Supraclavicular lymphadenopathy following COVID-19 vaccination: an increasing presentation to the two-week wait neck lump clinic?

The first COVID-19 vaccination was given in December 2020 and there is an effort to vaccinate the international population on a massive scale. Common side effects from the vaccine include headache and tiredness. Regional lymphadenopathy has been described in relation to other vaccines. We describe two cases of supraclavicular reactive lymphadenopathy presenting in patients who had the COVID vaccination in the ipsilateral arm. Awareness of this diagnosis is important for patients presenting to the neck lump clinic.     

Rethinking PICO in the Machine Learning Era: ML-PICO

Background  Machine learning (ML) has captured the attention of many clinicians who may not have formal training in this area but are otherwise increasingly exposed to ML literature that may be relevant to their clinical specialties. ML papers that follow an outcomes-based research format can be assessed using clinical research appraisal frameworks such as PICO (Population, Intervention, Comparison, Outcome). However, the PICO frameworks strain when applied to ML papers that create new ML models, which are akin to diagnostic tests. There is a need for a new framework to help assess such papers. Objective  We propose a new framework to help clinicians systematically read and evaluate medical ML papers whose aim is to create a new ML model: ML-PICO (Machine Learning, Population, Identification, Crosscheck, Outcomes). We describe how the ML-PICO framework can be applied toward appraising literature describing ML models for health care. Conclusion  The relevance of ML to practitioners of clinical medicine is steadily increasing with a growing body of literature. Therefore, it is increasingly important for clinicians to be familiar with how to assess and best utilize these tools. In this paper we have described a practical framework on how to read ML papers that create a new ML model (or diagnostic test): ML-PICO. We hope that this can be used by clinicians to better evaluate the quality and utility of ML papers.     

Citizen minds,citizen bodies: the citizenship experience and the government of mentally ill persons

The concept of citizenship is becoming more and more prominent in specific fields, such as psychiatry/mental health, where it is constituted as a solution to the issues of exclusion, discrimination, and poverty often endured by the mentally ill. We argue that such discourse of citizenship represents a break in the history of psychiatry and constitutes a powerful strategy to counter the effects of equally powerful psychiatric labelling. However, we call into question the emancipatory promise of a citizenship agenda. Foucault's concept of governmentality is helpful in understanding the production of the citizen subject, its location within the ‘art of government’, as well as the ethical and political implications of citizenship in the context of mental health.