Approximate inference for longitudinal mechanistic HIV contact network.

Network models are increasingly used to study infectious disease spread. Exponential Random Graph models have a history in this area, with scalable inference methods now available. An alternative approach uses mechanistic network models. Mechanistic network models directly capture individual behaviors, making them suitable for studying sexually transmitted diseases. Combining mechanistic models with Approximate Bayesian Computation allows flexible modeling using domain-specific interaction rules among agents, avoiding network model oversimplifications. These models are ideal for longitudinal settings as they explicitly incorporate network evolution over time. We implemented a discrete-time version of a previously published continuous-time model of evolving contact networks for men who have sex with men and proposed an ABC-based approximate inference scheme for it. As expected, we found that a two-wave longitudinal study design improves the accuracy of inference compared to a cross-sectional design. However, the gains in precision in collecting data twice, up to 18%, depend on the spacing of the two waves and are sensitive to the choice of summary statistics. In addition to methodological developments, our results inform the design of future longitudinal network studies in sexually transmitted diseases, specifically in terms of what data to collect from participants and when to do so.

Cost-based feature selection for network model choice.

Selecting a small set of informative features from a large number of possibly noisy candidates is a challenging problem with many applications in machine learning and approximate Bayesian computation. In practice, the cost of computing informative features also needs to be considered. This is particularly important for networks because the computational costs of individual features can span several orders of magnitude. We addressed this issue for the network model selection problem using two approaches. First, we adapted nine feature selection methods to account for the cost of features. We show for two classes of network models that the cost can be reduced by two orders of magnitude without considerably affecting classification accuracy (proportion of correctly identified models). Second, we selected features using pilot simulations with smaller networks. This approach reduced the computational cost by a factor of 50 without affecting classification accuracy. To demonstrate the utility of our approach, we applied it to three different yeast protein interaction networks and identified the best-fitting duplication divergence model. Supplemental materials, including computer code to reproduce our results, are available online.

Anti-PF4 immunothrombosis without proximate heparin or adenovirus vector vaccine exposure.

ABSTRACT: Platelet-activating anti-platelet factor 4 (PF4)/heparin antibodies and anti-PF4 antibodies cause heparin-induced thrombocytopenia (HIT) and vaccine-induced immune thrombocytopenia and thrombosis (VITT), respectively. Diagnostic and treatment considerations differ somewhat between HIT and VITT. We identified patients with thrombocytopenia and thrombosis without proximate heparin exposure or adenovirus-based vaccination who tested strongly positive by PF4/polyanion enzyme-immunoassays and negative/weakly positive by heparin-induced platelet activation (HIPA) test but strongly positive by PF4-induced platelet activation (PIPA) test (ie, VITT-like profile). We tested these patients by a standard chemiluminescence assay that detects anti-PF4/heparin antibodies found in HIT (HemosIL AcuStar HIT-IgG(PF4-H)) as well as a novel chemiluminescence assay for anti-PF4 antibodies found in VITT. Representative control sera included an exploratory anti-PF4 antibody-positive but HIPA-negative/weak cohort obtained before 2020 (n = 188). We identified 9 patients with a clinical-pathological profile of a VITT-like disorder in the absence of proximate heparin or vaccination, with a high frequency of stroke (arterial, n = 3; cerebral venous sinus thrombosis, n = 4), thrombocytopenia (median platelet count nadir, 49 × 109/L), and hypercoagulability (greatly elevated D-dimer levels). VITT-like serological features included strong reactivity by PIPA (aggregation <10 minutes in 9/9 sera) and positive testing in the novel anti-PF4 chemiluminescence assay (3/9 also tested positive in the anti-PF4/heparin chemiluminescence assay). Our exploratory cohort identified 13 additional patient sera obtained before 2020 with VITT-like anti-PF4 antibodies. Platelet-activating VITT-like anti-PF4 antibodies should be considered in patients with thrombocytopenia, thrombosis, and very high D-dimer levels, even without a proximate exposure to heparin or adenovirus vector vaccines.

Long-term outcome in vaccine-induced immune thrombocytopenia and thrombosis.

BACKGROUND: Rapid diagnosis and treatment has improved outcome of patients with vaccine-induced immune thrombocytopenia and thrombosis (VITT). However, after the acute episode, many questions on long-term management of VITT remained unanswered. OBJECTIVES: To analyze, in patients with VITT, the long-term course of anti-platelet factor 4 (PF4) antibodies; clinical outcomes, including risk of recurrent thrombosis and/or thrombocytopenia; and the effects of new vaccinations. METHODS: 71 patients with serologically confirmed VITT in Germany were enrolled into a prospective longitudinal study and followed for a mean of 79 weeks from March 2021 to January 2023. The course of anti-PF4 antibodies was analyzed by consecutive anti-PF4/heparin immunoglobulin G enzyme-linked immunosorbent assay and PF4-enhanced platelet activation assay. RESULTS: Platelet-activating anti-PF4 antibodies became undetectable in 62 of 71 patients (87.3%; 95% CI, 77.6%-93.2%). In 6 patients (8.5%), platelet-activating anti-PF4 antibodies persisted for >18 months. Five of 71 patients (7.0%) showed recurrent episodes of thrombocytopenia and/or thrombosis; in 4 of them (80.0%), alternative explanations beside VITT were present. After further COVID-19 vaccination with a messenger RNA vaccine, no reactivation of platelet-activating anti-PF4 antibodies or new thrombosis was observed. No adverse events occurred in our patients subsequently vaccinated against influenza, tick-borne encephalitis, varicella, tetanus, diphtheria, pertussis, and polio. No new thrombosis occurred in the 24 patients (33.8%) who developed symptomatic SARS-CoV-2 infection following recovery from acute VITT. CONCLUSION: Once the acute episode of VITT has passed, patients appear to be at low risk for recurrent thrombosis and/or thrombocytopenia.

Gender-Associated Variation in DOAC Levels.

BACKGROUND: Direct oral anticoagulants (DOAC) such as Xa inhibitors rivaroxaban (riva) and apixaban (apix) are increasingly replacing Vitamin K antagonists in prophylaxis and treatment of venous thromboembolism (VTE). Measurements of DOAC plasma levels may be necessary in certain clinical conditions to determine the further dosage. Making decisions is made more difficult by the fact that the peak and trough plasma levels are subject to strong inter-individual fluctuations with overlapping reference ranges. We wanted to find out whether the peak and trough levels can be narrowed if they are determined based on age and gender. METHODS: Therefore, we collected data on peak and trough anti-Xa concentrations in patients treated with either rivaroxaban (n = 93) or apixaban (n = 51) in one center. After exclusion of blood samples of uncertain oral intake, 83 samples for rivaroxaban and 49 samples for apixaban remained for further analysis. Differences between male (riva n = 42, apix n = 28) and female (riva n = 41 and apix n = 21) as well as young (≤ 60 years, riva n = 44, apix n = 23) and elder (> 60 years) patients (riva n = 39 and apix n = 26) were analyzed by Student`s t-test and retrospective regression. RESULTS: We found no differences in age and gender for the apix peak levels. But women had significantly higher riva peak concentrations than men (308.8 ± 178.1 ng/mL versus 206.4 ± 80 ng/mL, p = 0.013). Patients older than 60 years had significantly higher riva peak levels than those younger than 60 (293.7 ± 126.7 ng/mL versus 211.7 ± 158.4 ng/mL, p = 1.29 x 10-8). CONCLUSIONS: In search of narrowing standard peak and trough levels in patients' sera we found significant differ-ences between patients below and above sixty years of age. Gender-associated differences were found in rivaroxa-ban levels possibly explaining DOAC associated hypermenorrhea. In conclusion, gender and age should be included in the determination of peak blood concentration references.

An analysis of 45 large-scale wastewater sites in England to estimate SARS-CoV-2 community prevalence.

Accurate surveillance of the COVID-19 pandemic can be weakened by under-reporting of cases, particularly due to asymptomatic or pre-symptomatic infections, resulting in bias. Quantification of SARS-CoV-2 RNA in wastewater can be used to infer infection prevalence, but uncertainty in sensitivity and considerable variability has meant that accurate measurement remains elusive. Here, we use data from 45 sewage sites in England, covering 31% of the population, and estimate SARS-CoV-2 prevalence to within 1.1% of estimates from representative prevalence surveys (with 95% confidence). Using machine learning and phenomenological models, we show that differences between sampled sites, particularly the wastewater flow rate, influence prevalence estimation and require careful interpretation. We find that SARS-CoV-2 signals in wastewater appear 4-5 days earlier in comparison to clinical testing data but are coincident with prevalence surveys suggesting that wastewater surveillance can be a leading indicator for symptomatic viral infections. Surveillance for viruses in wastewater complements and strengthens clinical surveillance, with significant implications for public health.

Staphylococcus aureus increases platelet reactivity in patients with infective endocarditis.

Thromboembolism is frequent in infective endocarditis (IE). However, the optimal antithrombotic regimen in IE is unknown. Staphylococcus aureus (SA) is the leading cause of IE. First studies emphasize increased platelet reactivity by SA. In this pilot study, we hypothesized that platelet reactivity is increased in patients with SA- IE, which could be abrogated by antiplatelet medication. We conducted a prospective, observatory, single-center cohort study in 114 patients with IE, with four cohorts: (1) SA coagulase positive IE without aspirin (ASA) medication, (2) coagulase negative IE without ASA, (3) SA coagulase positive IE with ASA, (4) coagulase negative IE with ASA. Platelet function was measured by Multiplate electrode aggregometry, blood clotting by ROTEM thromboelastometry. Bleeding events were assessed according to TIMI classification. In ASA-naïve patients, aggregation with ADP was increased with coag. pos. IE (coagulase negative: 39.47 ± 4.13 AUC vs. coagulase positive: 59.46 ± 8.19 AUC, p = 0.0219). This was abrogated with ASA medication (coagulase negative: 42.4 ± 4.67 AUC vs. coagulase positive: 45.11 ± 6.063 AUC p = 0.7824). Aspirin did not increase bleeding in SA positive patients. However, in SA negative patients with aspirin, red blood cell transfusions were enhanced. SA coagulase positive IE is associated with increased platelet reactivity. This could be abrogated by aspirin without increased bleeding risk. The results of this pilot study suggest that ASA might be beneficial in SA coagulase positive IE. This needs to be confirmed in clinical trials.

Most anti-PF4 antibodies in vaccine-induced immune thrombotic thrombocytopenia are transient.

Vaccine-induced thrombotic thrombocytopenia (VITT) is triggered by vaccination against COVID-19 with adenovirus vector vaccines (ChAdOx1 nCoV-19; Ad26.COV2-S). In this observational study, we followed VITT patients for changes in their reactivity of platelet-activating antiplatelet factor 4 (PF4) immunoglobulin G (IgG) antibodies by an anti-PF4/heparin IgG enzyme immunoassay (EIA) and a functional test for PF4-dependent, platelet-activating antibodies, and new thrombotic complications. Sixty-five VITT patients (41 females; median, 51 years; range, 18-80 years) were followed for a median of 25 weeks (range, 3-36 weeks). In 48/65 patients (73.8%; CI, 62.0% to 83.0%) the functional assay became negative. The median time to negative functional test result was 15.5 weeks (range, 5-28 weeks). In parallel, EIA optical density (OD) values decreased from median 3.12 to 1.52 (P < .0001), but seroreversion to a negative result was seen in only 14 (21.5%) patients. Five (7.5%) patients showed persistent platelet-activating antibodies and high EIA ODs for >11 weeks. None of the 29 VITT patients who received a second vaccination dose with an mRNA COVID-19 vaccine developed new thromboses or relevant increase in anti-PF4/heparin IgG EIA OD, regardless of whether PF4-dependent platelet-activating antibodies were still present. PF4-dependent platelet-activating antibodies are transient in most patients with VITT. VITT patients can safely receive a second COVID-19 mRNA-vaccine shot.

Understanding and managing uncertainty and variability for wastewater monitoring beyond the pandemic: Lessons learned from the United Kingdom national COVID-19 surveillance programmes.

The COVID-19 pandemic has put unprecedented pressure on public health resources around the world. From adversity, opportunities have arisen to measure the state and dynamics of human disease at a scale not seen before. In the United Kingdom, the evidence that wastewater could be used to monitor the SARS-CoV-2 virus prompted the development of National wastewater surveillance programmes. The scale and pace of this work has proven to be unique in monitoring of virus dynamics at a national level, demonstrating the importance of wastewater-based epidemiology (WBE) for public health protection. Beyond COVID-19, it can provide additional value for monitoring and informing on a range of biological and chemical markers of human health. A discussion of measurement uncertainty associated with surveillance of wastewater, focusing on lessons-learned from the UK programmes monitoring COVID-19 is presented, showing that sources of uncertainty impacting measurement quality and interpretation of data for public health decision-making, are varied and complex. While some factors remain poorly understood, we present approaches taken by the UK programmes to manage and mitigate the more tractable sources of uncertainty. This work provides a platform to integrate uncertainty management into WBE activities as part of global One Health initiatives beyond the pandemic.

Sublingual microcirculation predicts survival after out-of-hospital cardiac arrest.

BACKGROUND: Despite successful resuscitation with return of spontaneous circulation (ROSC), the prediction of survival in patients suffering out-of-hospital cardiac arrest (OHCA) remains difficult. Several studies have shown alterations in sublingual microcirculation in the critical ill. We hypothesized that early alterations in sublingual microcirculation may predict short-term survival after OHCA. METHODS: We prospectively included all adults admitted to our university hospital between April and September 2019 with ROSC following OHCA. Sidestream dark-field microscopy to obtain sublingual microcirculation was performed at admission and after 6, 12 and 24 hours. Primary outcome was survival until discharge. RESULTS: Twenty-five patients were included. Six hours after ROSC, the proportion of perfused small vessels (PPVsmall ) was lower in non-survivors than in survivors (85 ± 7.9 vs. 75 ± 6.6%; p = .01). PPVsmall did not correlate with serum lactate. Stratification for survival with cutoff values >78.4% for PPVsmall 6 h post-admission and <5.15 mmol/l for initial serum lactate as suggested by ROC-Analyses results in a positive predictive value of 100% and a negative one of 67% for our study population. CONCLUSION: Estimating short-term prognosis of OHCA patients with ROSC may be supported by measuring the PPVsmall at the sublingual microcirculation 6 hours after admission.

Inference of a universal social scale and segregation measures using social connectivity kernels.

How people connect with one another is a fundamental question in the social sciences, and the resulting social networks can have a profound impact on our daily lives. Blau offered a powerful explanation: people connect with one another based on their positions in a social space. Yet a principled measure of social distance, allowing comparison within and between societies, remains elusive. We use the connectivity kernel of conditionally independent edge models to develop a family of segregation statistics with desirable properties: they offer an intuitive and universal characteristic scale on social space (facilitating comparison across datasets and societies), are applicable to multivariate and mixed node attributes, and capture segregation at the level of individuals, pairs of individuals and society as a whole. We show that the segregation statistics can induce a metric on Blau space (a space spanned by the attributes of the members of society) and provide maps of two societies. Under a Bayesian paradigm, we infer the parameters of the connectivity kernel from 11 ego-network datasets collected in four surveys in the UK and USA. The importance of different dimensions of Blau space is similar across time and location, suggesting a macroscopically stable social fabric. Physical separation and age differences have the most significant impact on segregation within friendship networks with implications for intergenerational mixing and isolation in later stages of life.

[Early Childhood Intervention for Children of Parents with Mental Health Issues - Results of the Research Program of the National Center for Early Prevention]. / Frühe Hilfen für Kinder psychisch kranker Eltern ­ Forschungsergebnisse des Nationalen Zentrums Frühe Hilfen.

Early Childhood Intervention for Children of Parents with Mental Health Issues - Results of the Research Program of the National Center for Early Prevention In Germany, networks and measures of early childhood intervention (ECI) have been implemented nationwide. By specifically targeting families with multiple psychosocial challenges, ECI contributes to the enhancement of families' parenting skills, in order to promote equal opportunities for all children to grow up healthy and safe. In many families supported by ECI measures at least one parent shows symptoms of a mental health disorder, which poses a major challenge to ECI practitioners. Nevertheless, there is a lack of valid scientific knowledge about the proportion of young families living with symptoms of mental disorders, the degree to which parents' psychic burdens affect care in ECI measures and about the cooperation of different care providing systems. The National Center for Early Prevention (NCEP) monitors and evaluates the scaling up of ECI networks and measures in Germany. The present article compiles results of different NCEP studies focusing on parents with mental illness in Early Childhood Intervention. Results are discussed with regard to their relevance for further improving the care systems.

The Impact of Intraoperative Patient Blood Management on Quality Development in Cardiac Surgery.

OBJECTIVES: Patient blood management (PBM) is increasingly introduced into clinical practice. Minimizing effects on transfusion have been proven, but relevance for clinical outcome has been sparsely examined. In regard to this, the authors analyzed the impact of introducing intraoperative PBM to cardiac surgery. DESIGN: Retrospective case-control study. SETTING: Single center. PARTICIPANTS: A total of 3,170 patients who underwent either coronary artery bypass grafting, isolated aortic valve replacement, or a combined procedure at the authors' institution between January 1, 2007, and December 31, 2015. INTERVENTION: In 2013, an intraoperative PBM service was established offering therapy recommendations on the basis of real-time laboratory monitoring. Comparisons to conventional coagulation management were adjusted for optimization of general, surgical, and perioperative care standards by interrupted time-series analysis and risk-dependent confounding by propensity- score matching. MEASUREMENTS AND MAIN RESULTS: Primary study endpoints were in-hospital mortality and morbidity. Morbidity was defined as clinically relevant prolongation of hospital stay, which was related to accumulation of postoperative complications. Transfusion requirements, bleeding, and thromboembolic complications were not treated as primary endpoints, but were also explored. The recommendations on the basis of real-time laboratory monitoring were adopted by the operative team in 72% of patients. Intraoperative PBM was associated independently with a reduction of morbidity (8.3% v 6.3%, p = 0.034), whereas in-hospitalmortality (3.0% v 2.6%, p = 0.521) remained unaffected. The need for red blood cell transfusion decreased (71.1% v 65.0%, p < 0.001), as did bleeding complications requiring surgical re-exploration (3.5% v 1.8%, p = 0.004). At the same time, stroke increased by statistical trend (1.0% v 1.9%, p = 0.038; after correction for imbalanced type of surgical procedure p = 0.085). CONCLUSIONS: Real-time laboratory recommendations achieved a high acceptance rate early after initiation. Improvement of clinical outcome by intraoperative PBM adds to the optimized surgical care. However, the corridor between hemostatic optimization and thromboembolic risk may be narrow.

Fibrinolysis and the Influence of Tranexamic Acid Dosing in Cardiac Surgery.

OBJECTIVE: The present study aimed to determine whether underlying disease, performed surgery, and dose of tranexamic acid influence fibrinolysis measured with D-dimer levels. DESIGN: Retrospective analysis. SETTING: Single institution (Department of Cardiac Surgery and Section of Clinical Hemostaseology at the Düsseldorf University Hospital). PARTICIPANTS: The study comprised 3,152 adult patients undergoing elective cardiac surgery between February 2013 and October 2016. INTERVENTIONS: Two doses of tranexamic acid during surgery were administered. MEASUREMENTS AND MAIN RESULTS: D-dimer levels were analyzed at the start of surgery and before protamine administration. D-dimer levels at the start of surgery were compared according to disease. Intraoperative D-dimer development was analyzed according to the type of surgery and within 2 cohorts with different tranexamic acid doses. Interindividual variability was pronounced for D-dimer levels at the start of surgery, with significant differences among patients with coronary artery disease, valve disease, and aortic disease and patients undergoing heart transplantation compared with patients receiving a left ventricular assist device (p < 0.01). Aortic dissection, endocarditis, and extracorporeal life support were associated with higher D-dimer levels (p ≤ 0.01). With tranexamic acid at a fixed dose, intraoperative D-dimer levels decreased in on-pump and off-pump coronary bypass surgery, valve surgery, and left ventricular assist device surgery (p ≤ 0.02), but levels increased in aortic surgery and heart transplantations (p < 0.01). A decrease or increase in D-dimer levels during surgery was influenced significantly by a higher or lower tranexamic acid dose (p ≤ 0.01). CONCLUSIONS: D-dimer testing allows for the assessment of individual fibrinolytic activity in cardiac surgery, which is influenced by disease type, surgery type, and dose of tranexamic acid. The assessment of the fibrinolytic status may have the potential to facilitate dose-adjusted antifibrinolytic therapy in the future.

Community detection in networks without observing edges.

We develop a Bayesian hierarchical model to identify communities of time series. Fitting the model provides an end-to-end community detection algorithm that does not extract information as a sequence of point estimates but propagates uncertainties from the raw data to the community labels. Our approach naturally supports multiscale community detection and the selection of an optimal scale using model comparison. We study the properties of the algorithm using synthetic data and apply it to daily returns of constituents of the S&P100 index and climate data from U.S. cities.

Rivaroxaban Reduces Arterial Thrombosis by Inhibition of FXa-Driven Platelet Activation via Protease Activated Receptor-1.

RATIONALE: A reduced rate of myocardial infarction has been reported in patients with atrial fibrillation treated with FXa (factor Xa) inhibitors including rivaroxaban compared with vitamin K antagonists. At the same time, low-dose rivaroxaban has been shown to reduce mortality and atherothrombotic events in patients with coronary artery disease. Yet, the mechanisms underlying this reduction remain unknown. OBJECTIVE: In this study, we hypothesized that rivaroxaban's antithrombotic potential is linked to a hitherto unknown rivaroxaban effect that impacts on platelet reactivity and arterial thrombosis. METHODS AND RESULTS: In this study, we identified FXa as potent, direct agonist of the PAR-1 (protease-activated receptor 1), leading to platelet activation and thrombus formation, which can be inhibited by rivaroxaban. We found that rivaroxaban reduced arterial thrombus stability in a mouse model of arterial thrombosis using intravital microscopy. For in vitro studies, atrial fibrillation patients on permanent rivaroxaban treatment for stroke prevention, respective controls, and patients with new-onset atrial fibrillation before and after first intake of rivaroxaban (time series analysis) were recruited. Platelet aggregation responses, as well as thrombus formation under arterial flow conditions on collagen and atherosclerotic plaque material, were attenuated by rivaroxaban. We show that rivaroxaban's antiplatelet effect is plasma dependent but independent of thrombin and rivaroxaban's anticoagulatory capacity. CONCLUSIONS: Here, we identified FXa as potent platelet agonist that acts through PAR-1. Therefore, rivaroxaban exerts an antiplatelet effect that together with its well-known potent anticoagulatory capacity might lead to reduced frequency of atherothrombotic events and improved outcome in patients.

Precision identification of high-risk phenotypes and progression pathways in severe malaria without requiring longitudinal data.

More than 400,000 deaths from severe malaria (SM) are reported every year, mainly in African children. The diversity of clinical presentations associated with SM indicates important differences in disease pathogenesis that require specific treatment, and this clinical heterogeneity of SM remains poorly understood. Here, we apply tools from machine learning and model-based inference to harness large-scale data and dissect the heterogeneity in patterns of clinical features associated with SM in 2904 Gambian children admitted to hospital with malaria. This quantitative analysis reveals features predicting the severity of individual patient outcomes, and the dynamic pathways of SM progression, notably inferred without requiring longitudinal observations. Bayesian inference of these pathways allows us assign quantitative mortality risks to individual patients. By independently surveying expert practitioners, we show that this data-driven approach agrees with and expands the current state of knowledge on malaria progression, while simultaneously providing a data-supported framework for predicting clinical risk.