Dose-dependent effects of randomized intraduodenal whey-protein loads on glucose, gut hormone, and amino acid concentrations in healthy older and younger men

Protein-rich supplements are used widely for the prevention and management of malnutrition in older people. We have reported that healthy older, compared to younger, adults have less suppression of energy intake by whey-protein-effects on appetite-related hormones are unknown. The objective was to determine the effects of intraduodenally administered whey-protein on glucose, gut hormone, and amino acid concentrations, and their relation to subsequent ad libitum energy intake at a buffet meal, in healthy older and younger men. Hydrolyzed whey-protein (30 kcal, 90 kcal, and 180 kcal) and a saline control (~0 kcal) were infused intraduodenally for 60 min in 10 younger (19-29 years, 73 ± 2 kg, 22 ± 1 kg/m²) and 10 older (68-81 years, 79 ± 2 kg, 26 ± 1 kg/m²) healthy men in a randomized, double-blind fashion. Plasma insulin, glucagon, gastric inhibitory peptide (GIP), glucagon-like peptide-1 (GLP-1), peptide tyrosine-tyrosine (PYY), and amino acid concentrations, but not blood glucose, increased, while ghrelin decreased during the whey-protein infusions. Plasma GIP concentrations were greater in older than younger men. Energy intake correlated positively with plasma ghrelin and negatively with insulin, glucagon, GIP, GLP-1, PYY, and amino acids concentrations (p < 0.05). In conclusion, intraduodenal whey-protein infusions resulted in increased GIP and comparable ghrelin, insulin, glucagon, GIP, GLP-1, PYY, and amino acid responses in healthy older and younger men, which correlated to subsequent energy intake.Caroline Giezenaar, Natalie D Luscombe-Marsh, Amy T Hutchison, Scott Standfield, Christine Feinle-Bisset, Michael Horowitz, Ian Chapman and Stijn Soene

Prognostic model to predict postoperative acute kidney injury in patients undergoing major gastrointestinal surgery based on a national prospective observational cohort study.

Background: Acute illness, existing co-morbidities and surgical stress response can all contribute to postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery. The aim of this study was prospectively to develop a pragmatic prognostic model to stratify patients according to risk of developing AKI after major gastrointestinal surgery. Methods: This prospective multicentre cohort study included consecutive adults undergoing elective or emergency gastrointestinal resection, liver resection or stoma reversal in 2-week blocks over a continuous 3-month period. The primary outcome was the rate of AKI within 7 days of surgery. Bootstrap stability was used to select clinically plausible risk factors into the model. Internal model validation was carried out by bootstrap validation. Results: A total of 4544 patients were included across 173 centres in the UK and Ireland. The overall rate of AKI was 14·2 per cent (646 of 4544) and the 30-day mortality rate was 1·8 per cent (84 of 4544). Stage 1 AKI was significantly associated with 30-day mortality (unadjusted odds ratio 7·61, 95 per cent c.i. 4·49 to 12·90; P < 0·001), with increasing odds of death with each AKI stage. Six variables were selected for inclusion in the prognostic model: age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker. Internal validation demonstrated good model discrimination (c-statistic 0·65). Discussion: Following major gastrointestinal surgery, AKI occurred in one in seven patients. This preoperative prognostic model identified patients at high risk of postoperative AKI. Validation in an independent data set is required to ensure generalizability

High-Resolution Additive Manufacturing Error Prediction and Compensation Through 3D CNN Leveraging Semantic Segmentation

Additive manufacturing (AM) is a relatively new domain of manufacturing processes that began with its first patent in 1986. Since then, AM processes quickly grew in popularity due to their flexibility, superior efficiency in high mix low volume manufacturing settings, and lower material costs compared to more subtractive processes. Despite its increasing popularity, AM processes remain behind subtractive processes in terms of quality and the speed at which new technologies are integrated. Introducing Industry 4.0 technologies is an excellent opportunity to address the need for quality assurance tools for AM processes. First, the question of how the quality of additively manufactured parts can be increased to match parts created through subtractive processes must be asked. In this dissertation, two machine learning (ML) models are developed and utilized in a federated environment to mimic what one would see in a production setting. The proposed models increase AM part quality by (1) predicting the resulting geometry of an AM process and (2) compensating for geometric errors by altering the initial stereolithography (STL) file before slicing. In addition to performing geometric error prediction and compensation, the models were enhanced to be resilient to changes in geometry by training on segments of a 3D object rather than the whole object. Next, process parameters from fused-filament fabrication (FFF) processes were added to the ML models to add resilience process parameter variance. Lastly, the ML models were deployed in a federated environment created from three FFF 3D printers that collaboratively created a dataset for the ML models. Collectively, these works expand the research area created by AM, federated learning, and error compensation. This proposal addresses research gaps in the current literature by first setting the prediction and compensation resolution of voxel-based ML methods to a static 100 µm, thereby reducing the error associated with each voxel. Secondly, process parameters are introduced to the model, further increasing prediction and compensation accuracy compared to predicting on the geometry alone. Lastly, the models are deployed in a federated AM environment with multiple 3D printers acting as clients to reduce each client's time spent generating data while maintaining model performance.Doctor of PhilosophyAdditive manufacturing (AM) is a relatively new field where parts are created by extruding material to build a product in the desired shape. A key advantage of such a process is that it is more flexible than those subtractive processes, which remove material from a part. On the other hand, parts produced by AM processes generally have lower quality due to the very specific environments necessary to obtain high-quality parts. Because there is an increased desire to make customized parts (high mix) in small amounts (low volume), AM processes are seeing a rise in popularity, but there is still a need to improve the quality of these produced parts. Furthermore, these environments where AM is utilized generally have multiple 3D printers that manufacturers can leverage to create comprehensive datasets for model development. This dissertation uses machine learning (ML) to collect data from AM processes and reduce AM process errors. By comparing the process's input with the process's output, an ML model can estimate the result of the AM process, including potential defects. This dissertation addresses research gaps in current literature by reducing the error associated with converting the input and output 3D objects to voxels, using parameters to the AM process in the ML models, and using the ML models with 3D printers in a networked environment while forbidding sharing private data

Pre-operative Radial Arterial Diameter Predicts Early Failure of Arteriovenous Fistula (AVF) for Haemodialysis

IntroductionLong term patency of arteriovenous fistula (AVF) is relevant to the management of end stage renal failure (ESRF) patients on haemodialysis (HD). We evaluated the role of routine radial arterial duplex for imaging radial artery before AVF formation to investigate the relationaship between radial artery internal diameter (ID) and AVF patency.Methods21 patients with ESRF were examined by duplex sonography before AVF formation, 1 day, 1 week, 4 week and 12 weeks post AVF formation. For assessment of AVF patency, patients were divided into 2 groups. Group-1, 11 patients with radial artery ID <1.5mm and Group-2, 10 patients with radial artery ID >1.5mm. Measurement of radial artery blood inflow rate was calculated from mean blood flow velocity and vessel diameter. All AVFs were constructed on the forearm using autologous veins.ResultsIn Group-1, 5 patients (45%) showed immediate thrombosis of AVF graft. All patients in group-2 had patent AVF at 12 weeks. Pre-AVF formation radial artery blood inflow rate between two groups was not significantly different (p=0.06). Radial artery blood inflow rate was consistently and significantly higher in group-2 at all later time points with p value of <0.01 (Mann Whitney test).ConclusionThere was a high failure rate of AVF with radial artery ID of <1.5mm. In the presence of small radial arteries primary access AVF in the upper arm should be considered

Impaired Hyperaemic and Rhythmic Vasomotor Response in Type 1 Diabetes Mellitus Patients: A Predictor of Early Peripheral Vascular Disease

ObjectivesThe smooth muscle of distal vascular networks exhibits periodical contraction and relaxation known as rhythmical vasomotion. The nature of microvascular vasomotion has been shown to correlate with severity of peripheral vascular disease. We present basal and post-ischaemic hyperaemic laser doppler flowmetry vasomotion in control and type 1 adult diabetic patients.DesignProspective case control study.MethodsLaser Doppler flowmetry was used to measure vasomotion and hyperaemic responses in age and body mass index matched male subjects (25 type 1 Diabetes Mellitus and 13 controls), all with ankle/brachial pressure index (ABPI) >1.0 but <1.2.ResultsThe frequency of resting vasomotion was raised in diabetics compared to controls 8 (5–9)min−1 vs. 5 (4–6)min−1 (median (range); p<0.0001). The post ischaemic hyperaemia response was significantly higher in the diabetic group compared to the controls 11 (7–12)min−1 vs. 6 (5–7)min−1 (median (range); p<0.05). Post ischaemic hyperaemic flux (expressed as percent increase from resting) was significantly lower in the diabetic group compared to controls (234±62 vs. 453±155%, p<0.01). The time to achieve peak post ischaemic response was also significantly increased in the diabetic group compared to control: 21.4±0.4 vs. 12.8±5.4sec (mean±SD, p<0.05).ConclusionsVasomotion frequency and its change during hyperaemic insult is significantly different in Type 1 Diabetes Mellitus subjects compared to controls. The results are similar to patients with macrovascular atherosclerosis. Long term studies of these groups of patients will be required to determine the significance of these findings and whether these changes could be used as a non invasive screening test to predict peripheral early vascular disease in type 1 diabetic patients

Achieving good-quality consent: review of literature, case law and guidance

Background Informed consent is an integral part of clinical practice. There is widespread agreement amongst health professionals that obtaining procedural consent needs to move away from a unidirectional transfer of information to a process of supporting patients in making informed, self‐determined decisions. This review aimed to identify processes and measures that warrant consideration when engaging in consent‐based discussions with competent patients undergoing elective procedures. Methods Formal written guidance from the General Medical Council and Royal College of Surgeons of England, in addition to peer‐reviewed literature and case law, was considered in the formulation of this review. Results A framework for obtaining consent is presented that is informed by the key tenets of shared decision‐making (SDM), a model that advocates the contribution of both the clinician and patient to the decision‐making process through emphasis on patient participation, analysis of empirical evidence, and effective information exchange. Moreover, areas of contention are highlighted in which further guidance and research are necessary for improved enhancement of the consent process. Conclusion This SDM‐centric framework provides structure, detail and suggestions for achieving meaningful consent

The Surgical Management of 73 Vascular Malformations and Preoperative Predictive Factors of Major Haemorrhage – A Single Centre Experience

AbstractObjectivesIn our series of patients with congenital vascular malformations (CVMs) we investigate the preoperative factors for predicting major haemorrhage at surgery and propose an algorithm for their surgical management.DesignThis is a partly prospective case series of patients with severe symptoms/complications due to CVMs.Materials and methodsData were collected on 73 consecutive procedures in 41 patients with CVMs from 1992 to 2006 at a large university hospital and the association of following factors with blood loss during the procedure were investigated: type of procedure, possibility of proximal tourniquet use, lesion flow characteristics, previous history of major haemorrhage with CVM surgery, platelet counts and length of hospital stay.ResultsSignificantly higher blood loss was associated with debulking surgery (p=0.006) and with previous history of major haemorrhage during CVM surgery, (p=0.041). Blood loss was higher in lesions where proximal tourniquet application was not possible (p=0.093). High-flow lesions were not strongly associated with major blood loss (p=0.288). Major blood loss (>2l) occurred in 16 (20.8%) procedures performed on 11 (26.2%) patients, but this did not prolong hospital stay.ConclusionSurgery can potentially improve morbidity/mortality in patients with life/limb-threatening complications or severe symptoms due to CVMs, providing they are managed in multidisciplinary specialised centres