NPJ Primary Care Respiratory Medicine最新文献

National applications (apps) for adults with asthma were implemented as part of a respiratory toolkit across Wales from 2020. Data were collected on patient recorded asthma control including the Royal College of Physicians three questions. All general practices in Wales had patients registered on the asthma app and by September 2024, 12,567 (57.8%) of patients who downloaded the app went on to register. Analysis comparing baseline with four or more months of app use demonstrated improvements in the percent of those having a Royal College of Physicians asthma score of 0 (26.5% vs 40.7%, p = 0.0011), together with improvements in those not using a reliever inhaler at all (29.1% vs 39.2%, p = 0.0001). Where we had paired data one year apart, the improvements in asthma control were greater in those from most deprived areas. For those who used the app there were improvements across important metrics of asthma control consistent with better patient self-management.

Acute respiratory infections (ARI) are the most common infections in the general population and represent an important socio-economic burden. Characterizing ARIs in primary care in patients of all ages in terms of clinical presentation, and virological results. We conducted a prospective multicenter study in primary care: 36 French general practitioners (GPs) included patients from all ages presenting with symptoms of ARI, and performed a nasopharyngeal swab, which was analyzed by Multiplex RT-PCR. 685 patients of all ages were included in the cohort. We found associations between clinical diagnosis and respiratory viruses: influenza was associated with the diagnosis of flu-like syndrome (p < 0.001), HRV with rhinitis (p < 0.05), and RSV with bronchiolitis (p < 0.001) and bronchitis (p < 0.05). Respiratory distress was associated with RSV (p = 0.002), and a cough at the inclusion was significantly not associated with the influenza virus (p = 0.009). Antibiotic prescriptions were not associated with any specific virus. By day 7, persistent cough was significantly associated with active and passive smoking (respectively p = 0.01 and p < 0.001), influenza and RSV-positive samples (p < 0.05) and an age of less than 2 years (p < 0.01). With this prospective cohort performed in primary care including patients of all ages, we characterized viral respiratory infections, to better understand correlations between clinical data and virological results.

Psychological distress is highly prevalent in people with chronic obstructive pulmonary disease (COPD), however, remains under-recognised and under-treated. A qualitative study using semi-structured interviews was undertaken to explore lived experiences of psychological distress of people with COPD and their informal carers, as well as barriers and facilitators to uptake of mental health treatments. Participants were recruited via purposive sampling from respiratory clinics at two Australian tertiary hospitals. Thirteen people with COPD and comorbid mental illnesses and two informal carers participated. Interview transcripts were analysed using the Theoretical Domains Framework (TDF). Barriers to patients' acceptance of structured management for psychological distress in COPD included: limited understanding of overlapping symptoms, high burden of care from physical issues, stigma, and healthcare that did not align with individual preferences. Increased psychoeducation, supported self-management, and individualised care were possible facilitators. Multidisciplinary care integrating mental health services within primary care and pulmonary rehabilitation settings are required to overcome current challenges and improve patient outcomes.

Obstructive sleep apnea (OSA) is a well-established risk factor for hypertension, with sleep duration being a modifiable factor influencing this risk. However, sleep misperception among OSA patients makes it unclear how subjective and objective sleep duration are associated with the prevalence and incidence of hypertension in this population. This study aims to examine these associations using data from the Sleep Heart Health Study cohort. Participants with OSA (apnea-hypopnea index ≥ 15 events/hour) were categorized based on objective sleep duration from polysomnography (PSGTST) and subjective sleep duration (morning-reported sleep time, AMTST; habitual sleep time, HABTST). Hypertension prevalence was assessed at baseline, while hypertension incidence was evaluated during a five-year follow-up. Multivariable logistic regression and Poisson log-link models were employed to explore the association between sleep duration and hypertension risk, with restricted cubic splines used to assess nonlinear trends. Among 2574 participants with OSA, 1263 had hypertension at baseline. Over 5.25 years, 376 of 1001 patients without baseline hypertension developed hypertension. Shorter PSGTST was linearly associated with higher hypertension prevalence (p = 0.009) and incidence (p = 0.024). HABTST showed a U-shaped relationship with hypertension prevalence, while AMTST was not significantly associated with either outcome. In patients with OSA, objective sleep duration is linearly and inversely associated with both the prevalence and incidence of hypertension, showing stronger and more consistent associations than subjective sleep duration measures. These findings highlight the value of incorporating objective sleep assessment in evaluating hypertension risk in this population.

Chronic respiratory diseases (CRD) are major contributors to mortality. The "obesity paradox" suggests that higher body mass index (BMI) may confer survival benefits in CRD patients. This study investigates the association between BMI and mortality risk in CRD patients, focusing on the mediating role of the triglyceride-glucose (TyG) index. A cross-sectional analysis of 7689 participants with CRD was conducted. Participants were categorized by BMI into <25.0, 25.0-29.9, 30.0-34.9, 35.0-39.9, and ≥40 kg/m². Outcomes included all-cause mortality, cardiovascular disease (CVD) mortality, and non-CVD mortality. Cox regression models assessed associations, and mediation analysis evaluated the role of the TyG index. Among 7689 CRD patients, higher BMI was associated with lower all-cause mortality (HR for BMI 25.0-29.9: 0.81, 95% CI 0.70-0.94; HR for BMI 30.0-34.9: 0.72, 95% CI 0.61-0.85; HR for BMI 35.0-39.9: 0.72, 95% CI 0.59-0.88; HR for BMI ≥ 40: 0.82, 95% CI 0.66-1.02) and non-CVD mortality (HR for BMI 25.0-29.9: 0.77, 95% CI 0.65-0.91; HR for BMI 30.0-34.9: 0.65, 95% CI 0.54-0.79; HR for BMI 35.0-39.9: 0.66, 95% CI 0.52-0.83; HR for BMI ≥ 40: 0.69, 95% CI 0.53-0.89), but not CVD mortality. The TyG index mediated a significant proportion of the association between BMI and mortality (mediation effects: -22.39 to -18.49%). Kaplan-Meier survival curves and restricted cubic spline regression further illustrated the significant associations between BMI and all-cause mortality and non-CVD mortality, while no significant association was observed for CVD mortality. Higher BMI is associated with lower mortality risk in CRD patients, particularly for non-CVD causes, mediated by the TyG index. This highlights the potential role of insulin resistance in the "obesity paradox" and suggests that metabolic health interventions may improve outcomes in CRD.

Primary care consultations provide an opportunity for patients and clinicians to assess asthma attack risk. Using a data-driven risk prediction tool with routinely collected health records may be an efficient way to aid promotion of effective self-management, and support clinical decision making. Longitudinal Scottish primary care data for 21,250 asthma patients were used to predict the risk of asthma attacks in the following year. A selection of machine learning algorithms (i.e., Naïve Bayes Classifier, Logistic Regression, Random Forests, and Extreme Gradient Boosting), hyperparameters, training data enrichment methods were explored, and validated in a random unseen data partition. Our final Logistic Regression model achieved the best performance when no training data enrichment was applied. Around 1 in 3 (36.2%) predicted high-risk patients had an attack within one year of consultation, compared to approximately 1 in 16 in the predicted low-risk group (6.7%). The model was well calibrated, with a calibration slope of 1.02 and an intercept of 0.004, and the Area under the Curve was 0.75. This model has the potential to increase the efficiency of routine asthma care by creating new personalized care pathways mapped to predicted risk of asthma attacks, such as priority ranking patients for scheduled consultations and interventions. Furthermore, it could be used to educate patients about their individual risk and risk factors, and promote healthier lifestyle changes, use of self-management plans, and early emergency care seeking following rapid symptom deterioration.

Patients seen in general practices can achieve improved asthma control with better identification of factors that contribute to uncontrolled asthma. Information is lacking on the proportion of patients with uncontrolled asthma, associated patient characteristics, and opportunities to improve management. The objectives of this study were to determine the proportion of general practice patients with uncontrolled asthma, as assessed during a regular consultation with the AsthmaOptimiser digital tool, identify the opportunities for improved management, and to evaluate the usability of this tool which is based on treatment recommendations from GINA. The CAPTURE study was a non-interventional, prospective, observational study of the AsthmaOptimiser in general practice settings in the Netherlands. Patients were at least 18 years of age with an asthma diagnosis. A total of 34 Dutch general practitioners or nurse practitioners participated in the study and planned to use the AsthmaOptimiser with 5 to 10 adult patients per practice. Interviews were conducted to gather information from practitioners about the tool's usability, its content, and areas for improvement. Of the 220 patients enrolled, 60% had uncontrolled asthma, of whom 64% had opportunities for management improvement that could be initiated during a primary care visit. Specialist referrals were advisable according to the AsthmaOptimiser in 45 patients with uncontrolled asthma. Practitioners reported that the AsthmaOptimiser was an added value and had suggestions on how to improve the tool. In Dutch general practices, the AsthmaOptimiser helped general practitioners identify opportunities for improved disease management by addressing poor disease control. Overall, the general practitioners found the AsthmaOptimiser easy to use and a good addition to asthma consultations.

We investigated healthcare avoidance during the first COVID-19 wave in a Dutch region with high infection rates. A mixed-method, multiphase study used (1) primary care electronic health records to identify patients, (2) questionnaires to capture patients with unreported COVID-19 symptoms, and (3) interviews om care avoidance. Additionally, a natural language model estimated COVID-19 incidence from routine care data. Of 2361 respondents (39% response rate), 535 (23%) reported COVID-19 symptoms; 180 sought help, mainly from GPs. Care-seeking rates did not differ significantly between those with or without relatives who experienced severe illness or death before their own illness (p = 0.270). Interviews showed the main barriers were feeling not ill enough and concerns about an overstressed healthcare system, especially GPs. Only a third of participants with symptoms sought help, mostly from GPs. Serious illness or death of loved ones had no significant impact. Findings highlight the need for clear communication and accessible healthcare, including telemedicine, for future pandemics.

Past epidemiological studies demonstrated mixed findings on the association between diabetes and lung cancer. Given the possible links between diabetes, smoking, and respiratory diseases, this study aims to examine the interaction patterns among factors associated with the risk of lung cancer among diabetes patients. A territory-wide retrospective cohort study was performed using electronic health records of Hong Kong. Patients who received diabetes care in general outpatient clinics between 2010 and 2019 without cancer history were included and followed up until December 2019. Conditional inference survival tree was applied to examine the interaction patterns among factors associated with the risk of lung cancer. A total of 385,521 patients were included. During a median follow-up of 6.2 years, 3395 developed lung cancer. Age emerged as primary factor in differentiating the risk of lung cancer. Conditional on age ( ≤ 64 vs >64 years), smoking appeared as subsequent dominant risk factor within each subpopulation. Among old smokers aged >64 years characterized by long duration of diabetes (median: 6-8 years), chronic obstructive pulmonary disease (COPD) emerged as key risk factor. Six distinct subgroups of diabetes patients with different risk levels of lung cancer according to age, smoking, metformin use, and COPD status were identified. Findings of the study suggest the interaction patterns among age, smoking, and COPD on the risk of lung cancer among diabetes patients, providing targets for public health interventions.