Publications by authors named "R K Kaushal"
Article Synopsis
- ALC-positive lung cancers generally respond well to oral tyrosine kinase inhibitors, with Lorlatinib being a preferred option after previous treatments; this study examines its use in patients who progressed or couldn't tolerate earlier therapies.
- In a study of 38 patients treated with Lorlatinib, most had extensive metastatic disease (mainly to the brain and bones), with a median follow-up of 49 months, revealing that 84% experienced disease control.
- Results indicated a median progression-free survival of 16 months and overall survival of 22 months, with common side effects including elevated cholesterol and triglycerides; some patients needed dose adjustments due to these toxicities.
Background: Immune check point inhibitors (ICIs) have an established role in Microsatellite-Instability-High (MSI-H) and Combined Positive Score (CPS) high advanced gastric/gastroesophageal (G/GE) adenocarcinomas, but there is limited real world data with regard to practice patterns, and efficacy of standard doses (SD-ICIs) and alternative lower doses (LD-ICIs).
Methods: A retrospective study of patients with advanced G/GE adenocarcinomas receiving ICIs was conducted. The primary endpoint of the study was 12-month overall survival (OS), which was computed by Kaplan-Meier method.
Cholangiocarcinomas and gallbladder carcinomas are epithelial tumours with biliary differentiation. On histology and immunohistochemistry, they resemble adenocarcinomas and possess overlapping immunohistochemical profiles. Diagnosing these tumours is best done using appropriate imaging and clinical features with compatible immunohistochemistry.
View Article and Find Full Text PDFBackground: Brain tumours represent a diagnostic challenge, especially in the imaging area, where the differentiation of normal and pathologic tissues should be precise. The use of up-to-date machine learning techniques would be of great help in terms of brain tumor identification accuracy from MRI data. Objective This research paper aims to check the efficiency of a federated learning method that joins two classifiers, such as convolutional neural networks (CNNs) and random forests (R.
View Article and Find Full Text PDFObjective: Studies show metformin use before and during SARS-CoV-2 infection reduces severe COVID-19 and postacute sequelae of SARS-CoV-2 (PASC) in adults. Our objective was to describe the incidence of PASC and possible associations with prevalent metformin use in adults with type 2 diabetes mellitus (T2DM).
Research Design And Methods: This is a retrospective cohort analysis using the National COVID Cohort Collaborative (N3C) and Patient-Centered Clinical Research Network (PCORnet) electronic health record (EHR) databases with an active comparator design that examined metformin-exposed individuals versus nonmetformin-exposed individuals who were taking other diabetes medications.