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Yashdeep Gupta,1 Bharti Kalra,2 Manash P Baruah,3 Rajiv Singla,4 Sanjay Kalra2 1Department of Medicine, Government Medical College and Hospital, Chandigarh, India; 2Bharti Hospital, Karnal, Haryana, India; 3Excel Center, Guwahati, Assam, India; 4Saket City Hospital, New Delhi, India Abstract: Gestational diabetes mellitus (GDM) is associated with an increased risk of complications for both mother and baby during pregnancy as well as in the postpartum period. Screening and identifying these high-risk women is important to improve short- and long-term maternal and fetal outcomes. However, there is a lack of international uniformity in the approach to the screening and diagnosis of GDM. The main purpose of this review is to provide an update on screening for GDM and overt diabetes during pregnancy, and discuss the controversies in this field. We take on debatable issues such as adoption of the new International association of diabetes and pregnancy study groups criteria instead of the Carpenter and Coustan criteria, one-step versus two-step screening, universal screening versus high-risk screening before 24 weeks of gestation for overt diabetes, and, finally, the role of HbA1c as a screening test of GDM. This discussion is followed by a review of recommendations by professional bodies. Certain clinical situations, in which a pragmatic approach is needed, are highlighted to provide a comprehensive overview of the subject. Keywords: pregnancy, guidelines, IADPSG, GDM, Carpenter and Coustan criteria

Inattention can negatively impact several aspects of a child's life, including at home and school. Cognitive and physical interventions are two promising non-pharmaceutical approaches used to enhance attention abilities, with combined approaches often being marketed to teachers, therapists, and parents typically without research validation. Here, we assessed the feasibility of incorporating an integrated, cognitive-physical, closed-loop video game (body-brain trainer or 'BBT') as an after-school program, and also evaluated if there were attention benefits following its use. Twenty-two children (7-12 years of age) with a range of attention abilities were recruited to participate in this proof of concept, single-arm, longitudinal study (24 sessions over 8 weeks, ~30 min/day). We interrogated attention abilities through a parent survey of their child's behaviors, in addition to objective performance-based and neural measures of attention. Here we observed 95% compliance as well as, significant improvements on the parent-based reports of inattention and on cognitive tests and neural measures of attention that were comparable in scale to previous work. Exploratory measures of other cognitive control abilities and physical fitness also showed similar improvement, with exploratory evaluation of retained benefits on the primary attention-related outcomes being present 1-year later. Lastly, there was no correlation between the baseline parent-rated inattention score and the improvement on the primary task-based measures of attention, suggesting that intervention-based benefits were not solely attained by those who stood the most to gain. These pilot findings warrant future research to replicate and extend these findings.

BACKGROUND: Optimal drug dosing is important to ensure adequate response to treatment, prevent development of drug resistance and reduce drug toxicity. The aim of these clinical standards is to provide guidance on 'best practice´ for dosing and management of TB drugs.METHODS: A panel of 57 global experts in the fields of microbiology, pharmacology and TB care were identified; 51 participated in a Delphi process. A 5-point Likert scale was used to score draft standards. The final document represents the broad consensus and was approved by all participants.RESULTS: Six clinical standards were defined: Standard 1, defining the most appropriate initial dose for TB treatment; Standard 2, identifying patients who may be at risk of sub-optimal drug exposure; Standard 3, identifying patients at risk of developing drug-related toxicity and how best to manage this risk; Standard 4, identifying patients who can benefit from therapeutic drug monitoring (TDM); Standard 5, highlighting education and counselling that should be provided to people initiating TB treatment; and Standard 6, providing essential education for healthcare professionals. In addition, consensus research priorities were identified.CONCLUSION: This is the first consensus-based Clinical Standards for the dosing and management of TB drugs to guide clinicians and programme managers in planning and implementation of locally appropriate measures for optimal person-centred treatment to improve patient care.

BACKGROUND: Increasing evidence suggests that post-TB lung disease (PTLD) causes significant morbidity and mortality. The aim of these clinical standards is to provide guidance on the assessment and management of PTLD and the implementation of pulmonary rehabilitation (PR).METHODS: A panel of global experts in the field of TB care and PR was identified; 62 participated in a Delphi process. A 5-point Likert scale was used to score the initial ideas for standards and after several rounds of revision the document was approved (with 100% agreement).RESULTS: Five clinical standards were defined: Standard 1, to assess patients at the end of TB treatment for PTLD (with adaptation for children and specific settings/situations); Standard 2, to identify patients with PTLD for PR; Standard 3, tailoring the PR programme to patient needs and the local setting; Standard 4, to evaluate the effectiveness of PR; and Standard 5, to conduct education and counselling. Standard 6 addresses public health aspects of PTLD and outcomes due to PR.CONCLUSION: This is the first consensus-based set of Clinical Standards for PTLD. Our aim is to improve patient care and quality of life by guiding clinicians, programme managers and public health officers in planning and implementing adequate measures to assess and manage PTLD.

BackgroundTreatment of multidrug-resistant tuberculosis requires long-term therapy with a combination of multiple second-line drugs. These drugs are associated with numerous adverse events that can cause severe morbidity, such as deafness, and in some instances can lead to death. Our aim was to estimate the absolute and relative frequency of adverse events associated with different tuberculosis drugs to provide useful information for clinicians and tuberculosis programmes in selecting optimal treatment regimens.MethodsWe did a meta-analysis using individual-level patient data that were obtained from studies that reported adverse events that resulted in permanent discontinuation of anti-tuberculosis medications. We used a database created for our previous meta-analysis of multidrug-resistant tuberculosis treatment and outcomes, for which we did a systematic review of literature published between Jan 1, 2009, and Aug 31, 2015 (updated April 15, 2016), and requested individual patient-level information from authors. We also considered for this analysis studies contributing patient-level data in response to a public call made by WHO in 2018. Meta-analysis for proportions and arm-based network meta-analysis were done to estimate the incidence of adverse events for each tuberculosis drug.Findings58 studies were identified, including 50 studies from the updated individual patient data meta-analysis for multidrug-resistant tuberculosis treatment. 35 of these studies, with 9178 patients, were included in our analysis. Using meta-analysis of proportions, drugs with low risks of adverse event occurrence leading to permanent discontinuation included levofloxacin (1·3% [95% CI 0·3-5·0]), moxifloxacin (2·9% [1·6-5·0]), bedaquiline (1·7% [0·7-4·2]), and clofazimine (1·6% [0·5-5·3]). Relatively high incidence of adverse events leading to permanent discontinuation was seen with three second-line injectable drugs (amikacin: 10·2% [6·3-16·0]; kanamycin: 7·5% [4·6-11·9]; capreomycin: 8·2% [6·3-10·7]), aminosalicylic acid (11·6% [7·1-18·3]), and linezolid (14·1% [9·9-19·6]). Risk of bias in selection of studies was judged to be low because there were no important differences between included and excluded studies. Variability between studies was significant for most outcomes analysed.InterpretationFluoroquinolones, clofazimine, and bedaquiline had the lowest incidence of adverse events leading to permanent drug discontinuation, whereas second-line injectable drugs, aminosalicylic acid, and linezolid had the highest incidence. These results suggest that close monitoring of adverse events is important for patients being treated for multidrug-resistant tuberculosis. Our results also underscore the urgent need for safer and better-tolerated drugs to reduce morbidity from treatment itself for patients with multidrug-resistant tuberculosis.FundingCanadian Institutes of Health Research, Centers for Disease Control and Prevention (USA), American Thoracic Society, European Respiratory Society, and Infectious Diseases Society of America.

Fault detection and diagnosis (FDD) algorithms for building systems and equipment represent one of the most active areas of research and commercial product development in the buildings industry. However, far more effort has gone into developing these algorithms than into assessing their performance. As a result, considerable uncertainties remain regarding the accuracy and effectiveness of both research-grade FDD algorithms and commercial products—a state of affairs that has hindered the broad adoption of FDD tools. This article presents a general, systematic framework for evaluating the performance of FDD algorithms. The article focuses on understanding the possible answers to two key questions: in the context of FDD algorithm evaluation, what defines a fault and what defines an evaluation input sample? The answers to these questions, together with appropriate performance metrics, may be used to fully specify evaluation procedures for FDD algorithms.

Buildings account for about 40 percent of the total energy consumption in the U.S. and emit approximately one third of greenhouse gas emissions. But they also offer tremendous potential for achieving significant greenhouse gas reductions with the right savings strategies. With an increasing amount of data from buildings and advanced computational and analytical abilities, buildings can be made “smart” to optimize energy consumption and occupant comfort. Smart buildings are often characterized as having a high degree of data and system integration, connectivity and control, as well as the advanced use of data analytics. These “smarts” can enable up to 10–20% savings in a building, and help ensure that they persist over time. In 2009, Microsoft Corporation launched the Energy-Smart Buildings (ESB) program with a vision to improve building operations services, security and accessibility in services, and new tenant applications and services that improve productivity and optimize energy use. The ESB program focused on fault diagnostics, advanced analytics and new organizational processes and practices to support their operational integration. In addition to the ESB program, Microsoft undertook capital improvement projects that made effective use of a utility incentive program and lab consolidations over the same duration. The ESB program began with a pilot at Microsoft's Puget Sound campus that identified significant savings of up to 6–10% in the 13 pilot buildings. The success of the pilot led to a global deployment of the program. Between 2009 and 2015, there was a 23.7% reduction in annual electricity consumption (kWh) at the Puget Sound campus with 18.5% of that resulting from the ESB and lab consolidations. This article provides the results of research conducted to assess the best-practice strategies that Microsoft implemented to achieve these savings, including the fault diagnostic routines that are the foundation of the ESB program and organizational change management practices. It also presents the process that was adopted to scale the ESB program globally. We conclude with recommendations for how these successes can be generalized and replicated by other corporate enterprises.

The evaluation of feedback collected from students at the end of the year is very essential for every educational institution. It is important to improve the teaching–learning process and the annual appraisal process. The existing approach utilizes a Likert scale questionnaire, which allows students to express their level of agreement or disagreement with given statements or provide a neutral response. Additionally, the feedback form includes open-ended questions where students can provide textual feedback. This study introduces a Lexicon-based approach to automatically analyze the textual feedback concerning different aspects of teaching. Aspect-based Sentiment Analysis (ABSA) of student feedback aims to identify sentiments expressed toward various aspects of teachers, such as their ability to address student doubts and their overall knowledge. This study explores linguistic characteristics found in sentences, including negation, modifiers and contact shifters. To assess the sentiment of a sentence, the SentiWordNet lexicon is utilized to assign scores to individual words. Based on these scores, the sentence is categorized as either positive, negative or neutral. According to the experimental findings, the Aspect-Oriented Lexicon-Based (AOLB) approach demonstrates superior performance compared to other baseline methods when it comes to accurately scoring sentiment. The approach achieved a high accuracy rate of 94% for the student feedback dataset-I, 74% for the student feedback dataset-II, 55% for laptop reviews and 59% for restaurant reviews in the SemEval 2014 dataset-III. [ABSTRACT FROM AUTHOR]