Obstructive sleep apnea: What is an orthodontist's role?

BACKGROUND: The American Association of Orthodontists white paper on obstructive sleep apnea and orthodontics remains the most authoritative statement on the topic. This was produced in 2019 due to increasing orthodontic interest in obstructive sleep apnea (OSA) and the lack of formal guidelines for orthodontists. Since the white paper's release, advocacy for contrarian ideas and practices remain. Orthodontists are sometimes acting as primary care providers for OSA. Procedures appropriate only for screening are sometimes being used for diagnosis. The side effects of effective treatments such as mandibular advancement devices need further consideration. Also, research has clarified the effectiveness and ineffectiveness of treatments such as palatal expansion. RESULTS: Part of an orthodontist's role is screening for OSA. The correct action when this is suspected remains referral to the appropriate physician specialist for diagnosis and treatment or coordination of treatment. Orthodontists may participate in the treatment of patients with OSA as a member of a multi-disciplinary team. Effective orthodontic treatments may include orthognathic surgery with maxillomandibular advancement and mandibular advancement devices. The negative effects of the latter make this a choice of last resort. Current research indicates that OSA alone is not sufficient indication for palatal expansion. CONCLUSIONS: Orthodontists should appropriately screen for obstructive sleep apnea. This may be done as part of our health histories, our clinical examination, and review of radiographs taken for purposes other than the diagnosis and screening for OSA. Orthodontic treatment for OSA can be helpful and effective. However, this may be done only after referral to the appropriate physician specialist, as part of a multi-disciplinary team, with consideration of the likely effectiveness of treatment, and after all likely and potential negative consequences have been considered and thoroughly discussed with the patient.

CODE-EHR best practice framework for the use of structured electronic healthcare records in clinical research.

Big data is central to new developments in global clinical science aiming to improve the lives of patients. Technological advances have led to the routine use of structured electronic healthcare records with the potential to address key gaps in clinical evidence. The covid-19 pandemic has demonstrated the potential of big data and related analytics, but also important pitfalls. Verification, validation, and data privacy, as well as the social mandate to undertake research are key challenges. The European Society of Cardiology and the BigData@Heart consortium have brought together a range of international stakeholders, including patient representatives, clinicians, scientists, regulators, journal editors and industry. We propose the CODE-EHR Minimum Standards Framework as a means to improve the design of studies, enhance transparency and develop a roadmap towards more robust and effective utilisation of healthcare data for research purposes.

CODE-EHR best-practice framework for the use of structured electronic health-care records in clinical research.

Big data is important to new developments in global clinical science that aim to improve the lives of patients. Technological advances have led to the regular use of structured electronic health-care records with the potential to address key deficits in clinical evidence that could improve patient care. The COVID-19 pandemic has shown this potential in big data and related analytics but has also revealed important limitations. Data verification, data validation, data privacy, and a mandate from the public to conduct research are important challenges to effective use of routine health-care data. The European Society of Cardiology and the BigData@Heart consortium have brought together a range of international stakeholders, including representation from patients, clinicians, scientists, regulators, journal editors, and industry members. In this Review, we propose the CODE-EHR minimum standards framework to be used by researchers and clinicians to improve the design of studies and enhance transparency of study methods. The CODE-EHR framework aims to develop robust and effective utilisation of health-care data for research purposes.

Design of a "Lean" Case Report Form for Heart Failure Therapeutic Development.

The development of treatments for heart failure (HF) is challenged by burdensome clinical trials. Reducing the need for extensive data collection and increasing opportunities for data compatibility between trials may improve efficiency and reduce resource burden. The Heart Failure Collaboratory (HFC) multi-stakeholder consortium sought to create a lean case report form (CRF) for use in HF clinical trials evaluating cardiac devices. The HFC convened patients, clinicians, clinical researchers, the U.S. Food and Drug Administration (FDA), payers, industry partners, and statisticians to create a consensus core CRF. Eight recent clinical trial CRFs for the treatment of HF from 6 industry partners were analyzed. All CRF elements were systematically reviewed. Those elements deemed critical for data collection in HF clinical trials were used to construct the final, harmonized CRF. The original CRFs included 176 distinct data items covering demographics, vital signs, physical examination, medical history, laboratory and imaging testing, device therapy, medications, functional and quality of life assessment, and outcome events. The resulting, minimally inclusive CRF device contains 75 baseline data items and 6 events, with separate modular additions that can be used depending on the additional detail required for a particular intervention. The consensus electronic form is now freely available for use in clinical trials. Creation of a core CRF is important to improve clinical trial efficiency in HF device development in the United States. This living document intends to reduce clinical trial administrative burden, increase evidence integrity, and improve comparability of clinical data between trials.