 3-month (AUC 0.81) mortality and moderate performance in predicting RRT (AUC 0.61). Conclusions : Whereas urinary calprotectin and KIM-1 can be useful for the prediction of RRT, urinary NGAL has a good diagnostic performance in predicting mortality in pediatric patients with AKI of heterogeneous etiology. What is known: • There is increasing evidence that urinary biomarkers like neutrophil gelatinase-associated lipocalin (NGAL) and kidney injury molecule-1 (KIM-1) are valuable for the prediction of adverse outcome in adult acute kidney injury (AKI), whereas data on pediatric AKI is scarce. What is new: • Urinary calprotectin and KIM-1 do not predict mortality in our heterogeneous pediatric AKI cohort, but they show moderate performance in the prediction of dialysis. • Urinary NGAL is a good predictor of mortality performing better than pRIFLE stage, eGFR, or creatinine, but it shows moderate performance in the prediction of dialysis.

The high proportion of people with overweight and obesity has become a worldwide problem in recent decades, mainly due to health consequences, such as cardiovascular diseases, neoplasia, and type 2 diabetes mellitus. Regarding effective countermeasures, the digitization of health services offers numerous potentials, which, however, have not yet been sufficiently evaluated. Web-based health programs are becoming increasingly interactive and can provide individuals with effective long-term weight management support. The purpose of this randomized controlled clinical trial was to evaluate the effectiveness of an interactive web-based weight loss program on anthropometric, cardiometabolic, and behavioral variables and to compare it with a noninteractive web-based weight loss program. The randomized controlled trial included people who were aged between 18 and 65 years (mean 48.92, SD 11.17 years) and had a BMI of 27.5 to 34.9 kg/m (mean 30.71, SD 2.13 kg/m ). Participants (n=153) were assigned to either (1) an interactive and fully automated web-based health program (intervention) or (2) a noninteractive web-based health program (control). The intervention program focused on dietary energy density and allowed for dietary documentation with appropriate feedback on energy density and nutrients. The control group only received information on weight loss and energy density, but the website did not contain interactive content. Examinations were performed at baseline (t0), at the end of the 12-week intervention (t1), and at 6 months (t2) and 12 months (t3) thereafter. The primary outcome was body weight. The secondary outcomes were cardiometabolic variables as well as dietary and physical activity behaviors. Robust linear mixed models were used to evaluate the primary and secondary outcomes. The intervention group showed significant improvements in anthropometric variables, such as body weight (P=.004), waist circumference (P=.002), and fat mass (P=.02), compared with the control group over the course of the study. The mean weight loss after the 12-month follow-up was 4.18 kg (4.7%) in the intervention group versus 1.29 kg (1.5%) in the control group compared with the initial weight. The results of the nutritional analysis showed that the energy density concept was significantly better implemented in the intervention group. Significant differences in cardiometabolic variables were not detected between the 2 groups. The interactive web-based health program was effective in reducing body weight and improving body composition in adults with overweight and obesity. However, these improvements were not associated with relevant changes in cardiometabolic variables, although it should be noted that the study population was predominantly metabolically healthy. German Clinical Trials Register DRKS00020249; https://drks.de/search/en/trial/DRKS00020249. RR2-10.3390/ijerph19031393.

Testicular germ cell cancer (TGCC) is the most common type of cancer in young men. Seminomas account for around half of them and are characterized by a pronounced infiltration of immune cells. So far, the impact of the tumor microenvironment (TME) on disease progression, especially the interaction of individual immune cell subtypes with the tumor cells, remains unclear. To address this question, we used an in vitro TME model involving the seminoma-derived cell line Tcam-2 and immune cell subsets purified from human peripheral blood. T cells and monocytes were strongly activated when individually cocultured with Tcam-2 cells as revealed by increased expression of activation markers and pro-inflammatory cytokines both on the mRNA and protein level. Importantly, the interaction between tumor and immune cells was mutual. Gene expression of pluripotency markers as well as markers of proliferation and cell cycle activity were upregulated in Tcam-2 cells in cocultures with T cells, whereas gene expression of SOX17, a marker for seminomas, was unaltered. Interestingly, the impact of monocytes on gene expression of Tcam-2 cells was less pronounced, indicating that the effects of individual immune cell subsets on tumor cells in the TME are highly specific. Collectively, our data indicate that seminoma cells induce immune cell activation and thereby generate a strong pro-inflammatory milieu, whereas T cells conversely increase the proliferation, metastatic potential, and stemness of tumor cells. Although the employed model does not fully mimic the physiological situation found in TGCC in vivo, it provides new insights potentially explaining the connection between inflammatory infiltrates in seminomas and their tendency to burn out and metastasize.

eHealth approaches show promising results for smoking cessation (SC). They can improve quit rates, but rigorous research is sparse regarding their effectiveness and the effects of their interactivity, tailoring, and use intensity. We examined the effectiveness of Techniker Krankenkasse Smoking Cessation Coaching (TK-SCC), an internet-based, tailored, and interactive SC intervention. Our hypotheses were as follows: hypothesis 1, in the intervention group (IG; access to TK-SCC), a clinically relevant number of participants will be abstinent at the 12-month follow-up (T3); hypothesis 2, the number of abstinent participants will be significantly greater in the IG than the control group (CG) at T3; and hypothesis 3, in the IG, more intense use of TK-SCC will be positively associated with abstinence. Individuals who smoke were randomized into the IG (563/1115, 50.49%) or CG (552/1115, 49.51%), which received a noninteractive, nontailored, and information-only web-based intervention. Data were collected before the intervention, at the postintervention time point (T1), at the 4-month follow-up (T2), and at T3. We tested hypothesis 1 through equivalence tests between the IG's success rate and success rates of comparable effective interventions reported in 2 current meta-analyses. For hypothesis 2, we conducted binary logistic regressions. For hypothesis 3, we assigned the IG participants to 1 of 4 user types and used binary logistic regressions with user types as the independent variable and smoking abstinence as the dependent variable. In the IG, 11.5% (65/563) and 11.9% (67/563) of participants were smoke free at T1 and T3, respectively. These values were statistically equivalent to the effects in the 2 meta-analyses, which reported 9% (z score=0.64, P=.74) and 10.9% (z score=-0.71, P=.24) success rates, respectively. In the CG, 6.2% (34/552) of the participants were smoke free at T1, which increased up to 8.2% (45/552) at T3. The difference between the IG and CG was statistically significant only at T1 (odds ratio [OR] 2.0, 99% CI 1.1 to 3.6; P=.002), whereas the effect was nonsignificant following α error corrections at T3 (OR 1.6, 99% CI 0.9 to 2.7; P=.02). In the IG, constant users of the program became smoke free significantly more often than rare users of the program (T1: OR 15.0, 99% CI 6.1 to 36.9; P<.001; T3: OR 6.5, 99% CI 2.8 to 15.5; P<.001). TK-SCC is effective for SC. However, its superiority compared with a minimal SC intervention could not be confirmed in the long term. Insufficient implementation of the techniques used and cotreatment bias could explain this outcome. Higher use intensity of TK-SCC was positively related to abstinence. Therefore, additional efforts to motivate users to adhere to intervention use as intended could improve the intervention's effectiveness. German Clinical Trials Register DRKS00020249, Universal Trial Number U1111-1245-0273; https://drks.de/search/de/trial/DRKS00020249. RR2-10.1186/s13063-021-05470-8.

Very preterm infants with immature kidneys exhibit high vulnerability to acute kidney injury (AKI). While AKI is associated with adverse outcomes, serum-creatinine-based diagnostics prove unreliable in early risk assessment of kidney damage. This pilot study investigated 1H-NMR spectroscopy-based metabolomics for the identification of very-low-birth-weight (VLBW < 1500 g) infants at risk of AKI before and during indomethacin treatment for patent ductus arteriosus (PDA). Longitudinal urine samples (0 h, 12 h, 36 h, 84 h, 120 h, 14 d, 28 d) from 12 VLBW infants receiving indomethacin for hemodynamically significant PDA were analyzed by 1H-NMR spectroscopy. In total, 150 urinary metabolites were annotated and single-metabolite and multivariate analyses were performed. At 36 h after treatment initiation, three patients (25%) developed AKI (KDIGO criteria). Principal component analysis (PCA) revealed significant differences in urinary metabolic profiles between the AKI and non-AKI groups 12 h after indomethacin initiation. Before treatment, five metabolites were significantly lower in the AKI group: adenine, creatine, dimethylglycine, 1-methylnicotinamide, and methylmalonic acid. Urinary creatine/creatinine (AUC 0.97) and 1-methylnicotinamide/creatinine (AUC 0.93) exhibited promising prognostic accuracy for the prediction of AKI. 1-methylnicotinamide/creatinine concentrations remained persistently reduced during the study. In conclusion, urinary metabolomics, particularly creatine and 1-methylnicotinamide levels, may serve as valuable non-invasive biomarkers for identifying VLBW infants at risk of AKI.