RESUMO
Background and aims: Patients often first present with symptoms of trigeminal neuralgia (TN) to primary care. However, there has been little research to determine whether the diagnosis and management of this condition is carried out according to current guidelines. Furthermore, there is little up-to-date information regarding the prevalence of TN in the UK. The aim is to estimate the prevalence of TN and to audit the diagnosis and management process of TN in primary care. Methods: Between 2019 and 2020 a search was made at five UK GP practices with a total patient population of 55,842 using EMIS and SystmOne patient record systems to review patient consultations to identify patients coded with TN or facial pain (FP). These records were reviewed to ascertain the basis for diagnosis, management in primary care and referral to secondary care. Results: 157 patients were identified; 54 coded with FP and 103 with TN. These results indicate a prevalence of 22.3 in 10,000. There was no difference in documented symptoms between the two groups. Seven patients had all ICDH3 criteria recorded, with two meeting the requirements for TN diagnosis. 58.8% of patients with TN were started on carbamazepine, the current gold standard treatment, compared with 16.7% in the FP group. 38.2% of TN patients were referred to a range of different specialities. Conclusion: The prevalence of TN may be higher than previously thought. Key diagnostic criteria are often omitted, leading to potential misdiagnosis or delays in diagnosis. Relatively few referrals are made, though all patients should be considered for imaging.
RESUMO
Background: The emerging field of artificial intelligence (AI) will probably affect the practice for the next generation of doctors. However, the students' views on AI have not been largely investigated. Methods: An anonymous electronic survey on AI was designed for medical and dental students to explore: (1) sources of information about AI, (2) AI applications and concerns, (3) AI status as a topic in medicine, and (4) students' feelings and attitudes. The questionnaire was advertised on social media platforms in 2020. Security measures were employed to prevent fraudulent responses. Mann-Whitney U-test was employed for all comparisons. A sensitivity analysis was also performed by binarizing responses to express disagreement and agreement using the Chi-squared test. Results: Three thousand one hundred thirty-three respondents from 63 countries from all continents were included. Most respondents reported having at least a moderate understanding of the technologies underpinning AI and of their current application, with higher agreement associated with being male (p < 0.0001), tech-savvy (p < 0.0001), pre-clinical student (p < 0.006), and from a developed country (p < 0.04). Students perceive AI as a partner rather than a competitor (72.2%) with a higher agreement for medical students (p = 0.002). The belief that AI will revolutionize medicine and dentistry (83.9%) with greater agreement for students from a developed country (p = 0.0004) was noted. Most students agree that the AI developments will make medicine and dentistry more exciting (69.9%), that AI shall be part of the medical training (85.6%) and they are eager to incorporate AI in their future practice (99%). Conclusion: Currently, AI is a hot topic in medicine and dentistry. Students have a basic understanding of AI principles, a positive attitude toward AI and would like to have it incorporated into their training.
