Common Pitfalls in Reporting the Use of SPSS Software

Gouda, Mohamed A.

doi:10.1159/000381953

Cited by 36 publications

(22 citation statements)

References 4 publications

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“…e tables show the frequency of isolated ocular bacteria and also compare the resistance percentage of different antibiotics. For the categorical variables, the chi-square test values <0.05 were considered significant [21].…”

Section: Discussionmentioning

confidence: 99%

Prevalence and Antibiotic Resistance Patterns of Ocular Bacterial Strains Isolated from Pediatric Patients in University Hospital of Campania “Luigi Vanvitelli,” Naples, Italy

Petrillo

Folliero

Santella

et al. 2020

International Journal of Microbiology

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Eye infections caused by bacteria are a serious public health problem among pediatric patients. These diseases, if not properly treated, can cause blindness and impaired vision. The study aimed to evaluate the antimicrobial resistance profiles of the main pathogens involved in eye infections. This study involved pediatric patients enrolled at the “Luigi Vanvitelli” University Hospital of Campania in Naples, Italy, between 2017 and 2019. Of a total of 228 pediatric patients, 73 (32%) tested positive for bacterial infection. In terms of strain distribution, 85% were Gram-positive bacteria, while 15% were Gram-negative bacteria. The most frequently isolated strains were coagulase-negative Staphylococci (60.4%), followed by Staphylococcus aureus (16.4%). The isolated bacteria showed a significant percentage of resistance to multiple antibiotics. Therefore, the identification of the causal bacteria and antimicrobial sensitivity tests are mandatory to select the effective drug for the treatment of eye infections and prevent the development of antibiotic-resistant bacteria.

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Section: Discussionmentioning

confidence: 99%

Prevalence and Antibiotic Resistance Patterns of Ocular Bacterial Strains Isolated from Pediatric Patients in University Hospital of Campania “Luigi Vanvitelli,” Naples, Italy

Petrillo

Folliero

Santella

et al. 2020

International Journal of Microbiology

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“…SPSS software version 22 reference [ 18 ] was used for Data analysis. Descriptive data are presented as mean ± standard deviation and percentages.…”

Section: Methodsmentioning

confidence: 99%

Bone density, fractures and the associated factors in iranian children and adolescent with Osteogenesis Imperfecta

et al. 2021

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Backround Osteogenesis imperfecta(OI) is a frequent bone fragility disorder in children. The purpose of this study was to assess the BMD and Vitamin D level in children with OI in southern Iran. Method This case-control study was conducted on 23 children, clinically diagnosed as osteogenesis imperfecta and 23 age- and gender-matched healthy controls. Demographic and anthropometric data, biochemical parameters, puberty, sun exposure and physical activity were assessed. Bone mineral density (BMD) was measured by Dual-energy X-ray absorptiometry (DXA). Data analysis was done by SPSS22. Results Forty-three point four percent of OI patients and fifty-six point five percent of control group had vitamin D deficiency (P = 0.376). Thirteen OI patients (56%) had low bone mass for chronological age in lumbar area (P < 0.001). Fracture episodes during treatment was significantly influenced by time of Pamidronate start, courses of Pamidronate injection, puberty and sun exposure (P values = 0.015, 0.030, 0.044 and 0.032, respectively). Fracture episodes during treatment had significantly increased in patients who had received Pamidronate more than 3 years compared with those received less than 3 years(P values = 0.047). Conclusions This study showed that vitamin D deficiency is prevalent amongst OI children in southern Iran. More than half of the OI children had low bone mass for chronological age in lumbar area, despite receiving bisphosphonate therapy. The present results revealed that early initiation of Pamidronate and number of Pamidronate courses are associated with lower fracture rate. However, treatment period more than 3 years can have adverse effect on fracture rates.

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“…Statistical analysis and visualization were then performed in R (https://www.r-project.org/)[17] using the package ggplot2. We then used SPSS (https://www.ibm.com/analytics/datascience-/predictive-analytics/spss)[18] to perform ANOVA on the alpha diversity results of samples to compare the difference of microbial community composition among the three sites.…”

Section: Methodsmentioning

confidence: 99%

Microbial contamination screening and interpretation for biological laboratory environments

Ning

Zhu

et al. 2018

Preprint

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13Advances in microbiome researches have led us to the realization that the composition of microbial 14 communities of indoor environment is profoundly affected by the function of buildings, and in turn 15 may bring detrimental effects to the indoor environment and the occupants. Thus investigation is 16 warranted for a deeper understanding of the potential impact of the indoor microbial communities. 17Among these environments, the biological laboratories stand out because they are relatively clean 18 and yet are highly susceptible to microbial contaminants. In this study, we assessed the microbial 19 compositions of samples from the surfaces of various sites across different types of biological 20 laboratories. We have qualitatively and quantitatively assessed these possible microbial 21 contaminants, and found distinct differences in their microbial community composition. We also 22 found that the type of laboratories has a larger influence than the sampling site in shaping the 23 microbial community, in terms of both structure and richness. On the other hand, the public areas of 24 the different types of laboratories share very similar sets of microbes. Tracing the main sources of 25 these microbes, we identified both environmental and human factors that are important factors in 26 shaping the diversity and dynamics of these possible microbial contaminations in biological 27 laboratories. These possible microbial contaminants that we have identified will be helpful for 28 people who aim to eliminate them from samples. 29

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Common Pitfalls in Reporting the Use of SPSS Software

Cited by 36 publications

References 4 publications

Prevalence and Antibiotic Resistance Patterns of Ocular Bacterial Strains Isolated from Pediatric Patients in University Hospital of Campania “Luigi Vanvitelli,” Naples, Italy

Prevalence and Antibiotic Resistance Patterns of Ocular Bacterial Strains Isolated from Pediatric Patients in University Hospital of Campania “Luigi Vanvitelli,” Naples, Italy

Bone density, fractures and the associated factors in iranian children and adolescent with Osteogenesis Imperfecta

Microbial contamination screening and interpretation for biological laboratory environments

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