Comparative effectiveness of second line oral antidiabetic treatments among people with type 2 diabetes mellitus: emulation of a target trial using routinely collected health data.

OBJECTIVE: To compare the effectiveness of three commonly prescribed oral antidiabetic drugs added to metformin for people with type 2 diabetes mellitus requiring second line treatment in routine clinical practice. DESIGN: Cohort study emulating a comparative effectiveness trial (target trial). SETTING: Linked primary care, hospital, and death data in England, 2015-21. PARTICIPANTS: 75 739 adults with type 2 diabetes mellitus who initiated second line oral antidiabetic treatment with a sulfonylurea, DPP-4 inhibitor, or SGLT-2 inhibitor added to metformin. MAIN OUTCOME MEASURES: Primary outcome was absolute change in glycated haemoglobin A1c (HbA1c) between baseline and one year follow-up. Secondary outcomes were change in body mass index (BMI), systolic blood pressure, and estimated glomerular filtration rate (eGFR) at one year and two years, change in HbA1c at two years, and time to ≥40% decline in eGFR, major adverse kidney event, hospital admission for heart failure, major adverse cardiovascular event (MACE), and all cause mortality. Instrumental variable analysis was used to reduce the risk of confounding due to unobserved baseline measures. RESULTS: 75 739 people initiated second line oral antidiabetic treatment with sulfonylureas (n=25 693, 33.9%), DPP-4 inhibitors (n=34 464 ,45.5%), or SGLT-2 inhibitors (n=15 582, 20.6%). SGLT-2 inhibitors were more effective than DPP-4 inhibitors or sulfonylureas in reducing mean HbA1c values between baseline and one year. After the instrumental variable analysis, the mean differences in HbA1c change between baseline and one year were -2.5 mmol/mol (95% confidence interval (CI) -3.7 to -1.3) for SGLT-2 inhibitors versus sulfonylureas and -3.2 mmol/mol (-4.6 to -1.8) for SGLT-2 inhibitors versus DPP-4 inhibitors. SGLT-2 inhibitors were more effective than sulfonylureas or DPP-4 inhibitors in reducing BMI and systolic blood pressure. For some secondary endpoints, evidence for SGLT-2 inhibitors being more effective was lacking-the hazard ratio for MACE, for example, was 0.99 (95% CI 0.61 to 1.62) versus sulfonylureas and 0.91 (0.51 to 1.63) versus DPP-4 inhibitors. SGLT-2 inhibitors had reduced hazards of hospital admission for heart failure compared with DPP-4 inhibitors (0.32, 0.12 to 0.90) and sulfonylureas (0.46, 0.20 to 1.05). The hazard ratio for a ≥40% decline in eGFR indicated a protective effect versus sulfonylureas (0.42, 0.22 to 0.82), with high uncertainty in the estimated hazard ratio versus DPP-4 inhibitors (0.64, 0.29 to 1.43). CONCLUSIONS: This emulation study of a target trial found that SGLT-2 inhibitors were more effective than sulfonylureas or DPP-4 inhibitors in lowering mean HbA1c, BMI, and systolic blood pressure and in reducing the hazards of hospital admission for heart failure (v DPP-4 inhibitors) and kidney disease progression (v sulfonylureas), with no evidence of differences in other clinical endpoints.

The impact of collaborative organisational models and general practice size on patient safety and quality of care in the English National Health Service: A systematic review.

Collaborative primary care has become an increasingly popular strategy to manage existing pressures on general practice. In England, the recent changes taking place in the primary care sector have included the formation of collaborative organisational models and a steady increase in practice size. The aim of this review was to summarise the available evidence on the impact of collaborative models and general practice size on patient safety and quality of care in England. We searched for quantitative and qualitative studies on the topic published between January 2010 and July 2023. The quality of articles was assessed using the Newcastle-Ottawa Scale and the Critical Appraisal Skills Programme checklist. We screened 6533 abstracts, with full-text screening performed on 76 records. A total of 29 articles were included in the review. 19 met the inclusion criteria following full-text screening, with seven identified through reverse citation searching and three through expert consultation. All studies were found to be of moderate or high quality. A predominantly positive impact on service delivery measures and patient-level outcomes was identified. Meanwhile, the evidence on the effect on pay-for-performance outcomes and hospital admissions is mixed, with continuity of care and access identified as a concern. While this review is limited to evidence from England, the findings provide insights for all health systems undergoing a transition towards collaborative primary care.

Back to basics: A mediation analysis approach to addressing the fundamental questions of integrated care evaluations.

Health systems around the world are aiming to improve the integration of health and social care services to deliver better care for patients. Existing evaluations have focused exclusively on the impact of care integration on health outcomes and found little effect. That suggests the need to take a step back and ask whether integrated care programmes actually lead to greater clinical integration of care and indeed whether greater integration is associated with improved health outcomes. We propose a mediation analysis approach to address these two fundamental questions when evaluating integrated care programmes. We illustrate our approach by re-examining the impact of an English integrated care program on clinical integration and assessing whether greater integration is causally associated with fewer admissions for ambulatory care sensitive conditions. We measure clinical integration using a concentration index of outpatient referrals at the general practice level. While we find that the scheme increased integration of primary and secondary care, clinical integration did not mediate a decrease in unplanned hospital admissions. Our analysis emphasizes the need to better understand the hypothesized causal impact of integration on health outcomes and demonstrates how mediation analysis can inform future evaluations and program design.

A firebreak placement model for optimizing biodiversity protection at landscape scale.

A solution approach is proposed to optimize the selection of landscape cells for inclusion in firebreaks. It involves linking spatially explicit information on a landscape's ecological values, historical ignition patterns and fire spread behavior. A firebreak placement optimization model is formulated that captures the tradeoff between the direct loss of biodiversity due to the elimination of vegetation in areas designated for placement of firebreaks and the protection provided by the firebreaks from losses due to future forest fires. The optimal solution generated by the model reduced expected losses from wildfires on a biodiversity combined index due to wildfires by 30% relative to a landscape without any treatment. It also reduced expected losses by 16% compared to a randomly chosen solution. These results suggest that biodiversity loss resulting from the removal of vegetation in areas where firebreaks are placed can be offset by the reduction in biodiversity loss due to the firebreaks' protective function.

Ethnic and socioeconomic disparities in initiation of second-line antidiabetic treatment for people with type 2 diabetes in England: A cross-sectional study.

AIMS: To assess any disparities in the initiation of second-line antidiabetic treatments prescribed among people with type 2 diabetes mellitus (T2DM) in England according to ethnicity and social deprivation level. MATERIALS AND METHODS: This cross-sectional study used linked primary (Clinical Practice Research Datalink) and secondary care data (Hospital Episode Statistics), and the Index of Multiple Deprivation (IMD). We included people aged 18 years or older with T2DM who intensified to second-line oral antidiabetic medication between 2014 and 2020 to investigate disparities in second-line antidiabetic treatment prescribing (one of sulphonylureas [SUs], dipeptidyl peptidase-4 [DPP-4] inhibitors, or sodium-glucose cotransporter-2 [SGLT2] inhibitors, in combination with metformin) by ethnicity (White, South Asian, Black, mixed/other) and deprivation level (IMD quintiles). We report prescriptions of the alternative treatments by ethnicity and deprivation level according to predicted percentages derived from multivariable, multinomial logistic regression. RESULTS: Among 36 023 people, 85% were White, 10% South Asian, 4% Black and 1% mixed/other. After adjustment, the predicted percentages for SGLT2 inhibitor prescribing by ethnicity were 21% (95% confidence interval [CI] 19-23%), 20% (95% CI 18-22%), 19% (95% CI 16-22%) and 17% (95% CI 14-21%) among people with White, South Asian, Black, and mixed/other ethnicity, respectively. After adjustment, the predicted percentages for SGLT2 inhibitor prescribing by deprivation were 22% (95% CI 20-25%) and 19% (95% CI 17-21%) for the least deprived and the most deprived quintile, respectively. When stratifying by prevalent cardiovascular disease (CVD) status, we found lower predicted percentages of people with prevalent CVD prescribed SGLT2 inhibitors compared with people without prevalent CVD across all ethnicity groups and all levels of social deprivation. CONCLUSIONS: Among people with T2DM, there were no substantial differences by ethnicity or deprivation level in the percentage prescribed either SGLT2 inhibitors, DPP-4 inhibitors or SUs as second-line antidiabetic treatment.

Optimization of Dominant Frequency and Bandwidth Analysis in Multi-Frequency 3D GPR Signals to Identify Contaminated Areas.

Ground-penetrating radar (GPR) has been widely used in investigations of contaminated areas because of its sensitivity to variations associated with the nature of pore fluids. However, most of the studies were usually based on the visual interpretation of radargrams or on a time domain amplitude analysis. In this work, we propose a methodology that consists of analyzing the spectral content of the signal recorded in multi-frequency 3D GPR profiles. A remarkable advantage of this type of antenna is its step-frequency system, which provides a much wider emission spectrum than the one corresponding to conventional single-frequency antennas. From the data in the frequency domain, the dominant frequency and bandwidth were calculated as parameters whose variation could be related to the presence of light non-aqueous phase liquid (LNAPL) in the subsurface. By analyzing the variations of these two parameters simultaneously, we were able to delimit the contaminated zones in a case study, associating them with a significant shift of the frequency spectrum with respect to the average of the study area. Finally, as a validation method of the proposed methodology, the results of the frequency analysis were compared with resistivity data obtained with an electromagnetic conductivity meter, showing a very good correlation between the results.

Visual Performance, Satisfaction, and Spectacle Independence after Implantation of a New Hydrophobic Trifocal Intraocular Lens.

The main objective was to evaluate distance, intermediate, and near vision in patients who have undergone cataract extraction with bilateral implantation of a new trifocal diffractive intraocular lens (IOL), along with patient-reported outcomes (PRO). A total of 50 eyes from 25 patients after AsqelioTM Trifocal IOL (AST Products, Inc., Billerica MA, USA) implantation were assessed in this study. At 3 months after surgery, the photopic visual acuity (VA) at distance, intermediate, and near distances was measured. Binocular photopic defocus curves were also obtained. Three questionnaires to assess patients' visual satisfaction and spectacle dependence, among other items, were completed: the Catquest-9SF, the patient-reported spectacle independence questionnaire (PRSIQ), and the patient-reported visual symptoms questionnaire (PRVSQ). The average spherical equivalent was 0.21 ± 0.37 D at 3 months post-operation, and the average absolute tolerance to defocus was 3.64 ± 0.70 D. The mean binocular uncorrected VAs for distance, intermediate, and near vision were -0.02 ± 0.09, 0.06 ± 0.08, and 0.11 ± 0.07 logMAR, respectively. The best-corrected VA was better than 0.1 logMAR for the whole range from distance to near. PROs revealed spectacle independence and general satisfaction with vision, and the incidence of photic phenomena were low. This study shows that the new bi-aspheric diffractive trifocal IOL provides a good visual performance at different distances under photopic conditions, accompanied by patient satisfaction and spectacle independence.

Microencapsulation of a Commercial Food-Grade Protease by Spray Drying in Cross-Linked Chitosan Particles.

In this study, the use of spray-drying technology for encapsulating Flavourzyme® (protease-peptidase complex) was evaluated to overcome the limitations (low encapsulation efficiency and no large-scale production) of other encapsulation processes. To the best of our knowledge, spray drying has not been applied previously for the immobilization of this enzyme. Firstly, bovine serum albumin (BSA), as a model protein, was encapsulated by spray drying in chitosan and tripolyphoshate (TPP) cross-linked-chitosan shell matrices. The results showed that the chitosan-TPP microcapsules provided a high encapsulation efficiency and better protein stability compared to the non-crosslinked chitosan microcapsules. The effect of enzyme concentration and drying temperature were tested during the spray drying of Flavourzyme®. In this regard, an activity yield of 88.0% and encapsulation efficiency of 78.6% were obtained with a concentration of 0.1% (v/v) and an inlet temperature of 130 °C. Flavourzyme®-loaded chitosan microcapsules were also characterized in terms of their size and morphology using scanning electron microscopy and laser diffractometry.

Kinetic Modeling, Thermodynamic Approach and Molecular Dynamics Simulation of Thermal Inactivation of Lipases from Burkholderia cepacia and Rhizomucor miehei.

The behavior against temperature and thermal stability of enzymes is a topic of importance for industrial biocatalysis. This study focuses on the kinetics and thermodynamics of the thermal inactivation of Lipase PS from B. cepacia and Palatase from R. miehei. Thermal inactivation was investigated using eight inactivation models at a temperature range of 40-70 °C. Kinetic modeling showed that the first-order model and Weibull distribution were the best equations to describe the residual activity of Lipase PS and Palatase, respectively. The results obtained from the kinetic parameters, decimal reduction time (D and tR), and temperature required (z and z') indicated a higher thermal stability of Lipase PS compared to Palatase. The activation energy values (Ea) also indicated that higher energy was required to denature bacterial (34.8 kJ mol-1) than fungal (23.3 kJ mol-1) lipase. The thermodynamic inactivation parameters, Gibbs free energy (ΔG#), entropy (ΔS#), and enthalpy (ΔH#) were also determined. The results showed a ΔG# for Palatase (86.0-92.1 kJ mol-1) lower than for Lipase PS (98.6-104.9 kJ mol-1), and a negative entropic and positive enthalpic contribution for both lipases. A comparative molecular dynamics simulation and structural analysis at 40 °C and 70 °C were also performed.

Local Instrumental Variable Methods to Address Confounding and Heterogeneity when Using Electronic Health Records: An Application to Emergency Surgery.

BACKGROUND: Electronic health records (EHRs) offer opportunities for comparative effectiveness research to inform decision making. However, to provide useful evidence, these studies must address confounding and treatment effect heterogeneity according to unmeasured prognostic factors. Local instrumental variable (LIV) methods can help studies address these challenges, but have yet to be applied to EHR data. This article critically examines a LIV approach to evaluate the cost-effectiveness of emergency surgery (ES) for common acute conditions from EHRs. METHODS: This article uses hospital episodes statistics (HES) data for emergency hospital admissions with acute appendicitis, diverticular disease, and abdominal wall hernia to 175 acute hospitals in England from 2010 to 2019. For each emergency admission, the instrumental variable for ES receipt was each hospital's ES rate in the year preceding the emergency admission. The LIV approach provided individual-level estimates of the incremental quality-adjusted life-years, costs and net monetary benefit of ES, which were aggregated to the overall population and subpopulations of interest, and contrasted with those from traditional IV and risk-adjustment approaches. RESULTS: The study included 268,144 (appendicitis), 138,869 (diverticular disease), and 106,432 (hernia) patients. The instrument was found to be strong and to minimize covariate imbalance. For diverticular disease, the results differed by method; although the traditional approaches reported that, overall, ES was not cost-effective, the LIV approach reported that ES was cost-effective but with wide statistical uncertainty. For all 3 conditions, the LIV approach found heterogeneity in the cost-effectiveness estimates across population subgroups: in particular, ES was not cost-effective for patients with severe levels of frailty. CONCLUSIONS: EHRs can be combined with LIV methods to provide evidence on the cost-effectiveness of routinely provided interventions, while fully recognizing heterogeneity. HIGHLIGHTS: This article addresses the confounding and heterogeneity that arise when assessing the comparative effectiveness from electronic health records (EHR) data, by applying a local instrumental variable (LIV) approach to evaluate the cost-effectiveness of emergency surgery (ES) versus alternative strategies, for patients with common acute conditions (appendicitis, diverticular disease, and abdominal wall hernia).The instrumental variable, the hospital's tendency to operate, was found to be strongly associated with ES receipt and to minimize imbalances in baseline characteristics between the comparison groups.The LIV approach found that, for each condition, there was heterogeneity in the estimates of cost-effectiveness according to baseline characteristics.The study illustrates how an LIV approach can be applied to EHR data to provide cost-effectiveness estimates that recognize heterogeneity and can be used to inform decision making as well as to generate hypotheses for further research.

Investigating the association between inpatient stroke therapy and disability, destination on discharge, length of stay and mortality: a prospective cohort study using the Sentinel Stroke National Audit Programme.

OBJECTIVE: 'More is better' is a recognised mantra within stroke therapy, however, this has been developed in patients receiving long term rehabilitation. We investigated the relationship between amount of therapy received (from therapists and psychologists) and key patient outcomes during inpatient care. DESIGN: A secondary analysis of data from a prospective cohort study was performed. Multilevel mixed models adjusting for measured confounders (eg, severity), explored the relationship between therapy dose (average minutes per day of stay) and outcomes (disability, length of stay, home at discharge and mortality). Therapy was explored using simple linear terms and flexible natural cubic splines to allow for more complex relationships. SETTING: Data from the Sentinel Stroke National Audit Programme, covering England, Wales and Northern Ireland between July 2013 and July 2015 contained 94 905 adults with a stroke and still an inpatient after 72 hours. These patients received 92% (physiotherapy), 88% (occupational therapy), 57% (speech and language therapy) and 5% (clinical psychology), respectively. RESULTS: The average amount of therapy, for individual and 'any' therapy combined per day of stay was low. Overall, 41% were discharged with an 'independent' modified Rankin Scale (≤2), 14% died, 44% were discharged home, and the median length of stay was 16 days. We observed complex relationships between amount of therapy received and outcomes. An additional minute of 'any' therapy, occupational therapy, speech and language therapy and clinical psychology was associated with improved outcomes. Conversely, more physiotherapy was also associated with lower mortality and shorter length of stay, but also lower independence and discharge home. CONCLUSIONS: Our findings suggest for stroke inpatients requiring therapy, 'More is better' may be overly simplistic. Strong limitations associated with analysis of routine data restrict further robust investigation of the therapy-response relationship. Robust prospective work is urgently needed to further investigate the relationships observed here.

Framework for identification and measurement of spillover effects in policy implementation: intended non-intended targeted non-targeted spillovers (INTENTS).

BACKGROUND: There is increasing awareness among researchers and policymakers of the potential for healthcare interventions to have consequences beyond those initially intended. These unintended consequences or "spillover effects" result from the complex features of healthcare organisation and delivery and can either increase or decrease overall effectiveness. Their potential influence has important consequences for the design and evaluation of implementation strategies and for decision-making. However, consideration of spillovers remains partial and unsystematic. We develop a comprehensive framework for the identification and measurement of spillover effects resulting from changes to the way in which healthcare services are organised and delivered. METHODS: We conducted a scoping review to map the existing literature on spillover effects in health and healthcare interventions and used the findings of this review to develop a comprehensive framework to identify and measure spillover effects. RESULTS: The scoping review identified a wide range of different spillover effects, either experienced by agents not intentionally targeted by an intervention or representing unintended effects for targeted agents. Our scoping review revealed that spillover effects tend to be discussed in papers only when they are found to be statistically significant or might account for unexpected findings, rather than as a pre-specified feature of evaluation studies. This hinders the ability to assess all potential implications of a given policy or intervention. We propose a taxonomy of spillover effects, classified based on the outcome and the unit experiencing the effect: within-unit, between-unit, and diagonal spillover effects. We then present the INTENTS framework: Intended Non-intended TargEted Non-Targeted Spillovers. The INTENTS framework considers the units and outcomes which may be affected by an intervention and the mechanisms by which spillover effects are generated. CONCLUSIONS: The INTENTS framework provides a structured guide for researchers and policymakers when considering the potential effects that implementation strategies may generate, and the steps to take when designing and evaluating such interventions. Application of the INTENTS framework will enable spillover effects to be addressed appropriately in future evaluations and decision-making, ensuring that the full range of costs and benefits of interventions are correctly identified.

Active Learning Methodology for Expert-Assisted Anomaly Detection in Mobile Communications.

Due to the great complexity, heterogeneity, and variety of services, anomaly detection is becoming an increasingly important challenge in the operation of new generations of mobile communications. In many cases, the underlying relationships between the multiplicity of parameters and factors that can cause anomalous behavior are only determined by human expert knowledge. On the other hand, although automatic algorithms have a great capacity to process multiple sources of information, they are not always able to correctly signal such abnormalities. In this sense, this paper proposes the integration of both components in a framework based on Active Learning that enables enhanced performance in anomaly detection tasks. A series of tests have been conducted using an online anomaly detection algorithm comparing the proposed solution with a method based on the algorithm output alone. The obtained results demonstrate that a hybrid anomaly detection model that automates part of the process and includes the knowledge of an expert following the described methodology yields increased performance.

QoE Optimization in a Live Cellular Network through RLC Parameter Tuning.

The mobile communication networks sector has experienced a great evolution during the last few years. The emergence of new services as well as the growth in the number of subscribers have motivated the search for new ways to optimize mobile networks. In this way, the objective pursued by optimization techniques has been evolving, shifting from the traditional optimization of radio parameters to the improvement of the quality perceived by users, known as quality of experience (QoE). In mobile networks, the radio link control (RLC) layer provides a reliable link between both ends of the communication and has a great impact on the QoE. In this paper, the optimization of the QoE for users based on the adjustment of the RLC layer is proposed. For this purpose, two typical services demanded by the users of mobile networks have been selected: the real-time video streaming service and file transfer service. For a broader view of the behavior of the QoE in relation to RLC, optimization tests have been carried out in scenarios with different system bandwidths. In this way, the relationship between the QoE and the optimal configuration of RLC in different network load situations has been analyzed. A proof of concept has been carried out to show the capability of this optimization. To that end, both a cellular network simulator and a live cellular network devised for research purposes have been used.

Framework for Behavioral Analysis of Mobile Networks.

The arrival of the Fifth Generation (5G) entails a significant evolution in the context of mobile communication networks. This new technology will bring heterogeneous scenarios with new types of services and an increasingly high number of users and nodes. The efficient management of such complex networks has become an important challenge. To address this problem, automatic and efficient algorithms must be developed to facilitate operators' management and optimization of their networks. These algorithms must be able to cope with a very high number of heterogeneous data and different types of scenarios. In this paper, a novel framework for a cellular network behavioral analysis and monitoring is presented. This framework is based on a combination of unsupervised and supervised machine learning techniques. The proposed system can analyze the behavior of cells and monitor them, searching for behavior changes over time. The information extracted by the framework can be used to improve subsequent management and optimization functions.

Stroke impairment categories: A new way to classify the effects of stroke based on stroke-related impairments.

OBJECTIVE: To create a classification system based on stroke-related impairments. DATA SOURCE: All adults with stroke admitted for at least 72 hours in England, Wales and Northern Ireland from July 2013 to July 2015 extracted from the Sentinel Stroke National Audit Programme. ANALYSIS: Impairments were defined using the National Institute of Health Stroke Scale scores at admission. Common combinations of impairments were identified based on geometric coding and expert knowledge. Validity of the classification was assessed using standard descriptive statistics to report and compare patients' characteristics, therapy received and outcomes in each group. RESULTS: Data from 94,905 patients were extracted. The items of the National Institute of Health Stroke Scale (on admission) were initially grouped into four body systems: Cognitive, Motor, Sensory and Consciousness. Seven common combinations of these impairments were identified (in order of stroke severity); Patients with Loss of Consciousness (n = 6034, 6.4%); those with Motor + Cognitive + Sensory impairments (n = 28,226, 29.7%); Motor + Cognitive impairments (n = 16,967, 17.9%); Motor + Sensory impairments (n = 9882, 10.4%); Motor Only impairments (n = 20,471, 21.6%); Any Non-Motor impairments (n = 7498, 7.9%); and No Impairments (n = 5827, 6.1%). There was a gradation of age, premorbid disability, mortality and disability on discharge. People with the most and least severe categories were least likely to receive therapy, and received least therapy (-20 minutes/day of stay) compared to -35 minutes/day of stay for the moderately severe categories. CONCLUSIONS: A classification system of seven Stroke Impairment Categories has been presented.

Online Anomaly Detection System for Mobile Networks.

The arrival of the fifth generation (5G) standard has further accelerated the need for operators to improve the network capacity. With this purpose, mobile network topologies with smaller cells are currently being deployed to increase the frequency reuse. In this way, the number of nodes that collect performance data is being further risen, so the number of metrics to be managed and analyzed is being highly increased. Therefore, it is fundamental to have tools that automatically inform the network operator of the relevant information within the vast amount of metrics collected. The continuous monitoring of the performance indicators and the automatic detection of anomalies is especially important for network operators to prevent the network degradation and user complaints. Therefore, this paper proposes a methodology to detect and track anomalies in the mobile networks performance indicators online, i.e., in real time. The feasibility of this system was evaluated with several performance metrics and a real LTE Advanced dataset. In addition, it was also compared with the performances of other state-of-the-art anomaly detection systems.

Feature Extraction for Dimensionality Reduction in Cellular Networks Performance Analysis.

Next-generation mobile communications networks will have to cope with an extraordinary amount and variety of network performance indicators, causing an increase in the storage needs of the network databases and the degradation of the management functions due to the high-dimensionality of every network observation. In this paper, different techniques for feature extraction are described and proposed as a means for reducing this high dimensionality, to be integrated as an intermediate stage between the monitoring of the network performance indicators and their usage in mobile networks' management functions. Results using a dataset gathered from a live cellular network show the benefits of this approach, in terms both of storage savings and subsequent management function improvements.

Factors influencing the amount of therapy received during inpatient stroke care: an analysis of data from the UK Sentinel Stroke National Audit Programme.

OBJECTIVES: To understand why most stroke patients receive little therapy. We investigated the factors associated with the amount of stroke therapy delivered. METHODS: Data regarding adults admitted to hospital with stroke for at least 72 hours (July 2013-July 2015) were extracted from the UK's Sentinel Stroke National Audit Programme. Descriptive statistics and multilevel mixed effects regression models explored the factors that influenced the amount of therapy received while adjusting for confounding. RESULTS: Of the 94,905 patients in the study cohort (mean age: 76 (SD: 13.2) years, 78% had a mild or moderate severity stroke. In all, 92% required physiotherapy, 87% required occupational therapy, 57% required speech therapy but only 5% were considered to need psychology. The average amount of therapy ranged from 2 minutes (psychology) to 14 minutes (physiotherapy) per day of inpatient stay. Unmodifiable characteristics (such as stroke severity) dominated the variation in the amount of therapy. However important, modifiable organizational factors were the day and time of admission, type of stroke team, timely therapy assessments, therapy and nursing staffing levels (qualified and support staff), and presence of weekend or early supported discharge services. CONCLUSION: The amount of stroke therapy is associated with unmodifiable patient-related characteristics and modifiable organizational factors in that more therapy was associated with higher therapy and nurse staffing levels, specialist stroke rehabilitation services, timely therapy assessments, and the presence of weekend and early discharge services.

On the Capability of QoE Improvement Based on the Adjustment of RLC Parameters.

The constant evolution in mobile communications networks have led operators to seek new techniques to optimize their mobile networks with the objective of satisfying the expectations of the users. In this way, traditional optimization techniques based on improving radio indicators, have given way to new techniques based on improving the quality of experience (QoE) perceived by users. This paper is focused on analyzing the impact of the adjustment of radio link control (RLC) layer configuration parameters on the QoE perceived by the users of two different types of services. Firstly, an evaluation of the QoE experienced by the user of a real-time video streaming service with respect to the transmission buffer size of the RLC layer in unacknowledged mode (UM) has been carried out. Secondly, the QoE perceived by the user of a file transfer service in relation to the variation of the configuration parameters of the RLC layer in acknowledged mode (AM) has been evaluated. The study, which has been carried out in a simulated cellular environment, has been performed for different system bandwidth values, thus proving the relationship between the QoE perceived by the users, the optimal RLC configuration parameters values and the available bandwidth.