Objective: This study aimed to understand the effect of time to remission of acromegaly on survival in people living with acromegaly.
Design, Patients And Measurement: This cross-sectional study used data from the UK Acromegaly Register. We considered remission of acromegaly growth hormone controlled at ≤2 μg/L following the diagnosis of acromegaly.
Aim: To understand the effect of intermittently scanned continuous glucose monitoring (isCGM) in people with diabetes with a 'psychosocial' indication for access.
Methods: The study utilized baseline and follow-up data from the Association of British Clinical Diabetologists nationwide audit of people with diabetes in the UK. Diabetes-related distress (DRD) was assessed using the two-item diabetes-related distress scale (DDS).
Aims: To evaluate the clinical features and impact of flash glucose monitoring in older adults with type 1 diabetes (T1D) across age groups defined as young-old, middle-old, and old-old.
Materials And Methods: Clinicians were invited to submit anonymized intermittently scanned continuous glucose monitoring (isCGM) user data to a secure web-based tool within the National Health Service secure network. We collected baseline data before isCGM initiation, such as demographics, glycated haemoglobin (HbA1c) values from the previous 12 months, Gold scores and Diabetes Distress Scale (DDS2) scores.
Introduction: Some but not all women with polycystic ovary syndrome (PCOS) develop the metabolic syndrome (MS). The objective of this study was to determine if a subset of women with PCOS had higher androgen levels predisposing them to MS and whether routinely measured hormonal parameters impacted the metabolic syndrome score (siMS).
Methods: We included data from a discovery (PCOS clinic data) and a replication cohort (Hull PCOS Biobank) and utilized eight routinely measured hormonal parameters in our clinics (free androgen index [FAI], sex hormone-binding globulin, dehydroepiandrosterone sulphate (DHEAS), androstenedione, luteinizing hormone [LH], follicular stimulating hormone, anti-Müllerian hormone and 17 hydroxyprogesterone [17-OHP]) to perform a K-means clustering (an unsupervised machine learning algorithm).
There had been an urgent call for the collection of standardized data describing clinical presentations, severity, outcomes, and epidemiology of COVID-19 by the World Health Organization (WHO). These data were expected to compliment the national pandemic data collated from countries by the World Health Organization (WHO). Nigeria, among other countries, is not an exception.
View Article and Find Full Text PDFTime-varying covariance occurs when a covariate changes over time during the follow-up period. Such variable can be analyzed with the Cox regression model to estimate its effect on survival time. For this it is essential to organize the data in a counting process style.
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