Caractéristiques bactériologiques des infections de liquide de dialyse péritonéale

La péritonite infectieuse (PI) est la principale complication de la dialyse péritonéale (DP). L'objectif de notre travail était de déterminer l'écologie bactérienne des PI et d'adapter l'antibiothérapie selon les germes isolés et les résistances observées. Étude rétrospective effectuée chez tous les enfants traités par DP et ayant présenté une PI dans le service de pédiatrie de l'hôpital Charles Nicolle de Tunis  (2004-2013). Au total, 61 ont développé 97 PI. L'incidence des PI était de 0,75 épisode/patient-année. La culture du LDP était négative dans 40 cas. Les Gram Positif ont été notés dans 56% des cas avec prédominance du Staphylococcus aureus. Les Gram négatif étaient retrouvés en seconde position (40%) représentés principalement par le Klebsiella  pneumoniae et le Pseudomonas aeruginosa. Des souches de Staphylocoque méticilline résistant étaient isolées dans 21,4%. Les bactéries à Gram positif étaient résistantes aux céphalosporines de première génération dans 25% des cas et aucune résistance à la vancomycine n'avait été décelée. Les bactéries à Gram négatif avaient une résistance globale de 38% avec des souches C-lactamase à spectre élargi (BLSE). L'antibiothérapie empirique devra couvrir les germes à Gram positif par la vancomycine et les germes à Gram négatif par la ceftazidime.Key words: Péritonite, antibiotiques, dialyse péritonéale, bactéries, enfan

Towards a decision-aid tool in the case of chemotherapy treatment for low-grade glioma

International audienceDiffuse low-grade gliomas are rare brain tumors of young adults. Several treatments are used by the neuro oncologist (surgery, chemotherapy, radiotherapy). Our goal is to create a decision-aid tool to ensure an individualized treatment strategy.In clinical practice, the monitoring of gliomas is based on the estimation of tumor volume, obtained from MRI. This is done either through the three diameters method, or through a manual segmentation followed by a software reconstruction ; a subjective test helped us to compare statistically the two methods. We explore also semi-automatic segmentation algorithms which seem to be a promising way.Once we studied the reliability in the calculation of the interest variable, we are interested in the modeling of the evolution of the tumor’s size, in order to help oncologists in decision making. Crucial questions include identifying subgroups of patients who could benefit from chemotherapy, determining the best time to initiate or end chemotherapy, ... Our aim is to design new predictive models dedicated to the evolution of the tumor. Preliminary but very promising results have been obtained by regression models on a database of 55 patients under neoadjuvant chemotherapy treatment. Two statistical models (linear and exponential) have been identified

Modèles prédictifs pour les gliomes diffus de bas grade sous chimiothérapie

National audienceLes gliomes diffus de bas grade sont des tumeurs cérébrales primitives rares des adultes. Ces tumeurs progressent de manière continue au cours du temps et se trans-forment, par la suite, en tumeurs de grade supérieur dont la malignité est associée à un handicap neurologique et à une issue fatale. La taille de la tumeur est l'un des facteurs pronostiques les plus importants. De ce fait, il est d'une grande importance d'évaluer le volume tumoral pendant le suivi des patients. On recommande, pour ce faire, l'utilisation de l'IRM comme modalité. En outre, si la chirurgie reste la première option thérapeutique pour les gliomes diffus de bas grade, la chimiothérapie est de plus en plus utilisée (avant ou après une chirurgie potentielle). Ce-pendant, des questions cruciales et difficiles restent à ré-soudre : l'identification de sous-groupes de patients qui pourraient bénéficier de la chimiothérapie, la détermination du meilleur moment pour entamer une chimiothérapie, la définition de la durée de la chimiothérapie et l'évaluation du meilleur moment pour effectuer une chirurgie ou, le cas échéant, une radiothérapie. Dans ce travail, nous nous proposons d'aider les cliniciens dans la phase de prise de décision, en concevant de nouveaux modèles prédictifs dédiés à l'évolution du diamètre tumoral. Nous proposons deux modèles statistiques (linéaires et exponentiels) que nous avons testés sur une base de données de 16 patients dont la chimiothérapie a duré entre 14 et 32 mois, avec une durée moyenne de 22,8125 mois. Le choix du modèle le plus approprié a été réalisé avec le critère d'information d'Akaike corrigé. Les résultats sont très prometteurs, avec des coefficients de détermination, pour le modèle linéaire, variant entre 0,79 et 0,97 et une valeur moyenne de 0,90. Cela montre qu'il est possible d'alerter le clinicien sur un changement de la dynamique du diamètre tumoral

Statistical evaluation of manual segmentation of a diffuse low-grade glioma MRI dataset

International audienceSoftware-based manual segmentation is critical to the supervision of diffuse low-grade glioma patients and to the optimal treatment’s choice. However, manual segmentationbeing time-consuming, it is difficult to include it in the clinicalroutine. An alternative to circumvent the time cost of manualsegmentation could be to share the task among different practitioners, providing it can be reproduced. The goal of our work is to assess diffuse low-grade gliomas’ manual segmentation’s reproducibility on MRI scans, with regard to practitioners, their experience and field of expertise. A panel of 13 experts manually segmented 12 diffuse low-grade glioma clinical MRI datasets using the OSIRIX software. A statistical analysis gave promising results, as the practitioner factor, the medical specialty and the years of experience seem to have no significant impact on the average values of the tumor volume variable

Predictive models for diffuse low-grade glioma patients under chemotherapy

International audienceDiffuse low-grade gliomas are rare primitive cerebral tumours of adults. These tumors progress continuously over time and then turn to a higher grade of malignancy associated with neurological disability, leading ultimately to death. Tumour size is one of the most important prognostic factors. Thus, it is of great importance to be able to assess the volume of the tumor during the patients’ monitoring.MRI is nowadays the recommended modality to achieve this. Furthermore, if surgery remains the first option for diffuse low-grade gliomas, chemotherapy is increasingly used (before or after a possible surgery). However, crucial and difficult questions remain to be answered: identifying subgroups ofpatients who could benefit from chemotherapy, determining the best time to initiate chemotherapy, defining the duration of chemotherapy and evaluating the optimal time to perform surgery, or otherwise radiotherapy. In this study, we propose to help clinicians in decision-making, by designing new predictivemodels dedicated to the evolution of the diameter of the tumor. Two proposed statistical models (linear and exponential) have been validated on a database of 16 patients whose temozolomide-based chemotherapy lasted between 14 and 32 months, with an average duration of 22.8 months. The selection of the most appropriate model has been achieved with the corrected Akaike’s Information Criterion. The results are very promising, with coefficients of determination varying from 0.79 to 0.97 with an average value of 0.90 for the linear model. This shows it is possible to alert the clinician to a change in the tumor diameter’s dynamics

Evaluation statistique de la segmentation manuelle de données IRM de gliomes diffus de bas grade

National audienceLes gliomes diffus de bas grade sont des tumeurs cérébrales primitives rares des adultes. La segmentation manuelle est essentielle pour le suivi des patients atteints de cette tumeur et pour le choix du traitement optimal. Cette méthode étant chronophage, il semble difficile de l'inclure dans la routine clinique. La segmentation automatique apparaît donc comme une solution potentielle pour répondre à cette problématique. Cependant, les algorithmes actuels de segmentation automatique n'ont pas encore prouvé leur efficacité pour les gliomes diffus de bas grade en raison de la spécificité de ce type de tumeurs. De ce fait, la segmentation manuelle demeure, aujourd'hui, la seule vérité terrain dans ce domaine. Une alternative pour contourner la perte en temps liée à la segmentation manuelle serait de partager la tâche entre différents praticiens, à condition que cette dernière soit reproductible. Le but de notre travail est d'évaluer la reproductibilité de la segmentation manuelle des examens IRM de gliomes diffus de bas grade, en fonction des praticiens, de leur expérience et de leur spécialité. Dans ce travail, nous avons conduit une étude statistique sur les volumes tumoraux d'un panel de 14 experts ayant manuellement segmenté 12 examens IRM de gliomes diffus de bas grade en utilisant le logiciel OsiriX. La plupart des études de segmentation de tumeurs cérébrales publiées mélangent différents types de tumeurs et comparent la segmentation automatique à la segmentation manuelle. Notre étude, au contraire, se focalise uniquement sur les gliomes diffus de bas grade et sur leur segmentation manuelle, car ce sont les plus difficiles à délimiter en raison de leur nature invasive. Une analyse statistique a fourni des résultats prometteurs en démontrant que les facteurs praticien, spécialité médi-cale et nombre d'années d'expérience n'ont pas d'impact significatif sur les valeurs moyennes de la variable volume tumoral

Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries

Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P < 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Delay of fibrinolysis in St- elevation myocardial infarction: Results of an investigation conducted in a single center in Sousse Tunisia

Background: The aim of our study was to assess the delay of fibrinolysis in ST elevation myocardial infarction (STEMI) in our region and to identify characteristics associated with prolonged delay. Patients and Methods: We analyzed clinical characteristics of a prospective cohort of unselected patients admitted for (STEMI). The study was conducted over three years 2007-2009 and 250 patients were included in a single center without capability of percutaneous coronary intervention. Results: The mean age of our patients was 58±13, 7 years. Ninety percent of our patients consult directly the emergency department and 61, (5%) of them were admitted within first 6 hours of onset of symptoms. Median time to reperfusion was 46 min. Predictor of this long delay to initiate fibrinolysis were inter-department decision OR 6; 95% CI 3,48-10,34, diabetes OR 2,25; 95% CI 1,28-3,96 age >58,4 years OR 1,97; 95% CI 1,19-3,25 and transfer from regional hospital to our center OR 1,78; 95% 1,03-3.07. Conclusion: These results suggest that improvement in organization health care system can shorten delay to fibrinolysis in a center without percutaneous coronary intervention capability

264: Myeloperoxidase, hs CRP and endothelial dysfunction in cardiovascular risk assessment in diabetic and hypertensive patients

IntroductionSeveral inflammatory markers have been associated with a greater likelihood of cardiovascular diseases. Of those C-reactive protein (CRP) and myeloperoxidase (MPO) are the most well known.The development of sensitive rapid tests for MPO and hs-CRP, together with a simple hand-held reader promises to open up the possibility of identifying high-risk patients early enough for the introduction of prophylactic therapies or the adoption of beneficial life-style changes.ObjectivesWe propose to evaluate the cardiovascular risk for 50 hypertensive and diabetic patients by rapid tests for MPO and hs-CRP and to compare with endothelial function and Framingham score.ResultsWe evaluate prospectively 50 patients without cardiovascular events, the mean age is 53 years, 78% have mean or high CV risk according to the Framingham score and 38% presenting endothelial dysfunction.The statistical analysis showed a significant association between the rate of hs-CRP, the Framingham score (p=0,02, r=0,424), with the metabolic syndrome (p=0,0001), and endothelial dysfunction (p=0,001).MPO level is correlated with the sex (p=0,002), age (p=0,05), as well with the Framingham score (r=0,345), the metabolic syndrome (p=0,001), the endothelial dysfunction (p=0,001), and also with the LDL cholesterol. (p=0,04; r=0,3).In the same way, a significant Correlation was shown between hs-CRP and MPO (p=0,016; r=0,34).The hs-CRP test showed a good specificity (85%), and VPP (96%), a weak VPN (27%).However MPO test showed a low specificity (25%) low sensitivity (25%), VPP of (73%) and a low VPN (5%).ConclusionThe hs-CRP represents the inflammatory marker most relevant in the prediction of risk CV, better than the MPO.These markers reflect the clinical potential of atherothrombotic disease may allow more precise risk stratification and prognostication in high-risk populations, and perhaps earlier diagnosis and intervention in patients at risk for or with occult cardiovascular disease