Αρχειοθήκη ιστολογίου

Πέμπτη 6 Οκτωβρίου 2022

Single‐rooted extraction socket classification: A systematic review and proposal of a new classification system based on morphologic and patient‐related factors

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Abstract

Taxonomy and classification of a disease contributes to facilitating the diagnosis and treatment planning process and simplifies communication between clinicians. The aim of this study was to provide a critical appraisal based on a systematic review of the single-rooted extraction socket (ES) classifications and subsequently, introduce a new classification system combining the cornerstones of the previously proposed systems and based on the latest consensus in implant dentistry. Following the systematic search process in PubMed, EMBASE, and SCOPUS databases 13 ES classifications were detected. The most repeated hard and soft tissue factors in the previous classifications were buccal bone dehiscence, interproximal bone, gingival recession, and soft tissue phenotype. However, there was minimal attention to patient-related factors such as systemic conditions and smoking. Therefore, a new classification system based on the combination of patient-related factors, clinical and radiograp hical parameters was proposed. This divides an ES into three types. Class I and II sockets are candidates for receiving immediate implant placement and conversely, a class III socket includes a compromised condition that requires multiple-stage reconstruction mostly suitable for standard delayed implant placement with alveolar ridge preservation. Within the limitations of this study, the new classification system not only provides comprehensive inclusion of various crucial parameters in implant placement (such as prediction of future implant position and osteotomy difficulty, etc.) but also, in contrast to the previously introduced systems, is able to classify the ES prior to extraction and also, takes into the account the patient-related factors as the class modifiers following the extraction.

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Acinetobacter baumannii: Pathogenesis, virulence factors, novel therapeutic options and mechanisms of resistance to antimicrobial agents with emphasis on tigecycline

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Acinetobacter baumannii: Pathogenesis, virulence factors, novel therapeutic options and mechanisms of resistance to antimicrobial agents with emphasis on tigecycline

This article summarizes the microbiological and virulence traits in A.baumannii. In addition, in this study, the mechanisms of resistance to tigecycline have been comprehensively investigated and novel therapeutic strategies have been expressed.


Abstract

What is known and objective

Acinetobacter baumannii is one of the most important nosocomial pathogens with the ability to cause infections such as meningitis, pneumonia, urinary tract, septicaemia and wound infections. A wide range of virulence factors are responsible for pathogenesis and high mortality of A. baumannii including outer membrane proteins, lipopolysaccharide, capsule, phospholipase, nutrient- acquisition systems, efflux pumps, protein secretion systems, quarom sensing and biofilm production. These virulence factors contribute in pathogen survival in stressful conditions and antimicrobial resistance.

Comment

According to the World Health Organization (WHO), A. baumannii is one of the most resistant pathogens of ESKAPE group (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, A. baumannii, Pseudomonas aeruginosa and Enterobacter spp.). In recent years, resistance to a wide range of antibiotics in A. baumannii has significantly increased and the high emergence of extensively drug resistant (XDR) isolates is challenging. Among therapeutic antibiotics, resistance to tigecycline as a last resort antibiotic has become a global concern. Several mechanisms are involved in tigecycline resistance, the most important of which is RND (Resistance-Nodulation-Division) family efflux pumps overexpression. The development of new therapeutic strategies to confront A. baumannii infections has been very promising in recent years.

What is new and conclusion

In the present review we highlight microbiological and virulence traits in A. baumannii and peruse the tigecycline resistance mechanisms and novel therapeutic options. Among the novel therapeutic strategies we focus on combination therapy, drug repurposing, novel antibiotics, bacteriophage therapy, antimicrobial peptides (AMPs), human monoclonal antibodies (Hu-mAbs), nanoparticles and gene editing.

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Pediatric vs Adult Septoplasty Revision Rates

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This cohort study used data from the IBM MarketScan Commercial Database to compare rates of revision surgery among pediatric vs adult patients undergoing septoplasty.
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BMI and Venous VTE Rates in Patients on Standard Chemoprophylaxis Regimens After H&N Surgery

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This cohort study assesses whether there is an association bet ween body mass index (BMI) and postoperative venous thromboembolism (VTE) and hematoma rates in patients treated with prophylactic enoxaparin 30 mg twice daily.
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Chemical behavior of 20%–22% carbamide peroxide gels in at‐home bleaching: Randomized crossover in situ trial

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Abstract

Objective

To evaluate if distinct 20%–22% carbamide peroxide bleaching gels present similar decomposition pattern and pH during the clinical use in both arches, as well as gels viscosity.

Methods

Participants randomly received treatments with carbamide peroxide gels (n = 10): OPF (OpalescencePF-20%); PNT (Polanight-22%); and WPC (Whiteness Perfect-22%) in three different days, with 2-day washout. Decomposition pattern was assessed by peroxide concentration. Both PC and pH of bleaching gels were measured in different time points in upper and lower trays during a total of 120 min of clinical use. Viscosity of bleaching gels was measured in triplicate. ANOVA and Tukey's test were applied (α = 0.05).

Results

Regarding decomposition pattern, no significant differences were observed for the interaction between gel, time, and tray position factors. The peroxide concentration progressively reduced until 120 min of trays use (p < 0.001), being overall more notable in lower trays (p < 0.001). Regarding pH, the lowest values were verified in WPC within time. At 120 min, an increase of pH was observed for both WPC and OPF (p < 0.001) compared to baseline means. PNT exhibited constant pH values over time. The values of viscosity were: OPF (1.682.000 ± 19 cP)a, WPC (1.388.667 ± 172.63 cP)ab, PNT (579.567 ± 0.98 cP)b.

Conclusions

The bleaching gels presented overall decomposition pattern clinically equivalent, being more notable in lower trays over time. Nevertheless, distinct pH and viscosities were observed among the products.

Clinical Significance

Although the manufacturers recommend different times of use for bleaching gels with similar peroxide concentrations, the commercial products tested did not exhibit clinically relevant difference in the decomposition pattern during the 120 min of clinical procedure.

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Active Surveillance for PTMC warranted for the UK population?

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Abstract

Background

The incidence of thyroid cancer is increasing globally due to the increase in detection of subclinical, low volume papillary thyroid microcarcinomas (PTMC) (<1cm). Several international groups have recommended an active surveillance approach for this low-risk disease. In contrast to many other countries, the UK's approach to thyroid nodules is to avoid detection of incidental lesions where appropriate.

Objective

This study aims to establish the proportion of patients with thyroid cancer in the UK that would benefit from active surveillance.

Design, participants, and outcome measures

Individuals with PTMC in NHS Lothian from 2009-2020 were reviewed from a local thyroid cancer database. The mode of detection of PTMC and proportion of patients who might benefit from active surveillance were established.

Results

From 651 individuals with differentiated thyroid cancer managed over 12-year period, 185 individuals with PTMC were identified (28.4%). The majority of PTMC 151/185 (81.6%) were either diagnosed post-operatively following thyroidectomy for benign disease or with nodal disease. Only 24 individuals with PTMC were identified following palpable thyroid nodule, incidental finding on imaging and surveillance screening. Therefore, when the indication for surgery was considered, only 24/651 (3.7%) patients were identified pre-operatively and would therefore be realistic candidates for active surveillance.

Conclusion

Less than 4% of patients with thyroid cancer in the UK would be appropriate for active surveillance. Rather than developing programs to deal with this minority of patients, focus should be maintained on minimizing detection of these low-risk cases.

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Differentiation of eosinophilic and non‐eosinophilic chronic rhinosinusitis on preoperative computed tomography using deep learning

alexandrossfakianakis shared this article with you from Inoreader

Abstract

Objective

This study aimed to develop deep learning (DL) models for differentiating between eosinophilic chronic rhinosinusitis (ECRS) and non-ECRS (NECRS) on preoperative CT.

Methods

A total of 878 chronic rhinosinusitis (CRS) patients undergoing nasal endoscopic surgery at Renmin Hospital of Wuhan University (Hubei, China) between October 2016 to June 2021 were included. Axial spiral CT images were pre-processed and used to build the dataset. Two semantic segmentation models based on U-net and Deeplabv3 were trained to segment the sinus area on CT images. All patient images were segmented using the better-performing segmentation model and used for training and testing of the transferred efficientnet_b0, resnet50, inception_resnet_v2, and Xception neural networks. Additionally, we evaluated the performances of the models trained using each image and each patient as a unit. The precision of each model was assessed based on the receiver operating characteristic curve. Further, we analyzed the confusion matrix and accuracy of each model.

Results

The Dice coefficients of U-net and Deeplabv3 were 0.953 and 0.961, respectively. The average area under the curve and mean accuracy values of the four networks were 0.848 and 0.762 for models trained using a single image as a unit, while the corresponding values for models trained using each patient as a unit were 0.893 and 0.853, respectively.

Conclusion

Combining semantic segmentation with classification networks could effectively distinguish between patients with ECRS and those with NECRS based on preoperative sinus CT images. Furthermore, labeling each patient to build a dataset for classification may be more reliable than labeling each medical image.

This article is protected by copyright. All rights reserved.

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