Background Chronic obstructive pulmonary disease (COPD) is a common and severely incapacitating respiratory illness that is characterized by ongoing, non-reversible airflow restrictions. Various medical treatment options include bronchodilators, anti-cholinergic drugs, and steroids. This study aimed to evaluate the effectiveness of oral roflumilast in addition to standard therapy among COPD patients to prevent exacerbations and improve pulmonary function tests (forced expiratory volume in one second (FEV1) and forced vital capacity (FVC)). Methodology This quasi-experimental study enrolled 80 moderate-to-severe COPD patients through non-probability sampling. They were divided into two groups. In Group A, participants received standard treatment as per the operational definition for six months. In Group B, participants received once-daily roflumilast, 500 µg, while maintaining background medications of COPD as per the operational definition for six months. Quantitative variables, including age, post-bronchodilator FEV1, and FVC, were expressed as mean ± SD. An independent-sample t-test was used to compare the outcome variables (FEV1 and FVC) between the two groups. The number of COPD exacerbations was analyzed using an appropriate statistical test, such as the Mann-Whitney U test. All the data were analyzed using SPSS version 28.0. Results Both groups showed a significant increment in mean FEV1 and FVC from day zero to six months; however, mean FEV1 and FVC were significantly higher for Group B patients from the fourth to sixth months. A decreasing trend was observed in the frequency of exacerbations in both groups. At the fifth and sixth months of treatment, Group B patients showed significantly lower frequency of exacerbations compared to Group A patients. Conclusions Oral roflumilast as an adjunct to standard COPD therapy improved clinical outcomes by enhancing pulmonary function (particularly FEV1) and reducing exacerbation frequency. Reduction in recurrent exacerbations may contribute to better symptom control, improved quality of life, and decreased healthcare burden. Therefore, roflumilast 500 µg once daily may be considered a useful add-on option in selected COPD patients, although larger studies with longer follow-up are warranted to establish long-term benefits.

This interdisciplinary longitudinal study examines the association between PM2.5 levels at sites downwind of a coal-fired thermal power plant (TPP) near the India-Bangladesh border and respiratory health in the exposed population, assessed using spirometry and fractional exhaled nitric oxide levels. Pulmonary function tests indicate significantly worse lung health at downwind sites in both India and Bangladesh compared with an upwind location. With averaged forced expiratory volume in one second (FEV1) values < 80% of predicted, evidence of preserved ratio impaired spirometry (PRISm), and significantly lower forced expiratory flow between 25% and 75% of vital capacity (FEF25-75), the population at the Indian downwind site is clearly at risk of developing obstructive pulmonary and related diseases. Although PM2.5 concentrations decline sharply during the monsoon across all sites, this does not translate into a recovery in lung health at the downwind location, consistent with chronic, irreversible effects potentially related to long-term exposure to TPP-associated PM2.5. Moreover, poorer socioeconomic conditions and exposure to emissions from biomass-based indoor cooking are associated with exacerbated respiratory effects. Overall, the study advocates transitioning to cleaner fuels for power generation and household use and recommends locating power plants away from densely populated areas to minimize health impacts.

Background. Early assessment of chronic obstructive pulmonary disease and other respiratory disorders relies heavily on pulmonary function tests (PFTs). However, PFTs are effort-dependent and require strict quality control, limiting their application in certain clinical scenarios requiring broad accessibility or repeated assessment.Purpose. This study developed a multidimensional feature-based model derived from paired inspiratory-expiratory computed tomography (CT) images for the noninvasive and quantitative prediction of key pulmonary function indices.Methods. A multidimensional feature set was constructed by integrating clinical variables, parametric response mapping (PRM)-derived lung density distribution features, registration-based ventilation heterogeneity features, and deformation-based local biomechanical response features. An elastic-net regression model was then developed to predict the ratio of forced expiratory volume in one second to forced vital capacity (FEV1/FVC) and the percent predicted FEV1%pred.Results. The model was evaluated on 120 subjects with paired inspiratory-expiratory CT scans and PFT data. The proposed multidimensional feature prediction model showed numerically better performance than models using clinical or PRM features alone for both prediction tasks. In the test set, the model achieved anR[2]of 0.572 with a mean absolute error (MAE) of 8.38 for FEV1/FVC, and anR[2]of 0.472 with an MAE of 13.65 for FEV1%pred. Interpretability analysis using SHapley Additive exPlanations revealed that among the newly proposed features, the proportion of voxels in the ventilation interval '0 <E-I< 50'(Vol0-50), as well as the higher-order statistics of the Jacobian determinant specifically fSAD_J_Skew, fSAD_J_Kurt and Emph_J_Skew, were critical predictors of pulmonary function.Conclusion. This method may serve as a complementary tool to PFTs for the quantitative prediction of pulmonary function indices in opportunistic functional assessment and longitudinal follow-up among patients who have already undergone dual-phase CT.

The promotion and application of pulmonary function tests (PFTs) in China have achieved preliminary success;however, numerous deficiencies persist in multidisciplinary PFT clinical application pathways and management. Current challenges remain in identifing target population, implementing pathways within and outside medical institutions, allocating hardware, training personnel, managing information, and assessing performance.The consensus aims to optimize multidisciplinary clinical pathways and management models for PFTs by leveraging information technology and strengthening organizational coordination. Using a modified Delphi method and a systematic literature review, 14 core clinical questions were identified across four categories: (1) cognitive and information management platforms, (2) laboratory infrastructure and personnel, (3) performance evaluation, and (4) outreach and expansion capabilities. Furthermore, it proposes targeted and feasible implementation pathways and solutions, aiming to standardize PFTs practices and enhance multidisciplinary collaboration nationwide.Summary of Key RecommendationsQuestion 1: How to identify the candidates eligible for PFTs?Recommendation 1: By defining keywords for the PFT-eligible population, clinical physicians can enhance their ability to identify individuals at high risk for pulmonary function abnormalities and increase PFT utilization rates. The eligible candidates can be automatically identified through Hospital Information System (HIS) that recognize keywords in outpatient or inpatient records and trigger pop-up alerts.Question 2: If pop-up alerts are not feasible, which scales can be used to assist in identifying the PFT-eligible candidates?Recommendation 2: Evaluating patients' history of high-risk exposure or completing the screening questionnaires before visits can help improve the identification rate of the PFT-eligible candidates. Questionnaires include the Chronic Obstructive Pulmonary Disease Screening Questionnaire (COPD-SQ) or the Lung Function Screening Questionnaire (LFQ), etc. (Strong Recommendation)Currently, the COPD-SQ and LFQ questionnaires are commonly used for screening high-risk COPD populations. Due to the low cost and ease of use, they are suitable for widespread use across all levels of medical institutions. Other risk factors such as significant exposure to biomass fuels, asthma, and recurrent respiratory infections in early childhood can also lead to lung function decline or impaired lung development. Some necessary items can be added to improve the sensitivity and applicability of PFTs, forming a modified version or Chinese version of PFT screening tool.Question 3: How to select appropriate PFT modalities based on clinical needs?Recommendation 3: Physicians should select the optimal testing methods and their combinations based on each patient's specific clinical status. (Strong Recommendation)PFTs include basic and advanced tests. Basic tests primarily refer to pulmonary ventilation function tests (spirometry) or forced oscillation technique (FOT). The latter is particularly suitable for patients with ventilation impairments who cannot cooperate with forced expiratory maneuvers. Advanced tests include Bronchodilator Test/Bronchodilator Reversibility Test, Diffusing Capacity of the Lung for Carbon Monoxide (DLCO) test, Lung Plethysmography, Airway Resistance Assessment, Fractional Exhaled Nitric Oxide (FeNO) test, 6-Minute Walk Test (6MWT), Cardiopulmonary Exercise Testing, etc. Physicians should strategically combine these tests into different clinical pathways according to the results of PFTs and clinical needs.Question 4: How to delineate responsibilities and implementation protocols for PFTs among different hospital departments?Recommendation 4: The attending physician who orders the PFT should follow up on the results and proceed with subsequent tests independently or by consulting with clinical specialists. If discrepancies are found, PFT laboratory staff should communicate in a timely and two-way manner to form a closed loop with the attending physician, including timely adjustment of test items, handling of emergencies, and explaining results to the patients. When necessary, PFT specialists should participate in clinical consultations. (Strong Recommendation)Question 5: How to develop the PFT pathways for health centers?Recommendation 5: Health centers should incorporate PFTs into routine physical examinations. For individuals aged ≥40 years, or those with high-risk factors for chronic respiratory diseases (such as a long-term smoking history, exposure to dusts, chronic respiratory symptoms, or a family history of chronic respiratory diseases), PFTs should be mandatory. After tests, the PFT results should be included in the health reports to provide information for health or referral recommendations. (Strong Recommendation)Question 6: How to establish PFT pathways based on imaging findings?Recommendation 6: For patients with abnormal radiographic findings such as emphysema, pulmonary fibrosis, or bronchiectasis, further PFTs should be recommended.① Keywords in manual or electronical imaging reports should be used to prompt the PFTs. Keywords for chest X-ray include: emphysema, pulmonary bullae, tracheal stenosis, bronchial wall thickening, mucous plugging, distal bronchiolar destruction, bronchiectasis, reticular and honeycomb-like lesions, interstitial fibrosis, chest wall deformity, etc. Keywords for CT imaging include: airway wall thickening,≥5% emphysema involvement (defined as areas with lung density below -950 HU), destruction or abnormal mucous plugging in distal bronchioles, atelectasis, giant lung mass, moderate or severe pleural effusion, etc. (Strong Recommendation)② Institutions with the requisite facilities are recommended to optimize the diagnosis and treatment of respiratory system diseases by integrating Artificial Intelligence (AI)-enhanced CT with PFTs. Using AI-CT for in-depth analysis of chest CT images can automatically assist in identifying lung lesions and, combined with PFT data, provide more accurate recommendations for clinical management. (Strong Recommendation)Question 7: How to enable the digital transmission of PFT data?Recommendation 7① PFT reports from different PFT analyzers should be integrated with HIS, picture archiving and communication system (PACS)and laboratory information system (LIS)to enable automated data synchronization. (Strong Recommendation)② Recommendations for information system access standards and conversion requirements: digital PFT reports should follow a unified and standardized format for HIS integration, including the patient's demographics, test indicators, data, images and the electronic signature of the operator or reviewing physician. If digital data cannot be integrated, images or PDFs of the reports can be uploaded to PACS. (Strong Recommendation)Question 8: How to establish a standardized PFT data platform within healthcare institutions?Recommendation 8① Integrate PFT data across all hospital departments to ensure real-time, accurate synchronization with the Hospital Information System (HIS). Records of the types, frequency and results of PFTs can be used to establish the unified, standardized PFT database for centralized management and analysis. (Strong Recommendation)② The platform should feature basic functions such as data storage, querying, statistics and quality control. It is recommended to embed a standardized quality assessment and grading system within electronic reports to assist clinicians in rapidly evaluating data quality and interpreting the reliability of results. (Strong Recommendation)③ Patients with confirmed chronic respiratory diseases should be integrated into the platform, or PFT data should be incorporated into existing patient management systems. This integration supports clinical research and hospital administration and enables the visual management of longitudinal pulmonary function data. (Strong Recommendation)Question 9: How to establish a Cloud-based Data Sharing Platform?Recommendation 9: Standards and specifications for uploading PFT data should be established to ensure data security and patient privacy. PFT data sharing among medical institutions within the region should be achieved through regional cloud storage to provide the data support for hierarchical diagnosis and treatment and telemedicine. In principle, patient information should be anonymized prior to being uploaded to regional sub-centers. Regional sub-centers are responsible for reviewing reports, revising conclusions, and assigning quality control ratings. The cloud data center should aggregate the quality control data from all sub-centers, and regularly evaluate and sample the sub-centers' quality control reports. (Strong Recommendation)Question 10: How to improve the quality control and the interpretation of PFTs?Recommendation 10① Quality control and interpretation of PFT results should be performed by physicians or technicians who have received specialized training in PFTs and possess relevant qualifications. In addition, AI can be utilized to achieve quality control and interpretation of pulmonary function test results, promoting the optimal allocation of medical resources and improving efficiency. (Strong Recommendation)② Implementation methods for AI-assisted PFTs: PFT equipment manufacturers should integrate AI-assisted PFT systems into instruments or cloud platforms. Using AI deep learning and other models to automatically identify abnormalities, the acceptability, repeatability and quality grading of PFT results can be intelligently interpreted, more accurately distinguishing types of ventilation dysfunction, improving diagnostic accuracy and efficiency, and achieving efficient automatic identification of abnormal populations. (Strong Recommendation)Currently, quality control and result interpretation of PFTs rely primarily on manual assessment, which is inefficient, subject to observer bias, and requires trained and qualified personnel. The introduction of AI technology can enable automatic quality control and assisted interpretation of PFT data, enhancing the efficiency and quality of PFTs.AI deep learning models based on large-scale standardized PFT data can perform real-time evaluation of data collection and curve quality during the testing process, issuing timely warnings and requesting re-testing for unqualified results. Acceptable PFT results can be used for further determining the abnormalities, assessing the type and severity of pulmonary function impairment, and intelligently generating real-time warnings, patient guidance and auxiliary interpretation, improving the quality control and interpretation efficiency of PFT results.Question 11: How to configure equipment and personnel for the PFT laboratory?Recommendation 11① Space configuration: A comfortable examination environment for patients should be provided by establishing PFT suites, ensuring reasonable spatial layout with proper ventilation and temperature/humidity control. (Strong Recommendation)② Hardware configuration: The PFT devices should be equipped according to the specific needs of the healthcare institution. The equipment should comply with industry technical specifications, undergo regular calibration and maintenance, and be documented in comprehensive equipment management logs. (Strong Recommendation)③ Personnel configuration: The full-time technical personnel should be assigned reasonably according to the equipment and workload needs, and should undergo the relevant training and pass the assessments. (Strong Recommendation)Question 12: How to improve the patient experience and PFT efficiency?Recommendation 12① By setting up self-service terminals for PFTs or using mobile applications, the process of registration, payment, appointment, check-in, and report viewing can be completed quickly, which helps improve the patient experience, reduce waiting time, and optimize workflow. (Strong Recommendation)② Instructional videos can visually help patients learn about the significance of PFTs, improve maneuver compliance, and adherence to precautions. (Strong Recommendation)③ Adopting augmented reality technology (e.g., head-mounted displays) helps facilitate rapid learning and improved testing efficiency. Providing an immersive interactive experience increases patient engagement and understanding, which helps to improve the implementation rate and efficiency of PFTs. (Strong Recommendation)Question 13: When conducting multidisciplinary PFTs, how to set the target testing rates for different departments?Recommendation 13: In addition to routine clinical application in the Department of Pulmonary and Critical Care Medicine (PCCM), PFTs are also significant in multiple departments such as Surgery, Cardiology and Geriatrics, and should be encouraged in high-risk populations. It is recommended that the proportion of PFTs ordered by clinical departments other than PCCM Department and Thoracic Surgery Department should constitute more than 30% of the total hospital-wide PFT volume. (Strong Recommendation)Question 14: How to set the assessment criteria for PFTs?Recommendation 14: Competency-based criteria for physicians and technicians performing PFTs should be established, encompassing both the quantity and quality of tests. Personnel who do not meet the standards should undergo re-training and re-assessment. (Strong Recommendation)This consensus is registered on the International Practice Guideline Registration and Transparency Platform:PREPARE-2025CN1382 DOI: 10.3760/cma.j.cn112147-20251114-00713.

Chronic Obstructive Pulmonary Disease (COPD), a major chronic respiratory disease with persistent airflow limitation, is a leading global cause of disability and mortality. Respiratory spirogram time series, routinely collected during pulmonary function tests (PFTs), play a critical role in the early detection of respiratory diseases and in monitoring lung function over time. However, most current AI models for COPD diagnosis are limited to outputting classification results without providing a rationale for their diagnostic process, while current Large Language Models (LLMs) cannot understand spirograms yet, which severely limits their clinical trust and adoption. To tackle this challenge, we leverage a cohort of 234,028 individuals from the UK Biobank (UKB) to propose SpiroLLM, the first multimodal large language model that can understand spirogram. The model extracts morphological features from respiratory curves via a SpiroEncoder and aligns them with PFT numerical values in a unified latent space using a SpiroProjector, ultimately empowering a large language model to generate a comprehensive diagnostic report. Experimental results confirm that SpiroLLM achieved a diagnostic AUROC of 0.8977 (95% CI: 0.88-0.91). In a robustness test with missing core data, it maintained a 100% valid response rate, far surpassing the 13.4% of a text-only model and showcasing the superiority of its multimodal design. This work demonstrates the substantial potential of deeply fusing physiological signals with large language models, establishing a new paradigm for the next generation of interpretable and reliable clinical decision support tools.