Investigating the spatiotemporal associations between meteorological conditions and air pollution in the federal state Baden-Württemberg (Germany).

When analyzing health data in relation to environmental stressors, it is crucial to identify which variables to include in the statistical model to exclude dependencies among the variables. Four meteorological parameters: temperature, ultraviolet radiation, precipitation, and vapor pressure and four outdoor air pollution parameters: ozone ( O 3 ), nitrogen dioxide ( NO 2 ), particulate matter ( P M 2.5 , P M 10 ) were studied on a daily basis for Baden-Württemberg (Germany). This federal state covers urban and rural compartments including mountainous and river areas. A temporal and spatial analysis of the internal relationships was performed among the variables using (a) cross-correlations, both on the grand ensemble of data as well as within subsets, and (b) the Local Indications of Spatial Association (LISA) method. Meteorological and air pollution variables were strongly correlated within and among themselves in time and space. We found a strong interaction between nitrogen dioxide and ozone, with correlation coefficients varying over time. The coefficients ranged from negative correlations in January (-0.84), April (-0.47), and October (-0.54) to a positive correlation in July (0.45). The cross-correlation plot showed a noticeable change in the correlation direction for O 3 and NO 2 . Spatially, NO 2 , P M 2.5 , and P M 10 concentrations were significantly higher in urban than rural regions. For O 3 , this effect was reversed. A LISA analysis confirmed distinct hot and cold spots of environmental stressors. This work examined and quantified the spatio-temporal relationship between air pollution and meteorological conditions and recommended which variables to prioritize for future health impact analyses. The results found are in line with the underlying physico-chemical atmospheric processes. It also identified postal code areas with dominant environmental stressors for further studies.

Pseudo-value regression trees.

This paper presents a semi-parametric modeling technique for estimating the survival function from a set of right-censored time-to-event data. Our method, named pseudo-value regression trees (PRT), is based on the pseudo-value regression framework, modeling individual-specific survival probabilities by computing pseudo-values and relating them to a set of covariates. The standard approach to pseudo-value regression is to fit a main-effects model using generalized estimating equations (GEE). PRT extend this approach by building a multivariate regression tree with pseudo-value outcome and by successively fitting a set of regularized additive models to the data in the nodes of the tree. Due to the combination of tree learning and additive modeling, PRT are able to perform variable selection and to identify relevant interactions between the covariates, thereby addressing several limitations of the standard GEE approach. In addition, PRT include time-dependent effects in the node-wise models. Interpretability of the PRT fits is ensured by controlling the tree depth. Based on the results of two simulation studies, we investigate the properties of the PRT method and compare it to several alternative modeling techniques. Furthermore, we illustrate PRT by analyzing survival in 3,652 patients enrolled for a randomized study on primary invasive breast cancer.

Vessel density on optical coherence tomography angiography is prognostic for future disease course in intermediate uveitis.

As most rare diseases, intermediate uveitis lacks reliable endpoints necessary for randomized clinical trials. Therefore, we investigated longitudinal changes of retinal and choriocapillaris perfusion on optical coherence tomography angiography (OCT-A) in intermediate uveitis and their prognostic value for future best corrected visual acuity (BCVA) and central retinal thickness (CRT). In this retrospective, longitudinal cohort study eyes of patients with intermediate uveitis were imaged by swept-source OCT-A (macula-centered 3 × 3 mm; PLEX Elite 9000, Zeiss) and stratified into clinically stable, worsened and improved based on changes in clinical parameters. Superficial (SRL) and deep retinal layers (DRL) were automatically analyzed for vessel density (VD) and choriocapillaris layer for non-perfused area (CCNPA) using ImageJ. Mixed-effects regression analysis controlling for age, sex, and OCT-A signal strength index (SSI) was used to evaluate the prognostic value of OCT-A parameters. 91 eyes (62 stable, 12 worsened, and 17 improved) were included in the analysis and mean follow-up time was 296 days. Longitudinal changes of VD were different between all three groups (p = 0.002 for SRL and p = 0.017 for DRL). Clinically worsened eyes showed a decrease in VD (- 0.032 ± 0.055 for SRL and - 0.027 ± 0.025 for DRL), whereas clinically improved eyes showed an increase in VD (0.037 ± 0.039 for SRL and 0.001 ± 0.023 for DRL). No difference was found for CCNPA. When controlling for age, sex, and SSI, observed differences held true in clinically worsened eyes for DRL (p = 0.011) and in clinically improved eyes for SRL (p = 0.002). An increase of CCNPA in clinically worsened eyes (p = 0.03) compared to clinically stable and improved eyes was evident. Predictive analysis revealed an association of VD in SRL and DRL at baseline with BCVA at follow-up (p = 0.039 and p = 0.047, respectively) and of VD in SRL at baseline with CRT at follow-up (p = 0.046). Alterations in retinal perfusion on OCT-A in intermediate uveitis are partly reversible and OCT-A VD may serve to predict future BCVA and CRT. Thus, perfusion parameters on OCT-A might aid monitoring and serve as prognostic imaging-biomarker.

A Novel Scoring System Predicting Red Blood Cell Transfusion Requirements in Patients Undergoing Invasive Spine Surgery.

Background: Access to blood products is crucial for patient safety during the perioperative course. However, reduced donations and seasonally occurring blood shortages pose a significant challenge to the healthcare system, with surgeries being postponed. The German Blood Transfusion act requires that RBC packages become assigned to an individual patient, resulting in a significant reduction in the available blood products, further aggravating shortages. We aimed to develop a scoring system predicting transfusion probability in patients undergoing spine surgery to reduce assignment and, thus, increase the availability of blood products. Methods: The medical records of 252 patients who underwent spine surgery were evaluated and 18 potential predictors for RBC transfusion were tested to construct a logistic-regression-based predictive scoring system for blood transfusion in patients undergoing spine surgery. Results: The variables found to be the most important included the type of surgery, vertebral body replacement, number of stages, and pre-operative Hb concentration, indicating that surgical specification and the extent of the surgical procedure were more influential than the pre-existing patient condition and medication. Conclusions: Our model showed a good discrimination ability with an average AUC [min, max] of 0.87 [0.6, 0.97] and internal validation with a similar AUC of 0.84 [0.66, 0.97]. In summary, we developed a scoring system to forecast patients' perioperative transfusion needs when undergoing spine surgery using pre-operative predictors, potentially reducing the need for RBC allocation and, thus, resulting in an increased availability of this valuable resource.

CT-derived Epicardial Adipose Tissue Inflammation Predicts Outcome in Patients Undergoing Transcatheter Aortic Valve Replacement.

PURPOSE: Inflammatory changes in epicardial (EAT) and pericardial adipose tissue (PAT) are associated with increased overall cardiovascular risk. Using routine, preinterventional cardiac CT data, we examined the predictive value of quantity and quality of EAT and PAT for outcome after transcatheter aortic valve replacement (TAVR). MATERIALS AND METHODS: Cardiac CT data of 1197 patients who underwent TAVR at the in-house heart center between 2011 and 2020 were retrospectively analyzed. The amount and density of EAT and PAT were quantified from single-slice CT images at the level of the aortic valve. Using established risk scores and known independent risk factors, a clinical benchmark model (BMI, Chronic kidney disease stage, EuroSCORE 2, STS Prom, year of intervention) for outcome prediction (2-year mortality) after TAVR was established. Subsequently, we tested whether the additional inclusion of area and density values of EAT and PAT in the clinical benchmark model improved prediction. For this purpose, the cohort was divided into a training (n=798) and a test cohort (n=399). RESULTS: Within the 2-year follow-up, 264 patients died. In the training cohort, particularly the addition of EAT density to the clinical benchmark model showed a significant association with outcome (hazard ratio 1.04, 95% CI: 1.01-1.07; P =0.013). In the test cohort, the outcome prediction of the clinical benchmark model was also significantly improved with the inclusion of EAT density (c-statistic: 0.589 vs. 0.628; P =0.026). CONCLUSIONS: EAT density as a surrogate marker of EAT inflammation was associated with 2-year mortality after TAVR and may improve outcome prediction independent of established risk parameters.

Different inflammatory signatures based on CSF biomarkers relate to preserved or diminished brain structure and cognition.

Neuroinflammation is a hallmark of Alzheimer's disease (AD) and both positive and negative associations of individual inflammation-related markers with brain structure and cognitive function have been described. We aimed to identify inflammatory signatures of CSF immune-related markers that relate to changes of brain structure and cognition across the clinical spectrum ranging from normal aging to AD. A panel of 16 inflammatory markers, Aß42/40 and p-tau181 were measured in CSF at baseline in the DZNE DELCODE cohort (n = 295); a longitudinal observational study focusing on at-risk stages of AD. Volumetric maps of gray and white matter (GM/WM; n = 261) and white matter hyperintensities (WMHs, n = 249) were derived from baseline MRIs. Cognitive decline (n = 204) and the rate of change in GM volume was measured in subjects with at least 3 visits (n = 175). A principal component analysis on the CSF markers revealed four inflammatory components (PCs). Of these, the first component PC1 (highly loading on sTyro3, sAXL, sTREM2, YKL-40, and C1q) was associated with older age and higher p-tau levels, but with less pathological Aß when controlling for p-tau. PC2 (highly loading on CRP, IL-18, complement factor F/H and C4) was related to male gender, higher body mass index and greater vascular risk. PC1 levels, adjusted for AD markers, were related to higher GM and WM volumes, less WMHs, better baseline memory, and to slower atrophy rates in AD-related areas and less cognitive decline. In contrast, PC2 related to less GM and WM volumes and worse memory at baseline. Similar inflammatory signatures and associations were identified in the independent F.ACE cohort. Our data suggest that there are beneficial and detrimental signatures of inflammatory CSF biomarkers. While higher levels of TAM receptors (sTyro/sAXL) or sTREM2 might reflect a protective glia response to degeneration related to phagocytic clearance, other markers might rather reflect proinflammatory states that have detrimental impact on brain integrity.

Development of a clinical algorithm to predict phenotypic switches between atopic dermatitis and psoriasis (the "Flip-Flop" phenomenon).

BACKGROUND: Atopic dermatitis (AD) and psoriasis vulgaris (PV) are almost mutually exclusive diseases with different immune polarizations, mechanisms and therapeutic targets. Switches to the other disease ("Flip-Flop" [FF] phenomenon) can occur with or without systemic treatment and are often referred to as paradoxical reactions under biological therapy. METHODS: The objective was to develop a diagnostic algorithm by combining clinical criteria of AD and PV to identify FF patients. The algorithm was prospectively validated in patients enrolled in the CK-CARE registry in Bonn, Germany. Afterward, algorithm refinements were implemented based on machine learning. RESULTS: Three hundred adult Caucasian patients were included in the validation study (n = 238 with AD, n = 49 with PV, n = 13 with FF; mean age 41.2 years; n = 161 [53.7%] female). The total FF scores of the PV and AD groups differed significantly from the FF group in the validation data (p < .001). The predictive mean generalized Youden-Index of the initial model was 78.9% [95% confidence interval 72.0%-85.6%] and the accuracy was 89.7%. Disease group-specific sensitivity was 100% (FF), 95.0% (AD), and 61.2% (PV). The specificity was 89.2% (FF), 100% (AD), and 100% (PV), respectively. CONCLUSION: The FF algorithm represents the first validated tool to identify FF patients.

Identification and comparison of sex-specific serious adverse drug reactions in spontaneous reports and systematically collected reports (ADRED).

AIMS: Adverse drug reactions (ADRs) are known to show sex-specific differences in occurrence and phenotype. The aim of this study was to analyse sex-specific differences in ADR-drug combinations that required hospitalization based on two different datasets. METHODS: We performed a complementary analysis of (i) spontaneously reported (n = 12 564, female = 51.7%) and (ii) systematically collected ADR reports from a prospective multicentre observational study (ADRED, n = 2355, female = 48.2%) from Germany in the ADR database EudraVigilance (EV). Both datasets were analysed separately concerning the suspected drugs, ADRs and ADR-drug combinations more frequently reported for females or males by calculating reporting odds ratios (ROR) with 95% confidence intervals. ADR-drug combinations more frequently reported for either females or males in EV reports were related to prescription data. Finally, the results from both datasets were discussed with regard to their (dis-)concordance. RESULTS: In both datasets, some antineoplastic agents and nervous system drugs were found to be reported more often for females than males (RORs ranging from 1.5 [1.1-2.1] for quetiapine in spontaneous reports to 41.3 [13.1-130.0] for trastuzumab in spontaneous reports). ADRs of the respiratory system, and haemorrhages were described predominantly for males in both datasets. In spontaneous reports the ADR-drug combination self-injurious behaviour-quetiapine was more often reported for females without and with consideration of drug prescriptions (ROR: 3.8 [1.3-11.0]). Quetiapine and psychiatric disorders (superordinate level) was exclusively reported for females in ADRED reports. CONCLUSIONS: Our results can contribute to raise awareness and further knowledge regarding sex-specific ADRs. The findings require further in-depth investigation.

Stage-Dependent Biomarker Changes in Spinocerebellar Ataxia Type 3.

Spinocerebellar ataxia type 3/Machado-Joseph disease is the most common autosomal dominant ataxia. In view of the development of targeted therapies, knowledge of early biomarker changes is needed. We analyzed cross-sectional data of 292 spinocerebellar ataxia type 3/Machado-Joseph disease mutation carriers. Blood concentrations of mutant ATXN3 were high before and after ataxia onset, whereas neurofilament light deviated from normal 13.3 years before onset. Pons and cerebellar white matter volumes decreased and deviated from normal 2.2 years and 0.6 years before ataxia onset. We propose a staging model of spinocerebellar ataxia type 3/Machado-Joseph disease that includes a biomarker stage characterized by objective indicators of neurodegeneration before ataxia onset. ANN NEUROL 2024;95:400-406.

A Platform for the Liebeskind-Srogl Coupling of Heteroaromatic Thioethers for Medicinal-Chemistry-Relevant Transformations.

General and robust conditions for the Liebeskind-Srogl coupling were developed and used in functionalization of medicinal-chemistry-relevant heterocyclic substrates. Applicability in HTE and library synthesis, combined with its orthogonality to other cross-coupling reactions, make it highly attractive for discovery chemistry workflows. Additionally, the results suggest that the nature of the Cu(I)-carboxylate plays a more prominent role in the reaction performance than the nature of Pd-catalysts, which is rather uncommon for Pd-catalysis and can be used in further optimization of Liebeskind-Srogl coupling.

Pre-Interventional Risk Assessment in The Elderly (PIRATE): Development of a scoring system to predict 30-day mortality using data of the Peri-Interventional Outcome Study in the Elderly.

Risk assessment before interventions in elderly patients becomes more and more vital due to an increasing number of elderly patients requiring surgery. Existing risk scores are often not tailored to marginalized groups such as patients aged 80 years or older. We aimed to develop an easy-to-use and readily applicable risk assessment tool that implements pre-interventional predictors of 30-day mortality in elderly patients (≥80 years) undergoing interventions under anesthesia. Using Cox regression analysis, we compared different sets of predictors by taking into account their ease of availability and by evaluating predictive accuracy. Coefficient estimates were utilized to set up a scoring system that was internally validated. Model building and evaluation were based on data from the Peri-Interventional Outcome Study in the Elderly (POSE), which was conducted as a European multicenter, observational prospective cohort study. Our risk assessment tool, named PIRATE, contains three predictors assessable at admission (urgency, severity and living conditions). Discriminatory power, as measured by the concordance index, was 0.75. The estimated prediction error, as measured by the Brier score, was 0.036 (covariate-free reference model: 0.043). PIRATE is an easy-to-use risk assessment tool that helps stratifying elderly patients undergoing interventions with anesthesia at increased risk of mortality. PIRATE is readily available and applies to a wide variety of settings. In particular, it covers patients needing elective or emergency surgery and undergoing in-hospital or day-case surgery. Also, it applies to all types of interventions, from minor to major. It may serve as a basis for multidisciplinary and informed shared decision-making.

Cardiovascular risk due to diabetes mellitus in patients with chronic kidney disease-prospective data from the German Chronic Kidney Disease cohort.

Background: Diabetes mellitus (DM) and chronic kidney disease (CKD) are well-known cardiovascular and mortality risk factors. To what extent they act in an additive manner and whether the etiology of CKD modifies the risk is uncertain. Methods: The multicenter, prospective, observational German Chronic Kidney Disease study comprises 5217 participants (1868 with DM) with a baseline mean estimated glomerular filtration rate of 30-60 mL/min/1.73 m2 and/or proteinuria >0.5 g/day. We categorized patients whose CKD was caused by cardiovascular or metabolic diseases (CKDcvm) with and without DM, as opposed to genuine CKD (CKDgen) with and without DM. Recorded outcomes were first events of non-cardiovascular and cardiovascular death, 4-point major adverse cardiovascular events (4-point MACE) and hospitalization for heart failure (HHF). Results: During the 6.5-year follow-up 603 (12%) non-cardiovascular and 209 (4%) cardiovascular deaths, 645 (12%) 4-point MACE, and 398 (8%) HHF were observed, most frequently in patients with DM having CKDcvm. DM increased the risk of non-cardiovascular [hazard ratio (HR) 1.92; 95% confidence interval (CI) 1.59-2.32] and cardiovascular (HR 2.25; 95% CI 1.62-3.12) deaths, 4-point MACE (HR 1.93; 95% CI 1.62-2.31) and HHF (HR 1.87; 95% CI 1.48-2.36). Mortality risks were elevated by DM to a similar extent in CKDcvm and CKDgen, but for HHF in CKDcvm only (HR 2.07; 95% CI 1.55-2.77). In patients with DM, CKDcvm (versus CKDgen) only increased the risk for HHF (HR 1.93; 95% CI 1.15-3.22). Conclusions: DM contributes to cardiovascular and mortality excess risk in patients with moderate to severe CKD in both, CKDcvm and CKDgen. Patients with DM and CKDcvm are particularly susceptible to HHF.

Copeptin, Natriuretic Peptides, and Cardiovascular Outcomes in Patients With CKD: The German Chronic Kidney Disease (GCKD) Study.

Rationale & Objective: Copeptin and Midrange pro-atrial natriuretic peptide (MR-pro-ANP) are associated with outcomes independently of N-terminal pro-brain natriuretic peptide (NT-pro-BNP) in patients with heart failure (HF). The value of these markers in patients with chronic kidney disease (CKD) has not been studied. Study Design: Prospective cohort study. Setting & Participants: A total of 4,417 patients enrolled in the German Chronic Kidney Disease (GCKD) study with an estimated glomerular filtration rate of 30-60 mL/min/1.73m2 or overt proteinuria (urinary albumin-creatinine ratio >300mg/g or equivalent). Exposures: Copeptin, MR-pro-ANP, and NT-pro-BNP levels were measured in baseline samples. Outcomes: Noncardiovascular death, cardiovascular (CV) death, major adverse CV event (MACE), and hospitalization for HF. Analytical Approach: HRs for associations of Copeptin, MR-pro-ANP, and NT-pro-BNP with outcomes were estimated using Cox regression analyses adjusted for established risk factors. Results: During a maximum follow-up of 6.5 years, 413 non-CV deaths, 179 CV deaths, 519 MACE, and 388 hospitalizations for HF were observed. In Cox regression analyses adjusted for established risk factors, each one of the 3 markers were associated with all the 4 outcomes, albeit the highest HRs were found for NT-pro-BNP. When models were extended to include all the 3 markers, NT-pro-BNP remained associated with all 4 outcomes. Conversely, from the 2 novel markers, associations remained only for Copeptin with non-CV death (HR, 1.62; 95% CI, 1.04-2.54 for highest vs lowest quintile) and with hospitalizations for HF (HR, 1.73; 95% CI, 1.08-2.75). Limitations: Single-point measurements of Copeptin, MR-pro-ANP, and NT-pro-BNP. Conclusions: In patients with moderately severe CKD, we confirm NT-pro-BNP to be strongly associated with all outcomes examined. As the main finding, the novel marker Copeptin demonstrated independent associations with non-CV death and hospitalizations for HF, and should therefore be evaluated further for risk assessment in CKD. Plain-Language Summary: A blood sample-based biomarker that indicates high cardiovascular risk in a patient with kidney disease would help to guide interventions and has the potential to improve outcomes. In 4,417 patients of the German Chronic Kidney Disease study, we assessed the relationship of Copeptin, pro-atrial natriuretic peptide, and N-terminal pro-brain natriuretic peptide (NT-pro-BNP) with important outcomes over a follow-up period of 6.5 years. NT-pro-BNP was strongly associated with all of the 4 outcomes, including death unrelated to cardiovascular disease, death because of cardiovascular disease, a major cardiovascular event, and hospitalization for heart failure. Copeptin was associated with death unrelated to cardiovascular disease and hospitalization for heart failure. NT-pro-BNP and Copeptin are, therefore, promising candidates for a blood sample-based strategy to identify patients with kidney disease at high cardiovascular risk.

Comparative Analysis of Information Provided in German Adverse Drug Reaction Reports Sent by Physicians, Pharmacists and Consumers.

INTRODUCTION: Adverse drug reactions (ADRs) can be reported by Health Care Professionals (HCPs; e.g., physicians, pharmacists) and non-Health Care Professionals (non-HCPs; e.g., consumers). Previous studies investigating differences between reports from HCPs and non-HCPs rarely considered the completeness of information provided. In addition, they mostly did not distinguish between physicians and pharmacists or were performed years ago. The aim of our study was to analyse and compare the completeness of information provided in reports from physicians, pharmacists and consumers from Germany in a more recent dataset. MATERIALS AND METHODS: We analysed all spontaneous reports from Germany received between 2018 and 2021 in the ADR database EudraVigilance exclusively reported by physicians (n = 69,976), pharmacists (n = 42,396) or consumers (n = 121,144). Demographical parameters of the patients were analysed descriptively. Completeness of reports was evaluated applying an established score (vigiGrade). Odds ratios (ORs) with 95% confidence intervals (CIs) were calculated using logistic regression analysis in order to identify report, patient, drug or ADR-specific information provided more often in reports from physicians, pharmacists or consumers. RESULTS: Within the study period the number of reports per year by physicians and pharmacists decreased steadily, while an opposite trend was observed for consumer reports. The proportion of female patients was higher in reports from pharmacists (64.4%) and consumers (64.8%) compared to those from physicians (55.3%). On average, patients in reports from pharmacists (58.7) were older compared to those from physicians (53.5) and consumers (52.6). As an example for the presence of specific information, the time to onset of the ADR could be calculated more often in consumer compared to physician (OR 1.9 [1.8-1.9]) and pharmacist reports (OR 1.7 [1.6-1.7]). In contrast, pharmacist (OR 0.5 [0.4-0.5]) and consumer (OR 0.5 [0.5-0.5]) reports included the indication of the suspected drug less often than physician reports. Physician reports on average (mean = 0.5) were slightly more complete according to the vigiGrade score compared to reports from consumers (mean = 0.4) and pharmacists (mean = 0.4). CONCLUSION: The ADR reports from consumers were comparable with regard to the completeness score with those from physicians and pharmacists underlining their value. Differences in completeness of specific information between the reporter types were found, suggesting that a common reporting of interactions between the three reporters may further improve the completeness of ADR reports. Furthermore, stratified analysis of ADR reports per reporter type may be helpful for certain objectives in scientific research.

Prevention of cerebral thromboembolism by oral anticoagulation with dabigatran after pulmonary vein isolation for atrial fibrillation: the ODIn-AF trial.

BACKGROUND AND OBJECTIVES: Long-term oral anticoagulation (OAC) following successful catheter ablation of atrial fibrillation (AF) remains controversial. Prospective data are missing. The ODIn-AF study aimed to evaluate the effect of OAC on the incidence of silent cerebral embolic events and clinically relevant cardioembolic events in patients at intermediate to high risk for embolic events, free from AF after pulmonary vein isolation (PVI). METHODS: This prospective, randomized, multicenter, open-label, blinded endpoint interventional trial enrolled patients who were scheduled for PVI to treat paroxysmal or persistent AF. Six months after PVI, AF-free patients were randomized to receive either continued OAC with dabigatran or no OAC. The primary endpoint was the incidence of new silent micro- and macro-embolic lesions detected on brain MRI at 12 months of follow-up compared to baseline. Safety analysis included bleedings, clinically evident cardioembolic, and serious adverse events (SAE). RESULTS: Between 2015 and 2021, 200 patients were randomized into 2 study arms (on OAC: n = 99, off OAC: n = 101). There was no significant difference in the occurrence of new cerebral microlesions between the on OAC and off OAC arm [2 (2%) versus 0 (0%); P = 0.1517] after 12 months. MRI showed no new macro-embolic lesion, no clinical apparent strokes were present in both groups. SAE were more frequent in the OAC arm [on OAC n = 34 (31.8%), off OAC n = 18 (19.4%); P = 0.0460]; bleedings did not differ. CONCLUSION: Discontinuation of OAC after successful PVI was not found to be associated with an elevated risk of cerebral embolic events compared with continued OAC after a follow-up of 12 months.

Prospective Cohort Study of Soluble Urokinase Plasminogen Activation Receptor and Cardiovascular Events in Patients With CKD.

Introduction: Soluble urokinase plasminogen activation receptor (suPAR) is an immune-derived pathogenic factor for kidney and atherosclerotic disease. Whether the association between suPAR and cardiovascular (CV) outcomes is dependent on the severity of underlying kidney disease is unclear. Methods: We measured serum suPAR levels in 4994 participants (mean age 60 years; 60% men; 36% with diabetes mellitus; mean estimated glomerular filtration rate (eGFR) 49 ml/min per 1.73 m2, SD 18) of the German Chronic Kidney Disease (GCKD) cohort and examined its association with all-cause death, CV death, and major CV events (MACE) across the range of eGFR and urine albumin-to-creatinine ratio (UACR). Results: The median suPAR level was 1771 pg/ml (interquartile range [IQR] 1447-2254 pg/ml). SuPAR levels were positively and independently correlated with age, eGFR, UACR, and parathyroid hormone levels. There were 573 deaths, including 190 CV deaths and 683 MACE events at a follow-up time of 6.5 years. In multivariable analyses, suPAR levels (log2) were associated with all-cause death (hazard ratio [HR] 1.36, 95% confidence interval [CI] 1.21-1.53), CV death (HR 1.27, 95% CI 1.03-1.57), and MACE (HR 1.13, 95% CI 1.00-1.28), and were not found to differ according to diabetes mellitus status, baseline eGFR, UACR, or parathyroid hormone levels. In mediation analysis, suPAR's direct effect on all-cause death, CV death, and MACE accounted for 77%, 67%, and 60% of the total effect, respectively; whereas the effect mediated through eGFR accounted for 23%, 34%, and 40%, respectively. Conclusion: In a large cohort of individuals with chronic kidney disease (CKD), suPAR levels were associated with mortality and CV outcomes independently of indices of kidney function, consistent with its independent role in the pathogenesis of atherosclerosis.

Calibrating machine learning approaches for probability estimation: A comprehensive comparison.

Statistical prediction models have gained popularity in applied research. One challenge is the transfer of the prediction model to a different population which may be structurally different from the model for which it has been developed. An adaptation to the new population can be achieved by calibrating the model to the characteristics of the target population, for which numerous calibration techniques exist. In view of this diversity, we performed a systematic evaluation of various popular calibration approaches used by the statistical and the machine learning communities for estimating two-class probabilities. In this work, we first provide a review of the literature and, second, present the results of a comprehensive simulation study. The calibration approaches are compared with respect to their empirical properties and relationships, their ability to generalize precise probability estimates to external populations and their availability in terms of easy-to-use software implementations. Third, we provide code from real data analysis allowing its application by researchers. Logistic calibration and beta calibration, which estimate an intercept plus one and two slope parameters, respectively, consistently showed the best results in the simulation studies. Calibration on logit transformed probability estimates generally outperformed calibration methods on nontransformed estimates. In case of structural differences between training and validation data, re-estimation of the entire prediction model should be outweighted against sample size of the validation data. We recommend regression-based calibration approaches using transformed probability estimates, where at least one slope is estimated in addition to an intercept for updating probability estimates in validation studies.

Deficient Immune Response following SARS-CoV-2 Vaccination in Patients with Hepatobiliary Carcinoma: A Forgotten, Vulnerable Group of Patients.

Introduction: Data on immune response rates following vaccination for severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) in patients with hepatobiliary carcinoma (HBC) are rare. However, impaired immunogenicity must be expected due to the combination of chronic liver diseases (CLDs) with malignancy and anticancer treatment. Methods: In this prospective, longitudinal study, 101 patients were included, of whom 59 were patients with HBC under anticancer treatment. A cohort of patients with a past medical history of gastrointestinal cancer, of whom 28.6% had HBC without detectable active tumor disease having been off therapy for at least 12 months, served as control. Levels of SARS-CoV-2 anti-spike IgG, surrogate neutralization antibodies (sNABs), and cellular immune responses were compared. In uni- and multivariable subgroup analyses, risk factors for impaired immunogenicity were regarded. Data on rates and clinical courses of SARS-CoV-2 infections were documented. Results: In patients with HBC under active treatment, levels of SARS-CoV-2 anti-spike IgG were significantly lower (2.55 log10 BAU/mL; 95% CI: 2.33-2.76; p < 0.01) than in patients in follow-up care (3.02 log10 BAU/mL; 95% CI: 2.80-3.25) 4 weeks after two vaccinations. Antibody levels decreased over time, and differences between the groups diminished. However, titers of SARS-CoV-2 sNAB were for a longer time significantly lower in patients with HBC under treatment (64.19%; 95% CI: 55.90-72.48; p < 0.01) than in patients in follow-up care (84.13%; 95% CI: 76.95-91.31). Underlying CLD and/or liver cirrhosis Child-Pugh A or B (less than 8 points) did not seem to further impair immunogenicity. Conversely, chemotherapy and additional immunosuppression were found to significantly reduce antibody levels. After a third booster vaccination for SARS-CoV-2, levels of total and neutralization antibodies were equalized between the groups. Moreover, cellular response rates were balanced. Clinically, infection rates with SARS-CoV-2 were low, and no severe courses were observed. Conclusion: Patients with active HBC showed significantly impaired immune response rates to basic vaccinations for SARS-CoV-2, especially under chemotherapy, independent of underlying cirrhotic or non-cirrhotic CLD. Although booster vaccinations balanced differences, waning immunity was observed over time and should be monitored for further recommendations. Our data help clinicians decide on individual additional booster vaccinations and/or passive immunization or antiviral treatment in patients with HBC getting infected with SARS-CoV-2.

Cognitive Trajectories in Preclinical and Prodromal Alzheimer's Disease Related to Amyloid Status and Brain Atrophy: A Bayesian Approach.

Background: Cognitive decline is a key outcome of clinical studies in Alzheimer's disease (AD). Objective: To determine effects of global amyloid load as well as hippocampus and basal forebrain volumes on longitudinal rates and practice effects from repeated testing of domain specific cognitive change in the AD spectrum, considering non-linear effects and heterogeneity across cohorts. Methods: We included 1,514 cases from three cohorts, ADNI, AIBL, and DELCODE, spanning the range from cognitively normal people to people with subjective cognitive decline and mild cognitive impairment (MCI). We used generalized Bayesian mixed effects analysis of linear and polynomial models of amyloid and volume effects in time. Robustness of effects across cohorts was determined using Bayesian random effects meta-analysis. Results: We found a consistent effect of amyloid and hippocampus volume, but not of basal forebrain volume, on rates of memory change across the three cohorts in the meta-analysis. Effects for amyloid and volumetric markers on executive function were more heterogeneous. We found practice effects in memory and executive performance in amyloid negative cognitively normal controls and MCI cases, but only to a smaller degree in amyloid positive controls and not at all in amyloid positive MCI cases. Conclusions: We found heterogeneity between cohorts, particularly in effects on executive functions. Initial increases in cognitive performance in amyloid negative, but not in amyloid positive MCI cases and controls may reflect practice effects from repeated testing that are lost with higher levels of cerebral amyloid.

Association of mineral and bone biomarkers with adverse cardiovascular outcomes and mortality in the German Chronic Kidney Disease (GCKD) cohort.

Mineral and bone disorder (MBD) in chronic kidney disease (CKD) is tightly linked to cardiovascular disease (CVD). In this study, we aimed to compare the prognostic value of nine MBD biomarkers to determine those associated best with adverse cardiovascular (CV) outcomes and mortality. In 5 217 participants of the German CKD (GCKD) study enrolled with an estimated glomerular filtration rate (eGFR) between 30-60 mL·min-1 per 1.73 m2 or overt proteinuria, serum osteoprotegerin (OPG), C-terminal fibroblast growth factor-23 (FGF23), intact parathyroid hormone (iPTH), bone alkaline phosphatase (BAP), cross-linked C-telopeptide of type 1 collagen (CTX1), procollagen 1 intact N-terminal propeptide (P1NP), phosphate, calcium, and 25-OH vitamin D were measured at baseline. Participants with missing values among these parameters (n = 971) were excluded, leaving a total of 4 246 participants for analysis. During a median follow-up of 6.5 years, 387 non-CV deaths, 173 CV deaths, 645 nonfatal major adverse CV events (MACEs) and 368 hospitalizations for congestive heart failure (CHF) were observed. OPG and FGF23 were associated with all outcomes, with the highest hazard ratios (HRs) for OPG. In the final Cox regression model, adjusted for CV risk factors, including kidney function and all other investigated biomarkers, each standard deviation increase in OPG was associated with non-CV death (HR 1.76, 95% CI: 1.35-2.30), CV death (HR 2.18, 95% CI: 1.50-3.16), MACE (HR 1.38, 95% CI: 1.12-1.71) and hospitalization for CHF (HR 2.05, 95% CI: 1.56-2.69). Out of the nine biomarkers examined, stratification based on serum OPG best identified the CKD patients who were at the highest risk for any adverse CV outcome and mortality.