British medical bulletin最新文献

Introduction: Management of patients in the acute care setting requires accurate diagnosis and rapid initiation of validated treatments; therefore, this setting is likely to be an environment in which cognitive augmentation of the clinician's provision of care with technology rooted in artificial intelligence, such as machine learning (ML), is likely to eventuate.

Sources of data: PubMed and Google Scholar with search terms that included ML, intensive/critical care unit, electronic health records (EHR), anesthesia information management systems and clinical decision support were the primary sources for this report.

Areas of agreement: Different categories of learning of large clinical datasets, often contained in EHRs, are used for training in ML. Supervised learning uses algorithm-based models, including support vector machines, to pair patients' attributes with an expected outcome. Unsupervised learning uses clustering algorithms to define to which disease grouping a patient's attributes most closely approximates. Reinforcement learning algorithms use ongoing environmental feedback to deterministically pursue likely patient outcome.

Areas of controversy: Application of ML can result in undesirable outcomes over concerns related to fairness, transparency, privacy and accountability. Whether these ML technologies irrevocably change the healthcare workforce remains unresolved.

Growing points: Well-resourced Learning Health Systems are likely to exploit ML technology to gain the fullest benefits for their patients. How these clinical advantages can be extended to patients in health systems that are neither well-endowed, nor have the necessary data gathering technologies, needs to be urgently addressed to avoid further disparities in healthcare.

Background: High rates of poor mental health in healthcare staff threatens the quality and sustainability of healthcare delivery. Multi-factorial causes include the nature and structure of work. We conducted a critical review of UK NHS (England) data pertaining to: doctors, nurses, midwives and paramedics.

Sources of data: Key demographic, service architecture (structural features of work) and well-being indicators were identified and reviewed by a stakeholder group. Data searching prioritized NHS whole workforce sources (focusing on hospital and community health services staff), which were rated according to strength of evidence.

Findings: Key differences between professions were: (i) demographics: gender (nursing and midwifery female-dominated, doctors and paramedics more balanced); age (professions other than doctors had ageing workforces); ethnicity (greater diversity among doctors and nurses); (ii) service architecture: despite net staffing growth, turnover and retention were problematic in all professions; 41.5% doctors were consultants but smaller proportions held high grade/band roles in other professions; salaries were higher for doctors; (iii) well-being: all reported high job stress, particularly midwives and paramedics; sickness absence rates for nurses, midwives and paramedics were three times those of doctors, and presenteeism nearly double.

Growing points: Sociocultural factors known to increase risk of poor mental health may explain some of the differences reported between professions. These factors and differences in service architecture are vital considerations when designing strategies to improve well-being.

Areas timely for developing research: Multi-level systems approaches to well-being are required that consider intersectionality and structural differences between professions; together with inter-professional national databases to facilitate monitoring.

Introduction or background: Antibiotic resistance raises ethical issues due to the severe and inequitably distributed consequences caused by individual actions and policies.

Sources of data: Synthesis of ethical, scientific and clinical literature.

Areas of agreement: Ethical analyses have focused on the moral responsibilities of patients to complete antibiotic courses, resistance as a tragedy of the commons and attempts to limit use through antibiotic stewardship.

Areas of controversy: Each of these analyses has significant limitations and can result in self-defeating or overly narrow implications for policy.

Growing points: More complex analyses focus on ethical implications of ubiquitous asymptomatic carriage of resistant bacteria, non-linear outcomes within and between patients over time and global variation in resistant disease burdens.

Areas timely for developing research: Neglected topics include the harms of antibiotic use, including off-target effects on the human microbiome, and the lack of evidence guiding most antibiotic prescription decisions.

Background: Traumatic brain injury (TBI) in combat sports is relatively common, and rotational acceleration (RA) is a strong biomechanical predictor of TBI. This review summarizes RA values generated from head impacts in combat sport and puts them in the context of present evidence regarding TBI thresholds.

Sources of data: PubMed, EMBASE, Web of Science, Cochrane Library and Scopus were searched from inception to 31st December 2021. Twenty-two studies presenting RA data from head impacts across boxing, taekwondo, judo, wrestling and MMA were included. The AXIS tool was used to assess the quality of studies.

Areas of agreement: RA was greater following direct head strikes compared to being thrown or taken down. RA from throws and takedowns was mostly below reported injury thresholds. Injury thresholds must not be used in the absence of clinical assessment when TBI is suspected. Athletes displaying signs or symptoms of TBI must be removed from play and medically evaluated immediately.

Areas of controversy: Methodological heterogeneity made it difficult to develop sport-specific conclusions. The role of headgear in certain striking sports remains contentious.

Growing points: RA can be used to suggest and assess the effect of safety changes in combat sports. Gradual loading of training activities based on RA may be considered when planning sessions. Governing bodies must continue to work to minimize RA generated from head impacts.

Areas timely for developing research: Prospective research collecting real-time RA data is required to further understanding of TBI in combat sports.