Impact of Imperfect Disease Detection on the Identification of Risk Factors in Veterinary Epidemiology

Risk factors are key epidemiological concepts that are used to explain disease distributions. Identifying disease risk factors is generally done by comparing the characteristics of diseased and non-diseased populations. However, imperfect disease detectability generates disease observations that do not necessarily represent accurately the true disease situation. In this study, we conducted an extensive simulation exercise to emphasize the impact of imperfect disease detection on the outcomes of logistic models when case reports are aggregated at a larger scale (e.g., diseased animals aggregated at farm level). We used a probabilistic framework to simulate both the disease distribution in herds and imperfect detectability of the infected animals in these herds. These simulations show that, under logistic models, true herd-level risk factors are generally correctly identified but their associated odds ratio are heavily underestimated as soon as the sensitivity of the detection is less than one. If the detectability of infected animals is not only imperfect but also heterogeneous between herds, the variables associated with the detection heterogeneity are likely to be incorrectly identified as risk factors. This probability of type I error increases with increasing heterogeneity of the detectability, and with decreasing sensitivity. Finally, the simulations highlighted that, when count data is available (e.g., number of infected animals in herds), they should not be reduced to a presence/absence dataset at the herd level (e.g., presence or not of at least one infected animal) but rather modeled directly using zero-inflated count models which are shown to be much less sensitive to imperfect detectability issues. In light of these simulations, we revisited the analysis of the French bovine abortion surveillance data, which has already been shown to be characterized by imperfect and heterogeneous abortion detectability. As expected, we found substantial differences between the quantitative outputs of the logistic model and those of the zero-inflated Poisson model. We conclude by strongly recommending that efforts should be made to account for, or at the very least discuss, imperfect disease detectability when assessing associations between putative risk factors and observed disease distributions, and advocate the use of zero-inflated count models if count data is available

Mycobacterium abscessus Glycopeptidolipid Prevents Respiratory Epithelial TLR2 Signaling as Measured by HβD2 Gene Expression and IL-8 Release

Mycobacterium abscessus has emerged as an important cause of lung infection, particularly in patients with bronchiectasis. Innate immune responses must be highly effective at preventing infection with M. abscessus because it is a ubiquitous environmental saprophyte and normal hosts are not commonly infected. M. abscessus exists as either a glycopeptidolipid (GPL) expressing variant (smooth phenotype) in which GPL masks underlying bioactive cell wall lipids, or as a variant lacking GPL which is immunostimulatory and invasive in macrophage infection models. Respiratory epithelium has been increasingly recognized as playing an important role in the innate immune response to pulmonary pathogens. Respiratory epithelial cells express toll-like receptors (TLRs) which mediate the innate immune response to pulmonary pathogens. Both interleukin-8 (IL-8) and human β-defensin 2 (HβD2) are expressed by respiratory epithelial cells in response to toll-like receptor 2 (TLR2) receptor stimulation. In this study, we demonstrate that respiratory epithelial cells respond to M. abscessus variants lacking GPL with expression of IL-8 and HβD2. Furthermore, we demonstrate that this interaction is mediated through TLR2. Conversely, M. abscessus expressing GPL does not stimulate expression of IL-8 or HβD2 by respiratory epithelial cells which is consistent with “masking” of underlying bioactive cell wall lipids by GPL. Because GPL-expressing smooth variants are the predominant phenotype existing in the environment, this provides an explanation whereby initial M. abscessus colonization of abnormal lung airways escapes detection by the innate immune system

T-cell immunophenotyping distinguishes active from latent tuberculosis.

BACKGROUND: Changes in the phenotype and function of Mycobacterium tuberculosis (M. tuberculosis)-specific CD4+ and CD8+ T-cell subsets in response to stage of infection may allow discrimination between active tuberculosis and latent tuberculosis infection. METHODS: A prospective comparison of M. tuberculosis-specific cellular immunity in subjects with active tuberculosis and latent tuberculosis infection, with and without human immunodeficiency virus (HIV) coinfection. Polychromatic flow cytometry was used to measure CD4+ and CD8+ T-cell subset phenotype and secretion of interferon γ (IFN-γ), interleukin 2 (IL-2), and tumor necrosis factor α (TNF-α). RESULTS: Frequencies of CD4+ and CD8+ cells secreting IFN-γ-only, TNF-α-only and dual IFN-γ/TNF-α were greater in active tuberculosis vs latent tuberculosis infection. All M. tuberculosis-specific CD4+ subsets, with the exception of IL-2-only cells, switched from central to effector memory phenotype in active tuberculosis vs latent tuberculosis infection, accompanied by a reduction in IL-7 receptor α (CD127) expression. The frequency of PPDspecific CD4+ TNF-α-only-secreting T cells with an effector phenotype accurately distinguished active tuberculosis from latent tuberculosis infection with an area under the curve of 0.99, substantially more discriminatory than measurement of function alone. CONCLUSIONS: Combined measurement of T-cell phenotype and function defines a highly discriminatory biomarker of tuberculosis disease activity. Unlocking the diagnostic and monitoring potential of this combined approach now requires validation in large-scale prospective studies

Ileal-J-Pouch Volvulus After Restorative Proctocolectomy

International audienc

Inferior Vena Cava Leiomyosarcoma What Method of Reconstruction for Which Type of Resection?

International audienceInferior vena cava leiomyosarcoma (IVCL) is a rare tumor with a poor prognosis, and its surgical resection remains a challenge. To date, surgery is the only potentially curative treatment for IVCL with a 5-year survival rate of 55%. The main challenge is to combine oncological surgery with clear margins and vascular reconstruction of the inferior vena cava (IVC). In this review, we discuss the different approaches to vascular reconstruction after IVCL resection, using a prosthetic or autologous patch, direct suture or simple ligation without IVC reconstruction. The reconstruction of IVC depends of tumor location and its extension. We recommend no reconstruction if venous collaterality is well-established. When vascular reconstruction is required, we prefer prosthetic PTFE graft. These patients should be referred to high-volume centers with a multidisciplinary team of sarcoma surgeons with cardiothoracic, vascular and hepatic specialties