Processing Diabetes Mellitus Composite Events in MAGPIE

Effect of adjuvant probiotic therapy (Lactobacillus reuteri) in the treatment of periodontitis associated with diabetes mellitus: clinical, controlled, and randomized study

OBJECTIVES

Subgingival instrumentation (SI) with probiotics may be a proposal for the treatment of periodontitis (P), for patients with type 2 diabetes mellitus (T2DM). The Lactobacillus reuteri probiotic as an adjunctive therapy in the treatment of P associated with T2DM was evaluated.

MATERIALS AND METHODS

Forty diabetic participants diagnosed with P (stage III and IV, grade B) were randomized into SI + Placebo (n = 20): subgingival instrumentation plus placebo lozenges and SI + Probi (n = 20): subgingival instrumentation plus probiotics. Probing depth (PD), gingival recession (GR), clinical attachment level (CAL), plaque index (PI), bleeding on probing (BoP), and PISA index were performed at baseline and 30, 90, and 180 days. Cytokine concentration in the gingival crevicular fluid, subgingival biofilm sample, and LDL and HDL subfractions were evaluated.

RESULTS

In the deep pockets, PD in SI + Probi showed increased values (p = 0.02) compared to SI + Placebo at 90 days. For CAL, SI + Probi showed increased values compared to SI + Placebo, with a significant difference at 30 days (p = 0.03), 90 days (p = 0.02), and 180 days (p = 0.04). At #PD ≥ 7 mm, SI + Probi had a more frequent number of sites (p = 0.03) compared to SI + Placebo only at baseline. For the PISA, SI + Probi showed a significant difference (p = 0.04) compared to SI + Placebo at 90 days. For cytokines, SI + Probi showed higher quantification than SI + Placebo for IL-10 (p < 0.001) at 90 days, IL-12 (p = 0.010) at 90 days, IL-1β (p = 0.035) at 90 days, and IL-8 (p = 0.003) at baseline. SI + Placebo showed higher quantification of IL-1β (p = 0.041) compared to SI + Probi only at 30 days. There was a reduction in all microbial complexes. SI + Probi improved LDL size (246.7 nm vs 260.4 nm; p < 0.001), while large HDL subfractions were reduced aft 180 days of treatment (24.0% vs 20.3%; p = 0.022) when compared with SI + Placebo; this response was dependent of probiotics (1.0 mg/dL vs - 6.2 mg/dL; p = 0.002).

CONCLUSION

Subgingival instrumentation improved the clinical periodontal parameters in patients with T2DM. The use of L. reuteri probiotics had no additional effects compared with the placebo; however, there was a positive effect on the lipoprotein subfraction.

CLINICAL RELEVANCE

Scientific rationale for study: subgingival instrumentation with probiotics may be a proposal for the treatment of periodontitis (P), especially for patients with type 2 diabetes mellitus (T2DM).

PRINCIPAL FINDINGS

the use of L. reuteri probiotics had no additional effects compared with the placebo; however, there was a positive effect on the lipoprotein subfraction.  Practical implications: L. reuteri as an adjunct to subgingival instrumentation may have significant therapeutic implications in dyslipidemia.

Scoping Review of Healthcare Literature on Mobile, Wearable, and Textile Sensing Technology for Continuous Monitoring

Remote monitoring of health can reduce frequent hospitalisations, diminishing the burden on the healthcare system and cost to the community. Patient monitoring helps identify symptoms associated with diseases or disease-driven disorders, which makes it an essential element of medical diagnoses, clinical interventions, and rehabilitation treatments for severe medical conditions. This monitoring can be expensive and time-consuming and provide an incomplete picture of the state of the patient. In the last decade, there has been a significant increase in the adoption of mobile and wearable devices, along with the introduction of smart textile solutions that offer the possibility of continuous monitoring. These alternatives fuel a technology shift in healthcare, one that involves the continuous tracking and monitoring of individuals. This scoping review examines how mobile, wearable, and textile sensing technology have been permeating healthcare by offering alternate solutions to challenging issues, such as personalised prescriptions or home-based secondary prevention. To do so, we have selected 222 healthcare literature articles published from 2007 to 2019 and reviewed them following the PRISMA process under the schema of a scoping review framework. Overall, our findings show a recent increase in research on mobile sensing technology to address patient monitoring, reflected by 128 articles published in journals and 19 articles in conference proceedings between 2014 and 2019, which represents 57.65% and 8.55% respectively of all included articles.

Complementing Agents with Cognitive Services: A Case Study in Healthcare

Personal Agents (PAs) have longly been explored as assistants to support users in their daily activities. Surprisingly, few works refer to the adoption of PAs in the healthcare domain, where they can assist physicians' activities reducing medical errors. Although literature proposes different approaches for modelling and engineering PAs, none of them discusses how they can be integrated with cognitive services in order to empower their reasoning capabilities. In this paper we present an integration model, specifically devised for healthcare applications, that enhances Belief-Desire-Intention agents reasoning with advanced cognitive capabilities. As a case study, we adopt this integrated model in the critical care path of trauma resuscitation, stepping forward to the vision of Smart Hospitals.

Influence of Periodontal Disease on cardiovascular markers in Diabetes Mellitus patients

The objective of the present study was to establish if individuals with Diabetes Mellitus (DM2) and periodontal diseases (gingivitis or periodontitis) presented an increase in the concentration of modified LDL (moLDL) and what is the influence of periodontal treatment on the decrease of moLDL particles with consequent improvement in the parameters of DM2. Twenty-four diabetic patients with periodontitis (Group 1) and twenty-four diabetic patients with gingivitis (Group 2) were followed up for a period of 12 months. Group 1 was treated with periodontal debridement, and Group 2 received supra-gingival scaling and prophylaxis. In both groups, periodontal clinical parameters: probing depth (PD), clinical attachment level (CAL), gingival resection (GR), bleeding on probing index (BOP) and plaque index; inflammatory serum markers (glycemia, A1c, total cholesterol, HDL-cholesterol (HDL-c), LDL-cholesterol (LDL-c), triglycerides and hs-CRP) and oxidized LDL (oxLDL) were measured at baseline, t = 6 and t = 12 months after treatment. Solutions of LDL were analyzed using the nonlinear optical Z-Scan and optical absorption techniques. The periodontal clinical parameters showed significant improvement (p < 0.05) in both Group after 12 months. For both groups, total cholesterol, HDL-c, LDL-c, triglycerides and A1c levels did not show significant reductions after periodontal therapy. hs-CRP levels in Group 1 presented a significant reduction after 12 months. The glycemic rate and the oxLDL concentrations did not show significant differences as a function of time. The optical measurements of LDL solutions revealed an improvement of the LDL-c quality in both groups. Periodontal debridement was able to improve periodontal parameters and the quality of LDL-c in diabetic patients but without changes in the oxLDL concentration in both groups. Considering the clinical relevance, the reduction of infectious and inflammatory sites present in the oral cavity through periodontal therapy may help with the control and prevention of hyperglycemia and precursors of cardiovascular diseases.

Real-time multi-agent systems for telerehabilitation scenarios

Telerehabilitation in older adults is most needed in the patient environments, rather than in formal ambulatories or hospitals. Supporting such practices brings significant advantages to patients, their family, formal and informal caregivers, clinicians, and researchers. This paper presents a focus group with experts in physiotherapy and telerehabilitation, debating on the requirements, current techniques and technologies developed to facilitate and enhance the effectiveness of telerehabilitation, and the still open challenges. Particular emphasis is given to (i) the body-parts requiring the most rehabilitation, (ii) the typical environments, initial causes, and general conditions, (iii) the values and parameters to be observed, (iv) common errors and limitations of current practices and technological solutions, and (v) the envisioned and desired technological support. Consequently, it has been performed a systematic review of the state of the art, investigating what types of systems and support currently cope with telerehabilitation practices and possible matches with the outcomes of the focus group. Technological solutions based on video analysis, wearable devices, robotic support, distributed sensing, and gamified telerehabilitation are examined. Particular emphasis is given to solutions implementing agent-based approaches, analyzing and discussing strength, limitations, and future challenges. By doing so, it has been possible to relate functional requirements expressed by professional physiotherapists and researchers, with the need for extending multi-agent systems (MAS) peculiarities at the sensing level in wearable solutions establishing new research challenges. In particular, to be employed in safety-critical cyber-physical scenarios with user-sensor and sensor-sensor interactions, MAS are requested to handle timing constraints, scarcity of resources and new communication means, crucial to providing real-time feedback and coaching. Therefore, MAS pillars such as the negotiation protocol and the agent's internal scheduler have been investigated, proposing solutions to achieve the aforementioned real-time compliance.

Indexing the Event Calculus: Towards practical human-readable Personal Health Systems

Personal Health Systems (PHS) are mobile solutions tailored to monitoring patients affected by chronic non communicable diseases. In general, a patient affected by a chronic disease can generate large amounts of events: for example, in Type 1 Diabetic patients generate several glucose events per day, ranging from at least 6 events per day (under normal monitoring) to 288 per day when wearing a continuous glucose monitor (CGM) that samples the blood every 5 minutes for several days. Just by itself, without considering other physiological parameters, it would be impossible for medical doctors to individually and accurately follow every patient, highlighting the need of simple approaches towards querying physiological time series. Achieving this with current technology is not an easy task, as on one hand it cannot be expected that medical doctors have the technical knowledge to query databases and on the other hand these time series include thousands of events, which requires to re-think the way data is indexed. Anyhow, handling data streams efficiently is not enough. Domain experts' knowledge must be explicitly included into PHSs in a way that it can be easily readed and modified by medical staffs. Logic programming represents the perfect programming paradygm to accomplish this task. In this work, an Event Calculus-based reasoning framework to standardize and express domain-knowledge in the form of monitoring rules is suggested, and applied to three different use cases. However, if online monitoring has to be achieved, the reasoning performance must improve dramatically. For this reason, three promising mechanisms to index the Event Calculus Knowledge Base are proposed. All of them are based on different types of tree indexing structures: k-d trees, interval trees and red-black trees. The paper then compares and analyzes the performance of the three indexing techniques, by computing the time needed to check different type of rules (and eventually generating alerts), when the number of recorded events (e.g. values of physiological parameters) increases. The results show that customized jREC performs much better when the event average inter-arrival time is little compared to the checked rule time-window. Instead, where the events are more sparse, the use of k-d trees with standard EC is advisable. Finally, the Multi-Agent paradigm helps to wrap the various components of the system: the reasoning engines represent the agent minds, and the sensors are its body. The said agents have been developed in MAGPIE, a mobile event based Java agent platform.

Type 2 Diabetes Patients Benefit from the COMODITY12 mHealth System: Results of a Randomised Trial

Patient acceptance is one of the major barriers toward widespread use of mHealth systems. The aim of this study was to assess system operability and whole trial feasibility, including patients' experience with their use of COMMODITY12 mHealth system under. Secondary study aims included assessment of several metabolic parameters as well as patient adherence to the treatment. This was a prospective parallel-arm randomized controlled trial in outpatients diagnosed with DM2, being treated in the primary care settings in Lodz region, Poland, with 6 weeks period of follow-up. Patients opinions were collected with 7-item questionnaire, assessing different aspects of system use, as well as EuroQol-5D-5 L questionnaire, assessing health-related quality of life. Sixty patients (female, 24, male, 36, mean age +/- SD 59.5 +/- 6.8) completed study. All four layers of the COMMODITY12 system proved to work smooth under real-life conditions, without major problems. All dimensions of experience with system use were assessed well, with maximum values for clearness of instructions, and ease of use (4.80, and 4.63, respectively). Health related quality of life, as assessed with cumulative utility measure, improved significantly in COMMODITY12 system users (P < 0.05). mHealth system modestly improved glycaemic and blood pressure control, assuring high level of patient adherence with overall adherence reaching 92.9 %. Study proved that the COMODITY12 system is well accepted by type 2 diabetes patients taking part in clinical trial, leading to several clinical benefits, and improved quality of life. Nevertheless, before future commercialisation of the system, several minor problems identified during the study need to be addressed.

Sensor Monitoring of Physical Activity to Improve Glucose Management in Diabetic Patients: A Review

Diabetic individuals need to tightly control their blood glucose concentration. Several methods have been developed for this purpose, such as the finger-prick or continuous glucose monitoring systems (CGMs). However, these methods present the disadvantage of being invasive. Moreover, CGMs have limited accuracy, notably to detect hypoglycemia. It is also known that physical exercise, and even daily activity, disrupt glucose dynamics and can generate problems with blood glucose regulation during and after exercise. In order to deal with these challenges, devices for monitoring patients’ physical activity are currently under development. This review focuses on non-invasive sensors using physiological parameters related to physical exercise that were used to improve glucose monitoring in type 1 diabetes (T1DM) patients. These devices are promising for diabetes management. Indeed they permit to estimate glucose concentration either based solely on physical activity parameters or in conjunction with CGM or non-invasive CGM (NI-CGM) systems. In these last cases, the vital signals are used to modulate glucose estimations provided by the CGM and NI-CGM devices. Finally, this review indicates possible limitations of these new biosensors and outlines directions for future technologic developments.