scholarly journals Histopathological Vs. cytological findings in cervical lesions (Bethesda System 2001) – A comparative study

2016 ◽  
Vol 7 (11) ◽  
pp. 530
Author(s):  
Kuntal Devesh Patel ◽  
Nisarg Champaneria ◽  
Shreya Shah ◽  
Mihir Sharma ◽  
Jasmin Jasani ◽  
...  
2014 ◽  
Vol 45 (4) ◽  
pp. 826-833 ◽  
Author(s):  
Jordi Genovés ◽  
Frances Alameda ◽  
Gemma Mancebo ◽  
Josep Maria Solé ◽  
Beatriz Bellosillo ◽  
...  

2021 ◽  
Vol 71 (1) ◽  
pp. 299-303
Author(s):  
Hannan Humayun Khan ◽  
Mafaza Alam ◽  
Syed Muzammil Hussain Shah ◽  
Saman Mehmood ◽  
Ajmal Yousaf ◽  
...  

Objective: To investigate and compare the retention rates of Flowable-Nanocluster-Composite and Resinmodified-Glass-Ionomers in non-carious cervical lesions in maxillary molars. Study Design: Prospective cross-sectional comparative study. Place and Duration of Study: Department of Operative Dentistry, Armed Forces Institute of Dentistry,Rawalpindi, from Jan 2017 to Dec 2018. Methodology: Male patients ranging from 30-40 years with moderate non-carious cervical lesions of maxillarypremolars and molars of either quadrant presenting to out-patient department were selected through convenience sampling. These lesions were restored with Flowable-Nanocluster-Composite and Resin-Modified-GlassIonomer. Retention of these two materials over the period of 6 months, 1 year and 2 years was noted. Chi square statistics were used to compare groups. Results: The retention of Flowable-Nanocluster-Composite was 92% in 6 months, 85% in one year and 81% in two years. Whereas, for resin-modified-glass-ionomer restorations, the frequency of retention of the filling material was 97% at 6 months, 93% at one year and 89% at two years period. Out of the total 74 resin-modified-glassionomers restorations, 8 (11%) had dislodged by the end of the second year as compared to 14 (19%) dislodged restorations for Flowable-Nanocluster-Composite. Conclusion: In conclusion, the study reveals that resin modified glass-ionomer has a superior retention rate over the period of two years as compared to Flowable-Nanocluster Composite. A dentist should have an insight into compositions of restorative materials for the longevity of their retention in various lesions.


2020 ◽  
Vol 64 (6) ◽  
pp. 539-546 ◽  
Author(s):  
Antônio Carlos Almeida de Oliveira ◽  
Miguel Fontes Domingues ◽  
Paulo Murilo Neufeld ◽  
Marcos Fleury ◽  
José Firmino Nogueira Neto

<b><i>Introduction:</i></b> Cervical cancer screening is an important tool in public health. Liquid-based cytology (LBC) has been performed at the studied hospital for 7 years. The present study compares the performance of 2 LBC techniques with conventional cytology. <b><i>Objective:</i></b> Our objective is to verify the sensitivity for the detection of neoplastic and preneoplastic epithelial atypia, as well as the positive predictive value of the 3 methodologies. <b><i>Methods:</i></b> We analyzed retrospectively 24,529 cases and evaluated the conventional cytology, ThinPrep®, and BD SurePath® performance categorizing the results according to the Bethesda system. We also compared the level of unsatisfactory samples, the presence of elements from the squamocolumnar junction, and the detection of pathogenic microorganisms. <b><i>Results:</i></b> ThinPrep® (1.43%) showed superior sensitivity over BD SurePath® (0.91%) and conventional cytology (0.71%) in terms of the detection of high-grade lesions; however, in terms of squamous atypia as a whole (ASC-US+), BD SurePath® (6.44%) proved to be more sensitive than conventional cytology (5.28%) and ThinPrep® (3.73%). <b><i>Conclusions:</i></b> The results show the advantage of implementing LBC in routine screening for cervical lesions. In this study, BD SurePath® achieved the overall best performance considering the studied variables.


2021 ◽  
Vol 0 (0) ◽  
pp. 0
Author(s):  
Megha Ralli ◽  
Pinki Pandey ◽  
Alok Dixit ◽  
Anshul Sawhney ◽  
Vineet Chaturvedi ◽  
...  

2013 ◽  
Vol 42 (3) ◽  
pp. 213-217 ◽  
Author(s):  
Kun Tao ◽  
Jing Yang ◽  
Hua Yang ◽  
Zhen-Hua Guo ◽  
Yue-Mei Hu ◽  
...  

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