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Background: People with severe asthma remain at risk of toxicity from maintenance oral corticosteroid (OCS) use and/or frequent OCS burst therapy. Cumulative exposures above 500–1000 mg prednisolone are associated with adverse effects, and recently OCS stewardship principles were promulgated to guide OCS prescription. Aims: To examine real‐world registry data to quantify OCS burden, ascertain trends over time in prescription and assess whether opportunities to implement steroid‐sparing strategies were utilised. Methods: Participants were enrolled in the Australasian Severe Asthma Registry for the period 2013–2021. Assessments were taken at enrolment and then annual follow‐up, which included asthma control and OCS use. Descriptive analyses were performed, and subgroups were compared at baseline and over time. Results: Nine hundred and twenty‐four participants were evaluated and 215/924 (23%) were taking maintenance OCS at baseline, with 44% and 32% of participants having exposure to ≥500 or 1000 mg of OCS respectively in the prior year. Twelve months later, an additional 10% and 9% of participants reached cumulative doses of 500 or 1000 mg. People exceeding thresholds had ongoing poor asthma control. At baseline, 240/924 (26%) people were treated with asthma biological therapy. An additional 83 (12%) participants were identified as potentially benefiting from this steroid‐sparing medication. Of these patients, only 23% commenced a biologic agent in the next 12 months. Conclusions: A large national asthma registry identifies exposure to toxic cumulative doses of OCS in more than a third of participants, with further subsequent cumulative dose escalation over 2 years. Steroid‐sparing strategies were often not employed, highlighting the need for implementation of OCS stewardship initiatives. [ABSTRACT FROM AUTHOR]

With the liberalization and deregulation of the power industry, the power market presents increasingly invisible dynamics and uncertainty. Establishing an effective price forecasting model has always been an important issue for power market participants to avoid risks and maximize economic benefits. However, due to the inherent characteristics of high frequency and high volatility of electricity price data, it is still a difficult and challenging problem to achieve high-precision forecasting. To overcome these difficulties, this study constructed a novel multivariate electric price bi-forecasting system based on the proposed linear operator combination mechanism and deep learning model. Specifically, improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) is used for data preprocessing, while the multiobjective golden eagle optimization algorithm (MOGEO) optimized deep belief network and bidirectional long short-term memory network are used as the main prediction models for realizing two forecasting modes of point forecast and interval forecast by a multi-input multi-output structure simultaneously. To verify the model forecasting ability and effectiveness, four datasets from Australia (New South Wales) from 2020.7 to 2021.1 are selected for experiments. According to the empirical results, the mean absolute percentage error results of the designed forecasting strategy in point forecasting are within 4% for the four datasets, and the average coverage width criterion values in interval forecasting are all approximately 0.3. The results show that the system has good electricity price forecasting ability and can help policy-makers better understand market dynamics and develop more effective market regulation and intervention measures. • A novel electric price multi-bi-forecasting is constructed using MIMO scheme. • Multi-variable forecast scheme is adopted using the electric price and load data. • A new combination mechanism is introduced to combine the member models. • A superior optimizer is introduced in this system to realize two functions. [ABSTRACT FROM AUTHOR]

Background: Asthma remission has emerged as a potential treatment goal. This study evaluated the effectiveness of two biologics (mepolizumab/omalizumab) in achieving asthma remission., Methods: This observational study included 453 severe asthma patients (41% male; mean age ± SD 55.7 ± 14.7 years) from two real-world drug registries: the Australian Mepolizumab Registry and the Australian Xolair Registry. The composite outcome clinical remission was defined as zero exacerbations and zero oral corticosteroids during the previous 6 months assessed at 12 months and 5-item Asthma Control Questionnaire (ACQ-5) ≤1 at 12 months. We also assessed clinical remission plus optimization (post-bronchodilator FEV1 ≥80%) or stabilization (post-bronchodilator FEV1 not greater than 5% decline from baseline) of lung function at 12 months. Sensitivity analyses explored various cut-offs of ACQ-5/FEV1 scores. The predictors of clinical remission were identified., Results: 29.3% (73/249) of AMR and 22.8% (37/162) of AXR cohort met the criteria for clinical remission. When lung function criteria were added, the remission rates were reduced to 25.2% and 19.1%, respectively. Sensitivity analyses identified that the remission rate ranged between 18.1% and 34.9% in the AMR cohort and 10.6% and 27.2% in the AXR cohort. Better lung function, lower body mass index, mild disease and absence of comorbidities such as obesity, depression and osteoporosis predicted the odds of achieving clinical remission., Conclusion: Biologic treatment with mepolizumab or omalizumab for severe asthma-induced asthma remission in a subgroup of patients. Remission on treatment may be an achievable treatment target and future studies should consider remission as an outcome measure., (© 2023 The Authors. Allergy published by European Academy of Allergy and Clinical Immunology and John Wiley & Sons Ltd.)