Automated Artificial Intelligence Model Trained on a Large Dataset Can Detect Pancreas Cancer on Diagnostic CTs as well as Visually Occult Pre-invasive Cancer on Pre-diagnostic CTs

The aims of our case-control study were – 1) to develop an automated 3D-Convolutional Neural Network (CNN) for detection of PDA on diagnostic CTs, 2) evaluate its generalizability on multi-institutional public datasets, 3) its utility as a potential screening tool using a simulated cohort with high pretest probability, and 4) its ability to detect visually occult pre-invasive cancer on pre-diagnostic CTs.

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Agosto 2023

Efficacy and safety of Android artificial pancreas system use at home among adults with type 1 diabetes mellitus in China: protocol of a 26-week, free-living, randomised, open-label, two-arm, two-phase, crossover trial

Introduction
Do-it-yourself artificial pancreas system (DIY APS) is built using commercially available insulin pump, continuous glucose monitoring (CGM) and an open-source algorithm. Compared with commercial products, DIY systems are affordable, allow personalised settings and provide updated algorithms, making them a more promising therapy for most patients with type 1 diabetes mellitus (T1DM). Many small and self-reported observational studies have found that their real-world use was associated with potential metabolic and psychological benefits. However, rigorous-designed studies are urgently needed to confirm its efficacy and safety.

Methods and analysis
In this 26-week randomised, open-label, two-arm, two-phase, crossover trial, participants aged 18–75 years, with T1DM and glycated haemoglobin (HbA1c) 7–11%, will use AndroidAPS during one 12-week period and sensor-augmented pump during another 12-week period. This study will recruit at least 24 randomised participants. AndroidAPS consists of three components: (1) real-time CGM; (2) insulin pump; (3) AndroidAPS algorithm implemented in Android smartphone. The primary endpoint is time in range (3.9–10.0 mmol/L) derived from CGM. The main secondary endpoints include percentage of sensor glucose values below, within and above target range; mean sensor glucose value; measures of glycaemic variability and centralised HbA1c. Safety endpoints mainly include the frequency of hypoglycaemia events, diabetic ketoacidosis and other serious adverse events.

Ethics and dissemination
This study has been approved by the Ethics Committee of the Third Affiliated Hospital of Sun Yat-sen University. There will be verbal and written information regarding the trial given to each participant. The study will be disseminated through peer-reviewed publications and conference presentations.

Overall status
Recruiting.

Study start
11 February 2023.

Primary completion
31 July 2024.

Trial registration number
ClinicalTrials.gov Registry (NCT05726461).

Leggi
Agosto 2023