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1.
BMJ Open Ophthalmol ; 9(1)2024 Jun 03.
Article in English | MEDLINE | ID: mdl-38830728

ABSTRACT

BACKGROUND: Unpreserved single-dose unit (SDU) eye drops are commonly used to avoid benzalkonium chloride-related toxicity. Although intended for single use, many patients report off-label repeated use of SDUs over a prolonged period. We investigated whether repeated use of dexamethasone 0.1% SDUs in the same patient increases the bacterial contamination rate. METHODS: We prospectively enrolled patients scheduled for inpatient corneal and glaucoma surgery receiving dexamethasone 0.1% SDU four times per day from the same vial. To assess contamination rates, one drop from the vial was cultured immediately after opening the SDU (t0), 10 hours later after four drop applications (t10) and 24 hours after opening without further drop applications (t24). Conjunctival swabs were taken before and after drop application. Contamination rate was assessed with a standard clinical culturing protocol without introducing a positive control. RESULTS: 110 eyes of 109 patients were evaluated. Drops collected immediately after opening the SDU (t0) were contaminated in 9/110 cultures (8.1%). At t10, 13/110 cultures were contaminated (11.8%; p=0.267) and 11/110 at t24 (10.0%; t24 vs t0; p=1.00). In 5 of 21 cases of contaminated drops at t10 and/or t24, the same isolates were cultured from the initial conjunctival swab and the SDU. In three cases, the same bacterial species was found in consecutive samples. CONCLUSION: The contamination rate of the SDU did not increase after multiple use within 24 hours. Contamination from fingertip flora was more likely than from ocular surface flora. Reuse of dexamethasone 0.1% SDU in the same patient within 24 hours appears to be safe.


Subject(s)
Dexamethasone , Glucocorticoids , Ophthalmic Solutions , Preservatives, Pharmaceutical , Humans , Dexamethasone/administration & dosage , Dexamethasone/adverse effects , Ophthalmic Solutions/adverse effects , Male , Female , Prospective Studies , Preservatives, Pharmaceutical/adverse effects , Preservatives, Pharmaceutical/administration & dosage , Aged , Middle Aged , Glucocorticoids/administration & dosage , Glucocorticoids/adverse effects , Aged, 80 and over , Adult , Drug Contamination , Glaucoma/drug therapy , Conjunctiva/microbiology , Conjunctiva/drug effects , Bacteria/drug effects , Bacteria/isolation & purification , Corneal Diseases/chemically induced
2.
J Big Data ; 10(1): 64, 2023.
Article in English | MEDLINE | ID: mdl-37215244

ABSTRACT

The number of published scientific paper grows rapidly each year, totaling more than 2.9 million annually. New methodologies and systems have been developed to analyze scientific production and performance indicators from large quantities of data available from the scientific databases, such as Web of Science or Scopus. In this paper, we analyzed the international scientific production and co-authorship patterns for the most productive authors from Serbia based on the obtained Web of Science dataset in the period 2006-2013. We performed bibliometric and scientometric analyses together with statistical and collaboration network analysis, to reveal the causes of extraordinary publishing performance of some authors. For such authors, we found significant inequality in distribution of papers over journals and countries of co-authors, using Gini coefficient and Lorenz curves. Most of the papers belong to multidisciplinary, interdisciplinary, and the field of applied sciences. We have discovered three specific collaboration patterns that lead to high productivity in international collaboration. First pattern corresponds to mega-authorship papers with hundreds of co-authors gathered in specific research groups. The other two collaboration patterns were found in mathematics and multidisciplinary science, mainly application of graph theory and computational methods in physical chemistry. The former pattern results in a star-shaped collaboration network with mostly individual collaborators. The latter pattern includes multiple actors with high betweenness centrality measure and identified brokerage roles. The results are compared with the later period 2014-2023, where high scientific production has been observed in some other fields, such as biology and food science and technology.

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