NPJ Primary Care Respiratory Medicine最新文献

Asthma and intrinsic capacity (IC) decline were individually examined with mortality, yet the complex interplay between them remains largely unknown. This study aimed to examine the potential roles of IC decline in the association between asthma and all-cause mortality. We conducted a prospective cohort study using data from UK Biobank, where IC decline was defined as a decline in any domain of psychological, sensory, vitality, and locomotion. Cox proportional hazard models were used to examine the associations between asthma, IC decline, and all-cause mortality. The relative excess risk due to additive interaction (RERI) was calculated. Mediation analysis was performed to explore the mediating effect of IC decline. And a four-way decomposition method was utilized to quantify both the interaction and mediation role of IC decline. Among 439,973 participants, 51,558 (11.7%) had asthma, 290,964 (66.1%) experienced IC decline, and 37,204 deaths occurred during 5.92 million person-years follow-up. Significant multiplicative and additive interactions were observed between asthma and any IC domain decline on all-cause mortality (Multiplicative: HR = 1.14, 95% CI: 1.06-1.24; Additive: RERI = 0.20, 95% CI: 0.11-0.29). The proportion of the association between asthma and all-cause mortality mediated by decline in all four domains was 28.14% (95% CI: 23.84-34.92%). The results of four-way decomposition were similar. Asthma was associated with increased all-cause mortality, and this association may be partially accounted for by both the interaction and mediation effects of IC decline. These findings underscore the importance of comprehensive interventions that address both asthma management and preservation of IC function to enhance health outcomes in middle-late life.

Breathlessness is prevalent in societies worldwide, with widespread health and socioeconomic impacts. Breathlessness self-management interventions developed in high-income countries (HICs) are promising but require contextual adaptation for low- and middle-income countries (LMICs) like India, where cultural beliefs, language, and delivery systems differ. We co-designed breathlessness self-management resources for use in India using a programme theory approach and Community-Based Participatory Research methods. We convened three stakeholder groups (Doctors (n = 9), Nurses and allied health (n = 6) and lived experiences (n = 9)) and added a fourth group (community health workers (n = 6)) based on emerging findings. We re-analysed 104 academic and lay sources identified iteratively and systematically by the Breathe-India project and presented evidence to stakeholder groups for discussion and feedback. Three rounds of online/face-to-face stakeholder workshops. Stakeholders reviewed evidence, developed shared definitions, and iteratively co-designed intervention components. Stakeholder engagement and evidence synthesis led to identification of seven key domains informing the intervention: (1) Identifying breathlessness- teach the difference between acute and persistent breathlessness (and acute-on persistent breathlessness); (2) Developing shared language-emphasising lived experience of breathlessness in simple, translatable language; (3) Addressing fear-teaching accessible methods (e.g. facial cooling) for regaining control that build confidence; (4) Building resilience-reframing activity as safe and beneficial; (5) Daily coping strategies-aligning with local beliefs and behaviours, e.g. inclusion of nutritional 'dos and don'ts'; (6) Delivery through community infrastructure-teaching Accredited Social Health Activists (ASHAs) how to identify breathlessness in communities and challenge unhelpful beliefs-at the point of care. Outputs included training curricula, educational resources, and public-facing materials co-developed with ASHA trainers and stakeholders. We co-designed India's first multicomponent, community-deliverable breathlessness self-management intervention using participatory methods and theory-driven processes. Implementation-effectiveness hybrid evaluation is needed to test feasibility, acceptability, and impact on patients and families.

Medication adherence is critical for successful tuberculosis (TB) treatment, yet non-adherence remains a major barrier to TB control globally. Digital adherence technologies (DAT) have emerged as promising tools to support adherence, but their effectiveness remains variably reported across settings and intervention types. To evaluate the effectiveness of DAT compared to directly observed therapy (DOT) in improving TB medication adherence through a systematic review and meta-analysis of randomized controlled trials (RCTs). A comprehensive literature search was conducted across PubMed, Scopus, EBSCO, and ScienceDirect from inception through November 7, 2024. RCTs comparing DAT (e.g., SMS reminders, video-observed therapy [VOT], medication event reminder monitors [MERM], biometric monitoring systems [BMS], ingestion sensors [IS]) with DOT were included. Study selection, data extraction, and quality appraisal were performed independently by multiple reviewers. Meta-analyses were conducted using a random-effects model, with subgroup and sensitivity analyses. This review followed the PRISMA 2020 reporting guidelines. Nineteen RCTs involving over 10,000 TB patients were included. Overall, DAT significantly improved medication adherence compared to DOT, with a pooled odds ratio (OR) of 2.853 (95% CI: 2.144-3.796; p < 0.001). Subgroup analyses indicated that VOT, MERM, and SMS reminder were consistently effective, while the highest effect sizes were seen in IS and BMS, albeit with wider confidence intervals. Effectiveness varied by country income level: DAT were more effective in high- and upper-middle-income countries, while findings in lower-income settings remained inconclusive, partly due to the limited number of studies. Sensitivity analysis confirmed the robustness of findings, and no significant publication bias was detected (Egger's test p = 0.979). DAT are significantly more effective than DOT in improving medication adherence among TB patients. Tailored implementation strategies are needed to ensure optimal selection and integration of DATs across diverse health systems. These findings support the scaling-up of context-appropriate digital tools as part of global TB control efforts.

Introduction: When high-risk patients present lung cancer symptoms (LCSs) in general practice, Computed Tomography of the thorax (CT thorax) is recommended, but chest X-ray (CXR) may still be used often. This population-based study aims to 1) compare the proportion of patients who completed diagnostic evaluation, and 2) analyse the associations between smoking status, symptom burden and first choice of imaging among patients who presented LCS to their general practitioner (GP) in 2012 and 2022.

Methods: Two random samples of 100,000 individuals ≥20 years were invited to a survey about symptoms and healthcare seeking in 2012 and 2022, respectively, with subsequently linkage to register data. We included individuals ≥40 years old who reported GP contact with LCSs. Descriptive statistics and multivariable regression models were applied.

Results: A total of 5910 (16%) and 4883 (22%) individuals reported at least one LCS in 2012 and 2022, respectively, and 2538 (43%) and 2229 (46%), respectively, had contacted their GP. Diagnostic imaging was completed by 2538 (24%) in 2012 and 2229 (22%) in 2022. CXR was the most common first choice of imaging in both years (22% and 15%, respectively), although CT thorax as first choice increased from 2% to 7%. Higher symptom burden and former smoking increased the odds of completing diagnostic imaging while current smoking did not.

Conclusion: One out of five patients with lung cancer symptoms completed diagnostic evaluation. CXR remained first choice, although more completed CT thorax in 2022. GPs may need tools to support risk stratification and choice of imaging.

Long COVID, defined by symptoms persisting three months post-SARS-CoV-2 infection, presents a significant global health and economic challenge, with global prevalence estimated at 36% (ranging from 1-92%). This brief communication consolidates current knowledge on its economic impacts, including macroeconomic, cost-of-illness, and microeconomic impacts, which are estimated at an average annual burden of $1 trillion globally and $9000 per patient in the USA, with some individuals covering substantial out-of-pocket expenses. Annual lost earnings in the USA alone are estimated at approximately $170 billion. Long COVID was associated with increased unemployment, financial distress, and work impairment for up to three years post-infection. This paper highlights discrepancies in impact estimation methodologies and calls for standardised metrics especially in emerging economies. Key research gaps include the absence of comprehensive longitudinal studies on individual and aggregated economic burden, specific long COVID phenotypes and biomarkers, and cost-effectiveness evaluations of interventions.

Objective: This study explored the application of Machine Learning (ML) techniques to cluster patients with suspected sleep apnea (SA), based on clinical-demographic data, with the aim of optimizing diagnostic pathways and enabling more personalized management.

Methods: A cohort of 5385 patients referred for suspected SA to a Sleep-Disordered Breathing Unit in northwest Spain was analyzed. Demographic, anthropometric, comorbidity, and symptom data were collected. Patients were grouped using the k-prototypes algorithm, with the elbow method determining the optimal number of clusters. These clusters were then correlated with cardiorespiratory polygraphy outcomes and continuous positive airway pressure (CPAP) prescription rates. Finally, we developed an Intelligent Clinical Decision Support System (ICDSS) based on Random Forest to assign new patients to clusters using a reduced set of variables.

Results: Five distinct clusters were identified: one of middle-aged men with low symptom burden; a cluster predominantly comprising symptomatic women with high use of psychotropic drugs; a group mainly of young men with severe daytime sleepiness; a cluster of middle-aged men with moderate symptoms; and a group of older men with high comorbidity yet low subjective symptomatology. Significant differences in apnea-hypopnea index (AHI) distributions and CPAP indications were observed among these clusters. The integration of polygraphic findings, CPAP prescription rates, and the distinct clinical features of each cluster supports the formulation of tailored diagnostic and therapeutic strategies according to the specific clinical profile of each subgroup. Using the ICDSS, we accurately assigned patients to their respective clusters based solely on clinical variables, achieving area under the receiver operating characteristic curve (AUC) values ranging from 0.87 to 0.95, reliably guiding precise diagnostic and therapeutic management.

Conclusions: ML techniques applied to routine data allow the identification of meaningful clinical clusters in patients with suspected SA. These clusters can guide differential diagnostic testing and personalized treatment strategies. The ICDSS enables early and accurate patient classification, supporting a precision medicine approach in sleep medicine.

The relationship between systemic inflammation and centripedal obesity in predicting mortality risk among patients with Preserved Ratio Impaired Spirometry (PRISm) has garnered increasing interest. This study aims to elucidate the joint effects of these factors on mortality risk in this patient population. This study included data from the National Health and Nutrition Examination Survey (NHANES) of U.S. adults collected from 2007-2012, calculating both the systemic inflammation response index (SIRI) and the weight-adjusted waist index (WWI). Lung function parameters were used to define PRISm cases. Generalized linear models and logistic regression were used to assess the individual and combined effects of SIRI and WWI, and further explored the mediating role of the SIRI. A total of 1454 PRISm patients were included in this study, with a median follow-up period of 9.5 years, during which 10.9% died from all causes and 3.6% from cardiovascular diseases. The restricted cubic spline curves for SIRI and WWI showed J-shaped associations with mortality. Participants with both high WWI (≥11.18) and high Ln SIRI (≥0.13) had significantly higher all-cause and cardiovascular mortality compared with those with low WWI and low SIRI. In the discordant groups, high WWI with low SIRI was associated with increased all-cause mortality (HR = 1.795, 1.050-3.064), while low WWI with high SIRI was linked to higher cardiovascular mortality (HR = 4.844, 1.505-15.591). This effect was more pronounced in the smoking subgroup. Additionally, SIRI mediated 9% of the association between WWI and all-cause mortality, and 12.94% of the association with cardiovascular mortality. Our study provides evidence for the relationship between SIRI and WWI with mortality in PRISm patients. The joint association of these factors provide potential insights for additional information for prognostic prediction and may contribute to identifying risk stratification in PRISm.

Upper respiratory tract infections (URTIs) are among the most common diseases encountered in primary medical care. Recurrent URTIs (RURTIs) considerably affect patient health and quality of life. Recent evidence indicates that increased attention is being paid to symptom improvement in clinical practice. However, the therapeutic opportunities associated with using a vector for improving the immune status of patients remain underestimated. As the most common sources of URTI are viral infections, antiviral agents with the potential to enhance host immune responses can be considered auxiliary, effective, and safe for children and adults with URTIs and RURTIs. This review reports the current evidence and expert opinions on immunity-targeted approaches in the management of viral URTIs. Undelayed diagnosis and initiating treatment in the early stages of URTIs are crucial elements that can significantly improve disease evolution and the overall health of patients of any age group. An immunomodulatory remedy would be optimal for facilitating the healing of acute infections, reducing recurrence and complications, antibiotic consumption, and the consequences of antibiotic overuse. Maintaining and protecting the intestinal microbiota is also an important step toward effective URTI treatment. The findings of this review provide valuable insights into the effective management of URTIs and RURTIs based on the latest clinical evidence.

The utility of fractional exhaled nitric oxide (FeNO) was evaluated alongside blood eosinophils in phenotyping mild asthma. Inclusion of FeNO improved classification accuracy and calibration in an adapted ISAR-based model; however, its predictive improvement was modest and its susceptibility to transient elevations suggests limited added value for routine clinical classification. Simplified algorithms may offer more accurate phenotyping in population-based settings with real-world constraints.