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Showing 3 results for Cross Infection

Mehdi Moradi , Firuzeh Nili , Fatemeh Nayeri, Elahe Amini, Tahere Esmaeilnia,
Volume 71, Issue 6 (9-2013)
Abstract

Background: Ventilator Associated Pneumonia (VAP), developing in mechanically ventilated patients after 48 hours of mechanical ventilation, is the second most common nosocomial infection. Therefore, there is a vital need to study the etiology and risk factors associated with VAP in neonates.
Methods: Neonates admitted to neonatal intensive care unit (NICU), over a period of one year and who required mechanical ventilation for more than 48 hours were enrolled consecutively into the study. Semi-quantitative assay of endotracheal aspirate was used for microbiological diagnoses of VAP. 105CFU/ml was taken as the cut off between evidence of pathological infection and colonization. The primary outcome measure was the development of VAP. Secondary outcome measures were length of mechanical ventilation, NICU length of stay, hospital cost, and death.
Results: Thirty eight patients were enrolled (58% were boys and 42% were girls). 42% of neonates developed VAP. The most common VAP organisms identified were Acinetobacter baumanni (43%). On multiple regression analysis, duration of mechanical ventilation was associated with VAP (P=0.00). Patients with VAP had greater need for mechanical ventilation (18.7 vs 6 median days), longer NICU length of stay (39 vs 21.5 median days) and higher total median hospital costs (79.5 vs 52 million rials) than those without VAP. The mortality rate was not different between two groups.
Conclusion: In mechanically ventilated neonates, those with VAP had a prolonged need for mechanical ventilation, a longer NICU stay, and a higher hospital costs. Longer mechanical ventilation was associated with an increased risk of developing VAP in these patients. Developing of VAP didn’t increase mortality in patients.

Shahram Shahraki Zahedani , Mojdeh Jahantigh , Yousef Amini ,
Volume 76, Issue 8 (11-2018)
Abstract

Background: Pseudomonas aeruginosa is an opportunistic pathogen and one of the important factors of hospital infection. It causes many issues such as urinary tract infections, respiratory infection in cystic fibrosis patients, and wound infection in burn patients, septicemia and meningitis. Antibiotic resistance through various mechanisms is one of the challenges for the treatment of pseudomonad-caused infections. According to the inherent and acquired capacity of this bacterium in creating resistance against the antimicrobial factors, it is very important to identify a pattern for its antibiotic resistance. The aim of this study was to deliberate the frequency of pattern antibiotic resistance of pseudomonas aeruginosa strains.
Methods: In this cross-sectional study, 200 pseudomonas aeruginosa isolations (from 86 males and 114 females) were collected from different samples such as urine, blood, wound, catheter and other samples from teaching hospitals in Zahedan City during nine-month period in 2017. After conducting biochemical tests and confirming bacterium type, based on Clinical Laboratory Standards Institute (CLSI), the antibiotic resistance of strains for 10 antibiotics was determined using disk diffusion method. In addition, the minimum inhibitory concentration of three antibiotics such as imipenem, piperacillin/tazobactam and ceftazidime were determined through E-test. The Chi-square test was used for statistical analysis through the SPSS software, version 16 (IBM SPSS, Armonk, NY, USA).
Results: Out of 200 pseudomonas aeruginosa isolations (from 86 males and 114 females), the maximum resistance was related to ciprofloxacin (37%) and gentamicin (28.5%). The minimum resistance was related to piperacillin/tazobactam (6.5%) and ceftazidime (6%). The highest separated strain was from urine sample (54%), blood sample (23.5%) and wound sample (10.5%). Additionally all strains were sensitive to colistin. In this study, the percentage of multidrug-resistance (MDR) and extensively drug-resistant (XDR) strains were investigated, which were 13% and 5.5%, respectively.
Conclusion: In this study, pseudomonas aeruginosa isolates had the lowest resistance to ceftazidime which this antibiotic could be the main treatment option. The high prevalence of MDR strains is a serious warning.

Mojtaba Hedayat Yaghoobi , Mohammadmahdi Sabahi , Elahe Ghaderi , Mohammad Ali Seifrabiei , Farshid Rahimi Bashar ,
Volume 77, Issue 11 (2-2020)
Abstract

Background: Health care associated infections (HAIs) are a class of infections that infect patients during hospital admissions and receive medical services. These infections occurs within 48 to 72 hours of admission and up to 6 weeks after discharge. Surveillance of device-associated infections (DAIs) in intensive care units (ICUs) is substantial in planning healthcare strategies. This study was conducted to determine the device-associated infections' burden and antimicrobial resistance patterns.
Methods: In this descriptive-analytic study, three common device-associated infections included central line-associated bloodstream infection (CLA-BSI), ventilator associated pneumonia (VAP), and catheter-associated urinary tract infection (CA-UTI), were assessed in intensive care units of Besat Hospital in Hamedan from April 2017 to April 2018. In order to determine the incidence of device-associated infections, the number of device-associated infection cases was calculated during the study period and divided into the number of device-days used. The device-days included all days of exposure to that device (vascular catheter, endotracheal tube (ventilator), or urinary catheter) in all patients in the study population.
Results: Out of 1806 intensive care unit admitted cases, 168 patients (9.3%) were device-associated infection with distribution of 92 cases (55%) of ventilator-associated pneumonia (VAP), 56 cases (34%) of catheter-associated urinary tract infection (CA-UTI) and 20 cases (11%) of central line-associated bloodstream infection (CL-BSI). The incidence of VAP, CA-UTI and CL-BSI was 44.7, 17.5, and 21.61 days, respectively. The most organisms were Acinetobacter (27.4%), Klebsiella (18.3%), Escherichia coli (E. coli) (15.4%). Vancomycin-resistant enterococcus (VRE) was 75%. Acinetobacter resistance to colistin and carbapenem was 16.8%. About half of Pseudomonas isolates were resistant to meropenem.
Conclusion: According to the present findings of this study, a high incidence of device-associated infections and resistant organisms in our intensive care units were documented, which represents a need to reinforce the preventive and control programs. Various results in different studies can be due to differences in the level of health care in different centers and countries.


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