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Aims: To explore healthcare professionals’ views about the training and support needed to rollout closed-loop technology to pregnant women with type 1 diabetes.Methods: We interviewed (n=19) healthcare professionals who supported pregnant women using CamAPS FX closed-loop during the AiDAPT trial. Data were analysed descriptively. An online workshop involving (n=15) trial team members was used to inform recommendations.Results: Interviewees expressed enthusiasm for a national rollout of closed-loop, but anticipated various challenges, some specific to use during pregnancy. These included variations in insulin pump and continuous glucose monitoring expertise and difficulties embedding and retaining key skills, due to the relatively small numbers of pregnant women using closed-loop. Inexperienced staff also highlighted difficulties interpreting data downloads. To support rollout, interviewees recommended providing expert initial advice training, delivered by device manufacturers together with online training resources and specific checklists for different systems. They also highlighted a need for 24-hour technical support, especially when supporting technology naïve women after first transitioning onto closed-loop in early pregnancy. They further recommended providing case-based meetings and mentorship for inexperienced colleagues, including support interpreting data downloads. Interviewees were optimistic that if healthcare professionals received training and support, their longer-term workloads could be reduced because closed-loop lessened women’s need for glycaemic management input, especially in later pregnancy.Conclusions: Interviewees identified challenges and opportunities to rolling-out closed-loop and provided practical suggestions to upskill inexperienced staff supporting pregnant women using closed-loop. A key priority will be to determine how best to develop mentorship services to support inexperienced staff delivering closed-loop.

CamAPS FX (CamDiab, Cambridge, UK) is a hybrid closed-loop app hosting the Cambridge closed-loop algorithm on an Android smartphone, and is approved in the EU for use in children ≥1 year, and adults (including during pregnancy) with type 1 diabetes (T1D). The interoperable CamAPS FX app receives glucose data from a compatible CGM system (Dexcom G6; Dexcom, San Diego, CA), connects to a compatible insulin pump (Dana Diabecare RS and DANA-i; Sooil, Seoul, South Korea) to direct glucose-responsive insulin delivery every 8-12 minutes, includes a bolus calculator allowing discrete bolusing via the app, and streams data in real-time to cloud-based diabetes data repositories (Diasend/Glooko, Gothenburg, Sweden).

Objective: The optimal method of monitoring glycemia in pregnant women with type 1 diabetes remains controversial. This study aimed to assess the predictive performance of HbA1c, continuous glucose monitoring (CGM) metrics, and alternative biochemical markers of glycemia to predict obstetric and neonatal outcomes. Methods: 157 women from the CGM in pregnant women with type 1 diabetes trial (CONCEPTT) were included in this pre-specified secondary analysis. HbA1c, CGM data, and alternative biochemical markers (glycated CD59, 1,5 anhydroglucitol, fructosamine and glycated albumin) were compared at approximately 12, 24 and 34 weeks gestation using logistic regression and ROC curves to predict pregnancy complications (pre-eclampsia, preterm delivery, large-for-gestational-age, neonatal hypoglycemia, admission to neonatal intensive care unit). Results: HbA1c, CGM metrics, and alternative laboratory markers were all significantly associated with obstetric and neonatal outcomes at 24 weeks gestation. More outcomes were associated with CGM metrics during the 1st trimester and with laboratory markers (area under ROC generally 140 mg/dl; >7.8 mmol/l) were the most consistently predictive CGM metrics. HbA1c was also a consistent predictor of suboptimal pregnancy outcomes. Some alternative laboratory markers showed promise, but overall, they had lower predictive ability than HbA1c. Conclusions: HbA1c is still an important biomarker for obstetric and neonatal outcomes in type 1 diabetes pregnancy. Alternative biochemical markers of glycemia and other CGM metrics did not substantially increase the prediction of pregnancy outcomes compared to widely available HbA1c and increasingly available CGM metrics (TIR and TAR).

Background: Diabetes in pregnancy is associated with preterm delivery, birthweight extremes, and increased rates of congenital anomaly, stillbirth, and neonatal death. We aimed to identify and compare modifiable risk factors associated with adverse pregnancy outcomes in women with type 1 diabetes and those with type 2 diabetes and to identify effective maternity clinics. Methods: In this national population-based cohort study, we used data for pregnancies among women with type 1 or type 2 diabetes collected in the first 5 years of the National Pregnancy in Diabetes audit across 172 maternity clinics in England, Wales, and the Isle of Man, UK. Data for obstetric complications (eg, preterm delivery [90th percentile]) and adverse pregnancy outcomes (congenital anomaly, stillbirth, neonatal death) were obtained for pregnancies completed between Jan 1, 2014, and Dec 31, 2018. We assessed associations between modifiable (eg, HbA 1c, BMI, pre-pregnancy care, maternity clinic) and non-modifiable risk factors (eg, age, ethnicity, deprivation, duration of type 1 diabetes) with pregnancy outcomes in women with type 1 diabetes compared with those with type 2 diabetes. We calculated associations between maternal factors and perinatal deaths using a regression model, including diabetes type and duration, maternal age, BMI, deprivation quintile, first trimester HbA 1c, preconception folic acid, potentially harmful medications, and third trimester HbA 1c. Findings: Our dataset included 17 375 pregnancy outcomes in 15 290 pregnant women. 8690 (50·0%) of 17 375 pregnancies were in women with type 1 diabetes (median age at delivery 30 years [10–90th percentile 22–37], median duration of diabetes 13 years [3–25]) and 8685 (50·0%) were in women with type 2 diabetes (median age at delivery 34 years [27–41], median duration of diabetes 3 years [0–10]). The rates of preterm delivery (3325 [42·5%] of 7825 pregnancies among women with type 1 diabetes, 1825 [23·4%] of 7815 with type 2 diabetes; p

Oncolytic viruses exploit the cancer cell phenotype to complete their lytic life cycle, releasing progeny virus to infect nearby cells and repeat the process. We modified the oncolytic group B adenovirus EnAdenotucirev (EnAd) to express a bispecific single‐chain antibody, secreted from infected tumour cells into the microenvironment. This bispecific T‐cell engager (BiTE) binds to EpCAM on target cells and cross‐links them to CD3 on T cells, leading to clustering and activation of both CD4 and CD8 T cells. BiTE transcription can be controlled by the virus major late promoter, limiting expression to cancer cells that are permissive for virus replication. This approach can potentiate the cytotoxicity of EnAd, and we demonstrate using primary pleural effusions and peritoneal malignant ascites that infection of cancer cells with the BiTE‐expressing EnAd leads to activation of endogenous T cells to kill endogenous tumour cells despite the immunosuppressive environment. In this way, we have armed EnAd to combine both direct oncolysis and T cell‐mediated killing, yielding a potent therapeutic that should be readily transferred into the clinic.