No abstract

Ventilator-associated pneumonia (VAP) is the most frequent infection in intensive care units (ICU). It is associated with high rates of long morbidity and mortality. Management of a case of VAP is often said to add $40,000 to hospital costs USA. All these data directed our interest to study the etiology, risk factors, and antibiotic susceptibility patterns of VAP in ICU of Tanta University Hospital. This study included 36 cases of VAP. Endotracheal aspirates were obtained from all cases and microbiologically analyzed. Samples were collected over 1 year. Forty-two strains were isolated from 28 cases, while eight cases showed no bacterial growth. The most frequent organism was Staphylococcus aureus (30.95%), followed by Acinetobacter baumannii and Pseudomonas aeruginosa (21.43% for each), and the least common was Staphylococcus epidermidis (2.38%). Multi-drug resistance was detected in (50%) of the isolated bacteria in this study. Imipenem, amikacin, linezolid, vancomycin, and levofloxacin are recommended to be the most effective drugs in management of VAP. VAP is a serious problem in ICU carrying many risks for the patient live. Regimens of empirical treatment should take in consideration the update in the bacterial etiology and antibiotic susceptibility patterns of VAP.

No abstract

No abstract

Background: The differentiation between malignant (MPE) and tuberculous (TPE) pleural effusions should be considered in any patient with an exudative lymphocytic pleural effusion. A rapid precise diagnosis is valuable as the treatment and prognosis are totally different. The histopathological proof may shorten the time to differential diagnosis. But it may be invasive and costly. The aim of this study is to validate the clinical reliability of joined detection of cancer ratio (serum LDH to pleural ADA), cancer ratio plus (cancer ratio to percentage of pleural fluid lymphocytic count), pleural interferon gamma (pIFN-ϒ), and pleural carcinoembryonic antigen (pCEA) values to differentiate between lymphocytic pleural effusions. Results: Seventy-eight patients were included with mean age ± SD 53.09 ± 9.56 years old, 49 males and 29 females, diagnosed as 47 MPE, 24 TPE, and 7 others. Cancer ratio at cutoff value of ≥ 22 and cancer ration plus at cutoff value of ≥ 41 can discriminate MPE from any other cause with sensitivity (91.5%, 93.6%), specificity (87.5%, 91.7%), and diagnostic accuracy (90.1%, 92.9%) respectively. When the levels of pCEA and pIFN-ϒ were combined with cutoff value of cancer ratio, there were powerful diagnostic differentiating results. Conclusions: Cancer ratio and cancer ratio plus offered valid, efficient, non-invasive, and easy measuring diagnostic tools. On diagnostic uncertainty, the add-on of pCEA in cases of suspected MPE, and pIFN-ϒ in cases of suspected TPE has a trustable diagnostic efficacy with no need for further investigations.

Background The recent pandemic of COVID‐19 has thrown the world into chaos due to its high rate of transmissions. This study aimed to highlight the encountered CT findings in 910 patients with COVID-19 pneumonia in Egypt including the mean severity score and also correlation between the initial CT finding and the short-term prognosis in 320 patients. Results All patients had confirmed COVID-19 infection. Non-contrast CT chest was performed for all cases; in addition, the correlation between each CT finding and disease severity or the short-term prognosis was reported. The mean age was higher for patients with unfavorable prognosis (P < 0.01). The patchy pattern was the most common, found in 532/910 patients (58.4%), the nodular pattern was the least common 123/910 (13.5%). The diffuse pattern was reported in 124 (13.6%). The ground glass density was the most common reported density in the study 512/910 (56.2%). The crazy pavement sign was reported more frequently in patients required hospitalization or ICU and was reported in 53 (56.9%) of patients required hospitalization and in 29 (40.2%) patients needed ICU, and it was reported in 11 (39.2%) deceased patients. Air bronchogram was reported more frequently in patients with poor prognosis than patients with good prognosis (16/100; 26% Vs 12/220; 5.4%). The mean CT severity score for patients with poor prognosis was 15.2. The mean CT severity score for patients with good prognosis 8.7., with statistically significant difference (P = 0.001). Conclusion Our results confirm the important role of the initial CT findings in the prediction of clinical outcome and short-term prognosis. Some signs like subpleural lines, halo sign, reversed halo sign and nodular shape of the lesions predict mild disease and favorable prognosis. The crazy paving sign, dense vessel sign, consolidation, diffuse shape and high severity score predict more severe disease and probably warrant early hospitalization. The high severity score is most important in prediction of unfavorable prognosis. The nodular shape of the lesions is the most important predictor of good prognosis.

Background & Aim: COVID-19 is a worldwide pandemic with high rates of morbidity and mortality, and an uncertain prognosis leading to an increased risk of infection in health providers and limited hospital care capacities. In this study, we have proposed a predictive, interpretable prognosis scoring system with the use of readily obtained clinical, radiological and laboratory characteristics to accurately predict worsening of the condition and overall survival of patients with COVID -19. Methods: This is a single-center, observational, prospective, cohort study. A total of 347 patients infected with COVID-19 presenting to the Tanta university hospital, Egypt, were enrolled in the study, and clinical, radiological and laboratory data were analyzed. Top-ranked variables were identified and selected to be integrated into a Cox regression model, building the scoring system for accurate prediction of the prognosis of patients with COVID-19. Results: The six variables that were finally selected in the scoring system were lymphopenia, serum CRP, ferritin, D-Dimer, radiological CT lung findings and associated chronic debilitating disease. The scoring system discriminated risk groups with either mild disease or severe illness characterized by respiratory distress (and also those with hypoxia and in need for oxygen therapy or mechanical ventilation) or death. The area under the curve to estimate the discrimination performance of the scoring system was more than 90%. Conclusion: We proposed a simple and clinically useful predictive scoring model for COVID-19 patients. However, additional independent validation will be required before the scoring model can be used commonly.

Methicillin-resistant in Staphylococci is a serious public health issue. It is mostly encoded by the mecA gene. The mecC gene is a new mecA analog responsible for resistance to methicillin in some Staphylococcal clinical isolates. This mecC gene is still underestimated in Egypt. The aim of the current study was to detect mecA and mecC genes in clinical Staphylococci isolates from a tertiary care university hospital in Egypt compared to the different phenotypic methods. A total of 118 Staphylococcus aureus (S. aureus) and 43 coagulase-negative Staphylococci (CoNS) were identified from various hospital-acquired infections. Methicillin resistance was identified genotypically using the PCR technique and phenotypically using the cefoxitin disc diffusion test, oxacillin broth microdilution and the VITEK2 system in all Staphylococcal isolates. The mecA gene was detected in 82.2% of S. aureus and 95.3% of CoNS isolates, while all of the isolates tested negative for the mecC gene. Interestingly, 30.2% of CoNS isolates showed the unique character of inducible oxacillin resistance, being mecA-positive but oxacillin-susceptible (OS-CoNS). The dual use of genotypic and phenotypic methods is highly recommended to avoid missing any genetically divergent strains.