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To compare the outcomes of intraoperative wavefront aberrometry versus optical biometry alone for intraocular lens (IOL) power calculation in eyes undergoing cataract surgery with monofocal IOL implantation.Preoperative data were obtained with the IOLMaster. Intraoperative aphakic measurements and IOL power calculations were obtained in some patients with the optiwave refractive analysis (ORA) system. Analysis was performed to determine the accuracy of monofocal IOL power prediction and postoperative manifest refraction at 1 month of the ORA versus IOLMaster.Two hundred and ninety-five eyes reviewed, 61 had only preoperative IOLMaster measurements and 234 had both IOLMaster and ORA measurements. Of these 234 eyes, 6 were excluded, 107 had the same recommended IOL power by ORA and IOLMaster. Sixty-four percent of these eyes were within ±0.5D. 95 eyes had IOL power implantation based on ORA instead of IOLMaster. Seventy percent of these eyes were within ±0.5D of target refraction. 26 eyes had IOL power chosen based on IOLMaster predictions instead of ORA. Sixty-five percent were within ±0.5D. In the group with IOLMaster without ORA measurements, 80% of eyes were within ±0.5D of target refraction. The absolute error was statistically smaller in those eyes where the ORA and IOLMaster recommended the same IOL power based on preoperative target refraction compared to instances in which IOL selection was based on ORA or IOLMaster alone. Neither prediction errors were statistically different between the ORA and IOLMaster alone.Intraoperative wavefront aberrometry with the ORA system provides postoperative refractive results comparable to conventional biometry with the IOLMaster for monofocal IOL selection.

BackgroundUnderstanding research activity within any given biomedical field is important. Search outputs generated by MEDLINE/PubMed are not well classified and require lengthy manual citation analysis. Automation of citation analytics can be very useful and timesaving for both novices and experts.ResultsPubFocus web server automates analysis of MEDLINE/PubMed search queries by enriching them with two widely used human factor-based bibliometric indicators of publication quality: journal impact factor and volume of forward references. In addition to providing basic volumetric statistics, PubFocus also prioritizes citations and evaluates authors' impact on the field of search. PubFocus also analyses presence and occurrence of biomedical key terms within citations by utilizing controlled vocabularies.ConclusionWe have developed citations' prioritisation algorithm based on journal impact factor, forward referencing volume, referencing dynamics, and author's contribution level. It can be applied either to the primary set of PubMed search results or to the subsets of these results identified through key terms from controlled biomedical vocabularies and ontologies. NCI (National Cancer Institute) thesaurus and MGD (Mouse Genome Database) mammalian gene orthology have been implemented for key terms analytics. PubFocus provides a scalable platform for the integration of multiple available ontology databases. PubFocus analytics can be adapted for input sources of biomedical citations other than PubMed.

Abstract Background Understanding research activity within any given biomedical field is important. Search outputs generated by MEDLINE/PubMed are not well classified and require lengthy manual citation analysis. Automation of citation analytics can be very useful and timesaving for both novices and experts. Results PubFocus web server automates analysis of MEDLINE/PubMed search queries by enriching them with two widely used human factor-based bibliometric indicators of publication quality: journal impact factor and volume of forward references. In addition to providing basic volumetric statistics, PubFocus also prioritizes citations and evaluates authors' impact on the field of search. PubFocus also analyses presence and occurrence of biomedical key terms within citations by utilizing controlled vocabularies. Conclusion We have developed citations' prioritisation algorithm based on journal impact factor, forward referencing volume, referencing dynamics, and author's contribution level. It can be applied either to the primary set of PubMed search results or to the subsets of these results identified through key terms from controlled biomedical vocabularies and ontologies. NCI (National Cancer Institute) thesaurus and MGD (Mouse Genome Database) mammalian gene orthology have been implemented for key terms analytics. PubFocus provides a scalable platform for the integration of multiple available ontology databases. PubFocus analytics can be adapted for input sources of biomedical citations other than PubMed.