British Journal of General Practice最新文献

Background: An increasing number of pregnant women now take antidepressants. Many pregnant women experience decisional conflict when deciding whether to take antidepressants, but little is known about the attitudes and experiences that influence these decisions.

Aim: To explore the attitudes and experiences influencing women's decisions about antenatal antidepressant use.

Design and setting: A qualitative study using in-depth interviews with a sample of UK women who experienced antenatal depression or took antidepressants antenatally within the preceding 3 years.

Method: Recruitment adverts were placed by a perinatal mental health charity and on parenting forums and social media platforms, resulting in a convenience sample. Interview data were coded and analysed with thematic analysis using QSR NVivo.

Results: Twenty-two women were interviewed; one-half had taken antidepressants during pregnancy. Most women had concerns about adverse effects and viewed antidepressants as adjunctive to non-pharmacological treatments, which were reported as difficult to access. Some women reported that professional advice was insufficiently detailed. Women described the need to cope with their symptoms, their baby, and existing responsibilities, and related their decisions to their perceived ability to cope. This perception was influenced by physical and emotional challenges relating to pregnancy. Women's decisions were influenced by their previous experiences and by the perceived societal expectations placed on pregnant women.

Conclusion: Decision making is a complex and dynamic process, personal to each woman's circumstances. Perceived ability to cope is an important factor in decision making. Detailed information should be offered to women for support with decision making in relation to antenatal medication use.

Background: Faecal immunochemical testing (FIT) is now core to the management of patients presenting in primary care with symptoms of possible colorectal cancer. Patients with a positive FIT (≥10 μg haemoglobin [Hb]/g faeces) qualify for an urgent suspected cancer referral. FIT-negative patients are typically managed in primary care or referred through routine pathways.

Aim: To examine practitioners' experiences of delivering symptomatic FIT, identifying perceived benefits, disbenefits, and implementation issues, to inform potential future service improvements.

Design and setting: A qualitative interview study with primary and secondary care health professionals involved in delivering symptomatic FIT pathways from across the UK.

Method: Thirty semi-structured interviews were conducted with professionals from a range of specialties. An iterative topic guide informed interviews while allowing freedom to explore novel lines of enquiry. Pseudo-anonymised transcripts were coded, and themes were identified and developed.

Results: Symptomatic FIT was seen to be beneficial for increasing confidence in clinical decision making and enriching the pool of patients being definitively investigated for colorectal neoplasia. There were varying views on the impact of symptomatic FIT on workload with the burden of additional workload generally seen to impact primary care. Concerns about current practice included overuse of FIT, burden of investigations in patients with false-positive results, and diagnostic delays for both cancer and benign disease. Uncertainties existed around management of patients with rectal bleeding, appropriate strategies for safety netting, and the value of repeat FIT.

Conclusion: Symptomatic FIT is largely seen as beneficial; however, health professionals would welcome further evidence and guidance around optimal application.

Background: The journey of >80% of patients diagnosed with lung cancer starts in general practice. About 75% of patients are diagnosed when it is at an advanced stage (3 or 4), leading to >80% mortality within 1 year at present. The long-term data in GP records might contain hidden information that could be used for earlier case finding of patients with cancer.

Aim: To develop new prediction tools that improve the risk assessment for lung cancer.

Design and setting: Text analysis of electronic patient data using natural language processing and machine learning in the general practice files of four networks in the Netherlands.

Method: Files of 525 526 patients were analysed, of whom 2386 were diagnosed with lung cancer. Diagnoses were validated by using the Dutch cancer registry, and both structured and free-text data were used to predict the diagnosis of lung cancer 5 months before diagnosis (4 months before referral).

Results: The algorithm could facilitate earlier detection of lung cancer using routine general practice data. Discrimination, calibration, sensitivity, and specificity were established under various cut-off points of the prediction 5 months before diagnosis. Internal validation of the best model demonstrated an area under the curve of 0.88 (95% confidence interval [CI] = 0.86 to 0.89), which shrunk to 0.79 (95% CI = 0.78 to 0.80) during external validation. The desired sensitivity determines the number of patients to be referred to detect one patient with lung cancer.

Conclusion: Artificial intelligence-based support enables earlier detection of lung cancer in general practice using readily available text in the patient files of GPs, but needs additional prospective clinical evaluation.

Background: Diagnosing cancer in general practice is complex, given the non-specific nature of many presenting symptoms and the overlap of potential diagnoses.

Aim: This trial aimed to evaluate the effectiveness of Future Health Today (FHT) - a technology that provides clinical decision support, auditing, and quality-improvement monitoring - on the appropriate follow-up of patients at risk of undiagnosed cancer.

Design and setting: Pragmatic, cluster randomised trial undertaken in general practices in Victoria and Tasmania, Australia.

Method: Practices were randomly assigned to receive recommendations for follow-up investigations for cancer (FHT cancer module) or the active control. Algorithms were applied to the electronic medical record, and used demographic information and abnormal test results that are associated with a risk of undiagnosed cancer (that is, anaemia/iron deficiency, thrombocytosis, and raised prostate-specific antigen) to identify patients requiring further investigation and provide recommendations for care. The intervention consisted of the FHT cancer module, a case-based learning series, and ongoing practice support. Using the intention-to-treat approach, the between-arm difference in the proportion of patients with abnormal test results who were followed up according to guidelines was determined at 12 months.

Results: In total, 7555 patients were identified as at risk of undiagnosed cancer. At 12 months post-randomisation, 76.0% of patients in the intervention arm had received recommended follow-up (21 practices, n = 2820/3709), compared with 70.0% in the control arm (19 practices, n = 2693/3846; estimated between-arm difference = 2.6% [95% confidence interval (CI)] = -2.8% to 7.9%; odds ratio = 1.15 [95% CI = 0.87 to 1.53]; P = 0.332).

Conclusion: The FHT cancer module intervention did not increase the proportion of patients receiving guideline-concordant care. The proportion of patients receiving recommended follow-up was high, suggesting a possible ceiling effect for the intervention.