Objective: Comprehending microbial diversity and antibiotic resistance patterns is essential for efficient treatment protocols. This study sought to determine the incidence of bacterial and fungal pathogens responsible for burn and wound infections and their antibiotic susceptibility profiles. Methods: This cross-sectional study involved 140 patients with burn or wound infections. Sterile swabs and pus aspiration were employed to collect samples, which were subsequently processed using standard microbiological procedures. Antibiotic resistance was determined using the Kirby-Bauer disc diffusion method, following Clinical and Laboratory Standards Institute (CLSI) guidelines. Data was analysed using IBM SPSS version 25.0, and the Chi-square test was used to evaluate resistance patterns (p < 0.05). Results: Seventy-five (53.6%) participants were male, while 65 (46.4%) were female. Pseudomonas aeruginosa was the predominant pathogen (30.7%), followed by Staphylococcus aureus (22.1%) and Klebsiella pneumoniae (15.7%). Antibiotic resistance patterns indicated significant resistance to Amoxicillin-clavulanic acid (72.1%), Ceftriaxone (65.0%), and Clindamycin (58.6%), although resistance to Amikacin (27.1%) and Ciprofloxacin (32.9%) was comparatively lower. The duration of healing differed among pathogens, with Acinetobacter baumannii requiring the longest length of 25 days, whereas Pseudomonas aeruginosa healed in a shorter duration of 14 days. Burn infection showed a strong link with antibiotic treatment (p = 0.024, 0.0182), whereas wound infection demonstrated a poor correlation (p = 0.089). Conclusion: The results underscore the necessity of ongoing monitoring of antibiotic resistance in wound and burn infections to inform empirical treatment. Targeted antimicrobial stewardship strategies can mitigate the advancement of resistance to infections and enhance clinical outcomes.
In this research an Artificial Neural Network (ANN) technique was applied for the prediction of Ryznar Index (RI) of the flowing water from WTPs in Al-Karakh side (left side) in Baghdad city for year 2013. Three models (ANN1, ANN2 and ANN3) have been developed and tested using data from Baghdad Mayoralty (Amanat Baghdad) including drinking water quality for the period 2004 to 2013. The results indicate that it is quite possible to use an artificial neural networks in predicting the stability index (RI) with a good degree of accuracy. Where ANN 2 model could be used to predict RI for the effluents from Al-Karakh, Al-Qadisiya and Al-Karama WTPs as the highest correlation coefficient were obtained 92.4, 82.9 and 79.1% respectively. For
... Show MoreThe study aims at identifying the morphological and psycho-socio-economic qualities wished to be in a life partner among a sample of Palestinian youth. The total sample was (231) and consisted of (83) male and (148) female students. Each student presented a detailed report on the qualities he/she wished to be in life partner. The study used the descriptive approach and content analysis method. The validity and stability of the analysis were calculated. The results showed eight qualities in both groups: physical, psychological, emotional, social, intellectual, familial, economic and academic. Female students were found to have more variations than male students in terms of the qualities preferable in the life partner. Male students
... Show MoreRetained soft tissue foreign bodies following injuries are frequently seen in the Emergency and Plastic Surgery practice. The patients with such presentations require a watchful and detailed clinical as- sessment to overcome the anticipant possibility of missing them. However, the diagnosis based on the clinical evaluation is usually challenging and needs to be supported by imaging modalities that are suboptimal and may fail in identifying some types of foreign bodies. Owing to that, serious complications such as chronic pain, infection, and delayed wound healing can be faced that necessitate a prompt intervention to halt those detrimental consequences. The classical method of removal is a surgical exploration which is not free of risks.
... Show MoreAn environmentally begnin second derivative spectrometric approach was developed for the estimation of the dissociation constants pKa(s) of metformin, a common anti-diabetic drug. The ultraviolet spectra of the aqueous solution of metformin were measured at different acidities, then the second derivative of each spectrum was graphed. The overlaid second derivative graphs exhibited two isobestic points at 225.5 nm and 244 nm pointing out to the presence of two dissociation constants for metformin pKa1 and pKa2, respectively. The method was validated by evaluating the reproducibility of the acquired results by comparing the estimated values of the dissociation constants of two different strategies that show excellent matching. As we
... Show MoreThree types of zeolite A were prepared from Iraqi kaoline which are 3A, 4A and 5A by ion exchange method .They were characterized by XRD and atomic absorption techniques .They were used as adsorbents to examine their applicability for H2S adsorption .The adsorption process was performed in a static form and constant volume system which constructed from stainless steel .The effect of zeolite type and temperature on the adsorption properties of H2S at -5 , 25 and 55 oC was studied .The zeolite type 5A has the highest adsorption value (79.384 µmol/g ) and the three types may be arranged in a sequence toward H2S adsorption as 5 A> 4A>3A .The amount of H2S adsorbed increased as temperature decreased from 55 to -5 for all samples. Langmuir , Fre
... Show MoreThe need for cloud services has been raised globally to provide a platform for healthcare providers to efficiently manage their citizens’ health records and thus provide treatment remotely. In Iraq, the healthcare records of public hospitals are increasing progressively with poor digital management. While recent works indicate cloud computing as a platform for all sectors globally, a lack of empirical evidence demands a comprehensive investigation to identify the significant factors that influence the utilization of cloud health computing. Here we provide a cost-effective, modular, and computationally efficient model of utilizing cloud computing based on the organization theory and the theory of reasoned action perspectives. A tot
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