An Introduction to Pharmacovigilance, 2nd ed

No abstract available

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In Response

No abstract available

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Preventing Adverse Events in Cataract Surgery: Sub-Tenon’s Block

No abstract available

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Survival Analysis and Interpretation of Time-to-Event Data: The Tortoise and the Hare

Survival analysis, or more generally, time-to-event analysis, refers to a set of methods for analyzing the length of time until the occurrence of a well-defined end point of interest. A unique feature of survival data is that typically not all patients experience the event (eg, death) by the end of the observation period, so the actual survival times for some patients are unknown. This phenomenon, referred to as censoring, must be accounted for in the analysis to allow for valid inferences. Moreover, survival times are usually skewed, limiting the usefulness of analysis methods that assume a normal data distribution. As part of the ongoing series in Anesthesia & Analgesia, this tutorial reviews statistical methods for the appropriate analysis of time-to-event data, including nonparametric and semiparametric methods—specifically the Kaplan-Meier estimator, log-rank test, and Cox proportional hazards model. These methods are by far the most commonly used techniques for such data in medical literature. Illustrative examples from studies published in Anesthesia & Analgesia demonstrate how these techniques are used in practice. Full parametric models and models to deal with special circumstances, such as recurrent events models, competing risks models, and frailty models, are briefly discussed. This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. Accepted for publication June 8, 2018. Funding: None. The authors declare no conflicts of interest. Reprints will not be available from the authors. Address correspondence to Patrick Schober, MD, PhD, MMedStat, Department of Anesthesiology, VU University Medical Center, De Boelelaan 1117, 1081 HV, Amsterdam, the Netherlands. Address e-mail to p.schober@vumc.nl. © 2018 International Anesthesia Research Society

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In silico study of Moxifloxacin derivatives with possible antibacterial activity against a resistant form of DNA gyrase from Porphyromonas gingivalis

Publication date: Available online 19 July 2018

Source: Archives of Oral Biology

Author(s): Cristian Rocha-Roa, Rodrigo Cossio-Pérez, Diego Molina, Jorge Patiño, Néstor Cardona

Abstract

We performed a homology modeling of the structure of a non-mutated and mutated Ser83→Phe DNA gyrase of Porphyromonas gingivalis. The model presented structural features conserved in type II topoisomerase proteins. We designed and evaluated in silico structural modifications to the core of Moxifloxacin by molecular docking, predicted toxicity and steered molecular dynamics simulations (SMD). Our results suggest that 8D derivative of Moxifloxacin could present a strong inhibitory activity in Porphyromonas gingivalis bacteria that exhibits resistance to some conventional fluoroquinolone drugs. Also, our results suggest that hydrophobic radicals in the hydroxyl group at position 3 of the quinolone core would increase the antibacterial activity of the compound when a reported mutation Ser83→Phe is present in the DNA gyrase protein. In addition, new candidates that could have a higher antibacterial activity compared to Moxifloxacin in non-resistant bacteria are proposed.

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Correlating regional emergency epistaxis visits with internet search activity

Publication date: Available online 19 July 2018

Source: American Journal of Otolaryngology

Author(s): Shane Griffith, Robert Archbold, Stephen Schell

Abstract

Purpose

To investigate the correlation between internet search activity and epistaxis-related Emergency Department visits.

Materials and methods

Data from Google Trends were obtained (www.google.com/trends) for the search term "nosebleed" in Erie County, Pennsylvania during a five-year period. All epistaxis-related CPT code events were obtained from one hospital in this county during the same period. Google total counts were cross tabulated with the following month's ED visits. Graphical analysis and correlation were used to assess the relationship between ED visits and search engine activity.

Results

A strong positive correlation was observed between epistaxis-related ED visits and search engine activity for the term "nosebleed" (r = 0.655).

Conclusion

Search engine activities for the term "nosebleed" correlates strongly with epistaxis-related ED visits. This study demonstrates the usefulness of utilizing Google Trends search data to assess regional disease burdens, which may provide a means for epidemiological study that is quicker than conventional methods.

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The socioeconomic determinants for transsphenoidal pituitary surgery: a review of New York State from 1995 to 2015

International Forum of Allergy &Rhinology, EarlyView.


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