Prediction of Effect of Pegylated Interferon Alpha-2b plus Ribavirin Combination Therapy in Patients with Chronic Hepatitis C Infection

Treatment with pegylated interferon alpha-2b (PEGIFN) plus ribavirin (RBV) is standard therapy for patients with chronic hepatitis C. Although the effectiveness, patients with high titres of group Ib hepatitis C virus (HCV) respond poorly compared to other genotypes. At present, we cannot predict the effect in an individual. Previous studies have used traditional statistical analysis by assuming a linear relationship between clinical features, but most phenomena in the clinical situation are not linearly related. The aim of this study is to predict the effect of PEG IFN plus RBV therapy on an individual patient level using an artificial neural network system (ANN). 156 patients with HCV group 1b from multiple centres were treated with PEGIFN (1.5 µg/kg) plus RBV (400–1000 mg) for 48 weeks. Data on the patients' demographics, laboratory tests, PEGIFN, and RBV doses, early viral responses (EVR), and sustained viral responses were collected. Clinical data were randomly divided into training data set and validation data set and analyzed using multiple logistic regression analysis (MLRs) and ANN to predict individual outcomes. The sensitivities of predictive expression were 0.45 for the MLRs models and 0.82 for the ANNs and specificities were 0.55 for the MLR and 0.88 for the ANN. Non-linear relation analysis showed that EVR, serum creatinine, initial dose of Ribavirin, gender and age were important predictive factors, suggesting non-linearly related to outcome. In conclusion, ANN was more accurate than MLRs in predicting the outcome of PEGIFN plus RBV therapy in patients with group 1b HCV

Complicated pyelonephritis caused by Proteus alimentorum in a woman with peritoneal cancer: a case report

Abstract Background Proteus spp. are widespread in the environment and comprise a part of the normal flora of the human gastrointestinal tract. Only six species in this genus, including Proteus mirabilis, Proteus vulgaris, Proteus terrae, Proteus penneri, Proteus hauseri, and Proteus faecis, have been isolated from human clinical specimens. However, there are no reports of Proteus alimentorum isolated from humans, and the clinical characteristics of P. alimentorum infection are unknown. Case presentation An 85-year-old female patient with peritoneal cancer was hospitalized for complicated pyelonephritis and bacteremia caused by P. alimentorum. The patient received antimicrobial therapy and was discharged on day 7 of hospitalization. No recurrence was observed 14 days after the treatment. Various methods were used to identify the Proteus sp. Furthermore, the VITEK-2 GN ID card resulted in low discrimination between P. hauseri and P. penneri. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry showed P. hauseri with a spectral score of 2.22 as the best match. Nevertheless, the pathogen was identified as P. alimentorum based on genetic investigation using 16 S rRNA gene sequencing and biochemical tests. Conclusion Proteus alimentorum is a human pathogen, and its infection has an excellent therapeutic response to antimicrobials based on antimicrobial susceptibility. Genomic methods may be helpful for the precise identification of P. alimentorum