Publications by authors named "J K Shetty"
Root caries: Prevalence, risk indicators, and clinical characteristics - A cross-sectional study.
J Conserv Dent Endod
November 2024
Objectives: The objectives of this study were to determine the prevalence of root caries (RC) in South Coastal population of India, to identify the risk indicators associated with it and to describe some clinical characteristics of RC lesions.
Materials And Methods: A cross-sectional study was conducted with a sample size of 1062 subjects to assess the prevalence of RC. Each subject underwent an oral examination, performed by a single-calibrated examiner.
Serial intrapartum ultrasound to predict vaginal delivery using angle of progression and head- progression distance in term nulliparous women.
Eur J Obstet Gynecol Reprod Biol
December 2024
Article Synopsis
- Over the past decade, intrapartum ultrasound (ITU) has gained attention for monitoring labor, but its application in low- and middle-income countries remains limited; the angle of progression (AOP) is the most researched parameter, with few studies suggesting the importance of other ITU measurements.
- This study aimed to evaluate the predictive accuracy of AOP and head perineal diameter (PD) for vaginal delivery, as well as the impact of changes in these measurements during the first stage of labor.
- Results showed that AOP ≥ 120° and PD ≥ 2.7 cm significantly correlated with vaginal delivery, with AOP changes (>10°) having the highest accuracy (81%), indicating that ITU provides valuable insights
Article Synopsis
- Microglial activation has been linked to neurodegenerative diseases like Alzheimer's and Parkinson's, but its role in metabolic disorders, particularly insulin resistance and type 2 diabetes, is gaining attention.
- The text examines the biochemical pathways involved in this connection, including IKKβ/NF-κβ and IRS-1/PI3K/Akt, as well as the impact of non-coding RNAs on insulin resistance.
- Finally, potential therapeutic strategies, both pharmaceutical and lifestyle-based, are discussed to reduce microglial activation and mitigate its effects on metabolism.
Background: Gestational Diabetes Mellitus (GDM) is a metabolic condition that develops in course of pregnancy. The World Health Organization describes it as carbohydrate intolerance that causes hyperglycemia of varying severity and manifests itself or is first noticed during pregnancy. Early prediction is now possible, owing to the application of cutting-edge methods like machine learning.
View Article and Find Full Text PDFObjectives: To estimate thresholds for defining meaningful within-patient improvement from baseline to weeks 13-24 and interpreting meaningfulness of between-group difference for the non-transfusion-dependent beta-thalassaemia patient-reported outcome (NTDT-PRO) tiredness/weakness (T/W) and shortness of breath (SoB) scores. A secondary objective was to determine the symptom severity threshold for the NTDT-PRO T/W domain to identify patients with symptomatic T/W.
Design: Pooled blinded data from the phase 2, double-blind, placebo-controlled, randomised BEYOND trial in NTDT (NCT03342404) were used.