Enhancing the Retinopathy Of Prematurity Risk Profile Through Placental Evaluation of Maternal and Fetal Vascular Malperfusion.

Purpose: To determine the independent effect of uteroplacental malperfusion on the development of retinopathy of prematurity (ROP). Methods: This cohort study included 591 neonates with a gestational age (GA) ≤ 32 weeks or birthweight (BW) ≤ 1500 g. Clinical data was retrospectively collected and placentas were prospectively examined for maternal vascular malperfusion (e.g., abruption, infarct, distal villous hypoplasia, ischemia, and decidual necrosis) and fetal vascular malperfusion (e.g., thrombosis, fetal hypoxia, and hydrops parenchyma). The primary outcome was ROP. Secondary outcomes were GA, BW, small for gestational age (SGA), mechanical ventilation duration, postnatal corticosteroids, sepsis, and necrotizing enterocolitis. Results: Maternal vascular malperfusion was associated with higher GA, lower BW, and increased SGA rates, except placental abruption, which was associated with lower SGA rates. Fetal vascular malperfusion was associated with lower BW, increased SGA rates and lower duration of mechanical ventilation. Subgroup analysis of placentas without inflammation showed increased rates of distal villous hypoplasia (44% vs. 31%) and hydrops parenchyma (7% vs. 0%) in neonates with ROP. Multivariate regression analyses revealed three placenta factors to be independently associated with ROP: distal villous hypoplasia (OR = 1.7; 95% CI, 1.0-3.0), severe acute histological chorioamnionitis (OR = 2.1; 95% CI, 1.1-3.9) and funisitis (OR = 1.8; 95% CI, 1.0-3.1). Conclusions: Placental evaluation of distal villous hypoplasia, severe acute chorioamnionitis and funisitis is a novel and valuable addition to the ROP risk profile. Evaluation of these placental risk factors shortly after birth can aid in identifying high-risk infants in an earlier stage than currently possible.

Combining Partial True Discovery Guarantee Procedures.

Closed testing has recently been shown to be optimal for simultaneous true discovery proportion control. It is, however, challenging to construct true discovery guarantee procedures in such a way that it focuses power on some feature sets chosen by users based on their specific interest or expertise. We propose a procedure that allows users to target power on prespecified feature sets, that is, "focus sets." Still, the method also allows inference for feature sets chosen post hoc, that is, "nonfocus sets," for which we deduce a true discovery lower confidence bound by interpolation. Our procedure is built from partial true discovery guarantee procedures combined with Holm's procedure and is a conservative shortcut to the closed testing procedure. A simulation study confirms that the statistical power of our method is relatively high for focus sets, at the cost of power for nonfocus sets, as desired. In addition, we investigate its power property for sets with specific structures, for example, trees and directed acyclic graphs. We also compare our method with AdaFilter in the context of replicability analysis. The application of our method is illustrated with a gene ontology analysis in gene expression data.

Early-Onset Sepsis as an Early Predictor for Retinopathy of Prematurity: A Meta-analysis.

OBJECTIVE: Neonatal sepsis has been established as a risk factor for retinopathy of prematurity (ROP) but previous meta-analyses have predominately focused on late-onset sepsis (LOS). This meta-analysis aims to explore the association between early-onset sepsis (EOS) and the risk of ROP. STUDY DESIGN: Observational studies reporting (unadjusted) data on proven EOS in neonates with ROP were included. PubMed, Embase, and Cochrane Library were searched. Proven EOS was defined as a positive blood or cerebrospinal fluid culture. Effect sizes were calculated by using logistic random-effects models and meta-regression analyses. Primary outcomes were any stage ROP and severe ROP (≥stage 3, type I, aggressive [posterior] ROP, plus disease or requiring treatment). Potential confounders explored were gestational age at birth, birth weight, small for gestational age, maternal steroid use, necrotizing enterocolitis, LOS, and mechanical ventilation duration. RESULTS: Seventeen studies reporting the incidence of proven EOS in neonates with ROP were included. Proven EOS showed no significant association with any stage ROP (odds ratio [OR] = 1.90; 95% confidence interval [CI]: 0.96-3.79, p = 0.067) but heterogeneity between studies was significantly high. Neonates with proven EOS had an increased risk for severe ROP (OR = 2.21; 95% CI: 1.68-2.90), and no significant confounders influencing this effect size were found in the meta-regression analysis. CONCLUSION: Neonates with proven EOS are at increased risk of severe ROP. Neonatologists need to be aware that EOS is an early predictor of ROP and should adapt their policy and treatment decisions where possible to reduce ROP. KEY POINTS: · This meta-analysis reveals a 2.2-fold increased risk of severe ROP in neonates with proven EOS.. · Future studies should distinguish between EOS and LOS when investigating risk factors of ROP.. · Treatment decisions should be adapted where possible in neonates with EOS before ROP screening begins..

The AccelerAge framework: a new statistical approach to predict biological age based on time-to-event data.

Aging is a multifaceted and intricate physiological process characterized by a gradual decline in functional capacity, leading to increased susceptibility to diseases and mortality. While chronological age serves as a strong risk factor for age-related health conditions, considerable heterogeneity exists in the aging trajectories of individuals, suggesting that biological age may provide a more nuanced understanding of the aging process. However, the concept of biological age lacks a clear operationalization, leading to the development of various biological age predictors without a solid statistical foundation. This paper addresses these limitations by proposing a comprehensive operationalization of biological age, introducing the "AccelerAge" framework for predicting biological age, and introducing previously underutilized evaluation measures for assessing the performance of biological age predictors. The AccelerAge framework, based on Accelerated Failure Time (AFT) models, directly models the effect of candidate predictors of aging on an individual's survival time, aligning with the prevalent metaphor of aging as a clock. We compare predictors based on the AccelerAge framework to a predictor based on the GrimAge predictor, which is considered one of the best-performing biological age predictors, using simulated data as well as data from the UK Biobank and the Leiden Longevity Study. Our approach seeks to establish a robust statistical foundation for biological age clocks, enabling a more accurate and interpretable assessment of an individual's aging status.

Clarifying the biological and statistical assumptions of cross-sectional biological age predictors: an elaborate illustration using synthetic and real data.

BACKGROUND: There is divergence in the rate at which people age. The concept of biological age is postulated to capture this variability, and hence to better represent an individual's true global physiological state than chronological age. Biological age predictors are often generated based on cross-sectional data, using biochemical or molecular markers as predictor variables. It is assumed that the difference between chronological and predicted biological age is informative of one's chronological age-independent aging divergence ∆. METHODS: We investigated the statistical assumptions underlying the most popular cross-sectional biological age predictors, based on multiple linear regression, the Klemera-Doubal method or principal component analysis. We used synthetic and real data to illustrate the consequences if this assumption does not hold. RESULTS: The most popular cross-sectional biological age predictors all use the same strong underlying assumption, namely that a candidate marker of aging's association with chronological age is directly informative of its association with the aging rate ∆. We called this the identical-association assumption and proved that it is untestable in a cross-sectional setting. If this assumption does not hold, weights assigned to candidate markers of aging are uninformative, and no more signal may be captured than if markers would have been assigned weights at random. CONCLUSIONS: Cross-sectional methods for predicting biological age commonly use the untestable identical-association assumption, which previous literature in the field had never explicitly acknowledged. These methods have inherent limitations and may provide uninformative results, highlighting the importance of researchers exercising caution in the development and interpretation of cross-sectional biological age predictors.

Cumulative incidence and risk factors for cutaneous squamous cell carcinoma metastases in organ transplant recipients: The Skin Care in Organ Transplant Patients in Europe-International Transplant Skin Cancer Collaborative metastases study, a prospective multicenter study.

INTRODUCTION: Solid organ transplant recipients (SOTRs) are believed to have an increased risk of metastatic cutaneous squamous cell carcinoma (cSCC), but reliable data are lacking regarding the precise incidence and associated risk factors. METHODS: In a prospective cohort study, including 19 specialist dermatology outpatient clinics in 15 countries, patient and tumor characteristics were collected using standardized questionnaires when SOTRs presented with a new cSCC. After a minimum of 2 years of follow-up, relevant data for all SOTRs were collected. Cumulative incidence of metastases was calculated by the Aalen-Johansen estimator. Fine and Gray models were used to assess multiple risk factors for metastases. RESULTS: Of 514 SOTRs who presented with 623 primary cSCCs, metastases developed in 37 with a 2-year patient-based cumulative incidence of 6.2%. Risk factors for metastases included location in the head and neck area, local recurrence, size > 2 cm, clinical ulceration, poor differentiation grade, perineural invasion, and deep invasion. A high-stage tumor that is also ulcerated showed the highest risk of metastasis, with a 2-year cumulative incidence of 46.2% (31.9%-68.4%). CONCLUSIONS: SOTRs have a high risk of cSCC metastases and well-established clinical and histologic risk factors have been confirmed. High-stage, ulcerated cSCCs have the highest risk of metastasis.

RNA-sequencing to discover genes and signaling pathways associated with venous thromboembolism in glioblastoma patients: A case-control study.

BACKGROUND: Glioblastoma patients are at high risk of developing venous thromboembolism (VTE). Tumor-intrinsic features are considered to play a role, but the underlying pathophysiological mechanisms remain incompletely understood. OBJECTIVES: To identify tumor-expressed genes and signaling pathways that associate with glioblastoma-related VTE by using next generation RNA-sequencing (RNA-Seq). METHODS: The tumor gene expression profile of 23 glioblastoma patients with VTE and 23 glioblastoma patients without VTE was compared using an unpaired analysis. Ingenuity Pathway Analysis (IPA) core analysis was performed on the top 50 differentially expressed genes to explore associated functions and pathways. Based on full RNA-Seq data, molecular glioblastoma subtypes were determined by performing cluster analysis. RESULTS: Of the 19,327 genes, 1246 (6.4 %) were differentially expressed between glioblastoma patients with and without VTE (unadjusted P < 0.05). The most highly overexpressed gene was GLI1, a classical target gene in the Sonic Hedgehog (Shh) signaling pathway (log2 fold change: 3.7; unadjusted P < 0.0001, adjusted P = 0.219). In line, Shh signaling was among the top canonical pathways and processes associated with VTE. The proportion of patients with the proneural/neural glioblastoma subtype was higher among those with VTE than controls. CONCLUSION: Shh signaling may be involved in the development of glioblastoma-related VTE.

Histological Chorioamnionitis and Funisitis as New Risk Factors for Retinopathy of Prematurity: A Meta-analysis.

OBJECTIVE: The role of placental inflammation in neonatal morbidities is underestimated due to lack of placental examination. This meta-analysis aims to assess the association between histological chorioamnionitis (HCA) with and without funisitis (FUN) and risk of retinopathy of prematurity (ROP). STUDY DESIGN: Forty-five studies reporting (unadjusted) data on HCA without FUN and HCA with FUN in neonates with ROP were included. Primary outcomes were any stage ROP and severe ROP. Potential confounders explored were gestational age (GA) at birth, birthweight, maternal steroid use, necrotizing enterocolitis, sepsis (suspected/proven) and mechanical ventilation duration. RESULTS: Neonates with HCA had increased risk for any stage ROP (odds ratio [OR] 1.8; 95% confidence interval [CI] 1.3-2.4) and severe ROP (OR 1.5; 95% CI 1.2-1.8) compared with neonates without HCA. The rates of any stage ROP (OR 1.8; 95% CI 1.4-2.2) and severe ROP (OR 1.4; 95% CI 1.1-1.6) were higher in neonates with FUN compared with neonates without FUN. Multivariate meta-regression analysis suggests that lower GA increases the effect size between FUN and severe ROP. CONCLUSION: This meta-analysis confirms that presence of HCA and FUN are risk factors for any stage ROP and severe ROP. Structured histological placental examination of HCA and FUN may be a tool to further refine the ROP risk profile. KEY POINTS: · This systematic review confirms that HCA is a risk factor for ROP.. · This meta-analysis reveals that FUN results in an even higher risk for developing ROP.. · Placental examination of HCA/FUN may be a tool to further refine the ROP risk profile..

Development and External Validation of a PET Radiomic Model for Prognostication of Head and Neck Cancer.

AIM: To build and externally validate an [18F]FDG PET radiomic model to predict overall survival in patients with head and neck squamous cell carcinoma (HNSCC). METHODS: Two multicentre datasets of patients with operable HNSCC treated with preoperative afatinib who underwent a baseline and evaluation [18F]FDG PET/CT scan were included (EORTC: n = 20, Unicancer: n = 34). Tumours were delineated, and radiomic features were extracted. Each cohort served once as a training and once as an external validation set for the prediction of overall survival. Supervised feature selection was performed using variable hunting with variable importance, selecting the top two features. A Cox proportional hazards regression model using selected radiomic features and clinical characteristics was fitted on the training dataset and validated in the external validation set. Model performances are expressed by the concordance index (C-index). RESULTS: In both models, the radiomic model surpassed the clinical model with validation C-indices of 0.69 and 0.79 vs. 0.60 and 0.67, respectively. The model that combined the radiomic features and clinical variables performed best, with validation C-indices of 0.71 and 0.82. CONCLUSION: Although assessed in two small but independent cohorts, an [18F]FDG-PET radiomic signature based on the evaluation scan seems promising for the prediction of overall survival for HNSSC treated with preoperative afatinib. The robustness and clinical applicability of this radiomic signature should be assessed in a larger cohort.

Permutation-based true discovery proportions for functional magnetic resonance imaging cluster analysis.

We propose a permutation-based method for testing a large collection of hypotheses simultaneously. Our method provides lower bounds for the number of true discoveries in any selected subset of hypotheses. These bounds are simultaneously valid with high confidence. The methodology is particularly useful in functional Magnetic Resonance Imaging cluster analysis, where it provides a confidence statement on the percentage of truly activated voxels within clusters of voxels, avoiding the well-known spatial specificity paradox. We offer a user-friendly tool to estimate the percentage of true discoveries for each cluster while controlling the family-wise error rate for multiple testing and taking into account that the cluster was chosen in a data-driven way. The method adapts to the spatial correlation structure that characterizes functional Magnetic Resonance Imaging data, gaining power over parametric approaches.

Molecular Landscape of Pelvic Organ Prolapse Provides Insights into Disease Etiology.

Pelvic organ prolapse (POP) represents a major health care burden in women, but its underlying pathophysiological mechanisms have not been elucidated. We first used a case-control design to perform an exome chip study in 526 women with POP and 960 control women to identify single nucleotide variants (SNVs) associated with the disease. We then integrated the functional interactions between the POP candidate proteins derived from the exome chip study and other POP candidate molecules into a molecular landscape. We found significant associations between POP and SNVs in 54 genes. The proteins encoded by 26 of these genes fit into the molecular landscape, together with 43 other POP candidate molecules. The POP landscape is located in and around epithelial cells and fibroblasts of the urogenital tract and harbors four interacting biological processes-epithelial-mesenchymal transition, immune response, modulation of the extracellular matrix, and fibroblast function-that are regulated by sex hormones and TGFB1. Our findings were corroborated by enrichment analyses of differential gene expression data from an independent POP cohort. Lastly, based on the landscape and using vaginal fibroblasts from women with POP, we predicted and showed that metformin alters gene expression in these fibroblasts in a beneficial direction. In conclusion, our integrated molecular landscape of POP provides insights into the biological processes underlying the disease and clues towards novel treatments.

Cancer-Associated Fibroblasts Are Key Determinants of Cancer Cell Invasion in the Earliest Stage of Colorectal Cancer.

BACKGROUND & AIMS: Improving clinical management of early stage colorectal cancers (T1CRCs) requires a better understanding of their underlying biology. Accumulating evidence shows that cancer-associated fibroblasts (CAFs) are important determinants of tumor progression in advanced colorectal cancer (CRC), but their role in the initial stages of CRC tumorigenesis is unknown. Therefore, we investigated the contribution of T1CAFs to early CRC progression. METHODS: Primary T1CAFs and patient-matched normal fibroblasts (NFs) were isolated from endoscopic biopsy specimens of histologically confirmed T1CRCs and normal mucosa, respectively. The impact of T1CAFs and NFs on tumor behavior was studied using 3-dimensional co-culture systems with primary T1CRC organoids and extracellular matrix (ECM) remodeling assays. Whole-transcriptome sequencing and gene silencing were used to pinpoint mediators of T1CAF functions. RESULTS: In 3-dimensional multicellular cultures, matrix invasion of T1CRC organoids was induced by T1CAFs, but not by matched NFs. Enhanced T1CRC invasion was accompanied by T1CAF-induced ECM remodeling and up-regulation of CD44 in epithelial cells. RNA sequencing of 10 NF-T1CAF pairs revealed 404 differentially expressed genes, with significant enrichment for ECM-related pathways in T1CAFs. Cathepsin H, a cysteine-type protease that was specifically up-regulated in T1CAFs but not in fibroblasts from premalignant lesions or advanced CRCs, was identified as a key factor driving matrix remodeling by T1CAFs. Finally, we showed high abundance of cathepsin H-expressing T1CAFs at the invasive front of primary T1CRC sections. CONCLUSIONS: Already in the earliest stage of CRC, cancer cell invasion is promoted by CAFs via direct interactions with epithelial cancer cells and stage-specific, cathepsin H-dependent ECM remodeling. RNA sequencing data of the 10 NF-T1CAF pairs can be found under GEO accession number GSE200660.

Dynamic characteristics of skin reaction force in different body postures.

Mechanical stress influences scarring of a surgical wound. Several lines have been proposed for the best excision direction. It is unknown if these lines still apply when the body posture changes. The objective is to measure the skin reaction force in four directions and determine the direction of least force. Secondary objective is to determine if the reaction force varies in a different body posture. Skin reaction force was measured with the compressiometer in 30 participants on four different locations (forearm/upper arm/shoulder blade/lower back) in four directions (0°-45°-90°-135°) and two body postures. The direction of least skin reaction force changed with a different body posture and was significant for the forearm (p < 0.01) and shoulder blade (p = 0.05) The skin reaction force in all four direction changed significantly in a different body posture, except the 45° line in the upper arm and shoulder blade. Our results demonstrate that the skin reaction force in four directions in four locations varies with change in body posture. Focus should therefore not only lay on choosing the right direction, but also on managing skin tension postoperatively.

HLA expression as a risk factor for metastases of cutaneous squamous-cell carcinoma in organ- transplant recipients.

BACKGROUND: Solid organ-transplant recipients (SOTR) have an increased risk of cutaneous squamous-cell carcinoma (cSCC), metastasis and death from cSCC. In immunocompetent patients with mucosal SCC, downregulation of HLA class I is associated with poor prognosis. Since the degree of HLA expression on tumor cells could play a role in immunogenicity and pathophysiology of cSCC metastasis, we hypothesized that decreased HLA expression is associated with an increased risk of metastasis. METHODS: We compared HLA expression between primary metastasized cSCCs, their metastases, and non-metastasized cSCCs from the same patients. Samples were stained for HLA-A, HLA-B/-C and quantified by calculating the difference in immunoreactivity score (IRS) of the primary cSCC compared with all non-metastasized cSCCs. RESULTS: The mean IRS score for HLA-B/C expression was 2.07 point higher in metastasized compared to non-metastasized cSCCs (p = 0.065, 95 % CI -0.18-4.32). 83.3 % of the primary metastasized cSCCs had an IRS score of 4 or higher, compared to 42.9 % in non-metastasized cSCCs. Moderately to poorly differentiated cSCCs had more HLA class I expression compared to well-differentiated cSCCs. CONCLUSION: Contrary to immunocompetent patients, HLA-B/C expression tends to be upregulated in metastasized cSCC compared to non-metastasized cSCC in SOTR, suggesting that different tumor escape mechanisms play a role in SOTR compared to immunocompetent patients.

Closed testing with Globaltest, with application in metabolomics.

The Globaltest is a powerful test for the global null hypothesis that there is no association between a group of features and a response of interest, which is popular in pathway testing in metabolomics. Evaluating multiple feature sets, however, requires multiple testing correction. In this paper, we propose a multiple testing method, based on closed testing, specifically designed for the Globaltest. The proposed method controls the familywise error rate simultaneously over all possible feature sets, and therefore allows post hoc inference, that is, the researcher may choose feature sets of interest after seeing the data without jeopardizing error control. To circumvent the exponential computation time of closed testing, we derive a novel shortcut that allows exact closed testing to be performed on the scale of metabolomics data. An R package ctgt is available on comprehensive R archive network for the implementation of the shortcut procedure, with applications on several real metabolomics data examples.

Maximum likelihood estimation in the additive hazards model.

The additive hazards model specifies the effect of covariates on the hazard in an additive way, in contrast to the popular Cox model, in which it is multiplicative. As the non-parametric model, additive hazards offer a very flexible way of modeling time-varying covariate effects. It is most commonly estimated by ordinary least squares. In this paper, we consider the case where covariates are bounded, and derive the maximum likelihood estimator under the constraint that the hazard is non-negative for all covariate values in their domain. We show that the maximum likelihood estimator may be obtained by separately maximizing the log-likelihood contribution of each event time point, and we show that the maximizing problem is equivalent to fitting a series of Poisson regression models with an identity link under non-negativity constraints. We derive an analytic solution to the maximum likelihood estimator. We contrast the maximum likelihood estimator with the ordinary least-squares estimator in a simulation study and show that the maximum likelihood estimator has smaller mean squared error than the ordinary least-squares estimator. An illustration with data on patients with carcinoma of the oropharynx is provided.

Cerebrospinal Fluid and Plasma Amine Profiles in Interictal Migraine.

OBJECTIVE: Impaired amine metabolism has been associated with the etiology of migraine, that is, why patients continue to get migraine attacks. However, evidence from cerebrospinal fluid (CSF) is lacking. Here, we evaluated individual amine levels, global amine profiles, and amine pathways in CSF and plasma of interictal migraine patients and healthy controls. METHODS: CSF and plasma were sampled between 8:30 am and 1:00 pm, randomly and interchangeably over the time span to avoid any diurnal and seasonal influences, from healthy volunteers and interictal migraine patients, matched for age, sex, and sampling time. The study was approved by the local medical ethics committee. Individual amines (n = 31), global amine profiles, and specific amine pathways were analyzed using a validated ultraperformance liquid chromatography mass spectrometry platform. RESULTS: We analyzed n = 99 participants with migraine with aura, n = 98 with migraine without aura, and n = 96 healthy volunteers. Univariate analysis with Bonferroni correction indicated that CSF L-arginine was reduced in migraine with aura (10.4%, p < 0.001) and without aura (5.0%, p = 0.03). False discovery rate-corrected CSF L-phenylalanine was also lower in migraine with aura (6.9%, p = 0.011) and without aura (8.1%, p = 0.001), p = 0.088 after Bonferroni correction. Multivariate analysis revealed that CSF global amine profiles were similar for both types of migraine (p = 0.64), but distinct from controls (p = 0.009). Global profile analyses were similar in plasma. The strongest associated pathways with migraine were related to L-arginine metabolism. INTERPRETATION: L-Arginine was decreased in the CSF (but not in plasma) of interictal patients with migraine with or without aura, and associated pathways were altered. This suggests that dysfunction of nitric oxide signaling is involved in susceptibility to getting migraine attacks. ANN NEUROL 2023;93:715-728.

NetTDP: permutation-based true discovery proportions for differential co-expression network analysis.

Existing methods for differential network analysis could only infer whether two networks of interest have differences between two groups of samples, but could not quantify and localize network differences. In this work, a novel method, permutation-based Network True Discovery Proportions (NetTDP), is proposed to quantify the number of edges (correlations) or nodes (genes) for which the co-expression networks are different. In the NetTDP method, we propose an edge-level statistic and a node-level statistic, and detect true discoveries of edges and nodes in the sense of differential co-expression network, respectively, by the permutation-based sumSome method. Furthermore, the NetTDP method could further localize the differences by inferring the TDPs for edge or gene subsets of interest, which can be selected post hoc. Our NetTDP method allows inference on data-driven modules or biology-driven gene sets, and remains valid even when these sub-networks are optimized using the same data. Experimental results on both simulation data sets and five real data sets show the effectiveness of the proposed method in inferring the quantification and localization of differential co-expression networks. The R code is available at https://github.com/LiminLi-xjtu/NetTDP.

Immune Determinants of Viral Clearance in Hospitalised COVID-19 Patients: Reduced Circulating Naïve CD4+ T Cell Counts Correspond with Delayed Viral Clearance.

Virus-specific cellular and humoral responses are major determinants for protection from critical illness after SARS-CoV-2 infection. However, the magnitude of the contribution of each of the components to viral clearance remains unclear. Here, we studied the timing of viral clearance in relation to 122 immune parameters in 102 hospitalised patients with moderate and severe COVID-19 in a longitudinal design. Delayed viral clearance was associated with more severe disease and was associated with higher levels of SARS-CoV-2-specific (neutralising) antibodies over time, increased numbers of neutrophils, monocytes, basophils, and a range of pro-inflammatory cyto-/chemokines illustrating ongoing, partially Th2 dominating, immune activation. In contrast, early viral clearance and less critical illness correlated with the peak of neutralising antibodies, higher levels of CD4 T cells, and in particular naïve CD4+ T cells, suggesting their role in early control of SARS-CoV-2 possibly by proving appropriate B cell help. Higher counts of naïve CD4+ T cells also correlated with lower levels of MIF, IL-9, and TNF-beta, suggesting an indirect role in averting prolonged virus-induced tissue damage. Collectively, our data show that naïve CD4+ T cell play a critical role in rapid viral T cell control, obviating aberrant antibody and cytokine profiles and disease deterioration. These data may help in guiding risk stratification for severe COVID-19.

Comparison of trends in Clostridioides difficile infections in hospitalised patients during the first and second waves of the COVID-19 pandemic: A retrospective sentinel surveillance study.

Background: During the COVID-19 pandemic, several factors, such as improved hand hygiene, social distancing, and restricted hospital referral, may have had an influence on the epidemiology of Clostridioides difficile infections (CDI). Methods: The annual CDI incidence rate of nine hospitals participating in the Dutch sentinel CI surveillance with complete data was compared between 2020 and the previous five surveillance years. Trends in characteristics of hospitalised CDI patients in 21-24 participating hospitals were compared between the first (March 13-May 12, 2020) or second Dutch COVID-19 wave (September 17, 2020-January 1, 2021) and the same calendar periods in 2015 through 2019. All analyses were adjusted for trend changes over time. Findings: The annual CDI incidence rate in 2020 was lower compared to previous years. During the second wave, the percentage of CDI patients with severe CDI was higher compared to earlier (25·8% in 2020 vs 17·9% in 2015-2019 (RR 1·6; 95%CI 1·1-2·3)). After adjustment for delayed C. difficile diagnostics (≥8 days from start symptoms), the increase disappeared. Delayed C. difficile diagnostics was indeed more common during the second wave (RR 1·7; 95%CI 1·1-2·6), but only for community-onset CDI (CO-CDI). Interpretation: This study shows that a higher percentage of severe CDI cases was observed during the second COVID-19 wave. This may partially be caused by delayed diagnostics, potentially due to decreased visits to a physician or restricted hospital referral for CO-CDI patients. Funding: Dutch ministry of Health.