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This study evaluated the spread and possible changes in resistance patterns of ESKAPE bacteria to first-choice antibiotics from 2015 to 2019 at a third-level university hospital after persuasive stewardship measures were implemented. Isolates were divided into three groups (group 1, low drug-resistant; group 2, multidrug/extremely drug-resistant; and group 3, pan-resistant bacteria) and a

Trial of labor after cesarean delivery (TOLAC) is a common practice worldwide but the evidence is still scant regarding this practice in women who underwent 2 previous cesareans. The purpose of this study is to retrospectively review our experience with vaginal birth after two previous cesarean sections (VBA2C), with specific attention to the indications for previous cesarean and to the women's motivation for attempting trial of labor.This was a retrospective cohort study conducted in a primary care hospital between January 2011 and December 2019. Inclusion criteria were: singleton pregnancies, absence of morphological abnormalities at ultrasonographic screening of the second trimester (or at any other stage of pregnancy), and two previous cesarean sections.The final analysis included 114 cases for maternal and neonatal outcomes. In total, 40.4% of women chose trial of labor after two cesarean delivery (TOLA2C group). TOLA2C was associated with a success rate of 76.1%, a higher gestational age at birth, and a shorter hospital stay, compared with elective repeated cesarean delivery group. There were no significant differences in the rate of Apgar scores at 5 minutes7 between both groups. The percentage of successful TOLA2C in women with prior vaginal delivery was 92.8%. Factors related to failed TOLA2C included failure to progress (3/11, 27.3%), nonreassuring fetal heart rate (3/11, 27.3%), and no onset of spontaneous labor after premature rupture of membranes (5/11, 45.4%). In the group of TOLA2C, more than 70% accepted to travel more than 45 minutes to reach our hospital, with the aim to attempt VBA2C.TOLA2C is a possible option for both mothers and neonates in selected cases. Adequate counseling about pros and cons of TOLA2C is mandatory. The woman's motivation represents a key element to determine the success of VBA2C.· Selection of candidates and motivation of the patients represent key elements for successful TOLA2C.. · A careful record of obstetrical history and previous deliveries can provide clinicians useful information.. · Mode of delivery in women with two previous cesareans is strongly associated with doctor's counseling..

Bayesian sequential integration is an appealing approach in drug development, as it allows to recursively update posterior distributions as soon as new data become available, thus considerably reducing the computation time. However, preclinical trials are often characterized by small sample sizes, which may affect the estimation process during the first integration steps, particularly when complex PK-PD models are used. In this case, sequential integration would not be practicable, and trials should be pooled together. This work is aimed at comparing simple Bayesian pooling with sequential integration through a simulation study. The two techniques are compared under several scenarios using linear as well as nonlinear models. The results of our simulation study encourage the use of Bayesian sequential integration with linear models. However, in the case of nonlinear models several caveats arise. This paper outlines some important recommendations and precautions in that respect.

Additional file 2: Table S2. Complete list of mutations identified in the SARS-CoV-2 genomes from patients described.

Additional file 1: Table S1. Metrics of Next Generation Sequencing reported for each viral isolate.

In patients with influenza‐related myocarditis, prompt diagnosis and treatment are important. Intravenous zanamivir can be an alternative to oral oseltamivir, especially in severe cases and when drug intestinal malabsorption is suspected or proven.

Cardiomyopathies are a heterogeneous group of disorders of the myocardium, characterized by multiple clinical manifestations with different prognoses (1). In cats, heart disease is frequent and is considered one of the most common causes of death (2,3). ARVC is rare in pets and has a lot of similarities to human ARVC (4,5). Signs of the disease include moderate/severe dilation of the right ventricle, regional or diffuse thinning of the wall, and sometimes aneurysm. The histological examination shows the presence of adipose or fibrous tissue that replaces myocardium, focal myocarditis, and cell apoptosis, more frequent in the right ventricular wall (6). Clinical signs are related to right-sided heart failure; dyspnea caused by pleural effusion, ascites, turgor of the jugular veins, episodes of syncope (5,6). The outcome of the disease is not favorable, especially when the symptoms of heart failure become evident (6)., Atti della Accademia Peloritana dei Pericolanti - Classe di Scienze Medico-Biologiche, Vol 109, No 1 (2021): Partial Issue

Since December 2019, coronavirus disease 2019 (COVID-19) pandemic has spread from China all over the world and many COVID-19 outbreaks have been reported in long-term care facilities (LCTF). However, data on clinical characteristics and prognostic factors in such settings are scarce. We conducted a retrospective, observational cohort study to assess clinical characteristics and baseline predictors of mortality of COVID-19 patients hospitalized after an outbreak of SARS-CoV-2 infection in a LTCF. A total of 50 patients were included. Mean age was 80 years (SD, 12 years), and 24/50 (57.1%) patients were males. The overall in-hospital mortality rate was 32%. At Cox regression analysis, significant predictors of in-hospital mortality were: hypernatremia (HR 9.12), lymphocyte count

Since December 2019, coronavirus disease 2019 (COVID-19) pandemic has spread from China all over the world, many COVID-19 outbreaks have been reported in long-term care facilities (LCTF). However, data on clinical characteristics and prognostic factors in such settings are scarce. We conducted a retrospective, observational cohort study to assess clinical characteristics and baseline predictors of mortality of COVID-19 patients hospitalized after an outbreak of SARS-CoV-2 infection in a LTCF.A total of 50 patients were included. Mean age was 80 years (SD, 12 years), and 24/50 (57.1%) patients were males. A total of 42/50 (84%) patients experienced symptoms of SARS-CoV-2 infection. The overall in-hospital mortality rate was 32%. In Cox regression, significant predictors of in-hospital mortality were: hypernatremia (HR 9.12), lymphocyte count Our study shows a high in-hospital mortality rate in a cohort of elderly patients with COVID-19 and hypernatremia, lymphopenia, CVD other than hypertension, and higher IL-6 serum levels were identified as independent predictors of in-hospital mortality. Further studies are necessary to better understand and confirm our findings in the setting of a LTCF outbreak of COVID-19.

Background and objectives: In Italy, Hepatitis C Virus (HCV) infections are most prevalent in people older than 50 years of age, who often experience multi-morbidities, take co-medications, and have a long history of liver disease. These characteristics could potentially affect tolerability of HCV treatments and adherence in this subgroup. After achievement of sustained virological response (SVR), retention into care is very important both to detect the onset of possible complications and prevent further infections. In this study, SVR rates and retention into care of patients treated with directly acting antivirals (DAAs) of a single-center cohort in Southern Italy were evaluated. Materials and Methods: Patients treated with directly acting antivirals from 2014 to 2018 were included. Patients were stratified by age (i.e., &lt, 65 vs. &ge, 65 years) and by cirrhosis presence (i.e., liver stiffness &gt, 14.6 KPa or clinical/ultrasound cirrhosis vs. absence of these criteria). Primary outcome was availability of SVR at Weeks 12&ndash, 24 after the end of treatment. Inter- and intra-group comparisons were performed along the follow-up for significant laboratory parameters. Results: In total, 212 patients were treated, 184 (87%) obtained SVR after the first treatment course and 4 patients after retreatment. Twenty-two (10.4%) patients were lost to follow-up before assessment of SVR, and two patients died before the end of treatment for liver decompensation. Considering only the first treatment episode, per protocol analysis (i.e., excluding patients lost to follow-up) showed the following rates of SVR: 97% (overall), 97% (older age group), 96% (age group &lt, 65 years), 94% (cirrhotics), and 100% (non-cirrhotics). By contrast, at the intention to treat analysis (i.e., patients lost were computed as failures), SVR percentages were significantly lower for patients &lt, 65 years of age (80%) and for non-cirrhotics (85%). Conclusions: High rates of SVR were obtained. However, younger patients and those without cirrhosis displayed an apparent high risk of being lost to follow-up. This may have important implications: since those who are lost may transmit HCV in case SVR is not achieved, these subpopulations should receive appropriate counselling during treatment.

Introduction The soluble receptor of urokinase plasminogen activator (suPAR) is an innate immunity/inflammation biomarker predicting cardiovascular (CV) and non-CV events in various conditions, including type 2 diabetic patients on dialysis. However, the relationship between suPAR and clinical outcomes in the hemodialysis population at large has not been tested. Methods We measured plasma suPAR levels (R&D enzyme-linked immunosorbent assay [ELISA]) in 1038 hemodialysis patients with a follow-up of 2.9 years (interquartile range = 1.7−4.2) who were enrolled in the PROGREDIRE study, a cohort study involving 35 dialysis units in 2 regions in Southern Italy. Results suPAR was strongly (P < 0.001) and independently related to female gender (β = −0.160), age (β = 0.216), dialysis vintage (β = 0.264), CV comorbidities (β = 0.105), alkaline phosphatase (β = 0.136), albumin (β = −0.147), and body mass index (BMI; β = 0.174) (all P < 0.006). In fully adjusted analyses, suPAR tertiles predicted the risk of all-cause mortality (third tertile vs. first tertile hazard ratio (HR) = 1.91, 95% confidence interval (CI) = 1.47 – 2.48, P < 0.001), CV mortality (HR = 1.47, 95% CI = 1.03–2.09, P = 0.03), and non-CV mortality (HR = 1.94, 95% CI = 1.28–2.93, P = 0.002); these relationships were not modified by diabetes or other risk factors. suPAR added only modest prognostic risk discrimination and reclassification power for these outcomes to parsimonious models based on simple clinical variables. Conclusion In conclusion, suPAR robustly predicted all-cause and both CV and non-CV mortality in a large unselected hemodialysis population. Intervention studies are needed to definitively test the hypothesis that suPAR is causally implicated in clinical outcomes in this population.

Coadministration of 2 or more compounds can alter both the pharmacokinetics and pharmacodynamics of individual compounds. While experiments on pharmacodynamic drug-drug interactions are usually performed in an in vitro setting, this experiment focuses on an in vivo setting. The change over time of a safety biomarker is modeled using an indirect response model, in which the virtual pharmacokinetic profile of one compound drives the effect of the other. Several experiments at different dose level combinations were performed sequentially. While a traditional frequentist analysis consists of estimating the model parameters based on all the data simultaneously, in this work, we consider a Bayesian inference framework allowing to incorporate the results from a historical dose-response experiment.

The present manuscript aims to discuss the implications of sequential knowledge integration of small preclinical trials in a Bayesian pharmacokinetic and pharmacodynamic (PK-PD) framework. While, at first sight, a Bayesian PK-PD framework seems to be a natural framework to allow for sequential knowledge integration, the scope of this paper is to highlight some often-overlooked challenges while at the same time providing some guidances in the many and overwhelming choices that need to be made. Challenges as well as opportunities will be discussed that are related to the impact of (1) the prior specification, (2) the choice of random effects, (3) the type of sequential integration method. In addition, it will be shown how the success of a sequential integration strategy is highly dependent on a carefully chosen experimental design when small trials are analyzed. European Union's Horizon 2020 research and innovation programme, Grant/Award Number: 633567; IAP Research Network P7/06 of the Belgian State (Belgian Science Policy); French National Cancer Institute (INCa), Grant/Award Number: INCA 9539

Background:LNA043 is a modified, recombinant version of the human angiopoietin-like 3 (ANGPTL3) protein acting directly on cartilage-resident cells to transmit its cartilage anabolic effect. A first-in-human study previously demonstrated the favourable safety profile and the modulation of several pathways involved in cartilage homeostasis and osteoarthritis (OA)1. A previous proof-of-mechanism imaging study used high field (7 Tesla) magnetic resonance imaging (MRI) to show formation of hyaline-like tissue after a single injection of 20 mg LNA043 (unpublished data).Objectives:To evaluate non-invasively the chondro-regenerative capacity of multiple intra-articular (i.a.) injections of LNA043 in patients with articular cartilage lesions in the knee (NCT03275064).Methods:This was a randomised, double-blind, placebo (PBO)-controlled, proof-of-concept study in patients with a partial thickness cartilage lesion. In total, 58 patients (43 [20 mg LNA043]; 15 [PBO]), stratified by lesion type (condylar or patellar) were treated with 4 weekly i.a. injections. The primary endpoint was T2 relaxation time measurement as a marker of collagen fiber network, and cartilage lesion-volume was a secondary endpoint, both using 3-Tesla MRI. Assessments were performed at baseline, weeks (wks) 8, 16, 28 and 52 (the latter in 23/58 patients). While lesion-volume for the secondary endpoint was determined from manually segmented images, the cartilage volume of 21 sub-regions spanning the entire knee was also measured from 3D isotropic MR images employing an automated segmentation prototype software (MR Chondral Health 2.1 [MRCH], Siemens Healthcare)2. An exploratory analysis evaluated the treatment effect for the additive volume of the 3 subregions in the weight-bearing area of the medial femur.Results:No change in T2 relaxation time was detected between treatment and PBO groups. Manual segmentation showed continuous filling of the cartilage lesions up to wk 28 in LNA043-treated patients with femoral lesions (p=0.08, vs PBO) while no effect was detected for patients with patellar lesions. Given the limitations of measuring small, irregularly shaped lesions with manual image-analysis, the MRCH approach was used (Figure 1). In the medial femoral weight-bearing region, refilling was detected over time (Δ=123 mm3 at wk 28, N= 37, p= 0.05). No overgrowth was detected in the lateral femoral condyles without cartilage damage. The overall safety profile was favourable; only mild/moderate local reactions were reported, including a higher incidence of joint swelling (9.3% vs 0%) and arthralgia (11.6% vs 6.7%) for LNA043 vs PBO resolving spontaneously or with paracetamol/NSAIDs. No anti-drug antibodies were detected.Conclusion:Treatment with 4 weekly i.a. injections of 20 mg LNA043 resulted in regeneration of damaged cartilage in patients with femoral articular cartilage lesions. Automated measurement of cartilage volume in the femoral index region was able to detect a relevant treatment effect and was found to be more sensitive than the manual segmentation method. No sign of cartilage overgrowth was observed in healthy femoral regions. A Phase 2b study in patients with mild to moderate knee OA is in preparation.References:[1]Scotti et al. ACR Convergence 2020; Abstract #1483[2]Juras et al. Cartilage 2020; Sep 29:1-12Disclosure of Interests:Siegfried Trattnig: None declared, Celeste Scotti Shareholder of: Novartis, Employee of: Novartis, Didier Laurent Shareholder of: Novartis, Employee of: Novartis, Vladimir Juras: None declared, Scott Hacker Grant/research support from: Novartis, Brian Cole: None declared, Libor Pasa: None declared, Roman Lehovec: None declared, Pavol Szomolanyi: None declared, Esther Raithel Employee of: Siemens Healthcare GmbH, Franziska Saxer Shareholder of: Novartis, Employee of: Novartis, Jens Praestgaard Shareholder of: Novartis, Employee of: Novartis, Fabiola La Gamba Shareholder of: Novartis, Employee of: Novartis, José L. Jiménez Employee of: Novartis, David Sanchez Ramos Shareholder of: Novartis, Employee of: Novartis, Ronenn Roubenoff Shareholder of: Novartis, Employee of: Novartis, Matthias Schieker Shareholder of: Novartis, Employee of: Novartis

The present manuscript aims to discuss the implications of sequential knowledge integration of small preclinical trials in a Bayesian PK-PD framework. While, at first sight, a Bayesian PK-PD framework seems to be a natural framework to allow for sequential knowledge integration, the scope of this paper is to highlight some often-overlooked challenges while at the same time providing some guidances in the many and overwhelming choices that need to be made. Challenges as well as opportunities will be discussed that are related to the impact of (i) the prior specification, (ii) the choice of random effects, (iii) the type of sequential integration method. In addition, it will be shown how the success of a sequential integration strategy is highly dependent on a carefully chosen experimental design when small trials are analyzed.

Although Bayesian methods are expanding considerably in various scientific areas, their applications in the field of pharmacokinetic/pharmacodynamic (PK/PD) modelling and simulation is still relatively limited. In this work, Bayesian techniques are used to facilitate the estimation of a novel PK/PD model which is developed to quantify the extent of PD synergy between two compounds using historical in vivo data. The model is fitted using package rstan, the R interface to Stan. Stan is a recently developed software package which allows an efficient estimation using the No-U-Turn Sampler (NUTS). Since the data consist of a series of 11 trials performed sequentially, a Bayesian sequential integration is considered: the posteriors resulting from the analysis of one trial are used to specify the hyperparameters of the priors of the next trial. The recursive update of posterior distributions whenever new information is available is less computationally intensive compared to the analysis of all data up to the current trial. However, this method implies the analysis of a limited amount of information during the first integration steps, which may hinder the estimation process. The aim of the present work is to discuss challenges as well as opportunities which are related to the impact of (i) prior specification, (ii) random effect choice and (iii) experimental design. In addition, the results from an extensive simulation study assessing the performance of the Bayesian sequential integration for an increasing model complexity are evaluated. The results suggest that the use of informative prior distributions reduces the correlation among parameters and improves the accuracy of estimates. Moreover, choosing the random effect on a parameter that is not highly correlated with others avoids overcompensations, thus ensuring better predictions. On top of that, trials should be designed so that each of them explores an exhaustive number of doses and sampling times. European Union's Horizon 2020 research and innovation programme, Grant/Award Number: 633567; IAP Research Network P7/06 of the Belgian State (Belgian Science Policy); French National Cancer Institute (INCa), Grant/Award Number: INCA 9539

Background Intravenous (IV) zanamivir could be a suitable alternative for the treatment of severe influenza A(H1N1)pdm09 infection in patients who are unable to take oral or inhaled medication, for example, those on mechanical ventilation and extracorporeal membrane oxygenation (ECMO). However, data on the clinical outcomes of such patients is limited. Case presentation We report the clinical outcomes of four patients who were admitted at the intensive care unit during the 2017–2018 influenza season with severe sepsis (SOFA score > 11) and acute respiratory distress syndrome requiring ECMO and mechanical ventilation. Two patients were immune-compromised. The A(H1N1)pdm09 genome was confirmed by polymerase chain reaction (PCR) on nasopharyngeal specimen swabs prior to administration of IV zanamivir at a dose of 600 mg twice daily. Weekly qualitative PCR analysis was done to monitor viral clearance, with zanamivir treatment being discontinued upon receipt of negative results. In addition, the patients were managed for concomitant multidrug-resistant bacterial infections, with infection resolution confirmed with blood cultures. The median time for zanamivir treatment was 10 days (IQR 10–17). The clinical outcome was favourable with all four patients surviving and improving clinically. All four patients achieved viral clearance of A(H1N1)pdm09 genome, and resolution of multidrug-resistant bacterial infections. Conclusions IV zanamivir could be a good therapeutic option in patients with severe influenza A(H1N1)pdm09 infection who are unable to take oral or aerosolised antiviral medication. We recommend prospective randomized control trials to support this hypothesis.