Helicobacter pylori Infection and Non-alcoholic Fatty Liver Disease: A Systematic Review and Meta-Analysis

Since numerous studies have stated that there may be a relationship between Helicobacter pylori infection and nonalcoholic fatty liver disease, and because of the high prevalence of both conditions worldwide, this study investigated the risk of non-alcoholic fatty liver disease in patients infected with H. pylori. Following a systematic review of PubMed, Scopus, Web of Science and Embase, and a search in Google Scholar using MeSH terms such as H. pylori and non-alcoholic fatty liver disease, the relevant papers up to November 2020 were reviewed. All cohort, case-control, and cross-sectional studies that examined the risk of developing non-alcoholic fatty liver disease in patients infected with H. pylori entered this study. A meta-analysis was conducted in STATA 11. This systematic review examined 22 papers with 117 117 participants (33 711 patients infected with H. pylori and 83 406 participants as control) and 20 studies were subjected to meta-analysis The results indicated a 22% to 27% increase in the risk of developing non-alcoholic fatty liver disease in patients infected with H. pylori (crude odds ratio: 1.27, 95% CI: 1.17-1.33; and adjusted odds ratio: 1.22, 95% CI: 1.09-1.35). According to the subgroup analysis, the study region, sample size, and the method of diagnosing H. pylori were the factors contributing to the high heterogeneity. The meta-analysis revealed the increased risk of developing non-alcoholic fatty liver disease in patients infected with H. pylori. This indicates that H. pylori is a serious risk factor in patients susceptible to NAFLD.

[Correlation between previous coronary artery stenting and early mortality in patients undergoing coronary artery bypass graft surgery]

BACKGROUND

In this study, we examine the effect of previous percutaneous intervention on the rate of adverse perioperative outcome in patients undergoing coronary artery bypass graft surgery (CABG).

METHODS

Outcomes of 240 CABG patients, collected consecutively in an observational study, were compared. Gp A (n=35) had prior PCI before CABG and Gp B (n=205) underwent primary CABG.

RESULTS

Statistically significant results were obtained for the following preoperative criteria: previous myocardial infarction: 48.6% vs 36.6% (P=0.003), distribution of CAD (P=0.0001), unstable angina: 45.7% vs 39% (P=0.04). For intraoperative data, the total number of established bypasses was 2.6 (GpA) vs 2.07 (Gp B) (P=0.017), with the number of arterial bypass grafts being: 20% vs 13% (P=ns). Regarding the postoperative course, no significant difference in troponine I rate, 24-hour bleeding: 962 ml (Gp A) vs 798 ml (Gp B) (P=0.004), transfusion (PRBC unit): 3.63 (Gp A) vs 2.5 (Gp B) (P=0.006). Previous PCI emerged as an independent predictor of postoperative in-hospital mortality (OR 2.24, 95% CI [1.52-2.75], P<0.01).

CONCLUSION

Patients with prior PCI presented for CABG with more severe CAD. Thirty-day mortality and morbidity were significantly higher in patients with prior PCI.

Prognostic significance of immunohistochemical markers in non-small cell lung cancer

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Background: The purpose of this study is to use a large patient population to identify immunohistochemical (IHC) biomarkers to enable improved prognostication in patients with non-small cell lung cancer (NSCLC). Methods: A tissue microarray was constructed using duplicate 0.6 mm cores of formalin-fixed paraffin embedded tissue blocks from 609 patients with NSCLC. IHC was used to detect 11 biomarkers including EGFR, HER2, HER3, p53, p63, Bcl-1, Bcl-2, TTF-1, CEA, Ch, and SNP. A clinical database was created prospectively at the time of tissue collection. Survival outcomes were obtained from a Provincial Cancer Registry database. Results: Male to female ratio was 400:209; median age 63yrs (range 35–82); median survival 3.5yrs (mean 5.7). All specimens were reviewed: 243 adenocarcinoma (ACA), 272 squamous cell carcinoma (SCC), 35 large cell carcinoma, 32 non-small cell carcinoma NOS, and 6 other (giant cell carcinoma). 21 patients with other histologies were excluded. Survival data for 535 cases was available. As of June 2005, 429 patients (80%) had died; of these 286 (54%) died of lung cancer, 117 (22%) died of other known causes, and for 26 (5%) the cause of death was not available. Bcl-2 (p = 0.007) was the only biomarker to predict better overall survival (OS). Bcl-2 (p = 0.021) and p63 (p = 0.025) were significant for disease specific survival (DSS) in all NSCLC. Analysis of the subgroups indicated that p63 was significant (p = 0.039) for DSS in squamous cell carcinoma (SCC) but not for adenocarcinoma (ACA) (p = 0.81). Bcl-2 was not significant for DSS in either subgroup (p = 0.28 for SCC, p = 0.112 for ACA). EGFR expression was associated with improved DSS in SCC (p = 0.012) but not for ACA. Co-expression of EGFR-HER3 was more likely in SCC then in ACA (p = 0.033). There was no correlation between outcome and any combination or clustering of biomarkers. Conclusions: The biomarkers p63 and Bcl-2 are predictive of DSS in NSCLC. EGFR expression is predictive of DSS in SCC. Sub-classification of NSCLC by histopathology is important as the relevance of some biomarkers (EGFR) would be lost if pooled. p63, Bcl-2, and EGFR may be used as prognostic markers in patients with NSCLC. Co-expression of EGFR-HER3 is more likely in SCC then in ACA. This may help explain the differential response to EGFR inhibitors in SCC versus ACA.

No significant financial relationships to disclose.

Postresonance electromagnetic absorption by man and animals

A surface integral equation (SIE) method is used to calculate the specific absorption rate (SAR) in spherically capped cylindrical models irradiated by an axially incident electromagnetic plane wave (K polarization) in a frequency range for which calculations previously have not been available (80-400 MHz for man models). In the SIE method, the electromagnetic (EM) field relations are formulated in terms of electric and magnetic currents on the surface of the model. The average SAR is calculated from the far scattered EM fields by means of the forward scattering theorem. SAR data calculated by the SIE method agree with data calculated by the extended boundary condition method (EBCM) for frequencies up to 80 MHz (the upper frequency limit of the EBCM) for man models. For rat models exposed to 1-3 GHz radiation, reasonable agreement was also obtained with the limited experimental data available.