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Osteoarticular infections are major disabling diseases that can occur after orthopedic implant surgery in patients. The management of these infections is very complex and painful, requiring surgical intervention in combination with long-term antibiotic treatment. Therefore, early and accurate diagnosis of the causal pathogens is essential before formulating chemotherapeutic regimens. Although culture-based microbiology remains the most common diagnosis of osteoarticular infections, its regular failure to identify the causative pathogen as well as its long-term modus operandi motivates the development of rapid, accurate, and sufficiently comprehensive bacterial species-specific diagnostics that must be easy to use by routine clinical laboratories. Based on these criteria, we reported on the feasibility of our DendrisCHIP

Clinical microbiology is experiencing the emergence of the syndromic approach of diagnosis. This paradigm shift will require innovative technologies to detect rapidly, and in a single sample, multiple pathogens associated with an infectious disease. Here, we report on a multiplex technology based on DNA-microarray that allows detecting and discriminating 11 bacteria implicated in respiratory tract infection. The process requires a PCR amplification of bacterial 16S rDNA, a 30 min hybridization step on species-specific oligoprobes covalently linked on dendrimers coated glass slides (DendriChips®) and a reading of the slides by a dedicated laser scanner. A diagnostic result is delivered in about 4 h as a predictive value of presence/absence of pathogens using a decision algorithm based on machine-learning method, which was constructed from hybridization profiles of known bacterial and clinical isolated samples and which can be regularly enriched with hybridization profiles from clinical samples. We demonstrated that our technology converged in more than 95% of cases with the microbiological culture for bacteria detection and identification.

Objectif Il est etabli que les pathologies respiratoires du sommeil (PRDS) sont a l’origine d’accidents vasculaires cerebraux severes. La mise au point de methodes diagnostiques en e-sante permettrait de detecter ces PRDS avant la survenue des graves complications. Dans cette perspective nous voulons valider la mesure des apnees a partir d’un simple electrocardiogramme nocturne. Methodes Nous avons compare deux methodes de diagnostic des PRDS basees sur des enregistrements classiquement utilises en ambulatoire. La population etait composee de 1046 patients hospitalises a l’UNV du CHU de Saint-Etienne pour un AVC. La methode classique consistait en la mesure de l’oxymetrie arterielle et du flux ventilatoire (AHI) par le Holter Vista O2 (oxymetrie et impedance thoracique). La nouvelle mesure evaluee consistait en une methode de diagnostic originale basee sur l’analyse de la morphologie de l’ECG enregistre simultanement : Electrocardiogram Derived Respiration (EDR). Resultats Les PRDS etaient tres frequentes dans cette population, atteignant 73,3 % des patients avec un seuil d’AHI a 15. La correlation entre l’AHI et l’EDR etait tres significative avec un p inferieur a 0,0001 mais presentait un R2 limite a 0,28. Il en est de meme pour la correlation entre EDR et des evenements hypoxiques. Conclusion Nous avons trouve un faible correlation entre EDR et AHI. Nous pensons que l’EDR est different de l’AHI car il est sensible a la duree et a la profondeur des evenements apneiques alors que l’AHI ne fait que compter ces evenements. Des etudes ulterieures seront necessaires pour evaluer le pouvoir predictif de l’EDR.