Declining incidence of major lower-extremity amputations in the Northern Danish Region between 2016 and 2021:The impact of diabetes and preventive vascular procedures

BackgroundPreventing lower-extremity amputations (LEAs) is pivotal. In the present study we aimed to examine the recent trends in non-traumatic LEAs seen in the Northern Danish Region.MethodsUsing data from the regional Business Intelligence unit we identified all non-traumatic LEAs (n=689) performed in people above 50 years of age in the Northern Danish Region between January 2016 and December 2021 (approximately 600.000 inhabitants). Persons with diabetes (n=26,025) were identified based on ICD-10 codes and data from The National Health Insurance Service Registry, while preventive vascular procedures (n=1,097) were identified using surgical codes. Major LEA was defined as any amputation above the ankle. Incidence rates were expressed as events per 1.000 person-years. Trends were described as differences between the periods 2016-2018 and 2019-2021.ResultsA total of 249 (36%) major LEAs were performed in people with diabetes. People with diabetes were younger (71 vs 77 years, p<0.001) and more frequently male (70% versus 54%, p<0.001). Between 2016-2018 and 2019-2021 the incidence of major LEA declined from 1.76 (95% CI: 1.75-1.76) to 1.39 (1.39-1.39) in people with diabetes, and from 0.47 (0.47-0.47) to 0.20 (0.20-0.20) in people without diabetes (all p<0.001). Simultaneously, the incidence of preventive vascular surgery increased from 2.26 (2.26-2.26) to 3.48 (3.48-3.48) in people with diabetes and declined slightly in people without 0.49 (0.49-0.49) to 0.47 (0.47-0.47) (all p<0.001).ConclusionDespite significant declines in major LEA in both people with and without diabetes, most of the decline was driven by a large reduction in major LEAs in people without diabetes. Diabetic foot, lower extremity amputation, major amputation, minor amputation, preventive vascular procedures, revascularization, vascular surgery

The Formation and Evolution of the First Massive Black Holes

The first massive astrophysical black holes likely formed at high redshifts (z>10) at the centers of low mass (~10^6 Msun) dark matter concentrations. These black holes grow by mergers and gas accretion, evolve into the population of bright quasars observed at lower redshifts, and eventually leave the supermassive black hole remnants that are ubiquitous at the centers of galaxies in the nearby universe. The astrophysical processes responsible for the formation of the earliest seed black holes are poorly understood. The purpose of this review is threefold: (1) to describe theoretical expectations for the formation and growth of the earliest black holes within the general paradigm of hierarchical cold dark matter cosmologies, (2) to summarize several relevant recent observations that have implications for the formation of the earliest black holes, and (3) to look into the future and assess the power of forthcoming observations to probe the physics of the first active galactic nuclei.Comment: 39 pages, review for "Supermassive Black Holes in the Distant Universe", Ed. A. J. Barger, Kluwer Academic Publisher

The Formation of the First Massive Black Holes

Supermassive black holes (SMBHs) are common in local galactic nuclei, and SMBHs as massive as several billion solar masses already exist at redshift z=6. These earliest SMBHs may grow by the combination of radiation-pressure-limited accretion and mergers of stellar-mass seed BHs, left behind by the first generation of metal-free stars, or may be formed by more rapid direct collapse of gas in rare special environments where dense gas can accumulate without first fragmenting into stars. This chapter offers a review of these two competing scenarios, as well as some more exotic alternative ideas. It also briefly discusses how the different models may be distinguished in the future by observations with JWST, (e)LISA and other instruments.Comment: 47 pages with 306 references; this review is a chapter in "The First Galaxies - Theoretical Predictions and Observational Clues", Springer Astrophysics and Space Science Library, Eds. T. Wiklind, V. Bromm & B. Mobasher, in pres

Fasting and postprandial plasma ghrelin levels are decreased in patients with liver failure previous to liver transplantation

[Abstract] Anorexia is a problem of paramount importance in patients with advanced liver failure. Ghrelin has important actions on feeding and weight homeostasis. Concentrations of ghrelin are controversial in liver cirrhosis. Our aim was to study fasting ghrelin and their response to an oral glucose tolerance test (OGTT) in liver failure patients and normal subjects. Methods We included 16 patients with severe liver failure prior to liver transplantation. As a control group we included 10 age- and BMI-matched healthy subjects. After an overnight fast, 75 g of oral glucose were administered; glucose, insulin, and ghrelin were obtained at baseline and at times 30, 60, 90, and 120 min, respectively. Results Fasting ghrelin (median and range) were statistically significantly lower for patients compared to the controls, 527 (377–971) pg/ml vs. 643 (523–2163) pg/ml, P = 0.045, for patients and controls, respectively. The area under the curve for total ghrelin post-OGTT were lower in end-stage liver failure patients than in the control group, 58815 (44730–87420) pg/ml min vs. 76560 (56160–206385) pg/ml min, for patients and controls, respectively, P = 0.027. Conclusions Ghrelin levels are significantly decreased both fasting and post-OGTT in patients with liver failure candidates for transplantation. Decreased ghrelin levels could contribute to anorexia in patients with cirrhosis.Instituto de Salud Carlos III; PI051024Instituto de Salud Carlos III; PI070413Xunta de Galicia; PS07/12Xunta de Galicia; PGIDT05PXIC91605PNXunta de Galicia; INCITE08ENA916110E

Echo mapping of the black hole accretion flow in NGC 7469

Reverberation mapping (RM) can measure black hole accretion disc sizes and radial structure through observable light travel time lags that should increase with wavelength as due to the disc’s temperature profile. Our 250-d RM campaign on NGC 7469 combines sub-day cadence 7-band photometry from the Las Cumbres Observatory robotic telescopes and weekly X-ray and UVOT data from Swift. By fitting these light curves, we measure the spectral energy distribution (SED) of the variable accretion disc, and inter-band lags of just 1.5 d across the UV to optical range. The disc SED is close to the expected , and the lags are consistent with , but three times larger than expected. We consider several possible modifications to standard disc assumptions. First, for a M black hole and two possible spins , we fit the X-ray-ultraviolet (UV)-optical SED with a compact relativistic corona at height irradiating a flat disc with accretion rate inclined to the line of sight by . To fit the lags as well as the SED, this model requires a low spin and boosts disc colour temperatures by a factor , which shifts reprocessed light to shorter wavelengths. Our Bowl model with neglects relativity near the black hole, but fits the UV-optical lags and SEDs using a flat disc with and a steep outer rim at d with . This rim occurs near the K dust sublimation temperature in the disc atmosphere, supporting models that invoke dust opacity to thicken the disc and launch failed radiatively driven dusty outflows at the inner edge of the broad line region (BLR). Finally, the disc lags and SEDs exhibit a significant excess in the u and r bands, suggesting Balmer continuum and H emission, respectively, from the BLR

Discovery of biomarkers for glycaemic deterioration before and after the onset of type 2 diabetes: descriptive characteristics of the epidemiological studies within the IMI DIRECT Consortium

\ua9 2019, The Author(s). Aims/hypothesis: Here, we describe the characteristics of the Innovative Medicines Initiative (IMI) Diabetes Research on Patient Stratification (DIRECT) epidemiological cohorts at baseline and follow-up examinations (18, 36 and 48 months of follow-up). Methods: From a sampling frame of 24,682 adults of European ancestry enrolled in population-based cohorts across Europe, participants at varying risk of glycaemic deterioration were identified using a risk prediction algorithm (based on age, BMI, waist circumference, use of antihypertensive medication, smoking status and parental history of type 2 diabetes) and enrolled into a prospective cohort study (n = 2127) (cohort 1, prediabetes risk). We also recruited people from clinical registries with type 2 diabetes diagnosed 6–24 months previously (n = 789) into a second cohort study (cohort 2, diabetes). Follow-up examinations took place at ~18 months (both cohorts) and at ~48 months (cohort 1) or ~36 months (cohort 2) after baseline examinations. The cohorts were studied in parallel using matched protocols across seven clinical centres in northern Europe. Results: Using ADA 2011 glycaemic categories, 33% (n = 693) of cohort 1 (prediabetes risk) had normal glucose regulation and 67% (n = 1419) had impaired glucose regulation. Seventy-six per cent of participants in cohort 1 was male. Cohort 1 participants had the following characteristics (mean \ub1 SD) at baseline: age 62 (6.2) years; BMI 27.9 (4.0) kg/m2; fasting glucose 5.7 (0.6) mmol/l; 2 h glucose 5.9 (1.6) mmol/l. At the final follow-up examination the participants’ clinical characteristics were as follows: fasting glucose 6.0 (0.6) mmol/l; 2 h OGTT glucose 6.5 (2.0) mmol/l. In cohort 2 (diabetes), 66% (n = 517) were treated by lifestyle modification and 34% (n = 272) were treated with metformin plus lifestyle modification at enrolment. Fifty-eight per cent of participants in cohort 2 was male. Cohort 2 participants had the following characteristics at baseline: age 62 (8.1) years; BMI 30.5 (5.0) kg/m2; fasting glucose 7.2 (1.4) mmol/l; 2 h glucose 8.6 (2.8) mmol/l. At the final follow-up examination, the participants’ clinical characteristics were as follows: fasting glucose 7.9 (2.0) mmol/l; 2 h mixed-meal tolerance test glucose 9.9 (3.4) mmol/l. Conclusions/interpretation: The IMI DIRECT cohorts are intensely characterised, with a wide-variety of metabolically relevant measures assessed prospectively. We anticipate that the cohorts, made available through managed access, will provide a powerful resource for biomarker discovery, multivariate aetiological analyses and reclassification of patients for the prevention and treatment of type 2 diabetes

Insulin and GH Signaling in Human Skeletal Muscle In Vivo following Exogenous GH Exposure: Impact of an Oral Glucose Load

GH induces acute insulin resistance in skeletal muscle in vivo, which in rodent models has been attributed to crosstalk between GH and insulin signaling pathways. Our objective was to characterize time course changes in signaling pathways for GH and insulin in human skeletal muscle in vivo following GH exposure in the presence and absence of an oral glucose load.Eight young men were studied in a single-blinded randomized crossover design on 3 occasions: 1) after an intravenous GH bolus 2) after an intravenous GH bolus plus an oral glucose load (OGTT), and 3) after intravenous saline plus OGTT. Muscle biopsies were taken at t = 0, 30, 60, and 120. Blood was sampled at frequent intervals for assessment of GH, insulin, glucose, and free fatty acids (FFA).GH increased AUC(glucose) after an OGTT (p<0.05) without significant changes in serum insulin levels. GH induced phosphorylation of STAT5 independently of the OGTT. Conversely, the OGTT induced acute phosphorylation of the insulin signaling proteins Akt (ser(473) and thr(308)), and AS160.The combination of OGTT and GH suppressed Akt activation, whereas the downstream expression of AS160 was amplified by GH. WE CONCLUDED THE FOLLOWING: 1) A physiological GH bolus activates STAT5 signaling pathways in skeletal muscle irrespective of ambient glucose and insulin levels 2) Insulin resistance induced by GH occurs without a distinct suppression of insulin signaling proteins 3) The accentuation of the glucose-stimulated activation of AS 160 by GH does however indicate a potential crosstalk between insulin and GH.ClinicalTrials.gov NCT00477997

Bayesian network imputation methods applied to multi-omics data identify putative causal relationships in a type 2 diabetes dataset containing incomplete data: An IMI DIRECT Study

\ua9 2025 Howey et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Here we report the results from exploratory analysis using a Bayesian network approach of data originally derived from a large North European study of type 2 diabetes (T2D) conducted by the IMI DIRECT consortium. 3029 individuals (795 with T2D and 2234 without) within 7 different study centres provided data comprising genotypes, proteins, metabolites, gene expression measurements and many different clinical variables. The main aim of the current study was to demonstrate the utility of our previously developed method to fit Bayesian networks by performing exploratory analysis of this dataset to identify possible causal relationships between these variables. The data was analysed using the BayesNetty software package, which can handle mixed discrete/continuous data with missing values. The original dataset consisted of over 16,000 variables, which were filtered down to 260 variables for analysis. Even with this reduction, no individual had complete data for all variables, making it impossible to analyse using standard Bayesian network methodology. However, using the recently proposed novel imputation method implemented in BayesNetty we computed a large average Bayesian network from which we could infer possible associations and causal relationships between variables of interest. Our results confirmed many previous findings in connection with T2D, including possible mediating proteins and genes, some of which have not been widely reported. We also confirmed potential causal relationships with liver fat that were identified in an earlier study that used the IMI DIRECT dataset but was limited to a smaller subset of individuals and variables (namely individuals with complete data at predefined variables of interest). In addition to providing valuable confirmation, our analyses thus demonstrate a proof-of-principle of the utility of the method implemented within BayesNetty. The full final average Bayesian network generated from our analysis is freely available and can be easily interrogated further to address specific focussed scientific questions of interest