Plasma immune signatures can predict rejection-free survival in the first year after pediatric liver transplantation.

BACKGROUND & AIMS: After pediatric liver transplantation (pLT), children undergo life-long immunosuppression since reliable biomarkers for the assessment of rejection probability are scarce. In the multicentre (n=7) prospective clinical cohort "ChilSFree" study, we aimed to characterize longitudinal dynamics of soluble and cellular immune mediators during the first year after pLT and identify early biomarkers associated with outcome. METHODS: Using paired Luminex-based multiplex technique and flow cytometry, we characterized longitudinal dynamics of soluble immune mediators (SIM, n=50) and immune cells in the blood of 244 patients at 8 visits over one year: before, 7/14/21/28 days, 3/6/12 months after pLT. RESULTS: The unsupervised clustering of patients based on SIM profiles revealed 6 unique SIM signatures associated with clinical outcome. From 3 signatures linked to improved outcome, one was associated with one-year-long rejection-free survival and stable graft function and was characterized by low levels of pro-inflammatory (CXCL8/9/10/12, CCL7, SCGF-ß, sICAM-1), high levels of regenerative (SCF, TNF-ß), and pro-apoptotic (TRAIL) SIM (all, p<0.001, fold change >100). Of note, this SIM signature appeared two weeks after pLT and remained stable over the entire year, pointing towards its potential as a novel early biomarker for minimizing or weaning immunosuppression. In the blood of these patients, a higher frequency of CD56bright NK cells (p<0.01), a known hallmark also associated with operationally tolerant pLT patients, was detected. The concordance of the model for prediction of rejection based on identified SIM signatures was 0.715, and 0.795, in combination with living-related transplantation as co-variate, respectively. CONCLUSIONS: SIM blood signatures may enable the non-invasive and early assessment of rejection risks in the first year after pLT, paving the way to improved therapeutic options.

Diagnostic test accuracy in longitudinal study settings: theoretical approaches with use cases from clinical practice.

OBJECTIVES: In this study, we evaluate how to estimate diagnostic test accuracy (DTA) correctly in the presence of longitudinal patient data (ie, repeated test applications per patient). STUDY DESIGN AND SETTING: We used a nonparametric approach to estimate the sensitivity and specificity of three tests for different target conditions with varying characteristics (ie, episode length and disease-free intervals between episodes): 1) systemic inflammatory response syndrome (n = 36), 2) depression (n = 33), and 3) epilepsy (n = 30). DTA was estimated on the levels 'time', 'block', and 'patient-time' for each diagnosis, representing different research questions. The estimation was conducted for the time units per minute, per hour, and per day. RESULTS: A comparison of DTA per and across use cases showed variations in the estimates, which resulted from the used level, the time unit, the resulting number of observations per patient, and the diagnosis-specific characteristics. Intra- and inter-use-case comparisons showed that the time-level had the highest DTA, particularly the larger the time unit, and that the patient-time-level approximated 50% sensitivity and specificity. CONCLUSION: Researchers need to predefine their choices (ie, estimation levels and time units) based on their individual research aims, estimands, and diagnosis-specific characteristics of the target outcomes to make sure that unbiased and clinically relevant measures are communicated. In cases of uncertainty, researchers could report the DTA of the test using more than one estimation level and/or time unit.

Salivary biomarkers for early detection of oral squamous cell carcinoma (OSCC) and head/neck squamous cell carcinoma (HNSCC): A systematic review and network meta-analysis.

Oral cancer became a very common condition. WHO estimates that there are 4 cases of lip and oral cavity cancer for every 100,000 people worldwide. The early diagnosis of cancers is currently a top focus in the health sector. Recent systematic reviews and meta-analyses have identified promising biomarkers for early detection in several original research investigations. However, it is still unclear the quality of these evidence and which biomarker performs the best in terms of early detection. Therefore, the objective was, to map the methodological and reporting quality of available oral squamous cell carcinoma (OSCC) or head/neck squamous cell carcinoma (HNSCC) systematic reviews and meta-analysis. Secondly, to evaluate diagnostic accuracy of salivary biomarkers for common craniofacial cancers and to compare the diagnostic value of different salivary biomarkers. PubMed, Scopus, Web of Science, Embase and Cochrane Library electronic databases were used to map the methodological and reporting quality of the systematic reviews and meta-analysis conducted on the HNSCC, OSCC using the AMSTAR-2 checklist. The inclusion criteria were systematic reviews and meta-analysis published in the topic of HNSCC and OSCC biomarkers. Exclusion criteria were no animal studies; original primary studies, due to limitation of competency in other languages articles with language other than English were excluded. The sensitivity and specificity were calculated for salivary biomarkers and ranked according to network meta-analysis principles. A total of N = 5893 patients were included from four meta-analysis studies. All together, these included n = 37 primary studies. n = 94 biomarkers were pooled from these four meta-analyses and categorised into the stages at which they were detected (I-IV). In OSCC, Chemerin and MMP-9 displayed the highest sensitivity, registering 0.94 (95% CI 0.78, 1.00) and a balanced accuracy of 0.93. Phytosphingosine closely followed, with a sensitivity of 0.91 (95% CI 0.68, 0.99) and a balanced accuracy of 0.87. For HNSCC, the top three biomarkers are Actin, IL-1ß Singleplex, and IL-8 ELISA. Actin leads with a sensitivity of 0.91 (95% CI 0.68-0.99), a specificity of 0.67, and an overall accuracy of 0.79. Subsequently, IL-1ß Singleplex exhibits a sensitivity of 0.62 (95% CI 0.30-0.88), a specificity of 0.89, and an accuracy of 0.75, followed by IL-8 ELISA with a sensitivity of 0.81 (95% CI 0.54-0.97), a specificity of 0.59, and an accuracy of 0.70. In conclusion, there was highest sensitivity for MMP-9 and chemerin salivary biomarkers. There is need of further more studies to identify biomarkers for HNSCC and OSCC.

The impact of inaccurate assumptions about antibody test accuracy on the parametrisation and results of infectious disease models of epidemics.

The parametrisation of infectious disease models is often done based on epidemiological studies that use diagnostic and serology tests to establish disease prevalence or seroprevalence in the population being modelled. During outbreaks of an emerging infectious disease, tests are often used, both for disease control and epidemiological studies, before studies evaluating their accuracy in the population have concluded, with assumptions made about accuracy parameters like sensitivity and specificity. In this simulation study, we simulated such an outbreak, based on the case study of COVID-19, and found that inaccurate parametrisation of infectious disease models due to assumptions about antibody test accuracy in a seroprevalence study can cause modelling results that inform public health decisions to be inaccurate; for example, in our simulation setup, assuming that antibody test specificity was 0.99 instead of 0.90 when it was in fact 0.90 led to an average relative difference of 0.78 in model-projected peak hospitalisations, even when test sensitivity and all other parameters were accurately characterised. We therefore suggest that methods to speed up test evaluation studies are vitally important in the public health response to an emerging outbreak.

Estimates of protection levels against SARS-CoV-2 infection and severe COVID-19 in Germany before the 2022/2023 winter season: the IMMUNEBRIDGE project.

PURPOSE: Despite the need to generate valid and reliable estimates of protection levels against SARS-CoV-2 infection and severe course of COVID-19 for the German population in summer 2022, there was a lack of systematically collected population-based data allowing for the assessment of the protection level in real time. METHODS: In the IMMUNEBRIDGE project, we harmonised data and biosamples for nine population-/hospital-based studies (total number of participants n = 33,637) to provide estimates for protection levels against SARS-CoV-2 infection and severe COVID-19 between June and November 2022. Based on evidence synthesis, we formed a combined endpoint of protection levels based on the number of self-reported infections/vaccinations in combination with nucleocapsid/spike antibody responses ("confirmed exposures"). Four confirmed exposures represented the highest protection level, and no exposure represented the lowest. RESULTS: Most participants were seropositive against the spike antigen; 37% of the participants ≥ 79 years had less than four confirmed exposures (highest level of protection) and 5% less than three. In the subgroup of participants with comorbidities, 46-56% had less than four confirmed exposures. We found major heterogeneity across federal states, with 4-28% of participants having less than three confirmed exposures. CONCLUSION: Using serological analyses, literature synthesis and infection dynamics during the survey period, we observed moderate to high levels of protection against severe COVID-19, whereas the protection against SARS-CoV-2 infection was low across all age groups. We found relevant protection gaps in the oldest age group and amongst individuals with comorbidities, indicating a need for additional protective measures in these groups.

Early steroids after pediatric liver transplantation protect against T-cell-mediated rejection: Results from the ChilSFree study.

Steroid-free immunosuppression protocols gained popularity in pediatric liver transplantation (pLT) after the introduction of IL-2-receptor blockade for induction therapy. We analyzed the clinical and immunologic outcome data of the multicenter prospective observational ChilSFree study to compare the impact of steroid-free versus steroid-containing immunosuppressive therapy following pLT in a real-life scenario. Two hundred forty-six children [55.3% male, age at pLT median: 2.4 (range: 0.2-17.9) y] transplanted for biliary atresia (43%), metabolic liver disease (9%), acute liver failure (4%), hepatoblastoma (9%), and other chronic end-stage liver diseases (39%) underwent immune monitoring and clinical data documentation over the first year after pLT. Patient and graft survival at 1 year was 98.0% and 92.7%, respectively. Primary immunosuppression was basiliximab induction followed by tacrolimus (Tac) monotherapy (55%), Tac plus steroid tapering over 3 months (29%), or cyclosporine and steroid tapering (7%). One center used intraoperative steroids instead of basiliximab followed by Tac plus mycophenolate mofetil (7% of patients). N = 124 biopsy-proven T-cell-mediated rejections were documented in n = 82 (33.3%) patients. T-cell-mediated rejection occurred early (median: 41 d, range: 3-366 d) after pLT. Patients initially treated with Tac plus steroids experienced significantly fewer episodes of rejection than patients treated with Tac alone (chi-square p <0.01). The use of steroids was associated with earlier downregulation of proinflammatory cytokines interferon (IFN)-γ, Interleukin (IL)-6, CX motif chemokin ligand (CXCL)8, IL-7, and IL-12p70. Both primary immunosuppression with Tac plus steroids and living donor liver transplantation were independent predictors of rejection-free survival 1 year after pLT on logistic regression analysis. Adjunctive steroid therapy after pLT leads to earlier suppression of the post-pLT proinflammatory response and significantly reduced rejection rates during the first year after pLT (15.9%). Fifty-one percent of patients initially treated without steroids remain steroid-free over the first 12 months without rejection.

Effect of risk status for severe COVID-19 on individual contact behaviour during the SARS-CoV-2 pandemic in 2020/2021-an analysis based on the German COVIMOD study.

BACKGROUND: One of the primary aims of contact restriction measures during the SARS-CoV-2 pandemic has been to protect people at increased risk of severe disease from the virus. Knowledge about the uptake of contact restriction measures in this group is critical for public health decision-making. We analysed data from the German contact survey COVIMOD to assess differences in contact patterns based on risk status, and compared this to pre-pandemic data to establish whether there was a differential response to contact reduction measures. METHODS: We quantified differences in contact patterns according to risk status by fitting a generalised linear model accounting for within-participant clustering to contact data from 31 COVIMOD survey waves (April 2020-December 2021), and estimated the population-averaged ratio of mean contacts of persons with high risk for a severe COVID-19 outcome due to age or underlying health conditions, to those without. We then compared the results to pre-pandemic data from the contact surveys HaBIDS and POLYMOD. RESULTS: Averaged across all analysed waves, COVIMOD participants reported a mean of 3.21 (95% confidence interval (95%CI) 3.14,3.28) daily contacts (truncated at 100), compared to 18.10 (95%CI 17.12,19.06) in POLYMOD and 28.27 (95%CI 26.49,30.15) in HaBIDS. After adjusting for confounders, COVIMOD participants aged 65 or above had 0.83 times (95%CI 0.79,0.87) the number of contacts as younger age groups. In POLYMOD, this ratio was 0.36 (95%CI 0.30,0.43). There was no clear difference in contact patterns due to increased risk from underlying health conditions in either HaBIDS or COVIMOD. We also found that persons in COVIMOD at high risk due to old age increased their non-household contacts less than those not at such risk after strict restriction measures were lifted. CONCLUSIONS: Over the course of the SARS-CoV-2 pandemic, there was a general reduction in contact numbers in the German population and also a differential response to contact restriction measures based on risk status for severe COVID-19. This differential response needs to be taken into account for parametrisations of mathematical models in a pandemic setting.

Gut microbiota dysbiosis in Parkinson disease: A systematic review and pooled analysis.

BACKGROUND AND PURPOSE: The role of the gut microbiome in the pathogenesis of Parkinson disease (PD) is under intense investigation, and the results presented are still very heterogeneous. These discrepancies arise not only from the highly heterogeneous pathology of PD, but also from widely varying methodologies at all stages of the workflow, from sampling to final statistical analysis. The aim of the present work is to harmonize the workflow across studies to reduce the methodological heterogeneity and to perform a pooled analysis to account for other sources of heterogeneity. METHODS: We performed a systematic review to identify studies comparing the gut microbiota of PD patients to healthy controls. A workflow was designed to harmonize processing across all studies from bioinformatics processing to final statistical analysis using a Bayesian random-effects meta-analysis based on individual patient-level data. RESULTS: The results show that harmonizing workflows minimizes differences between statistical methods and reveals only a small set of taxa being associated with the pathogenesis of PD. Increased shares of the genera Akkermansia and Bifidobacterium and decreased shares of the genera Roseburia and Faecalibacterium were most characteristic for PD-associated microbiota. CONCLUSIONS: Our study summarizes evidence that reduced levels of butyrate-producing taxa in combination with possible degradation of the mucus layer by Akkermansia may promote intestinal inflammation and reduced permeability of the gut mucosal layer. This may allow potentially pathogenic metabolites to transit and enter the enteric nervous system.

Diagnosing Acute Cellular Rejection after Paediatric Liver Transplantation-Is There Room for Interleukin Profiles?

BACKGROUND: The current gold standard to diagnose T-cell-mediated acute rejection (TCMR) requires liver histology. Using data from the ChilSFree study on immune response after paediatric liver transplantation (pLT), we aimed to assess whether soluble cytokines can serve as an alternative diagnostic tool in children suspected to have TCMR. METHODS: A total of n = 53 blood samples obtained on the day of or up to 3 days before liver biopsy performed for suspected TCMR at median 18 days (range 7-427) after pLT in n = 50 children (38% female, age at pLT 1.8 (0.5-17.5) years) were analysed for circulating cytokine levels using Luminex-based Multiplex technology. Diagnostic accuracy of cytokine concentrations was assessed using a multivariable model based on elastic net regression and gradient boosting machine analysis. RESULTS: TCMR was present in 68% of biopsies. There was strong evidence that patients with TCMR had increased levels of soluble CXCL8, CXCL9, CXCL10, IL-16, IL-18, HGF, CCL4, MIF, SCGF-ß, and HGF before biopsy. There was some evidence for increased levels of sCD25, ICAM-1, IL-6, IL-3, and CCL11. Diagnostic value of both single cytokine levels and a combination of cytokines and clinical markers was poor, with AUROCs not exceeding 0.7. CONCLUSION: Patients with TCMR showed raised levels of cytokines and chemokines reflective of T-cell activation and chemotaxis. Despite giving insight into the mechanisms of TCMR, the diagnostic value of soluble cytokines for the confirmation of TCMR in a clinical scenario of suspected TCMR is poor.

Major depressive disorders increase the susceptibility to self-reported infections in two German cohort studies.

INTRODUCTION: In several claims-based studies, major depressive disorder (MDD) has been associated with increased risk of hospitalization due to acute infections. It remains unclear if this is a causal effect, and if it generalizes to an increased susceptibility to infections. METHODS: We used data of the BiDirect (n = 925) and the HaBIDS (n = 1007) cohort studies to estimate the effect of MDD on self-reported infections, which were assessed with identical infection susceptibility questionnaires in both studies. We used the Center for Epidemiologic Studies Depression Scale (CES-D) to examine if there was a dose-response relationship between depressive symptom severity and self-reported infections. RESULTS: BiDirect participants with MDD diagnosis (48%) had a higher risk of lower respiratory tract infections (incidence rate ratio 1.32, 95% confidence interval [1.00-1.75]), gastrointestinal infections (1.68 [1.30-2.16]) and fever (1.48 [1.11-1.98]) after adjusting for confounders identified by a directed acyclic graph approach. There was a dose-response relationship, i.e. individuals with higher CES-D scores reported more infections. Effect sizes were similar in HaBIDS (4% individuals with MDD). CONCLUSION: We found increased risks of mild infections in patients with MDD diagnosis and a dose-response relationship between depressive symptom severity and infection frequency. While causal immunological pathways remain unclear, the results of our study might contribute to a change in prevention strategies, e.g. by recommending vaccination against influenza and S. pneumoniae to MDD patients because observed effect sizes in our study are similar to those of patients with cardiovascular and metabolic diseases for which the respective vaccinations are recommended.

Systematic review identifies deficiencies in reporting of diagnostic test accuracy among clinical decision support systems.

OBJECTIVES: This systematic review assesses the reporting quality and risk of bias in studies evaluating the diagnostic test accuracy (DTA) of clinical decision support systems (CDSS). STUDY DESIGN AND SETTING: The Cochrane Library, PubMed/MEDLINE, Scopus, and Web of Science were searched for studies, published between January 1, 2016 and May 31, 2021, evaluating the DTA of CDSS for human patients. Articles using a patient's self-diagnosis, assessing disease severity, focusing on treatment/follow-up, or comparing pre-post CDSS implementation periods were excluded. All eligible studies were assessed for reporting quality using STARD 2015 and for risk of bias using QUADAS-2. Item ratings were presented using heat maps. This study was reported as per PRISMA-DTA. RESULTS: In total, 158 of 2,820 screened articles were included in the analysis. The studies were heterogeneous in terms of study characteristics, reporting quality, risk of biases, and applicability concerns with few highly rated studies. Mostly the overall quality was deficient for items addressing the domains 'methodology,' 'results,' and 'other information'. CONCLUSION: Our analysis revealed shortcomings in critical domains of reporting quality and risk of bias, indicating the need for additional guidance and training in an interdisciplinary scientific field with mixed biostatistical expertise.

High-sensitivity troponin I with or without ultra-sensitive copeptin for the instant rule-out of acute myocardial infarction.

Background: The instant, single-sampling rule-out of acute myocardial infarction (AMI) is still an unmet clinical need. We aimed at testing and comparing diagnostic performance and prognostic value of two different single-sampling biomarker strategies for the instant rule-out of AMI. Methods: From the Biomarkers in Acute Cardiac Care (BACC) cohort, we recruited consecutive patients with acute chest pain and suspected AMI presenting to the Emergency Department of the University Medical Center Hamburg-Eppendorf, Hamburg, Germany. We compared safety, effectiveness and 12-month incidence of the composite endpoint of all-cause death and myocardial infarction between (i) a single-sampling, dual-marker pathway combining high-sensitivity cardiac troponin I (hs-cTnI) and ultra-sensitive copeptin (us-Cop) at presentation (hs-cTnI ≤ 27 ng/L, us-Cop < 10 pmol/L and low-risk ECG) and (ii) a single-sampling pathway based on one-off hs-cTnI determination at presentation (hs-cTnI < 5 ng/L and low-risk ECG). As a comparator, we used the European Society of Cardiology (ESC) 0/1-h dual-sampling algorithm. Results: We enrolled 1,136 patients (male gender 65%) with median age of 64 years (interquartile range, 51-75). Overall, 228 (20%) patients received a final diagnosis of AMI. The two single-sampling instant rule-out pathways yielded similar negative predictive value (NPV): 97.4% (95%CI: 95.4-98.7) and 98.7% (95%CI: 96.9-99.6) for dual-marker and single hs-cTnI algorithms, respectively (P = 0.11). Both strategies were comparably safe as the ESC 0/1-h dual-sampling algorithm and this was consistent across subgroups of early-comers, low-intermediate risk (GRACE-score < 140) and renal dysfunction. Despite a numerically higher rate of false-negative results, the dual-marker strategy ruled-out a slightly but significantly higher percentage of patients compared with single hs-cTnI determination (37.4% versus 32.9%; P < 0.001). There were no significant between-group differences in 12-month composite outcome. Conclusions: Instant rule-out pathways based on one-off determination of hs-cTnI alone or in combination with us-Cop are comparably safe as the ESC 0/1 h algorithm for the instant rule-out of AMI, yielding similar prognostic information. Instant rule-out strategies are safe alternatives to the ESC 0/1 h algorithm and allow the rapid and effective triage of suspected AMI in patients with low-risk ECG. However, adding copeptin to hs-cTn does not improve the safety of instant rule-out compared with the single rule-out hs-cTn at very low cut-off concentrations.

A Method to Combine Neurofilament Light Measurements From Blood Serum and Plasma in Clinical and Population-Based Studies.

Introduction: Neurofilament light (NfL) can be detected in blood of healthy individuals and at elevated levels in those with different neurological diseases. We investigated if the choice of biological matrix can affect results when using NfL as biomarker in epidemiological studies. Method: We obtained paired serum and EDTA-plasma samples of 299 individuals aged 37-67 years (BiDirect study) and serum samples of 373 individuals aged 65-83 years (MEMO study). In BiDirect, Passing-Bablok analyses were performed to assess proportional and systematic differences between biological matrices. Associations between serum or EDTA-plasma NfL and renal function (serum creatinine, serum cystatin C, glomerular filtration rate, and kidney disease) were investigated using linear or logistic regression, respectively. All regression coefficients were estimated (1) per one ng/L increase and (2) per one standard deviation increase (standardization using z-scores). In MEMO, regression coefficients were estimated (1) per one ng/L increase of serum or calculated EDTA-plasma NfL and (2) per one standard deviation increase providing a comparison to the results from BiDirect. Results: We found proportional and systematic differences between paired NfL measurements in BiDirect, i.e., serum NfL [ng/L] = -0.33 [ng/L] + 1.11 × EDTA-plasma NfL [ng/L]. Linear regression coefficients for the associations between NfL and renal function did not vary between the different NfL measurements. In MEMO, one standard deviation increase in serum NfL was associated with greater changes in the outcomes than in BiDirect. Conclusion: Although there are differences between serum and EDTA-plasma NfL, results can be used interchangeably if standardized values are used.

Development and Validation of Prediction Models for Severe Complications After Acute Ischemic Stroke: A Study Based on the Stroke Registry of Northwestern Germany.

Background The treatment of stroke has been undergoing rapid changes. As treatment options progress, prediction of those under risk for complications becomes more important. Available models have, however, frequently been built based on data no longer representative of today's care, in particular with respect to acute stroke management. Our aim was to build and validate prediction models for 4 clinically important, severe outcomes after stroke. Methods and Results We used German registry data from 152 710 patients with acute ischemic stroke obtained in 2016 (development) and 2017 (validation). We took into account potential predictors that were available at admission and focused on in-hospital mortality, intracranial mass effect, secondary intracerebral hemorrhage, and deep vein thrombosis as outcomes. Validation cohort prediction and calibration performances were assessed using the following 4 statistical approaches: logistic regression with backward selection, l1-regularized logistic regression, k-nearest neighbor, and gradient boosting classifier. In-hospital mortality and intracranial mass effects could be predicted with high accuracy (both areas under the curve, 0.90 [95% CI, 0.90-0.90]), whereas the areas under the curve for intracerebral hemorrhage (0.80 [95% CI, 0.80-0.80]) and deep vein thrombosis (0.73 [95% CI, 0.73-0.73]) were considerably lower. Stroke severity was the overall most important predictor. Models based on gradient boosting achieved better performances than those based on logistic regression for all outcomes. However, area under the curve estimates differed by a maximum of 0.02. Conclusions We validated prediction models for 4 severe outcomes after acute ischemic stroke based on routinely collected, recent clinical data. Model performance was superior to previously proposed approaches. These predictions may help to identify patients at risk early after stroke and thus facilitate an individualized level of care.

Providing laypeople with results from dynamic infectious disease modelling studies affects their allocation preference for scarce medical resources-a factorial experiment.

BACKGROUND: Allocation of scarce medical resources can be based on different principles. It has not yet been investigated which allocation schemes are preferred by medical laypeople in a particular situation of medical scarcity like an emerging infectious disease and how the choices are affected by providing information about expected population-level effects of the allocation scheme based on modelling studies. We investigated the potential benefit of strategic communication of infectious disease modelling results. METHODS: In a two-way factorial experiment (n = 878 participants), we investigated if prognosis of the disease or information about expected effects on mortality at population-level (based on dynamic infectious disease modelling studies) influenced the choice of preferred allocation schemes for prevention and treatment of an unspecified sexually transmitted infection. A qualitative analysis of the reasons for choosing specific allocation schemes supplements our results. RESULTS: Presence of the factor "information about the population-level effects of the allocation scheme" substantially increased the probability of choosing a resource allocation system that minimized overall harm among the population, while prognosis did not affect allocation choices. The main reasons for choosing an allocation scheme differed among schemes, but did not differ among those who received additional model-based information on expected population-level effects and those who did not. CONCLUSIONS: Providing information on the expected population-level effects from dynamic infectious disease modelling studies resulted in a substantially different choice of allocation schemes. This finding supports the importance of incorporating model-based information in decision-making processes and communication strategies.

Symptom Burden and Factors Associated with Acute Respiratory Infections in the First Two Years of Life-Results from the LoewenKIDS Cohort.

Acute respiratory infections (ARIs) are the most common childhood illnesses worldwide whereby the reported frequency varies widely, often depending on type of assessment. Symptom diaries are a powerful tool to counteract possible under-reporting, particularly of milder infections, and thus offer the possibility to assess the full burden of ARIs. The following analyses are based on symptom diaries from participants of the German birth cohort study LoewenKIDS. Primary analyses included frequencies of ARIs and specific symptoms. Factors, which might be associated with an increased number of ARIs, were identified using the Poisson regression. A subsample of two hundred eighty-eight participants were included. On average, 13.7 ARIs (SD: 5.2 median: 14.0 IQR: 10-17) were reported in the first two years of life with an average duration of 11 days per episode (SD: 5.8, median: 9.7, IQR: 7-14). The median age for the first ARI episode was 91 days (IQR: 57-128, mean: 107, SD: 84.5). Childcare attendance and having siblings were associated with an increased frequency of ARIs, while exclusive breastfeeding for the first three months was associated with less ARIs, compared to exclusive breastfeeding for a longer period. This study provides detailed insight into the symptom burden of ARIs in German infants.

Richness estimation in microbiome data obtained from denoising pipelines.

The quantification of richness within a sample-either measured as the number of observed species or approximated by estimation-is a common first step in microbiome studies and is known to be highly dependent on sequencing depth, which itself is highly variable between samples. Rarefaction curves serve as a tool to investigate this dependency and it is often argued that after rarefying data-sub-sampling to an equal sequencing depth-richness estimates no longer depend on sequencing depth. However, the estimation of richness from data obtained by high throughput sequencing methods and processed by current bioinformatics pipelines may be subject to various sources of variation related to sequencing depth. Those that may confound inference based on richness estimates and cannot be solved by sub-sampling. We investigated how pipeline settings in DADA2 and deblur affect estimates of richness and showed that the use of rarefaction and sub-sampling is inappropriate when default pipeline settings are applied. Furthermore, we showed how independent sample-wise processing established spurious correlations between sequencing depth and richness estimations in data produced by DADA2 and how this problem can be solved by a pooled processing approach.

Diagnostic accuracy of cerebrospinal fluid biomarkers for the differential diagnosis of sporadic Creutzfeldt-Jakob disease: a (network) meta-analysis.

BACKGROUND: There are no systematic reviews of cerebrospinal fluid and blood biomarkers for sporadic Creutzfeldt-Jakob disease (sCJD) in specialized care settings that compare diagnostic accuracies in a network meta-analysis (NMA). METHODS: We searched Medline, Embase, and Cochrane Library for diagnostic studies of sCJD biomarkers. Studies had to use established diagnostic criteria for sCJD and for diseases in the non-CJD groups, which had to represent a consecutive population of patients suspected as a CJD case, as reference standard. Risk of bias was assessed with QUADAS-2. We conducted individual biomarker meta-analyses with generalized bivariate models. To investigate heterogeneity, we performed subgroup analyses based on QUADAS-2 quality and clinical criteria. For the NMA, we applied a Bayesian beta-binomial ANOVA model. The study protocol was registered at PROSPERO (CRD42019118830). RESULTS: Of 2976 publications screened, we included 16 studies, which investigated 14-3-3ß (n = 13), 14-3-3γ (n = 3), neurofilament light chain (NfL, n = 1), neuron-specific enolase (n = 1), p-tau181/t-tau ratio (n = 2), RT-QuIC (n = 7), S100B (n = 3), t-tau (n = 12), and t-tau/Aß42 ratio (n = 1). Excluded diagnostic studies had strong limitations in study design. In the NMA, RT-QuIC (0.91; 95% CI [0.83, 0.95]) and NfL (0.93 [0.78, 0.99]) were the most sensitive biomarkers for the diagnosis of definite, probable, and possible sCJD cases. RT-QuIC was the most specific biomarker (0.97 [0.89, 1.00]). Heterogeneity in accuracy estimates was high between studies. CONCLUSIONS: We identified RT-QuIC as the most accurate biomarker, partially confirming currently applied diagnostic criteria. The shortcomings identified in many diagnostic studies for sCJD biomarkers need to be addressed in future studies.

Prediction models for SIRS, sepsis and associated organ dysfunctions in paediatric intensive care: study protocol for a diagnostic test accuracy study.

INTRODUCTION: Systemic inflammatory response syndrome (SIRS), sepsis and associated organ dysfunctions are life-threating conditions occurring at paediatric intensive care units (PICUs). Early recognition and treatment within the first hours of onset are critical. However, time pressure, lack of personnel resources, and the need for complex age-dependent diagnoses impede an accurate and timely diagnosis by PICU physicians. Data-driven prediction models integrated in clinical decision support systems (CDSS) could facilitate early recognition of disease onset. OBJECTIVES: To estimate the sensitivity and specificity of previously developed prediction models (index tests) for the detection of SIRS, sepsis and associated organ dysfunctions in critically ill children up to 12 hours before reference standard diagnosis is possible. METHODS AND ANALYSIS: We conduct a monocentre, prospective diagnostic test accuracy study. Clinicians in the PICU of the tertiary care centre Hannover Medical School, Germany, continuously screen and recruit patients until the adaptive sample size (originally intended sample size of 500 patients) is enrolled. Eligible are children (0-17 years, all sexes) who stay in the PICU for ≥12 hours and for whom an informed consent is given. All eligible patients are independently assessed for SIRS, sepsis and organ dysfunctions using corresponding predictive and knowledge-based CDSS models. The knowledge-based CDSS models serve as imperfect reference standards. The assessments are used to estimate the sensitivities and specificities of each predictive model using a clustered nonparametric approach (main analysis). Subgroup analyses ('age groups', 'sex' and 'age groups by sex') are predefined. ETHICS AND DISSEMINATION: This study obtained ethics approval from the Hannover Medical School Ethics Committee (No. 10188_BO_SK_2022). Results will be disseminated as peer-reviewed publications, at scientific conferences, and to patients in an appropriate dissemination approach. TRIAL REGISTRATION NUMBER: This study was registered with the German Clinical Trial Register (DRKS00029071) on 2022-05-23. PROTOCOL VERSION: 10188_BO_SK_2022_V.2.0-20220330_4_Studienprotokoll.