Effect of Out-Gassing on the Onset of Hypersonic Boundary Layer Transition

Prediction and control of the onset of transition and the associated variation in aerothermodynamic parameters in high-speed flows is key to optimize the performance and design of Thermal Protection Systems (TPS) of next-generation aerospace vehicles [1]. Boundary Layer Transition (BLT) characteristics can influence the surface heating budget determining the TPS thickness and consequently its weight penalty. Ablative heatshields are designed to alleviate the high heat flux at the surface through pyrolysis of their polymeric matrix and subsequent fiber ablation [2]. Pyrolysis leads to out-gassing and non-uniform ablation lead to surface roughness, both of which are known to influence the transition process. An ablator impacts BLT through three main routes: gas injecting into the boundary layer from the wall, changing the surface heat transfer due to wall-flow chemical reactions, and modifying surface roughness [3]. In preparation to Mars 2020 mission post-flight analysis, the predictive transition capability has been initiated toward hard-coupling porous material response analysis and aerothermal environment calculation

Supported self-management for adults with type 2 diabetes and a learning disability (OK-Diabetes): study protocol for a randomised controlled feasibility trial

Background: Individuals with a learning disability (LD) are at higher risk of developing type 2 diabetes, but LD is not straightforward to define or identify, especially at the milder end of the spectrum, which makes case finding difficult. While supported self-management of health problems is now established, current material is largely educational and didactic with little that facilitates behavioural change. The interaction between the person with diabetes and others supporting their care is also largely unknown. For these reasons, there is considerable work needed to prepare for a definitive trial. The aim of this paper is to publish the abridged protocol of this preparatory work. Methods/Design: Phase I is a prospective case-finding study (target n = 120 to 350) to identify and characterise potential participants, while developing a standardised supported self-management intervention. Phase II is a randomised feasibility trial (target n = 80) with blinded outcome assessment. Patients identified in Phase I will be interviewed and consented prior to being randomised to (1) standard treatment, or (2) supported self-management. Both arms will also be provided with an ‘easy read’ accessible information resource on managing type 2 diabetes. The intervention will be standardised but delivered flexibly depending on patient need, including components for the participant, a supporter, and shared activities. Outcomes will be (i) robust estimates of eligibility, consent and recruitment rates with refined recruitment procedures; (ii) characterisation of the eligible population; (iii) a standardised intervention with associated written materials, (iv) adherence and negative outcomes measures; (v) preliminary estimates of adherence, acceptability, follow-up and missing data rates, along with refined procedures; and (vi) description of standard treatment. Discussion: Our study will provide important information on the nature of type 2 diabetes in adults with LD living in the community, on the challenges of identifying those with milder LD, and on the possibilities of evaluating a standardised intervention to improve self-management in this population. Trial registration: Current Controlled Trials ISRCTN41897033 (registered 21 January 2013)

Association between SGLT2 inhibitor treatment and diabetic ketoacidosis and mortality in people with type 2 diabetes admitted to hospital with COVID-19

   Objective  To determine the association between prescription of SGLT2 inhibitors and diabetic ketoacidosis (DKA) incidence or mortality in people with type 2 diabetes hospitalized with COVID-19.  Research Design and Methods  This was a retrospective cohort study based on secondary analysis of data from a large nationwide audit from a network of 40 centres in United Kingdom with data collection up to December 2020 that was originally designed to describe risk factors associated with adverse outcomes among people with diabetes who were admitted to hospital with COVID-19.. The primary outcome for this analysis was DKA on or during hospital admission. The secondary outcome was mortality. Crude, age-sex adjusted and multivariable logistic regression models, were used to generate odds ratios and 95% confidence intervals for people prescribed SGLT2 inhibitor compared to those not prescribed SGLT2 inhibitor.   Results  The original national audit included 3067 people with type 2 diabetes who were admitted to hospital with COVID-19, of whom 230 (7.5%) were prescribed SGLT2 inhibitors prior to hospital admission. Mean (SD) age of the overall cohort was 72 years, 62.3% were men and 34.9% were prescribed insulin. Overall, 2.8% of the total population had DKA and 35.6% people died. The adjusted odds of DKA were not significantly different between those prescribed SGLT2 inhibitors and those not (OR 0.56, 0.16-1.97). The adjusted odds of mortality associated with SGLT2 inhibitors were similar in the total study population (OR 1.13, 0.78-1.63 ), in the sub-group prescribed insulin (OR 1.02, 0.59-1.77), and in the sub-group that developed DKA (OR 0.21, 0.01-8.76).  Conclusions We demonstrate a low risk of DKA and high mortality rate in people with type 2 diabetes admitted to hospital with COVID-19 and limited power but no evidence of increased risk of DKA or in-hospital mortality associated with prescription of SGLT2 inhibitors. </p

A nationwide study of adults admitted to hospital with diabetic ketoacidosis or hyperosmolar hyperglycaemic state and COVID‐19

AimsTo investigate characteristics of people hospitalized with coronavirus-disease-2019 (COVID-19) and diabetic ketoacidosis (DKA) or hyperosmolar hyperglycaemic state (HHS), and to identify risk factors for mortality and intensive care admission.Materials and methodsRetrospective cohort study with anonymized data from the Association of British Clinical Diabetologists nationwide audit of hospital admissions with COVID-19 and diabetes, from start of pandemic to November 2021. The primary outcome was inpatient mortality. DKA and HHS were adjudicated against national criteria. Age-adjusted odds ratios were calculated using logistic regression.ResultsIn total, 85 confirmed DKA cases, and 20 HHS, occurred among 4073 people (211 type 1 diabetes, 3748 type 2 diabetes, 114 unknown type) hospitalized with COVID-19. Mean (SD) age was 60 (18.2) years in DKA and 74 (11.8) years in HHS (p < .001). A higher proportion of patients with HHS than with DKA were of non-White ethnicity (71.4% vs 39.0% p = .038). Mortality in DKA was 36.8% (n = 57) and 3.8% (n = 26) in type 2 and type 1 diabetes respectively. Among people with type 2 diabetes and DKA, mortality was lower in insulin users compared with non-users [21.4% vs. 52.2%; age-adjusted odds ratio 0.13 (95% CI 0.03-0.60)]. Crude mortality was lower in DKA than HHS (25.9% vs. 65.0%, p = .001) and in statin users versus non-users (36.4% vs. 100%; p = .035) but these were not statistically significant after age adjustment.ConclusionsHospitalization with COVID-19 and adjudicated DKA is four times more common than HHS but both associate with substantial mortality. There is a strong association of previous insulin therapy with survival in type 2 diabetes-associated DKA

Evaluation of prognostic risk models for postoperative pulmonary complications in adult patients undergoing major abdominal surgery: a systematic review and international external validation cohort study

Background Stratifying risk of postoperative pulmonary complications after major abdominal surgery allows clinicians to modify risk through targeted interventions and enhanced monitoring. In this study, we aimed to identify and validate prognostic models against a new consensus definition of postoperative pulmonary complications. Methods We did a systematic review and international external validation cohort study. The systematic review was done in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We searched MEDLINE and Embase on March 1, 2020, for articles published in English that reported on risk prediction models for postoperative pulmonary complications following abdominal surgery. External validation of existing models was done within a prospective international cohort study of adult patients (≥18 years) undergoing major abdominal surgery. Data were collected between Jan 1, 2019, and April 30, 2019, in the UK, Ireland, and Australia. Discriminative ability and prognostic accuracy summary statistics were compared between models for the 30-day postoperative pulmonary complication rate as defined by the Standardised Endpoints in Perioperative Medicine Core Outcome Measures in Perioperative and Anaesthetic Care (StEP-COMPAC). Model performance was compared using the area under the receiver operating characteristic curve (AUROCC). Findings In total, we identified 2903 records from our literature search; of which, 2514 (86·6%) unique records were screened, 121 (4·8%) of 2514 full texts were assessed for eligibility, and 29 unique prognostic models were identified. Nine (31·0%) of 29 models had score development reported only, 19 (65·5%) had undergone internal validation, and only four (13·8%) had been externally validated. Data to validate six eligible models were collected in the international external validation cohort study. Data from 11 591 patients were available, with an overall postoperative pulmonary complication rate of 7·8% (n=903). None of the six models showed good discrimination (defined as AUROCC ≥0·70) for identifying postoperative pulmonary complications, with the Assess Respiratory Risk in Surgical Patients in Catalonia score showing the best discrimination (AUROCC 0·700 [95% CI 0·683–0·717]). Interpretation In the pre-COVID-19 pandemic data, variability in the risk of pulmonary complications (StEP-COMPAC definition) following major abdominal surgery was poorly described by existing prognostication tools. To improve surgical safety during the COVID-19 pandemic recovery and beyond, novel risk stratification tools are required. Funding British Journal of Surgery Society