Head and Neck Medicine by Alexandros G.Sfakianakis

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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Salivary adiponectin, but not adenosine deaminase, correlates with clinical signs in women with Sjögren’s syndrome: a pilot study

Abstract

Objectives

To evaluate salivary adiponectin and adenosine deaminase (ADA) in women suffering from Sjögren's syndrome (SS).

Methods

Salivary adiponectin and ADA were measured in patients with SS (n = 17) and compared to their values in healthy controls (n = 13) and patients suffering from drug-induced xerostomia (non-SS sicca group; n = 19). A clinical history was made for each patient, patients were examined clinically, and xerostomia inventory (XI) was performed.

Results

Salivary adiponectin corrected by total protein was higher in patients with SS than in healthy individuals (P < 0.05) or patients with non-SS sicca (P < 0.01) and correlated with XI (r = 0.555; P < 0.05). Salivary ADA was higher in patients with SS and non-SS sicca compared to controls (P < 0.05 in both cases).

Conclusion

The results of the present study indicate that adiponectin and ADA are increased in the saliva of patients with SS.

Clinical relevance

Salivary adiponectin corrected by total protein can be a potential biomarker of SS.

Trial registration

NCT03156569

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Correction to: Effectiveness of adjunctive hyaluronic acid application in coronally advanced flap in Miller class I single gingival recession sites: a randomized controlled clinical trial

The figure 2 of the original version of this article was incorrect. Correct figure is presented below.

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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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