Standard Control Strategies Research Articles

Towards stable and efficient nitrogen removal in wastewater treatment processes via an adaptive neural network based sliding mode controller

Advanced controllers often offer an innovative solution to proper quality control in wastewater treatment processes (WWTPs). However, nonlinearity and uncertain disturbances usually make the conventional control strategies inadequate or impossible for the stable operations of WWTPs. To guarantee the stability of ammonia nitrogen concentration (SNH) control in WWTPs, a direct adaptive neural networks-based sliding mode control (ANNSMC) strategy has been proposed in this article. A sliding mode controller is designed and implemented with the help of an adaptive Neural Network (ANN), named Radial Basis Function Neural Network (RBFNN), which can approach the desired control law accurately. Also, the stability of a system installed with the ANNSMC is analyzed by using the Lyapunov theorem, which ensures system robustness and adaptability. Additionally, to deal with high energy consumption and low treatment efficiency problems in the wastewater denitrification processes, this paper proposes a dual-loop denitrification control strategy and validates it in the Benchmark Simulation Model No.2 (BSM2) platform. The strategy can strengthen the denitrification efficiency by collaborating the SNH with nitrate nitrogen (SNO) concentration in the WWTPs properly. The experimental results demonstrate that the proposed strategy can obtain remarkable stability and robustness, reducing energy consumption effectively compared with other standard and advanced control strategies.

Adaptive second order sliding mode control of an oscillating water column

AbstractThe energy from waves has a vast untapped potential to contribute to renewable energy supply and diversification. For that reason, wave energy conversion systems have been a topical research area in recent years. In particular, harnessing wave energy with an oscillating water column converter has proved to be one suitable solution, which has also seen a number of successful deployments. Nevertheless, additional research is required for this technology in order to reach full commercial maturity and economic performance. This paper proposes an adaptive second order sliding mode controller to maximise the converted energy. In particular, the proposed adaptive control setup maintains the sliding mode robust features, while reducing high frequency oscillations and abrupt control actions produced by fixed‐gain algorithms. A comparison of energy generation performance shows better energy conversion efficiency of the proposed control strategy over standard speed regulation control strategies, even considering air compression dynamics and hydrodynamics in the tests.

A hybrid smell agent symbiosis organism search algorithm for optimal control of microgrid operations.

This paper presents a hybrid Smell Agent Symbiosis Organism Search Algorithm (SASOS) for optimal control of autonomous microgrids. In microgrid operation, a single optimization algorithm often lacks the required balance between accuracy and speed to control power system parameters such as frequency and voltage effectively. The hybrid algorithm reduces the imbalance between exploitation and exploration and increases the effectiveness of control optimization in microgrids. To achieve this, various energy resource models were coordinated into a single model for optimal energy generation and distribution to loads. The optimization problem was formulated based on the network power flow and the discrete-time sampling of the constrained control parameters. The development of SASOS comprises components of Symbiotic Organism Search (SOS) and Smell Agent Optimization (SAO) codified in an optimization loop. Twenty-four standard test function benchmarks were used to evaluate the performance of the algorithm developed. The experimental analysis revealed that SASOS obtained 58.82% of the Desired Convergence Goal (DCG) in 17 of the benchmark functions. SASOS was implemented in the Microgrid Central Controller (MCC) and benchmarked alongside standard SOS and SAO optimization control strategies. The MATLAB/Simulink simulation results of the microgrid load disturbance rejection showed the viability of SASOS with an improved reduction in Total Harmonic Distortion (THD) of 19.76%, compared to the SOS, SAO, and MCC methods that have a THD reduction of 15.60%, 12.74%, and 6.04%, respectively, over the THD benchmark. Based on the results obtained, it can be concluded that SASOS demonstrates superior performance compared to other methods. This finding suggests that SASOS is a promising solution for enhancing the control system of autonomous microgrids. It was also shown to apply to other sectors of engineering optimization.

Use of a Statistical Adaptive Treatment Strategy Approach for Emulating Randomized Controlled Trials Using Observational Data: The Example of Blood-Pressure Control Strategies for the Prevention of Cardiovascular Events Among Individuals With Hypertension at High Cardiovascular Risk.

Statistical approaches to adaptive treatment strategies (ATS) can be used to mimic the sequential decision-making inherently found in clinical practice. To illustrate the use of a statistical ATS approach, we emulated a target trial of different blood pressure (BP) control plans for the prevention of cardiovascular events among individuals with hypertension at high cardiovascular risk, inspired by the Systolic Blood Pressure Intervention Trial (SPRINT). We included 103,708 patients with hypertension and a "QRISK3" estimated 10-year risk of cardiovascular disease of ≥20% who initiated an antihypertensive drug between 1998 and 2018. Dynamic marginal structural models estimated the comparative effects of treating patients with intensive (target BP: 130/80 mm Hg), standard (140/90 mm Hg), and conservative (150/90 mm Hg) BP control strategies. The adjusted hazard ratios (HRs) for the intensive versus standard strategy were 0.96 (95% confidence interval (CI): 0.92, 1.00) for major adverse cardiovascular events and 0.93 (95% CI: 0.88, 0.97) for death from cardiovascular causes. For the conservative versus standard strategy, they were 1.06 (95% CI: 1.02, 1.10) and 1.08 (95% CI: 1.03, 1.13), respectively. These results are largely compatible with SPRINT. ATS can be used to emulate randomized controlled trials of complex treatment strategies in an observational setting and represents an alternative approach for situations where randomized controlled trials are not feasible.

Real-time wavelet-based adaptive algorithm for low inertia AC microgrids power measurements

This paper proposes a real-time wavelet-based power estimator using a real-time modified stationary discrete wavelet packet transform (RT-MSDWPT). The proposed method overcomes the conventional SDWPT main constraints of power estimations related to the lack of reactive power flow direction and susceptibility to off-nominal frequency operation. The introduction of a digital sampling-shifting of a quarter of the fundamental, applied to the filtered voltages, assures the reactive power flow direction. Additionally, the insertion of an adaptive sampling time procedure based on the power grid frequency estimation mitigates the errors introduced by the network frequency deviations. These modifications make the RT-MSDWPT suitable for being embedded into the standard hierarchical power flow control strategies of ac microgrids. Experimental results assessed using an ac microgrid laboratory setup, operating under different operational scenarios, demonstrate the feasibility of the proposed solution.

Operability and biomimetic control of a micro-aerated fermentation process

The design of reliable control systems to maintain feasible optimal conditions and intensify bioprocesses is a requirement to achieve high product yields and cost-efficient process operations. Micro-aeration is an approach to increase bioprocess product yield. However, standard control strategies may present unsatisfactory performance under oxygen supply constraints. In this paper, a novel framework using process operability and biomimetic control algorithms is proposed to define a control strategy for improved micro-aerated batch process fermentations. In particular, process operability is employed to characterize the ideal operating regions. Then, the Biologically-Inspired Optimal Control Strategy (BIOCS) is implemented to take the process to the optimal path by manipulating the inlet gas flow rate and controlling the metabolic cell state. By employing the developed framework, an optimal operating region is successfully obtained for the controller to maintain the desired metabolic state. Specific scenarios of measurement noise, plant-model mismatch, and step disturbance rejection are successfully addressed in the BIO-CS implementations, while a proportional-integral controller presented noisy control actions under the same conditions. This developed control framework is a novel step towards Industry 4.0 concepts associated with bioprocess systems engineering and could also be implemented to improve other oxygen-limited processes.

The effect of community-driven larval source management and house improvement on malaria transmission when added to the standard malaria control strategies in Malawi: a cluster-randomized controlled trial

BackgroundCurrent standard interventions are not universally sufficient for malaria elimination. The effects of community-based house improvement (HI) and larval source management (LSM) as supplementary interventions to the Malawi National Malaria Control Programme (NMCP) interventions were assessed in the context of an intensive community engagement programme.MethodsThe study was a two-by-two factorial, cluster-randomized controlled trial in Malawi. Village clusters were randomly assigned to four arms: a control arm; HI; LSM; and HI + LSM. Malawi NMCP interventions and community engagement were used in all arms. Household-level, cross-sectional surveys were conducted on a rolling, 2-monthly basis to measure parasitological and entomological outcomes over 3 years, beginning with one baseline year. The primary outcome was the entomological inoculation rate (EIR). Secondary outcomes included mosquito density, Plasmodium falciparum prevalence, and haemoglobin levels. All outcomes were assessed based on intention to treat, and comparisons between trial arms were conducted at both cluster and household level.ResultsEighteen clusters derived from 53 villages with 4558 households and 20,013 people were randomly assigned to the four trial arms. The mean nightly EIR fell from 0.010 infectious bites per person (95% CI 0.006–0.015) in the baseline year to 0.001 (0.000, 0.003) in the last year of the trial. Over the full trial period, the EIR did not differ between the four trial arms (p = 0.33). Similar results were observed for the other outcomes: mosquito density and P. falciparum prevalence decreased over 3 years of sampling, while haemoglobin levels increased; and there were minimal differences between the trial arms during the trial period.ConclusionsIn the context of high insecticide-treated bed net use, neither community-based HI, LSM, nor HI + LSM contributed to further reductions in malaria transmission or prevalence beyond the reductions observed over two years across all four trial arms. This was the first trial, as far as the authors are aware, to test the potential complementary impact of LSM and/or HI beyond levels achieved by standard interventions. The unexpectedly low EIR values following intervention implementation indicated a promising reduction in malaria transmission for the area, but also limited the usefulness of this outcome for measuring differences in malaria transmission among the trial arms.Trial registration PACTR, PACTR201604001501493, Registered 3 March 2016, https://pactr.samrc.ac.za/.

Conceptual design overview of the ITER WCLL Water Cooling System and supporting thermal-hydraulic analysis

In this paper, the conceptual design of the International Thermonuclear Experimental Reactor (ITER) Water-Cooled Lithium-Lead (WCLL) Test Blanket Module (TBM) Water Cooling System (WCS) from Europe is presented. The system consists of two loops in series. This design feature allows the removal of heat from the TBM box avoiding at the same time the release of radionuclides into the ITER Component Cooling Water System (CCWS), that acts as WCLL Test Blanket System heat sink. For this purpose, the WCS primary loop deals with the direct heat removal from the ITER TBM and the secondary one implements physical separation between the contaminated primary loop coolant and the CCWS. The insertion of an economizer into the primary loop determines the characteristic “eight” shape of the circuit. This choice was done in order to reduce the temperature difference on the intermediate heat exchanger. Hairpin type and steam bubble are the technologies selected for heat exchangers and pressurizers, respectively. Pressure and temperature control systems are foreseen to limit excursions from rated values in normal operational states and abnormal transients.A computational activity was promoted to assess the WCLL-WCS conceptual design, using a modified version of the RELAP5 Mod3.3 system code. A detailed thermal-hydraulic model was developed on the basis of design outcomes. The nodalization scheme includes the TBM, the WCS, a portion of the CCWS and the lithium-lead circuit. The computational campaign involved both the normal operational state and selected abnormal transients. In all the scenarios simulated, the conceptual design has highlighted the capability of operating the system respecting all the thermal-hydraulic requirements. The abnormal transient selected and presented is the loss of flow in the CCWS (loss of heat sink). In these conditions, TBM cooling function has been verified, keeping standard control strategies without any external action.

Wolbachia modulates prevalence and viral load of Culex pipiens densoviruses in natural populations.

The inadequacy of standard mosquito control strategies calls for ecologically safe novel approaches, for example the use of biological agents such as the endosymbiotic α-proteobacteria Wolbachia or insect-specific viruses (ISVs). Understanding the ecological interactions between these "biocontrol endosymbionts" is thus a fundamental step. Wolbachia are transmitted vertically from mother to offspring and modify their hosts' phenotypes, including reproduction (e.g., cytoplasmic incompatibility) and survival (e.g., viral interference). In nature, Culex pipiens (sensu lato) mosquitoes are always found infected with genetically diverse Wolbachia called wPip that belong to five phylogenetic groups. In recent years, ISVs have also been discovered in these mosquito species, although their interactions with Wolbachia in nature are unknown. Here, we studied the interactions between a widely prevalent ISV, the Culex pipiens densovirus (CpDV, Densovirinae), and Wolbachia in northern Tunisian C. pipiens populations. We showed an influence of different Wolbachia groups on CpDV prevalence and a general positive correlation between Wolbachia and CpDV loads. By investigating the putative relationship between CpDV diversification and wPip groups in the different sites, we detected a signal linked to wPip groups in CpDV phylogeny in sites where all larvae were infected by the same wPip group. However, no such signal was detected where the wPip groups coexisted, suggesting CpDV horizontal transfer between hosts. Overall, our results provide good evidence for an ecological influence of Wolbachia on an ISV, CpDV, in natural populations and highlight the importance of integrating Wolbachia in our understanding of ISV ecology in nature.

Exposure Risks and Preventive Strategies Considered in Dental Care Settings to Combat Coronavirus Disease (COVID-19).

In recent times, numerous scientific articles have been published on the risks of exposure to infectious microorganisms in dental care settings. The main mode of transmission of such infectious organisms is primarily through bioaerosols generated during routine dental procedures which put both dental care providers and their patients at an increased risk of exposure. Other frequent modes of infection transmission often reported include cross contamination and inadequate adoption of infection control protocols. The main objective of this article is to highlight the findings of those studies that have reported on the routes and modes of transmission of infectious organisms in dental settings, to report possibilities of cross contamination in dental care settings, and also to report any breach in adherence to infection control protocols in dental care settings. We also intend to emphasize on standard infection control protocols and strategies that need to be considered in dental care settings during disease outbreaks like coronavirus disease (COVID-19).

Gastrointestinal endoscopy infection control strategy during COVID-19 pandemic: Experience from a tertiary medical center in China.

ObjectivesCoronavirus disease 2019 (COVID‐19) has spread globally and become a pandemic. The severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) not only infects the gastrointestinal (GI) tract and causes GI symptoms, but also increases nosocomial transmission risk during endoscopic procedures for aerosol generation. We hereby share our infection control strategies aiming to minimize COVID‐19 transmission in the endoscopy center.MethodsWe established our infection control strategies based on the guidance of Chinese Society of Digestive Endoscopy and inputs from hospital infection control experts: admission control through the procedure and patient triage, environmental control to reduce possible virus exposure, proper usage of personal protective equipment (PPE), and scope disinfection and room decontamination. All endoscopic procedures accomplished during COVID‐19 outbreak and progress of stepwise resumption of elective endoscopy procedures were retrospectively reviewed.ResultsOnly urgent or semi‐urgent procedures were performed during COVID‐19 outbreak. After no local new‐onset COVID‐19 case in Beijing for four weeks, we reopened the endoscopy center for elective procedures and monitored the outbreak continuously while maintaining a sustainable endoscopy service.ConclusionsIt is imperative that all endoscopy centers should establish standard infection control strategies in order to fight COVID‐19 pandemic based on national guidance and academic society guidelines and tailor them to individual resources. These measures and setup can also be reserved for future pandemics.

Temporal and Microspatial Heterogeneity in Transmission Dynamics of Coendemic Plasmodium vivax and Plasmodium falciparum in Two Rural Cohort Populations in the Peruvian Amazon.

Malaria is highly heterogeneous: its changing malaria microepidemiology needs to be addressed to support malaria elimination efforts at the regional level. A 3-year, population-based cohort study in 2 settings in the Peruvian Amazon (Lupuna, Cahuide) followed participants by passive and active case detection from January 2013 to December 2015. Incidence and prevalence rates were estimated using microscopy and polymerase chain reaction (PCR). Lupuna registered 1828 infections (1708 Plasmodium vivax, 120 Plasmodium falciparum; incidence was 80.7 infections/100 person-years (95% confidence interval [CI] , 77.1-84.5). Cahuide detected 1046 infections (1024 P vivax, 20 P falciparum, 2 mixed); incidence was 40.2 infections/100 person-years (95% CI, 37.9-42.7). Recurrent P vivax infections predominated onwards from 2013. According to PCR data, submicroscopic predominated over microscopic infections, especially in periods of low transmission. The integration of parasitological, entomological, and environmental observations evidenced an intense and seasonal transmission resilient to standard control measures in Lupuna and a persistent residual transmission after severe outbreaks were intensively handled in Cahuide. In 2 exemplars of complex local malaria transmission, standard control strategies failed to eliminate submicroscopic and hypnozoite reservoirs, enabling persistent transmission.

Dynamic optimization of the operation of a solar thermal plant

France is behind its objectives regarding the development of solar thermal energy. The company NEWHEAT has the objective to help reducing this gap by designing, financing, building and operating solar thermal plants which provide solar heat to large consumers: industrial processes and district heating networks. The present work focuses on the optimization of the operation of a solar thermal plant working at low temperatures (<100°C) from a techno-economic point of view. The plant’s architecture is defined and the models (solar field, thermal energy storage, plate heat exchanger) are validated with experimental data from the largest solar thermal plant in France (Condat-sur-Vézèe). An optimization problem is formulated: the objective is to maximize, on a short time horizon, the profits from the heat sale to the consumer by taking into account the operating costs. An equation-oriented solution strategy is used to solve the NonLinear Programming (NLP) problem. Very often, operating costs are not taken into account but the results of this work show that they have an impact on the operation of the plant which differs from standard control strategies. A major part of this work was done using a tilted solar field but in a second part, as it was the case for the solar plant in Condat-sur-Vézèe, the use of a solar tracking device was demonstrated and found to be an interesting alternative for the future of this field.

Temperature Control for Induction Heating of Thin Strips

In this work, a model-based temperature controller for an induction heating system for moving thin metal strips is developed. The most significant disturbance of the system is an uncertain air gap geometry caused by flatness defects of the metal strip. A computationally expensive calculation of the electromagnetic field is avoided by using an equivalent circuit model and the energy balance. A thermal model of the moving strip is derived in the form of a convection-reaction equation and simplified to a linear time-invariant model. A 2-degrees-of-freedom controller is designed based on the simplified model and tested using a finite-element simulation model of the induction heating system. The simulations demonstrate that the proposed controller clearly outperforms standard feedback control strategies.

Integrated Power Flow Analysis with Large-scale Solar Photovoltaic Power Systems Employing N-R Method

Abstract A method is proposed to modify the conventional load flow programme to accommodate large-scale Solar PhotoVoltaics (SPV) power plant with series power specifications. The programme facilitates easy handling of any number of SPV systems with standard control strategies such as pf-control and voltage-control, considering solar inverter’s power constraints. In this method, the non-linear equations related to SPV systems, located at multiple locations, are solved with the main load flow equations in an integrated fashion, considerably reducing the implementation task. This task is achieved by augmenting the inverter buses to the existing power system network in such a way that the changes required in the conventional programme are minimal. To show the effectiveness of the proposed method, it is compared with the alternate-iteration method popularly followed in the literature. The workability of the proposed method has been demonstrated by using a Single Machine Infinite Bus (SMIB) system and the IEEE14-bus power system with SPV systems. Various test cases pertaining to meteorological variables and control strategies are also presented.

Cost-effectiveness analysis of intensive hypertension control in China

China has the largest population of adults with hypertension in the world. Recent clinical trials have shown that intensive hypertension control can help patients achieve lower blood pressure and reduce the incidence of major cardiovascular disease (CVD) events, but this level of hypertension control also incurs additional costs to patients and society and may result in a substantial increase in adverse events. The objective of this study is to assess the cost-effectiveness of intensive hypertension control to inform health policymakers and health care delivery systems in China in their decision-making regarding hypertension treatment strategies. We developed a Markov based simulation model of hypertension to assess the impact of intensive and standard hypertension control strategies for the Chinese population who are diagnosed with hypertension. Model parameters were estimated based on the best available data and the literature. We projected that intensive hypertension control would avert about 2.2 million coronary heart disease events and 4.4 million stroke events for all hypertensive patients in China in 10 years compared to standard hypertension control. The incremental cost-effectiveness ratio (ICER) for intensive hypertension control was estimated at 7876 CNY per quality-adjusted life year (QALY) compared to standard hypertension control. Intensive hypertension control would be more cost-effective than standard hypertension control in China. Our findings indicated that China should consider expanding intensive hypertension control among hypertensive patients given its great potential in preventing CVD.

An immune memory inspired case-based reasoning system to control interrupted flow at a signalized intersection

To monitor and control traffic at signalized intersections, several traffic signal control systems (TSCSs) were developed based on optimization and artificial intelligence techniques. Unfortunately, existing approaches put little emphasis on providing concepts and mechanisms that are generic enough to deal with a variety of disturbances while maintaining traffic fluidity. Moreover, only a few works have investigated case-based reasoning (CBR) to control traffic at signalized intersections. Existing works usually state that the case-base is created using experts’ knowledge but do not specify how this knowledge is acquired and how the case-base is built. The contribution of this study is threefold. First, a new TSCS is designed to monitor and control traffic at a signalized intersection using innovative concepts and mechanisms borrowed from the biological immune memory and secondary immune response. Immune memory provides the concepts to represent cases to deal with disturbances in a more generic way, and immune secondary response mechanisms guide the design of a CBR system to monitor traffic and control disturbances. Second, a new learning algorithm for the creation of the case-base combining simulation-optimisation, condensed nearest neighbour algorithm and a rule-based system are developed. Third, the performance of the suggested TSCS is assessed by benchmarking it against two standard control strategies from the literature, namely fixed-time traffic signal control and the longest queue first-maximal weight matching algorithm. The suggested TSCS is implemented in Python and applied on an intersection simulated using VISSIM, a state-of-the-art traffic simulation software. The results show that the suggested TSCS is able to handle different traffic scenarios with competitive performance, and that it is recommended for extreme situations involving blocked approaches and high traffic flow.

An artificial immune network to control interrupted flow at a signalized intersection

To monitor and control interrupted flow at signalized intersections, several Traffic Signal Control Systems (TSCSs) were developed based on optimization and artificial intelligence techniques. Although learning can provide intelligent ways to deal with disturbances, existing approaches still lack concepts and mechanisms that enable direct representation of knowledge and explicit learning, particularly to capture and reuse previous experiences with disturbances. This article addresses this gap by designing a new TSCS based on innovative concepts and mechanisms borrowed from biological immunity. Immune memory enables the design of a Case-Based Reasoning (CBR) System in which cases provide a direct representation of knowledge about disturbances. Immune network theory enables the design of a Reinforcement Learning (RL) mechanism to interconnect cases, capture explicit knowledge about the outcomes (success and failure) of control decisions and enable decision-making by taking advantage of previous outcomes in reaction to new occurrences of disturbances. We provide a detailed description of new learning algorithms, both to create the case-base and to interconnect cases using RL. The performance of the suggested TSCS is assessed by benchmarking it against two standard control strategies from the literature, namely fixed-time and adaptive control using the Longest Queue First – Maximal Weight Matching (LQF-MWM) algorithm. The suggested TSCS is applied on an intersection simulated using VISSIM, a state-of-the-art traffic simulation software. The results show that the suggested TSCS is able to handle different traffic scenarios with competitive performance, and that it is recommended for extreme situations involving blocked approaches and high traffic flow.

Assessment of the effect of larval source management and house improvement on malaria transmission when added to standard malaria control strategies in southern Malawi: study protocol for a cluster-randomised controlled trial

BackgroundDue to outdoor and residual transmission and insecticide resistance, long-lasting insecticidal nets (LLINs) and indoor residual spraying (IRS) will be insufficient as stand-alone malaria vector control interventions in many settings as programmes shift toward malaria elimination. Combining additional vector control interventions as part of an integrated strategy would potentially overcome these challenges. Larval source management (LSM) and structural house improvements (HI) are appealing as additional components of an integrated vector management plan because of their long histories of use, evidence on effectiveness in appropriate settings, and unique modes of action compared to LLINs and IRS. Implementation of LSM and HI through a community-based approach could provide a path for rolling-out these interventions sustainably and on a large scale.Methods/designWe will implement community-based LSM and HI, as additional interventions to the current national malaria control strategies, using a randomised block, 2 × 2 factorial, cluster-randomised design in rural, southern Malawi. These interventions will be continued for two years. The trial catchment area covers about 25,000 people living in 65 villages. Community participation is encouraged by training community volunteers as health animators, and supporting the organisation of village-level committees in collaboration with The Hunger Project, a non-governmental organisation. Household-level cross-sectional surveys, including parasitological and entomological sampling, will be conducted on a rolling, 2-monthly schedule to measure outcomes over two years (2016 to 2018). Coverage of LSM and HI will also be assessed throughout the trial area.DiscussionCombining LSM and/or HI together with the interventions currently implemented by the Malawi National Malaria Control Programme is anticipated to reduce malaria transmission below the level reached by current interventions alone. Implementation of LSM and HI through a community-based approach provides an opportunity for optimum adaptation to the local ecological and social setting, and enhances the potential for sustainability.Trial RegistrationRegistered with The Pan African Clinical Trials Registry on 3 March 2016, trial number PACTR201604001501493.

Effect of the treatment of Type 2 diabetes mellitus on the development of cognitive impairment and dementia.

Prevention of cognitive impairment and dementia is an important public health goal. Epidemiological evidence shows a relationship between cognitive impairment and Type 2 diabetes mellitus. The risk of dementia increases with duration of disease. This updated systematic review investigated the effect on cognitive function of the type of treatment and level of metabolic control in people with Type 2 diabetes. To assess the effects of different strategies for managing Type 2 diabetes mellitus on cognitive function and the incidence of dementia. We searched ALOIS (the Specialized Register of the Cochrane Dementia and Cognitive Improvement Group (CDCIG)), the Cochrane Library, MEDLINE, Embase, PsycINFO, CINAHL and LILACS on 15 October 2016. ALOIS contains records from all major health care databases, (CENTRAL, MEDLINE, Embase, PsycINFO, CINAHL, LILACS), as well as from many trials' registers and grey literature sources. We included randomised controlled trials (RCTs) which compared two or more different treatments for Type 2 diabetes mellitus and in which cognitive function was measured at baseline and after treatment. Two review authors independently extracted data and assessed the quality of the included RCTs. We pooled data for comparable trials and estimated the effects of treatment by using risk ratios (RRs) and mean differences (MDs), according to the nature of the outcome. We assessed the quality of the evidence using GRADE methods. We identified seven eligible studies but only four provided data we could include in efficacy analyses. Two of these studies compared intensive versus standard glycaemic control and two compared different pharmacological treatments. All studies were at unclear risk of bias in at least two domains and one large study was at high risk of performance and detection bias.(a) Two studies with 13,934 participants at high cardiovascular risk provided efficacy data on intensive versus standard glycaemic control. A third study with 1791 participants provided additional data on hypoglycaemic episodes and mortality. There is probably no difference between treatment groups in the number of participants who decline by at least 3 points on the Mini-Mental State Examination (MMSE) over five years (RR 0.98, 95% CI 0.88 to 1.08; 1 study; n = 11,140; moderate-quality evidence); and there may also be little or no difference in the incidence of dementia (RR 1.27, 95% CI 0.87 to 1.85; 1 study; n = 11,140; low-quality evidence). From another study, there was probably little or no difference in MMSE score after 40 months (MD -0.01, 95% CI -0.18 to 0.16; 1 study; n = 2794; moderate quality evidence). Participants exposed to the intensive glycaemic control strategy probably experience more episodes of severe hypoglycaemia than those who have standard treatment (RR 2.18, 95% CI 1.52 to 3.14; 2 studies; n = 12,827; moderate-quality evidence). The evidence from these trials suggests that the intensity of glycaemic control may have little or no effect on all-cause mortality (RR 0.99, 95% CI 0.87 to 1.13; 3 studies; n = 15,888; low-quality evidence).(b) One study with 156 participants compared glibenclamide (glyburide) with repaglinide. There may be a small advantage of glibenclamide on global cognitive function measured with the MMSE after 12 months (MD -0.90, 95% CI -1.68 to -0.12; low-quality evidence). No data were reported on the incidence of dementia, hypoglycaemic events or all-cause mortality.(c) One study with 145 participants compared rosiglitazone plus metformin to glibenclamide (glyburide) plus metformin over 24 weeks. It reported only on cognitive subdomains and not on global cognitive function, incidence of MCI or dementia, hypoglycaemic events or all causes of mortality. We found no good evidence that any specific treatment or treatment strategy for Type 2 diabetes can prevent or delay cognitive impairment. The best available evidence related to the comparison of intensive with standard glycaemic control strategies. Here there was moderate-quality evidence that the strategies do not differ in their effect on global cognitive functioning over 40 to 60 months.