Genotyping and molecular investigation of plasmid-mediated carbapenem resistant clinical Klebsiella pneumoniae isolates in Egypt

Klebsiella pneumoniae is a multidrug-resistant nosocomial pathogen. Carbapenem resistance is mediated mainly by enzymes carried on transmissible plasmids causing their dissemination among other members of Enterobacteriaceae. This study aimed to molecularly detect carbapenem resistance genes in K. pneumoniae clinical isolates, genotype them using ERIC-PCR, and investigate plasmid transformation of resistant genes by using ERIC-PCR and sequencing. Methods: Antimicrobial resistance of sixty carbapenem-resistant K. pneumoniae strains was evaluated by using the disc diffusion method. Five carbapenemases' genes were amplified by conventional PCR. Genotyping was performed using ERIC-PCR. Gene transformation was performed for the five genes to sensitive isolates. Wild and transformed isolates were genetically investigated using ERIC-PCR and sequencing. Results: Carbapenem resistance in our isolates was associated with high resistance to all tested antibiotics. The 60 K. pneumoniae isolates were divided into 6 resistor types. The prevalence of KPC, IMP, VIM, NDM, and OXA-48 genes were 17%, 63%, 93%, 85% and 100%, respectively. Dendrogram analysis showed 57 distinct patterns, arranged in three clusters. The five genes were transformed successfully into sensitive isolates. ERIC profiles of wild and transformed isolates showed cluster A contained all the wild isolates, and cluster B contained all transformed isolates. Genetic sequences of the 5 genes reflected high genetic similarity with the GenBank reference genes before plasmid transformation; however, a distinguishable decrease of genetic similarity was observed after transformation. Conclusion: Plasmid-mediated carbapenem resistance in K. pneumoniae and its dissemination among different strains is a real threat to public health

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

Similarity Evaluation Based on Contextual Modelling

Measuring Text similarity problem still one of opened fields for research area in natural language processing and text related research such as text mining, Web page retrieval, information retrieval and textual entailment. Several measures have been developed for measuring similarity between two texts: such as Wu and Palmer, Leacock and Chodorow measure and others . But these measures do not take into consideration the contextual information of the text .This paper introduces new model for measuring semantic similarity between two text segments. This model is based on building new contextual structure for extracting semantic similarity. This approach can contribute in solving many NLP problems such as te xt entailment and information retrieval fields