Sophie Bartier

Bio: Sophie Bartier is an academic researcher from Paris 12 Val de Marne University. The author has contributed to research in topics: Medicine & Nasal polyps. The author has an hindex of 3, co-authored 3 publications receiving 57 citations.

How your ears can tell what is hidden in your heart: wild-type transthyretin amyloidosis as potential cause of sensorineural hearing loss inelderly-AmyloDEAFNESS pilot study.

Abstract: Background: Wild-type transthyretin amyloidosis (ATTRwt) is an age-related life-threatening condition. Prognosis is mainly dependent on cardiac involvement. Other organs and tissues may be affected...

Pharyngo-laryngeal involvement in systemic amyloidosis with cardiac involvement: a prospective observational study

Abstract: Background: Systemic amyloidosis with cardiac involvement (CA) is a severe disease caused by the aggregation of misfolded proteins infiltrating organs and tissues and leading to their dysfunction. ...

Proviral role of human respiratory epithelial cell‐derived small extracellular vesicles in SARS‐CoV‐2 infection

Abstract: Abstract Small Extracellular Vesicles (sEVs) are 50–200 nm in diameter vesicles delimited by a lipid bilayer, formed within the endosomal network or derived from the plasma membrane. They are secreted in various biological fluids, including airway nasal mucus. The goal of this work was to understand the role of sEVs present in the mucus (mu‐sEVs) produced by human nasal epithelial cells (HNECs) in SARS‐CoV‐2 infection. We show that uninfected HNECs produce mu‐sEVs containing SARS‐CoV‐2 receptor ACE2 and activated protease TMPRSS2. mu‐sEVs cleave prefusion viral Spike proteins at the S1/S2 boundary, resulting in higher proportions of prefusion S proteins exposing their receptor binding domain in an ‘open’ conformation, thereby facilitating receptor binding at the cell surface. We show that the role of nasal mu‐sEVs is to complete prefusion Spike priming performed by intracellular furin during viral egress from infected cells. This effect is mediated by vesicular TMPRSS2 activity, rendering SARS‐CoV‐2 virions prone to entry into target cells using the ‘early’, TMPRSS2‐dependent pathway instead of the ‘late’, cathepsin‐dependent route. These results indicate that prefusion Spike priming by mu‐sEVs in the nasal cavity plays a role in viral tropism. They also show that nasal mucus does not protect from SARS‐CoV‐2 infection, but instead facilitates it.

Objective diagnosis of internal nasal valve collapse by four‐phase rhinomanometry

Abstract: Internal valve collapse is a frequent cause of nasal obstruction but remains poorly understood and is sometimes treated inappropriately as a result. No functional or imaging test for the condition has been validated and the reference diagnostic technique is physical examination. The objective of this study was to evaluate the potential of four‐phase rhinomanometry as a diagnostic test for internal valve collapse.

Signs and symptoms to determine if a patient presenting in primary care or hospital outpatient settings has COVID-19 disease.

Abstract: BACKGROUND: The clinical implications of SARS-CoV-2 infection are highly variable. Some people with SARS-CoV-2 infection remain asymptomatic, whilst the infection can cause mild to moderate COVID-19 and COVID-19 pneumonia in others. This can lead to some people requiring intensive care support and, in some cases, to death, especially in older adults. Symptoms such as fever, cough, or loss of smell or taste, and signs such as oxygen saturation are the first and most readily available diagnostic information. Such information could be used to either rule out COVID-19, or select patients for further testing. This is an update of this review, the first version of which published in July 2020. OBJECTIVES: To assess the diagnostic accuracy of signs and symptoms to determine if a person presenting in primary care or to hospital outpatient settings, such as the emergency department or dedicated COVID-19 clinics, has COVID-19. SEARCH METHODS: For this review iteration we undertook electronic searches up to 15 July 2020 in the Cochrane COVID-19 Study Register and the University of Bern living search database. In addition, we checked repositories of COVID-19 publications. We did not apply any language restrictions. SELECTION CRITERIA: Studies were eligible if they included patients with clinically suspected COVID-19, or if they recruited known cases with COVID-19 and controls without COVID-19. Studies were eligible when they recruited patients presenting to primary care or hospital outpatient settings. Studies in hospitalised patients were only included if symptoms and signs were recorded on admission or at presentation. Studies including patients who contracted SARS-CoV-2 infection while admitted to hospital were not eligible. The minimum eligible sample size of studies was 10 participants. All signs and symptoms were eligible for this review, including individual signs and symptoms or combinations. We accepted a range of reference standards. DATA COLLECTION AND ANALYSIS: Pairs of review authors independently selected all studies, at both title and abstract stage and full-text stage. They resolved any disagreements by discussion with a third review author. Two review authors independently extracted data and resolved disagreements by discussion with a third review author. Two review authors independently assessed risk of bias using the Quality Assessment tool for Diagnostic Accuracy Studies (QUADAS-2) checklist. We presented sensitivity and specificity in paired forest plots, in receiver operating characteristic space and in dumbbell plots. We estimated summary parameters using a bivariate random-effects meta-analysis whenever five or more primary studies were available, and whenever heterogeneity across studies was deemed acceptable. MAIN RESULTS: We identified 44 studies including 26,884 participants in total. Prevalence of COVID-19 varied from 3% to 71% with a median of 21%. There were three studies from primary care settings (1824 participants), nine studies from outpatient testing centres (10,717 participants), 12 studies performed in hospital outpatient wards (5061 participants), seven studies in hospitalised patients (1048 participants), 10 studies in the emergency department (3173 participants), and three studies in which the setting was not specified (5061 participants). The studies did not clearly distinguish mild from severe COVID-19, so we present the results for all disease severities together. Fifteen studies had a high risk of bias for selection of participants because inclusion in the studies depended on the applicable testing and referral protocols, which included many of the signs and symptoms under study in this review. This may have especially influenced the sensitivity of those features used in referral protocols, such as fever and cough. Five studies only included participants with pneumonia on imaging, suggesting that this is a highly selected population. In an additional 12 studies, we were unable to assess the risk for selection bias. This makes it very difficult to judge the validity of the diagnostic accuracy of the signs and symptoms from these included studies. The applicability of the results of this review update improved in comparison with the original review. A greater proportion of studies included participants who presented to outpatient settings, which is where the majority of clinical assessments for COVID-19 take place. However, still none of the studies presented any data on children separately, and only one focused specifically on older adults. We found data on 84 signs and symptoms. Results were highly variable across studies. Most had very low sensitivity and high specificity. Only cough (25 studies) and fever (7 studies) had a pooled sensitivity of at least 50% but specificities were moderate to low. Cough had a sensitivity of 67.4% (95% confidence interval (CI) 59.8% to 74.1%) and specificity of 35.0% (95% CI 28.7% to 41.9%). Fever had a sensitivity of 53.8% (95% CI 35.0% to 71.7%) and a specificity of 67.4% (95% CI 53.3% to 78.9%). The pooled positive likelihood ratio of cough was only 1.04 (95% CI 0.97 to 1.11) and that of fever 1.65 (95% CI 1.41 to 1.93). Anosmia alone (11 studies), ageusia alone (6 studies), and anosmia or ageusia (6 studies) had sensitivities below 50% but specificities over 90%. Anosmia had a pooled sensitivity of 28.0% (95% CI 17.7% to 41.3%) and a specificity of 93.4% (95% CI 88.3% to 96.4%). Ageusia had a pooled sensitivity of 24.8% (95% CI 12.4% to 43.5%) and a specificity of 91.4% (95% CI 81.3% to 96.3%). Anosmia or ageusia had a pooled sensitivity of 41.0% (95% CI 27.0% to 56.6%) and a specificity of 90.5% (95% CI 81.2% to 95.4%). The pooled positive likelihood ratios of anosmia alone and anosmia or ageusia were 4.25 (95% CI 3.17 to 5.71) and 4.31 (95% CI 3.00 to 6.18) respectively, which is just below our arbitrary definition of a 'red flag', that is, a positive likelihood ratio of at least 5. The pooled positive likelihood ratio of ageusia alone was only 2.88 (95% CI 2.02 to 4.09). Only two studies assessed combinations of different signs and symptoms, mostly combining fever and cough with other symptoms. These combinations had a specificity above 80%, but at the cost of very low sensitivity (< 30%). AUTHORS' CONCLUSIONS: The majority of individual signs and symptoms included in this review appear to have very poor diagnostic accuracy, although this should be interpreted in the context of selection bias and heterogeneity between studies. Based on currently available data, neither absence nor presence of signs or symptoms are accurate enough to rule in or rule out COVID-19. The presence of anosmia or ageusia may be useful as a red flag for COVID-19. The presence of fever or cough, given their high sensitivities, may also be useful to identify people for further testing. Prospective studies in an unselected population presenting to primary care or hospital outpatient settings, examining combinations of signs and symptoms to evaluate the syndromic presentation of COVID-19, are still urgently needed. Results from such studies could inform subsequent management decisions.

Senile systemic amyloidosis affects 25% of the very aged and associates with genetic variation in alpha2-macroglobulin and tau: a population-based autopsy study. Ann Med 2008; 40: 232-9

Abstract: Background. Senile systemic amyloidosis (SSA) is characterized by deposition of wild‐type transthyretin (TTR)‐based amyloid in parenchymal organs in elderly individuals. Previously, no population‐based studies have been performed on SSA. Methods. Here we have studied the prevalence and risk factors for SSA in a Finnish autopsied population aged 85 or over, as part of the population‐based Vantaa 85+ Autopsy Study (n = 256). The diagnosis of SSA was based on histological examination of myocardial samples stained with Congo red and anti‐TTR immunohistochemistry. The genotype frequencies of 20 polymorphisms in 9 genes in subjects with and without SSA were compared. Results. The prevalence of SSA was 25%. SSA was associated with age, myocardial infarctions, the G/G (Val/Val) genotype of the exon 24 polymorphism in the alpha2‐macroglobulin (α2M), and the H2 haplotype of the tau gene (P‐values 0.002, 0.004, 0.042, and 0.016). Conclusion. This population‐based study shows that SSA is very common in old individuals, affecting one‐quarter of people aged over 85 years. Myocardial infarctions and variation in the genes for α2M and tau may be associated with SSA.