Publications by authors named "Kian Daneshi"

Background: Implant-based breast reconstruction (IBR), following mastectomy, significantly impacts patients' quality of life (QoL), necessitating accurate measurement through psychometrically robust patient-reported outcome measure (PROM) tools. This bibliometric analysis aims to discern trends, identify gaps, and evaluate the use of such tools in the IBR literature.

Methods: The 100 most cited publications regarding QoL in implant-based reconstruction were identified on Web of Science, across all available journal years (from 1977 to 2024) on 10 March 2024.

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Background: Gluteoplasty or gluteal augmentation is a popular cosmetic procedure that is used to improve the volume, shape, and contour of the buttocks.

Objectives: This bibliometric analysis aims to characterize emerging research trends and to assess the methodological quality of the highest impact gluteoplasty research.

Methods: The 100 most-cited publications in gluteoplasty were identified on Web of Science, across all available journal years (from Inception to August 2023).

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Closed suction drains are placed to prevent seroma formation after abdominoplasty, but evidence of their effectiveness is limited, and they may increase infection risk and patient discomfort. Previous meta-analyses comparing progressive tension suturing (PTS) to drainage (D) in abdominoplasty have been methodologically weak and small in sample size. In this study we aimed to conduct the first robust systematic review comparing PTS and D outcomes in abdominoplasty.

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Background: Aesthetic breast surgery (ABS) encompasses breast augmentation, breast reduction, mastopexy, and mastopexy augmentation. This topic has seldom been assessed as a bibliometric study. This analysis aims to address this gap and identify trends in ABS literature to guide future research areas.

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Background: Abdominal wall reconstruction (AWR) is a treatment option for structural defects of the abdominal wall. The most frequently cited publications related to AWR have not been quantitatively or qualitatively assessed. This bibliometric analysis characterizes and assesses the most frequently cited AWR publications, to identify trends, gaps, and guide future efforts for the international research community.

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While modelling and simulation are powerful techniques for exploring complex phenomena, if they are not coupled with suitable real-world data any results obtained are likely to require extensive validation. We consider this problem in the context of search game modelling, and suggest that both demographic and behaviour data are used to configure certain model parameters. We show this integration in practice by using a combined dataset of over 150,000 individuals to configure a specific search game model that captures the environment, population, interventions and individual behaviours relating to winter health service pressures.

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Synopsis of recent research by authors named "Kian Daneshi"

  • - Kian Daneshi's research primarily focuses on the bibliometric analysis of trends and methodologies in cosmetic and reconstructive surgery literature, aiming to identify gaps and improve patient quality of life measurements in procedures such as implant-based breast reconstruction and gluteal augmentation.
  • - His systematic review and meta-analysis comparing surgical outcomes of progressive tension suturing versus drainage in abdominoplasty highlights the need for more robust evidence regarding postoperative care practices and their impact on patient outcomes.
  • - Daneshi's work also addresses the integration of real-world data into modeling for healthcare simulations, emphasizing the importance of demographic and behavioral data in better understanding and managing health service pressures.