Partially Free Journal ISSN (Print) 0008-350X - ISSN (Online) 1715-5258 This journal is no longer being updated because: the publisher no longer provides RSS feeds
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Authors:
Iio, K; Goldman, R. D. Pages: e44 - e46 PubDate: 2024-03-18T11:10:14-07:00 DOI: 10.46747/cfp.7003e44 Issue No:Vol. 70, No. 3 (2024)
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Van Der Loo; S. Pages: 153 - 154 PubDate: 2024-03-18T11:10:14-07:00 DOI: 10.46747/cfp.7003153 Issue No:Vol. 70, No. 3 (2024)
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Katz, A; Singer, A. G. Pages: 155 - 157 PubDate: 2024-03-18T11:10:14-07:00 DOI: 10.46747/cfp.7003155 Issue No:Vol. 70, No. 3 (2024)
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Katz, A; Singer, A. G. Pages: 158 - 160 PubDate: 2024-03-18T11:10:14-07:00 DOI: 10.46747/cfp.7003158 Issue No:Vol. 70, No. 3 (2024)
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Authors:
Kueper, J. K; Emu, M, Banbury, M, Bjerre, L. M, Choudhury, S, Green, M, Pimlott, N, Slade, S, Tsuei, S. H, Sisler, J. Pages: 161 - 168 Abstract: ObjectiveTo understand the current landscape of artificial intelligence (AI) for family medicine (FM) research in Canada, identify how the College of Family Physicians of Canada (CFPC) could support near-term positive progress in this field, and strengthen the community working in this field.Composition of the committeeMembers of a scientific planning committee provided guidance alongside members of a CFPC staff advisory committee, led by the CFPC-AMS TechForward Fellow and including CFPC, FM, and AI leaders.MethodsThis initiative included 2 projects. First, an environmental scan of published and gray literature on AI for FM produced between 2018 and 2022 was completed. Second, an invitational round table held in April 2022 brought together AI and FM experts and leaders to discuss priorities and to create a strategy for the future.ReportThe environmental scan identified research related to 5 major domains of application in FM (preventive care and risk profiling, physician decision support, operational efficiencies, patient self-management, and population health). Although there had been little testing or evaluation of AI-based tools in practice settings, progress since previous reviews has been made in engaging stakeholders to identify key considerations about AI for FM and opportunities in the field. The round-table discussions further emphasized barriers to and facilitators of high-quality research; they also indicated that while there is immense potential for AI to benefit FM practice, the current research trajectory needs to change, and greater support is needed to achieve these expected benefits and to avoid harm.ConclusionTen candidate action items that the CFPC could adopt to support near-term positive progress in the field were identified, some of which an AI working group has begun pursuing. Candidate action items are roughly divided into avenues where the CFPC is well-suited to take a leadership role in tackling priority issues in AI for FM research and specific activities or initiatives the CFPC could complete. Strong FM leadership is needed to advance AI research that will contribute to positive transformation in FM. PubDate: 2024-03-18T11:10:14-07:00 DOI: 10.46747/cfp.7003161 Issue No:Vol. 70, No. 3 (2024)
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Iio, K; Goldman, R. D. Pages: 169 - 170 Abstract: QuestionAn 8-month-old boy presented to our clinic with a 3-day history of fever. He has had a cough and rhinorrhea since the onset of the fever, and his 4-year-old sibling has recently had cough and cold symptoms. I have heard that the presence of respiratory symptoms means that urinary tract infection (UTI) is less likely. In infants with fever and respiratory symptoms, who should have a sample collected for urinalysis for UTI'AnswerThe approach to diagnosing febrile infants who have respiratory symptoms varies by age. Urinalysis should be done for all febrile infants younger than 2 months of age, regardless of whether they have respiratory symptoms. Clinicians should assess risk factors for UTI in every infant between 2 and 24 months of age and should not exclude the diagnosis of UTI based on respiratory symptoms alone. Use of a predictive tool to estimate the pretest probability of UTI would aid decision making about patients in this population. PubDate: 2024-03-18T11:10:14-07:00 DOI: 10.46747/cfp.7003169 Issue No:Vol. 70, No. 3 (2024)
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Young, J; Lee, E, Lindblad, A. J, Falk, J. Pages: 183 - 184 PubDate: 2024-03-18T11:10:14-07:00 DOI: 10.46747/cfp.7003183 Issue No:Vol. 70, No. 3 (2024)
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Young, J; Lee, E, Lindblad, A. J, Falk, J. Pages: 185 - 186 PubDate: 2024-03-18T11:10:14-07:00 DOI: 10.46747/cfp.7003185 Issue No:Vol. 70, No. 3 (2024)
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Spohn, O; Morkem, R, Singer, A. G, Barber, D. Pages: 187 - 196 Abstract: ObjectiveTo estimate the prevalence of dyslipidemia and to describe its management in Canadian primary care.DesignRetrospective cohort study using primary care electronic medical record data.SettingCanada.ParticipantsAdults aged 40 years or older who saw a Canadian Primary Care Sentinel Surveillance Network contributor between January 1, 2018, and December 31, 2019.Main outcome measuresPresence or absence of dyslipidemia as identified by a validated case definition and the treatment status of patients identified as having dyslipidemia based on having been prescribed a lipid-lowering agent (LLA).ResultsIn total, 50.0% of the 773,081 patients 40 years of age or older who had had a primary care visit in 2018 or 2019 were identified as having dyslipidemia. Dyslipidemia was more prevalent in patients 65 or older (61.5%), in males (56.7%) versus females (44.7%), and in those living in urban areas (50.0%) versus rural areas (45.2%). In patients with documented dyslipidemia, 42.8% had evidence of treatment with an LLA. Stratifying patients by Framingham risk score revealed that those in the high-risk category were more likely to have been prescribed an LLA (65.0%) compared with those in the intermediate-risk group (48.7%) or the low-risk group (22.8%). The strongest determinants of receiving LLA treatment for dyslipidemia include sex, with males being 1.95 times more likely to have been treated compared with females (95% CI 1.91 to 1.98; P PubDate: 2024-03-18T11:10:14-07:00 DOI: 10.46747/cfp.7003187 Issue No:Vol. 70, No. 3 (2024)
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