Pulmonary Disease Research Articles

Chinese expert consensus on home management of oral anticoagulants(2024 edition)

Oral anticoagulants are widely used in the home care of patients who require prevention and treatment of thromboembolic diseases. The irrational use of anticoagulants may cause thrombosis and hemorrhage. Currently, there are no national or international guidelines or consensus providing recommendations for home management of oral anticoagulants. Therefore, the Hospital Pharmacy Professional Committee of the Chinese Pharmaceutical Association organized domestic experts in the fields of clinical pharmacy, cardiovascular surgery, cardiovascular medicine, vascular surgery, respiratory medicine and laboratory science to sort out the relevant issues and compile the expert consensus on the home management of oral anticoagulants. The main contents of this consensus include pharmacological monitoring of oral anticoagulants, the process and precautions of carrying out home management of oral anticoagulants, and treatment of some special conditions during home management, with the aim of enhancing the safety and effectiveness of oral anticoagulants' usage and reducing the adverse events.

Detail-sensitive 3D-UNet for pulmonary airway segmentation from CT images.

The segmentation of airway from computed tomography (CT) images plays a vital role in pulmonary disease diagnosis, evaluation, surgical planning, and treatment. Nevertheless, it is still challenging for current methods to handle distal thin and low-contrast airways, leading to mis-segmentation issues. This paper proposes a detail-sensitive 3D-UNet (DS-3D-UNet) that incorporates two new modules into 3D-UNet to segment airways accurately from CT images. The feature recalibration module is designed to give more attention to the foreground airway features through a new attention mechanism. The detail extractor module aims to restore multi-scale detailed features by fusion of features at different levels. Extensive experiments were conducted on the ATM'22 challenge dataset composed of 300 CT scans with airway annotations to evaluate its performance. Quantitative comparisons prove that the proposed model achieves the best performance in terms of Dice similarity coefficient (92.6%) and Intersection over Union (86.3%), outperforming other state-of-the-art methods. Qualitative comparisons further exhibit the superior performance of our method in segmenting thin and confused distal bronchi. The proposed model could provide important references for the diagnosis and treatment of pulmonary diseases, holding promising prospects in the field of digital medicine. Codes are available at https://github.com/nighlevil/DS-3D-UNet/tree/master .

Open Access Data and Deep Learning for Cardiac Device Identification on Standard DICOM and Smartphone-based Chest Radiographs.

"Just Accepted" papers have undergone full peer review and have been accepted for publication in Radiology: Artificial Intelligence. This article will undergo copyediting, layout, and proof review before it is published in its final version. Please note that during production of the final copyedited article, errors may be discovered which could affect the content. Purpose To develop and evaluate a publicly available deep learning model for segmenting and classifying cardiac implantable electronic devices (CIEDs) on Digital Imaging and Communications in Medicine (DICOM) and smartphone-based chest radiograph (CXR) images. Materials and Methods This institutional review board-approved retrospective study included patients with implantable pacemakers, cardioverter defibrillators, cardiac resynchronization therapy devices, and cardiac monitors who underwent chest radiography between January 2012 and January 2022. A U-Net model with a ResNet-50 backbone was created to classify CIEDs on DICOM and smartphone images. Using 2,321 CXRs from 897 patients (median age, 76 years (range 18-96 years); 625 male, 272 female), CIEDs were categorized into four manufacturers, 27 models, and one 'other' category. Five smartphones were used to acquire 11,072 images. Performance was reported using the Dice coefficient on the validation set for segmentation or balanced accuracy on the test set for manufacturer and model classification, respectively. Results The segmentation tool achieved a mean Dice coefficient of 0.936 (IQR: 0.890-0.958). The model had an accuracy of 94.36% (95% CI: 90.93%-96.84%; n = 251/266) for CIED manufacturer classification and 84.21% (95% CI: 79.31%-88.30%; n = 224/266) for CIED model classification. Conclusion The proposed deep learning model, trained on both traditional DICOM and smartphone images, showed high accuracy for segmentation and classification of CIEDs on CXRs. ©RSNA, 2024.

Genomic Comparative of Pseudomonas aeruginosa Small Colony Variant, Mucoid and Non-mucoid Phenotypes Obtained from a Patient with Cystic Fibrosis During Respiratory Exacerbations.

Pseudomonas aeruginosa, the most prevalent opportunistic pathogen in chronic obstructive pulmonary disease, associated with high morbidity and mortality in patients with cystic fibrosis (CF), is practically impossible to be eradicated from the airways in chronicity. Its extraordinary genomic plasticity is possibly associated with high antimicrobial resistance, virulence factors, and its phenotypic diversity. The occurrence of P. aeruginosa isolates promoting airway infection, showing mucoid, non-mucoid, and small colony variant (SCV) phenotypes, was observed simultaneously, in the present study, in sputum cultures obtained from a male CF young patient with chronic pulmonary infection for over a decade. The isolates belonged to a new ST (2744) were obtained in two moments of exacerbation of the respiratory disease, in which he was hospitalized. Genetic background and phenotypic analysis indicated that the isolates exhibited multi- and pan-antimicrobial resistant profiles, as well as non-susceptible to polymyxin and predominantly hypermutable (HPM) phenotypes. Whole genome sequencing showed variations in genome sizes, coding sequences and their determinants of resistance and virulence. The annotated genomes were compared for antimicrobial resistance, hypermutability, and SCV characteristics. We highlight the lack of reported genetic determinants of SCV emergence and HPM phenotypes, which can be explained in part due to the very short time between collections of isolates. To the best of our knowledge, this is the first report of genome sequencing of P. aeruginosa SCV from a CF patient in Brazil.

Burden of illness and mortality in men with Adrenomyeloneuropathy: a retrospective cohort study

BackgroundAdrenomyeloneuropathy (AMN) is a neurodegenerative disease phenotype of X-linked adrenoleukodystrophy (ALD), resulting in progressive myeloneuropathy causing spastic paraparesis, sensory ataxia, and bowel/bladder symptoms. We conducted a retrospective cohort study using two large administrative databases to characterize mortality and the burden of illness in adult men with AMN in the US.ResultsHealthcare resource use was assessed using a national commercial insurance claims database (2006–2021). Males with AMN ages 18–64 years and no evidence of cerebral ALD or other peroxisomal disorders were included and 1:4 matched on demographic characteristics to individuals without AMN. All study participants were followed for as long as observable. Patients with AMN were also identified in the Medicare Limited Dataset (2017–2022); mortality and age at death were compared with all Medicare enrollees. We identified 303 commercially insured men with AMN. Compared with non-AMN, individuals with AMN had significantly more inpatient hospital admissions (0.44 vs. 0.04 admissions/patient/year), outpatient clinic (8.88 vs. 4.1 visits/patient/year), outpatient hospital (5.33 vs. 0.99 visits/patient/year), and home healthcare visits (4.66 vs. 0.2 visits/patient/year), durable medical equipment claims (0.7 vs. 0.1 claims/patient/year), and prescription medication fills (18.1 vs. 5.4 fills/patient/year) (all p < 0.001). Average length-of-stay per hospitalization was also longer in AMN (8.88 vs. 4.3 days; p < 0.001). Rates of comorbidities were significantly more common in AMN compared to controls, including peripheral vascular disease (4.6% vs. 0.99%), chronic pulmonary disease (6.3% vs. 2.6%), and liver disease (5.6% vs. 0.88%), all p < 0.001. Among individuals age < 65 with Medicare disability coverage, mortality rates were 5.3x higher for adult AMN males (39.3% vs. 7.4%) and the age at death significantly younger (47.0 ± 11.3 vs. 56.5 ± 7.8 years), both p < 0.001. Among Medicare beneficiaries ages ≥ 65 mortality rates were 2.2x higher for men with AMN vs. those without AMN (48.6% vs. 22.4%), p < 0.001.ConclusionAMN imposes a substantial and underrecognized health burden on men, with higher healthcare utilization, greater medical comorbidity, higher mortality rates, and younger age at death.

Ag decoration as a strategy to enhance the methanol and ethanol sensing on the biphenylene sheet

Efficient, miniaturized, and highly sensitive sensors to detect volatile organic compounds (VOCs) have become vital tools to minimize pulmonary diseases and other sicknesses. Therefore, the adsorption capabilities of methanol and ethanol were investigated on the recently synthesized biphenylene (BPN) monolayer using the Ag decoration. Although the pristine BPN has suitable VOCs adsorption, the lower adsorption strength and the small charge transfer affect the sensor performance. On the other hand, the Ag decoration increases the gas sensitivity, with moderate chemisorption values of –0.67eV and –0.83eV for methanol and ethanol, respectively, and transitory chemical bond character (neither ionic nor covalent) between Ag atoms and the –OH radical. In addition, significative work function changes (Δϕ > 0.23 eV), huge charge transfer, and rapid recovery times at room temperature, τ = 0.18s and τ = 87.9s for methanol and ethanol, respectively, indicate a great VOCs sensitivity. The feasibility of the Ag-BPN and Ag-BPN + VOCs systems by ab initio molecular dynamics (AIMDs) was analyzed, which confirms that both systems are stable at 500K. Therefore, the DFT calculations employed here can guide experimentalists in exploring new miniaturized sensor devices based on BPN.

Reappraisal of Pidotimod: an immunomodulatory agent with 30-year evidence.

Pidotimod (3-L-pyroglutamyl-L-thiaziolidine-4-carboxylic acid) is a synthetic dipeptide with immunomodulatory properties that is indicated for use in adults and children over 3 years of age with documented cell-mediated immunodepression during respiratory and urinary tract infections. Infections are associated with an immune response that helps fight pathogens. In this scenario, inflammatory events occur to improve the antimicrobial reaction. However, defective immunity and/or sustained inflammation may adversely affect the course of the infection. Thus, modulating immune function could be a valuable option in managing patients with infections. The multifaceted mechanism of action of Pidotimod enables it to modulate innate and adaptive immunity. Extensive evidence about Pidotimod, accumulated over the last 30 years, has provided much data on the prevention of recurrent respiratory infections in susceptible children and respiratory exacerbations in patients with chronic bronchitis. Recent studies provide interesting information on how Pidotimod affects the metabolomic profiles of patients with bronchiectasis, clinical and immunological outcomes of elderly patients with pneumonia, clinical and cellular changes in patients with allergic rhinitis and asthma, and beneficial effects on cytokines and humoral immunity in human immunodeficiency virus (HIV) patients. Preliminary experience suggests that Pidotimod can shorten the duration of COVID-19 infection and reduce clinical severity by modulating the immune response, as well as prevent vaccination-related adverse events. In conclusion, the immunomodulatory properties of Pidotimod indicate that it may be a valuable option in managing patients with respiratory infections and other immune-mediated disorders, including allergy, chronic obstructive pulmonary disease, and asthma.

High level of genomic divergence in orf-I p12 and hbz genes of HTLV-1 subtype-C in Central Australia

BackgroundHuman T cell lymphotropic virus type 1 (HTLV-1) infection remains a largely neglected public health problem, particularly in resource-poor areas with high burden of communicable and non-communicable diseases, such as some remote populations in Central Australia where an estimated 37% of adults are infected with HTLV-1. Most of our understanding of HTLV-1 infection comes from studies of the globally spread subtype-A (HTLV-1a), with few molecular studies reported with the Austral-Melanesian subtype-C (HTLV-1c) predominant in the Indo-Pacific and Oceania regions.ResultsUsing a primer walking strategy and direct sequencing, we constructed HTLV-1c genomic consensus sequences from 22 First Nations participants living with HTLV-1c in Central Australia. Phylogenetic and pairwise analysis of this subtype-C proviral gDNA showed higher levels of genomic divergence in comparison to previously published HTLV-1a genomes. While the overall genomic homology between subtypes was 92.5%, the lowest nucleotide and amino acid sequence identity occurred near the 3′ end of the proviral genome coding regulatory genes, especially overlapping hbz (85.37%, 77.46%, respectively) and orf-I product p12 (82.00%, 70.30%, respectively). Strikingly, the HTLV-1c genomic consensus sequences uniformly showed a defective translation start codon for the immune regulatory proteins p12/p8 encoded by the HTLV-1A orf-I. Deletions in the proviral genome were detected in many subjects, particularly in the structural gag, pol and env genes. Similarly, using a droplet digital PCR assay measuring the copies of gag and tax per reference host genome, we quantitatively confirmed that provirus retains the tax gene region at higher levels than gag.ConclusionsOur genomic analysis of HTLV-1c in Central Australia in conjunction with earlier Melanesian HTLV-1c sequences, elucidate substantial differences with respect to the globally spread HTLV-1a. Future studies should address the impact these genomic differences have on infection and the regionally distinctive frequency of associated pulmonary disease. Understanding the host and virus subtype factors which contribute to the differential morbidity observed, is crucial for the development of much needed therapeutics and vaccine strategies against this highly endemic infection in remote First Nations communities in Central Australia.

Targeting CCL2-CCR2 signaling pathway alleviates macrophage dysfunction in COPD via PI3K-AKT axis

BackgroundChronic obstructive pulmonary disease (COPD) remains a leading cause of morbidity and mortality worldwide, characterized by persistent respiratory symptoms and airflow limitation. The involvement of C–C motif chemokine ligand 2 (CCL2) in COPD pathogenesis, particularly in macrophage regulation and activation, is poorly understood despite its recognized role in chronic inflammation. Our study aims to elucidate the regulatory role and molecular mechanisms of CCL2 in the pathogenesis of COPD, providing new insights for therapeutic strategies.MethodsThis study focused on the CCL2-CCR2 signaling pathway, exploring its role in COPD pathogenesis using both Ccl2 knockout (KO) mice and pharmacological inhibitors. To dissect the underlying mechanisms, we employed various in vitro and in vivo methods to analyze the secretion patterns and pathogenic effects of CCL2 and its downstream molecular signaling through the CCL2-CCR2 axis.ResultsElevated Ccl2 expression was confirmed in the lungs of COPD mice and was associated with enhanced recruitment and activation of macrophages. Deletion of Ccl2 in knockout mice, as well as treatment with a Ccr2 inhibitor, resulted in protection against CS- and LPS-induced alveolar injury and airway remodeling. Mechanistically, CCL2 was predominantly secreted by bronchial epithelial cells in a process dependent on STAT1 phosphorylation and acted through the CCR2 receptor on macrophages. This interaction activated the PI3K-AKT signaling pathway, which was pivotal for macrophage activation and the secretion of inflammatory cytokines, further influencing the progression of COPD.ConclusionsThe study highlighted the crucial role of CCL2 in mediating inflammatory responses and remodeling in COPD. It enhanced our understanding of COPD's molecular mechanisms, particularly how CCL2's interaction with the CCR2 activates critical signaling pathways. Targeting the CCL2-CCR2 axis emerged as a promising strategy to alleviate COPD pathology.Graphical

The potential and pitfalls of using a large language model such as ChatGPT, GPT-4, or LLaMA as a clinical assistant.

This study aims to evaluate the utility of large language models (LLMs) in healthcare, focusing on their applications in enhancing patient care through improved diagnostic, decision-making processes, and as ancillary tools for healthcare professionals. We evaluated ChatGPT, GPT-4, and LLaMA in identifying patients with specific diseases using gold-labeled Electronic Health Records (EHRs) from the MIMIC-III database, covering three prevalent diseases-Chronic Obstructive Pulmonary Disease (COPD), Chronic Kidney Disease (CKD)-along with the rare condition, Primary Biliary Cirrhosis (PBC), and the hard-to-diagnose condition Cancer Cachexia. In patient identification, GPT-4 had near similar or better performance compared to the corresponding disease-specific Machine Learning models (F1-score ≥ 85%) on COPD, CKD, and PBC. GPT-4 excelled in the PBC use case, achieving a 4.23% higher F1-score compared to disease-specific "Traditional Machine Learning" models. ChatGPT and LLaMA3 demonstrated lower performance than GPT-4 across all diseases and almost all metrics. Few-shot prompts also help ChatGPT, GPT-4, and LLaMA3 achieve higher precision and specificity but lower sensitivity and Negative Predictive Value. The study highlights the potential and limitations of LLMs in healthcare. Issues with errors, explanatory limitations and ethical concerns like data privacy and model transparency suggest that these models would be supplementary tools in clinical settings. Future studies should improve training datasets and model designs for LLMs to gain better utility in healthcare. The study shows that LLMs have the potential to assist clinicians for tasks such as patient identification but false positives and false negatives must be mitigated before LLMs are adequate for real-world clinical assistance.

The potential protective effects of probiotics, prebiotics, or yogurt on chronic obstructive pulmonary disease: Results from NHANES 2007–2012

The potential protective effects of probiotics, prebiotics, or yogurt on chronic obstructive pulmonary disease: Results from <scp>NHANES</scp> 2007–2012

Risk factors of acute exacerbation and disease progression in young patients with COPD

ObjectiveWe aimed to elucidate the clinical factors associated with acute exacerbation and disease progression in young patients with chronic obstructive pulmonary disease (COPD).MethodsThis retrospective longitudinal observational study included patients with...

Risk of Atherosclerotic Cardiovascular Disease Hospitalizations after COPD Hospitalization among Older Adults.

Meta-analyses have suggested the risk of cardiovascular disease (CVD) events is significantly higher after a chronic obstructive pulmonary disease (COPD) exacerbation. However, many of these studies have included a broad array of CVD events or have been limited to highly selected patient populations potentially not generalizable to the broader population of COPD. We assessed the risk of atherosclerotic cardiovascular disease (ASCVD)hospitalizations after COPD hospitalization compared to before COPD hospitalization and identified patient factors associated with ASCVD hospitalizations after COPD hospitalization. This retrospective cohort study used claims data from 920,550 Medicare beneficiaries hospitalized for COPD from 2016-2019 in the US. The primary outcome was risk of a ASCVD hospitalization composite outcome (myocardial infarction, percutaneous coronary intervention, coronary artery by-pass graft surgery, stroke, or transient ischemic attack) in the 30-days and 1 year after-COPD hospitalization relative to the same time period before-COPD hospitalization. Time in the before- and after-COPD hospitalization time periods to a composite ASCVD hospitalization outcome were modeled using an extension of the Cox Proportional-Hazards model, the Anderson-Gill model with adjustment for patient characteristics. Additional analyses evaluated for interactions in subgroups associated with the composite ASCVD hospitalization outcome. Among 920,550 patients in the 30-day and 1-year cohorts, (mean age, 73-74 years) the hazard ratio estimate (HR; 95% CI) for the composite ASCVD hospitalization outcome after-COPD hospitalization vs before-COPD hospitalization for the 30-day cohort was 0.99 (0.93, 1.05; p = 0.67) and for the 1-year cohort was 0.99 (0.97, 1.02; p = 0.53) following adjustment. We observed 3 subgroups that were significantly associated with higher risk for ASCVD hospitalizations 1 year after COPD hospitalization: 76+ years old, women, COPD hospitalization severity. Among Medicare beneficiaries hospitalized for COPD, the risk of ASCVD hospitalizations was not significantly increased 30-day or 1-year after COPD-hospitalization relative to before-COPD hospitalization. In sub-group analyses, we identified age 76+ years old, female sex, and COPD hospitalization severity as high risk subgroups with increased risk of ASCVD events 1-year after-COPD hospitalization. Further research is needed to characterize the COPD exacerbation populations at highest ASCVD hospitalization risk.

COPD is associated with increased cardiovascular disease risk independent of phenotype.

Chronic obstructive pulmonary disease (COPD) is a leading cause of death worldwide that frequently presents with concomitant cardiovascular diseases. Despite the pathological distinction between individual COPD phenotypes such as emphysema and chronic bronchitis, there is a lack of knowledge about the impact of COPD phenotype on cardiovascular disease risk. Thus, this study aimed to utilize a nationally representative sample to investigate cardiovascular disease prevalence in patients with COPD with emphysema and chronic bronchitis phenotypes. Data from 31,560 adults including 2504 individuals with COPD, collected as part of the National Health and Nutrition Examination Survey (1999-2018), were examined. A significantly increased cardiovascular disease risk, including coronary heart disease, heart failure, myocardial infarction and stroke, was identified in patients with COPD among all disease phenotypes. Particularly, compared to those without COPD, individuals with chronic bronchitis presented with 1.76 (95% CI: 1.41-2.20) times greater odds, individuals with emphysema with 2.31 (95% CI: 1.80-2.96) times greater odds, while those with a concurrent phenotype (combined chronic bronchitis and emphysema) exhibited 2.98 (95% CI: 2.11-4.21) times greater odds of reporting cardiovascular diseases. Our data confirms that patients with COPD present an elevated risk of developing cardiovascular disease among all phenotypes, with the most marked increase being in those with concurrent chronic bronchitis and emphysema phenotypes. These findings emphasize the need for awareness and appropriate cardiovascular screening in COPD.

Inhalation of hydrogen gas protects against mitomycin-induced pulmonary veno-occlusive disease

BackgroundAs a subtype of pulmonary hypertension (PH), pulmonary veno-occlusive disease (PVOD) is devastating and life-threatening disease without effective therapy. Hydrogen has been reported to exhibits antioxidant and anti-inflammatory effects in a rat model induced by monocrotaline of PH. In this study, we investigated the effects of inhaled hydrogen gas on the prevention and treatment of PVOD induced by mitomycin C (MMC) in rats.MethodsPVOD was induced in female Sprague-Dawley rats through intraperitoneal injection of MMC at a concentration of 3 mg·kg− 1·wk− 1 for 2 weeks. Inhalation of hydrogen gas (H2) was administered through a designed rat cage concurrently or two weeks after MMC administration. The severity of PVOD was assessed by using hemodynamic measurements and histological analysis. The expression levels of general control nonderepressible 2 (GCN2), nuclear factor erythroid 2-related factor-2 (Nrf2), heme oxygenase-1 (HO-1) and endothelial-to-mesenchymal transition (EndoMT) related proteins in lung tissue were measured. Levels of lipid peroxidation pro-inflammatory cytokines in serum were determined.ResultsInhaled H2 improved hemodynamics and right heart function, reversed right ventricular hypertrophy, and prevented pulmonary vessel reconstitution in both prevention and treatment approaches. It decreased malondialdehyde (MDA) levels in the serum and the expression of NADPH oxidase 1 (NOX-1) in lung tissue. It regulated Nrf2/HO-1 signaling pathway and anti-inflammatory factor GCN2 in lung tissue, accompanied by a decrease in macrophages and pro-inflammatory cytokines. Our data suggested that H2 inhalation effectively countered EndoMT induced by MMC, as evidenced by the detection of endothelial markers (e.g., VE-cadherin and CD31) and mesenchymal markers (e.g., vimentin and fibronectin). Further research revealed that H2 preserved p-Smad3 and induced p-Smad1/5/9.ConclusionInhalation of H2 effectively inhibits the pathogenesis of PVOD induced by MMC in rats. This inhibitory effect may be attributed to the antioxidant and anti-inflammatory properties of H2.

At-admission prediction of mortality and pulmonary embolism in an international cohort of hospitalised patients with COVID-19 using statistical and machine learning methods

By September 2022, more than 600 million cases of SARS-CoV-2 infection have been reported globally, resulting in over 6.5 million deaths. COVID-19 mortality risk estimators are often, however, developed with small unrepresentative samples and with methodological limitations. It is highly important to develop predictive tools for pulmonary embolism (PE) in COVID-19 patients as one of the most severe preventable complications of COVID-19. Early recognition can help provide life-saving targeted anti-coagulation therapy right at admission. Using a dataset of more than 800,000 COVID-19 patients from an international cohort, we propose a cost-sensitive gradient-boosted machine learning model that predicts occurrence of PE and death at admission. Logistic regression, Cox proportional hazards models, and Shapley values were used to identify key predictors for PE and death. Our prediction model had a test AUROC of 75.9% and 74.2%, and sensitivities of 67.5% and 72.7% for PE and all-cause mortality respectively on a highly diverse and held-out test set. The PE prediction model was also evaluated on patients in UK and Spain separately with test results of 74.5% AUROC, 63.5% sensitivity and 78.9% AUROC, 95.7% sensitivity. Age, sex, region of admission, comorbidities (chronic cardiac and pulmonary disease, dementia, diabetes, hypertension, cancer, obesity, smoking), and symptoms (any, confusion, chest pain, fatigue, headache, fever, muscle or joint pain, shortness of breath) were the most important clinical predictors at admission. Age, overall presence of symptoms, shortness of breath, and hypertension were found to be key predictors for PE using our extreme gradient boosted model. This analysis based on the, until now, largest global dataset for this set of problems can inform hospital prioritisation policy and guide long term clinical research and decision-making for COVID-19 patients globally. Our machine learning model developed from an international cohort can serve to better regulate hospital risk prioritisation of at-risk patients.

Clinical Profile and Echocardiographic Evaluation of COPD Patients Admitted in a Tertiary Care Hospital

Introduction: Chronic obstructive pulmonary disease (COPD) ranks as the fourth leading cause of global mortality, with anticipated increases in prevalence and mortality in the future. The Global Initiative for Chronic Obstructive Lung Disease (GOLD) highlights the importance of considering COPD diagnosis in patients with relevant symptoms or risk factors, confirmed through spirometry. While COPD is preventable and treatable, it often presents with significant extra-pulmonary effects, particularly cardiac manifestations. Echocardiography offers a rapid, noninvasive method to assess these cardiac complications. Objective: This study aimed to investigate the clinical profiles and echocardiographic changes in COPD patients and their correlation with disease severity. Method: Conducted as an observational cross-sectional study, the research took place in the indoor departments of Medicine and Respiratory Medicine at Sir Salimullah Medical College &amp; Mitford Hospital, Dhaka, between May 25th, 2017, and November 24th, 2017; enrolling 105 diagnosed COPD patients aged e”18 years. Data collection involved a structured questionnaire covering socio-demographic details, risk behavior, and respiratory complaints. Physical examinations, spirometry, and echocardiography were conducted for diagnosis, severity grading, and cardiac evaluation, respectively. Statistical analysis employed SPSS software (version-22), presenting results through frequency, percentage, tables, graphs, and figures. Result: The study population was predominantly male (88.6%) with a mean age of 64.1 years. Most patients (94.2%) were smokers with a mean pack-year history of 22.03. All patients presented with cough and shortness of breath, and 88.5% had wheezing. Spirometry revealed moderate COPD in 40% of patients, with a distribution across all severity grades. Echocardiography showed abnormalities in 52.4% of patients, with tricuspid regurgitation, pulmonary hypertension, and right ventricular dilatation being the most frequent findings. A significant correlation was observed between C OPD severity and the presence of these echocardiographic abnormalities. Conclusion: Clinical examination unveiled common respiratory findings, while echocardiography demonstrated diverse cardiac manifestations in COPD patients. A significant proportion of patients exhibited normal findings on X-ray and echocardiography. The study highlights the prevalence of moderate COPD severity and the association between very severe COPD and specific cardiac complications, emphasizing the importance of comprehensive assessment and management strategies for COPD patients. J MEDICINE 2024; 25: 115-120

A systems approach to developing user requirements for increased pulmonary rehabilitation uptake by COPD patients

Chronic Obstructive Pulmonary Disease is a progressive lung disease associated with anxiety, depression, and reduced health-related quality of life. Pulmonary rehabilitation (PR) is a cost-effective and transformative treatment, but 31% of referred patients do not take up their PR appointment. The study aimed to develop user requirements for an intervention to increase PR uptake. A systems approach, the Engineering Better Care framework, was used to develop a system map of the PR pathway, translate evidence-based user needs into user requirements, and validate the user requirements in a stakeholder workshop. Eight user requirements addressed patient and health care practitioner needs to understand what PR entails, understand the benefits of PR and have positive conversations about PR to address patient concerns. The solution-independent user requirements can be applied to the development of any intervention sharing similar goals. The study demonstrates potential in taking a systems approach to more challenges within respiratory medicine.

The Role of Artificial Intelligence in Pulmonary Medicine: Transforming Diagnosis, Treatment, and Research

The Role of Artificial Intelligence in Pulmonary Medicine: Transforming Diagnosis, Treatment, and Research

Sarcoidosis-associated pulmonary hypertension due to pulmonary arteries stenosis – a case report

BackgroundSarcoidosis-associated pulmonary hypertension (SAPH) is listed in Group 5 of the clinical classification of pulmonary hypertension, due to its complex and multifactorial pathophysiology. The most common cause of SAPH development is advanced lung fibrosis with the associated destruction of the vascular bed, and/or alveolar hypoxia. However, a substantial proportion of SAPH patients (up to 30%) do not have significant fibrosis on chest imaging. In such cases, the development of pulmonary hypertension may be due to the lesions directly affecting the pulmonary vasculature, such as granulomatous angiitis, pulmonary veno-occlusive disease, chronic thromboembolism or external compression of vessels by enlarged lymph nodes. Based on the case of a 69-year-old female who developed SAPH due to pulmonary arteries stenosis, diagnostic difficulties and therapeutic management are discussed.Case presentationThe patient, non-smoking female, diagnosed with stage II sarcoidosis twelve years earlier, presented with progressive dyspnoea on exertion, dry cough, minor haemoptysis and increasing oedema of the lower limbs. Computed tomography pulmonary angiography (CTPA) showed complete occlusion of the right upper lobe artery and narrowing of the left lower lobe artery, with post-stenotic dilatation of the arteries of the basal segments. The vascular pathology was caused by adjacent, enlarged lymph nodes with calcifications and fibrotic tissue surrounding the vessels. Pulmonary artery thrombi were not found. The patient was treated with systemic corticosteroid therapy and subsequently with balloon pulmonary angioplasty. Partial improvement in clinical status and hemodynamic parameters has been achieved.ConclusionsAn appropriate screening strategy is required for early detection of pulmonary hypertension in sarcoidosis patients. Once SAPH diagnosis is confirmed, it is crucial to determine the appropriate phenotype of pulmonary hypertension and provide the most effective treatment plan. Although determining SAPH phenotype is challenging, one should remember about the possibility of pulmonary arteries occlusion.