Artificial neural network algorithm for online glucose prediction from continuous glucose monitoring.

Background and Aims: Continuous glucose monitoring (CGM) devices could be useful for real-time management of diabetes therapy. In particular, CGM information could be used in real time to predict future glucose levels in order to prevent hypo-/hyperglycemic events. This article proposes a new online method for predicting future glucose concentration levels from CGM data. Methods: The predictor is implemented with an artificial neural network model (NNM). The inputs of the NNM are the values provided by the CGM sensor during the preceding 20 min, while the output is the prediction of glucose concentration at the chosen prediction horizon (PH) time. The method performance is assessed using datasets from two different CGM systems (nine subjects using the Medtronic [Northridge, CA] Guardian® and six subjects using the Abbott [Abbott Park, IL] Navigator®). Three different PHs are used: 15, 30, and 45 min. The NNM accuracy has been estimated by using the root mean square error (RMSE) and prediction delay. Results: The RMSE is around 10, 18, and 27 mg/dL for 15, 30, and 45 min of PH, respectively. The prediction delay is around 4, 9, and 14 min for upward trends and 5, 15, and 26 min for downward trends, respectively. A comparison with a previously published technique, based on an autoregressive model (ARM), has been performed. The comparison shows that the proposed NNM is more accurate than the ARM, with no significant deterioration in the prediction delay

Determinants of enhanced thromboxane biosynthesis in renal transplantation

Background. Despite great improvement in patient and graft survival, the long-term morbidity and mortality in renal transplant recipients (RTRs) are still significant, with a high incidence of cardiovascular disease-related deaths. Methods. We investigated thromboxane (TXA2) biosynthesis and endothelial and coagulative activation in 65 patients who received a renal transplant. Results. The rate of TXA2 biosynthesis (urinary 11-dehydro-TXB2 excretion largely reflects platelet TXA2 production in vivo) was significantly (P < 0.0001) higher in RTRs than in healthy subjects. Plasma von Willebrand factor (vWF) and thrombin-antithrombin (TAT) complexes were significantly higher (P < 0.001) in RTRs compared with controls. Urinary 11-dehydro-TXB2 directly correlated with plasma vWF and cholesterol. We next examined the relative influence of cyclosporine A (CsA) on TXA2 biosynthesis and endothelial activation, comparing a group of RTRs not receiving CsA with an age- and sex-matched group of patients treated with CsA. Urinary excretion of 11-dehydro-TXB2 and plasma levels of vWF were significantly increased in RTRs who received CsA compared with those who did not. After an overall follow-up of 120 months, RTRs who experienced cardiovascular events had a higher frequency of abnormal plasma levels of vWF than patients who remained event free. Conclusion. Renal transplantation is associated with in vivo platelet activation highly related to endothelial activation. This is particularly evident in CsA-treated patients. Administration of drugs that are able to reduce or eliminate thromboxane-dependent platelet activation in vivo may be beneficial to reduce the risk of cardiovascular events in RTRs

Pioglitazone Decreases Fasting and Postprandial Endogenous Glucose Production in Proportion to Decrease in Hepatic Triglyceride Content

OBJECTIVE—Hepatic triglyceride is closely associated with hepatic insulin resistance and is known to be decreased by thiazolididinediones. We studied the effect of pioglitazone on hepatic triglyceride content and the consequent effect on postprandial endogenous glucose production (EGP) in type 2 diabetes

Participants’ perspectives on mindfulnessbased cognitive therapy for inflammatory bowel disease: a qualitative study nested within a pilot randomised controlled trial

Background: Mindfulness-based interventions have shown to improve depression and anxiety symptoms as well as quality of life in patients with inflammatory bowel disease (IBD). However, little is known about the experiences of this group of patients participating in mindfulness interventions. This paper sets out to explore the perspectives of patients with IBD recruited to a pilot randomised controlled trial (RCT) of mindfulness-based cognitive therapy (MBCT) about the intervention. Methods: In a qualitative study nested within a parallel two-arm pilot RCT of mindfulness-based cognitive therapy for patients with IBD, two focus group interviews (using the same schedule) and a free text postal survey were conducted. Data from both were analysed using thematic analysis. Data and investigator triangulation was performed to enhance confidence in the ensuing findings. Forty-four patients with IBD were recruited to the pilot RCT from gastroenterology outpatient clinics from two Scottish NHS boards. Eighteen of these patients (ten from mindfulness intervention and eight from control group) also completed a postal survey and participated in two focus groups after completing post intervention assessments. Results: The major themes that emerged from the data were the following: perceived benefits of MBCT for IBD, barriers to attending MBCT and expectations about MBCT. Participants identified MBCT as a therapeutic, educational and an inclusive process as key benefits of the intervention. Key barriers included time and travel constraints. Conclusions: This qualitative study has demonstrated the acceptability of MBCT in a group of patients with IBD. Participants saw MBCT as a therapeutic and educational initiative that transformed their relationship with the illness. The inclusive process and shared experience of MBCT alleviated the sense of social isolation commonly associated with IBD. However, time commitment and travel were recognised as a barrier to MBCT which could potentially influence the degree of therapeutic gain from MBCT for some participants. Keywords: Inflammatory bowel disease, Mindfulness, MBCT, Focus groups, Qualitative stud

Personalizing Cancer Pain Therapy: Insights from the Rational Use of Analgesics (RUA) Group

Introduction: A previous Delphi survey from the Rational Use of Analgesics (RUA) project involving Italian palliative care specialists revealed some discrepancies between current guidelines and clinical practice with a lack of consensus on items regarding the use of strong opioids in treating cancer pain. Those results represented the basis for a new Delphi study addressing a better approach to pain treatment in patients with cancer. Methods: The study consisted of a two-round multidisciplinary Delphi study. Specialists rated their agreement with a set of 17 statements using a 5-point Likert scale (0 = totally disagree and 4 = totally agree). Consensus on a statement was achieved if the median consensus score (MCS) (expressed as value at which at least 50% of participants agreed) was at least 4 and the interquartile range (IQR) was 3–4. Results: This survey included input from 186 palliative care specialists representing all Italian territory. Consensus was reached on seven statements. More than 70% of participants agreed with the use of low dose of strong opioids in moderate pain treatment and valued transdermal route as an effective option when the oral route is not available. There was strong consensus on the importance of knowing opioid pharmacokinetics for therapy personalization and on identifying immediate-release opioids as key for tailoring therapy to patients’ needs. Limited agreement was reached on items regarding breakthrough pain and the management of opioid-induced bowel dysfunction. Conclusion: These findings may assist clinicians in applying clinical evidence to routine care settings and call for a reappraisal of current pain treatment recommendations with the final aim of optimizing the clinical use of strong opioids in patients with cancer

Development of an error model for a factory-calibrated continuous glucose monitoring sensor with 10-day lifetime

Factory-calibrated continuous glucose monitoring (FC-CGM) sensors are new devices used in type 1 diabetes (T1D) therapy to measure the glucose concentration almost continuously for 10–14 days without requiring any in vivo calibration. Understanding and modelling CGM errors is important when designing new tools for T1D therapy. Available literature CGM error models are not suitable to describe the FC-CGM sensor error, since their domain of validity is limited to 12-h time windows, i.e., the time between two consecutive in vivo calibrations. The aim of this paper is to develop a model of the error of FC-CGM sensors. The dataset used contains 79 FC-CGM traces collected by the Dexcom G6 sensor. The model is designed to dissect the error into its three main components: effect of plasma-interstitium kinetics, calibration error, and random measurement noise. The main novelties are the model extension to cover the entire sensor lifetime and the use of a new single-step identification procedure. The final error model, which combines a first-order linear dynamic model to describe plasma-interstitium kinetics, a second-order polynomial model to describe calibration error, and an autoregressive model to describe measurement noise, proved to be suitable to describe FC-CGM sensor errors, in particular improving the estimation of the physiological time-delay

Strumenti di simulazione per il controllo di gestione: dall’analisi dei sistemi alla System Dynamics

Il contributo prende in analisi le potenzialità che gli strumenti di simulazione possono avere ai fini di una migliore comprensione e gestione di sistemi complessi, proponendo in tal senso anche un esempio relativo ad un caso operativ