Family Medicine and Community Health最新文献

Objective: Neighbourhood deprivation increases the risk of colorectal neoplasia and contributes to racial disparities observed in this disease. Developing race-specific advanced colorectal neoplasia (ACN) prediction models that include neighbourhood socioeconomic status has the potential to improve the accuracy of prediction.

Methods: The study includes 1457 European Americans (EAs) and 936 African Americans (AAs) aged 50-80 years undergoing screening colonoscopy. Race-specific ACN risk prediction models were developed for EAs and AAs, respectively. Area Deprivation Index (ADI), derived from 17 variables of neighbourhood socioeconomic status, was evaluated by adding it to the ACN risk prediction models. Prediction accuracy was evaluated by concordance statistic (C-statistic) for discrimination and Hosmer-Lemeshow goodness-of-fit test for calibration.

Results: With fewer predictors, the EA-specific and AA-specific prediction models had better prediction accuracy in the corresponding race/ethnic subpopulation than the overall model. Compared with the overall model which had poor calibration (P _Calibration=0.053 in the whole population and P _Calibration=0.011 in AAs), the EA model had C-statistic of 0.655 (95% CI 0.594 to 0.717) and P _Calibration=0.663; and the AA model had C-statistic of 0.637 ((95% CI 0.572 to 0.702) and P _Calibration=0.810. ADI was a significant predictor of ACN in EAs (OR=1.24 ((95% CI 1.03 to 1.50), P=0.029), but not in AAs (OR=1.07 ((95% CI 0.89 to 1.28), P=0.487). Adding ADI to the EA-specific ACN prediction model substantially improved ACN calibration accuracy of the prediction across area deprivation groups (P _Calibration=0.924 with ADI vs P _Calibration=0.140 without ADI) in EAs.

Conclusions: Neighbourhood socioeconomic status is an important factor to consider in ACN risk prediction modeling. Moreover, non-race-specific prediction models have poor generalisability. Race-specific prediction models incorporating neighbourhood socioeconomic factors are needed to improve ACN prediction accuracy.

Introduction: The application of large language models such as generative pre-trained transformers (GPTs) has been promising in medical education, and its performance has been tested for different medical exams. This study aims to assess the performance of GPTs in responding to a set of sample questions of short-answer management problems (SAMPs) from the certification exam of the College of Family Physicians of Canada (CFPC).

Method: Between August 8th and 25th, 2023, we used GPT-3.5 and GPT-4 in five rounds to answer a sample of 77 SAMPs questions from the CFPC website. Two independent certified family physician reviewers scored AI-generated responses twice: first, according to the CFPC answer key (ie, CFPC score), and second, based on their knowledge and other references (ie, Reviews' score). An ordinal logistic generalised estimating equations (GEE) model was applied to analyse repeated measures across the five rounds.

Result: According to the CFPC answer key, 607 (73.6%) lines of answers by GPT-3.5 and 691 (81%) by GPT-4 were deemed accurate. Reviewer's scoring suggested that about 84% of the lines of answers provided by GPT-3.5 and 93% of GPT-4 were correct. The GEE analysis confirmed that over five rounds, the likelihood of achieving a higher CFPC Score Percentage for GPT-4 was 2.31 times more than GPT-3.5 (OR: 2.31; 95% CI: 1.53 to 3.47; p<0.001). Similarly, the Reviewers' Score percentage for responses provided by GPT-4 over 5 rounds were 2.23 times more likely to exceed those of GPT-3.5 (OR: 2.23; 95% CI: 1.22 to 4.06; p=0.009). Running the GPTs after a one week interval, regeneration of the prompt or using or not using the prompt did not significantly change the CFPC score percentage.

Conclusion: In our study, we used GPT-3.5 and GPT-4 to answer complex, open-ended sample questions of the CFPC exam and showed that more than 70% of the answers were accurate, and GPT-4 outperformed GPT-3.5 in responding to the questions. Large language models such as GPTs seem promising for assisting candidates of the CFPC exam by providing potential answers. However, their use for family medicine education and exam preparation needs further studies.

Background: As populations age globally, effectively managing geriatric health poses challenges for primary care. Comprehensive geriatric assessments (CGAs) aim to address these challenges through multidisciplinary screening and coordinated care planning. However, most CGA tools and workflows have not been optimised for routine primary care delivery.

Objective: This study aimed to evaluate the impact of a computerised CGA tool, called the Golden Age Visit, implemented in primary care in Israel.

Methods: This study employed a quasiexperimental mixed-methods design to evaluate outcomes associated with the Golden Age electronic health assessment tool. Quantitative analysis used electronic medical records data from Maccabi Healthcare Services, the second largest health management organisation (HMO) in Israel. Patients aged 75 and older were included in analyses from January 2017 to December 2019 and January 2021 to December 2022. For patients, data were also collected on controls who did not participate in the Golden Age Visit programme during the same time period, to allow for comparison of outcomes. For physicians, qualitative data were collected via surveys and interviews with primary care physicians who used the Golden Age Visit SMARTEST e-assessment tool.

Results: A total of 9022 community-dwelling adults aged 75 and older were included in the study: 1421 patients received a Golden Age Visit CGA (intervention group), and 7601 patients did not receive the assessment (control group). After CGAs, diagnosis rates increased significantly for neuropsychiatric conditions and falls. Referrals to physiotherapy, occupational therapy, dietetics and geriatric outpatient clinics also rose substantially. However, no differences were found in rates of hip fracture or relocation to long-term care between groups. Surveys among physicians (n=151) found high satisfaction with the programme.

Conclusion: Implementation of a large-scale primary care CGA programme was associated with improved diagnosis and management of geriatric conditions. Physicians were also satisfied, suggesting good uptake and feasibility within usual care. Further high-quality studies are still needed but these results provide real-world support for proactively addressing geriatric health needs through structured screening models.

The conversation about consciousness of artificial intelligence (AI) is an ongoing topic since 1950s. Despite the numerous applications of AI identified in healthcare and primary healthcare, little is known about how a conscious AI would reshape its use in this domain. While there is a wide range of ideas as to whether AI can or cannot possess consciousness, a prevailing theme in all arguments is uncertainty. Given this uncertainty and the high stakes associated with the use of AI in primary healthcare, it is imperative to be prepared for all scenarios including conscious AI systems being used for medical diagnosis, shared decision-making and resource management in the future. This commentary serves as an overview of some of the pertinent evidence supporting the use of AI in primary healthcare and proposes ideas as to how consciousnesses of AI can support or further complicate these applications. Given the scarcity of evidence on the association between consciousness of AI and its current state of use in primary healthcare, our commentary identifies some directions for future research in this area including assessing patients', healthcare workers' and policy-makers' attitudes towards consciousness of AI systems in primary healthcare settings.

Introduction: Pelvic floor disorders (PFDs) pose substantial physical and psychological burdens for a growing number of women. Given the ubiquity of these conditions and known patient reluctance to seek care, primary care providers (PCPs) have a unique opportunity to increase treatment and provide appropriate referrals for these patients.

Methods: An online survey was administered to PCPs to assess provider practices, knowledge, comfort managing and ease of referral for PFDs. Logistic regression was used to assess the association between demographic/practice characteristics of PCPs and two primary outcomes of interest: discomfort with management and difficulty with referral of PFDs.

Results: Of the 153 respondents to the survey, more felt comfortable managing stress urinary incontinence (SUI) and overactive bladder (OAB), compared with pelvic organ prolapse (POP) and faecal incontinence (FI) and were less likely to refer patients with urinary symptoms. Few providers elicited symptoms for POP and FI as compared with SUI and OAB. Provider variables that were significantly associated with discomfort with management varied by PFD, but tended to correlate with less exposure to PFDs (eg, those with fewer years of practice, and internal medicine and family physicians as compared with geriatricians); whereas the factors that were significantly associated with difficulty in referral, again varied by PFD, but were related to practice characteristics (eg, specialist network, type of practice, practice setting and quantity of patients).

Conclusion: These findings highlight the need to increase PCPs awareness of PFDs and develop effective standardised screening protocols, as well as collaboration with pelvic floor specialists to improve screening, treatment and referral for patients with PFDs.

This paper proposes the utilisation of twin studies as a novel and powerful methodological approach to investigate critical research questions pertaining to cancer prevention, screening, diagnosis, treatment and survivorship within primary care contexts. The inherent genetic similarity between monozygotic (MZ) (identical) twins provides a unique opportunity to disentangle genetic and environmental influences on cancer-related outcomes. MZ twins share virtually identical genetic makeup, offering a unique opportunity to discern the relative contributions of genetic and environmental factors to cancer-related outcomes. In contrast, dizygotic (DZ) twins, also known as fraternal twins, develop from two separate eggs fertilised by two different sperm and share on average 50% of their genetic material, the same level of genetic similarity found in non-twin siblings. Comparisons between MZ and DZ twins enable researchers to disentangle hereditary factors from shared environmental influences. This methodology has the potential to advance our understanding of the multifaceted interplay between genetic predisposition, lifestyle factors and healthcare interventions in the context of cancer care. This paper outlines the rationale, design considerations and potential applications of twin studies in primary care-based cancer research.

Cervical intraepithelial neoplasia grade 2 (CIN2) lesions may regress spontaneously, offering an alternative to immediate treatment, especially for women of childbearing age (15-45 years).We conducted a prospective multicentre study on conservative CIN2 management, with semiannual follow-up visits over 24 months, biomarkers' investigation and treatment for progression to CIN3+ or CIN2 persistence for more than 12 months. Here, we assess women's willingness to participate and adherence to the study protocol.The study was set in population-based organised cervical cancer screening.From April 2019 to October 2021, 640 CIN2 cases were diagnosed in women aged 25-64 participating in the screening programmes.According to our predefined inclusion and exclusion criteria, 228 (35.6%) women were not eligible; 93 (22.6%) of the 412 eligible refused, and 319 (77.4%) were enrolled. Refusal for personal reasons (ie, desire to become pregnant, anxiety, difficulty in complying with the study protocol) and external barriers (ie, residence elsewhere and language problems) accounted for 71% and 17%, respectively. Only 9% expressed a preference for treatment. The primary ineligibility factor was the upper age limit of 45 years. After enrolment, 12 (4%) women without evidence of progression requested treatment, 125 (39%) were lost to follow-up (mostly after 6-12 months) and 182 (57%) remained compliant. Remarkably, 40% of enrolees did not fully adhere to the protocol, whereas only 5% (20/412) of the eligible women desired treatment.Our study demonstrates a good acceptance of conservative management for CIN2 lesions by the women, supporting its implementation within cervical screening programmes.