Internal medicine journal
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Internal medicine journal · Sep 2021
Retrospective analysis of the efficacy and duration of botulinum toxin A injections in 30 patients with palmar hyperhidrosis.
Palmar hyperhidrosis is a common disorder characterised by excessive sweating due to hyperfunction of the sweat glands. It can be classified as primary disease, or secondary to other causes. It has a high morbidity, and a range of treatment options. ⋯ There was evidence for a median reduction in the Hyperhidrosis Disease Severity Scale, a qualitative self-reported score, as well as an increasing duration of efficacy with repeated injections. There were minimal side-effects of weakness and numbness. There is also an association between treatment of palmar disease and improvement in plantar disease, which suggests that treatment of palmar hyperhidrosis should be considered earlier and more frequently.
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Internal medicine journal · Sep 2021
"Concerns and Psychological Wellbeing of Health Care Workers During the COVID-19 Pandemic in a Tertiary Care Hospital in NSW".
In early 2020, the impending COVID-19 pandemic placed a once-in-a-generation professional and personal challenge on healthcare workers. Publications on direct physical disease abound. The authors wanted to focus on doctors' psychological well-being. ⋯ Both COVID-19 specific concerns and psychological well-being improved greatly in the second survey. Possible explanations are the fall in COVID-19 cases in the district, improvements in PPE supply and supportive measures communicated to doctors during this period.
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Internal medicine journal · Sep 2021
ReviewDemystifying machine learning - a primer for physicians.
Machine learning is a tool for analysing digitised data sets and formulating predictions that can optimise clinical decision-making. It aims to identify complex patterns in large data sets and encode them into models that can then classify new unseen cases or make predictions on new data. Machine learning methods take several forms and individual models can be of many different types. ⋯ The reliability and robustness of any model depends on multiple factors, including the quality and quantity of the data used to develop the models, and the selection of features in the data considered most important to maximising accuracy. In ensuring models are safe, effective and reproducible in routine care, physicians need to have some understanding of how these models are developed and evaluated, and to collaborate with data and computer scientists in their design and validation. This narrative review introduces principles, methods and examples of machine learning in a way that does not require mastery of highly complex statistical and computational concepts.