[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-studies-list:{\"conditionNormalized\":\"chronic-lung-diseases\",\"overallStatus\":[\"RECRUITING\",\"AVAILABLE\",\"NOT_YET_RECRUITING\"],\"orderBy\":\"LastUpdateSubmitDate:desc\",\"size\":25,\"offset\":0}":3,"health-study-condition:chronic-lung-diseases":25},{"pageToken":4,"total":5,"offset":6,"count":5,"results":7},null,3,0,[8,41,68],{"id":9,"slug":10,"hasResults":11,"nctId":12,"briefTitle":13,"officialTitle":14,"acronym":15,"eligibilityCriteria":16,"healthyVolunteers":11,"sex":17,"minAge":18,"maxAge":4,"enrollmentInfo":19,"targetDuration":4,"studyType":22,"phases":4,"briefSummary":23,"conditions":24,"keywords":26,"overallStatus":29,"whyStopped":4,"lastUpdateSubmitDate":30,"lastUpdatePostDateStruct":31,"startDateStruct":34,"completionDateStruct":36,"leadSponsor":38,"locationsCount":4},"100641375","an-observational-study-into-antimicrobial-resistance-in-patients-with-a-chronic-lung-disease-100641375",false,"NCT07646691","An Observational Study Into Antimicrobial Resistance in Patients With a Chronic Lung Disease","Prospective Study of Antimicrobial RESIstance in Chronic Lung DiseasE","PRESIDE","Inclusion Criteria:\n\n* Presence of an underlying chronic lung disease (e.g. Bronchiectasis, COPD) stratified by colonisation status:\n\n  * Pseudomonas sp (n=30)\n  * Klebsiella sp (n=20)\n  * Haemophilus sp (n=20)\n  * E-coli sp (n=20)\n  * Stenotrophomonas sp (n=20)\n  * Staphylococcus sp (n=20)\n  * Other chronic colonisation (n=20)\n  * Not colonised with any bacterial pathogen (n=20)\n\nExclusion Criteria:\n\n* Inability to provide informed consent\n* Pregnancy\n* Medical instability preventing ability to attend for regular study visits at baseline.","ALL","18 Years",{"count":20,"type":21},170,"ESTIMATED","OBSERVATIONAL","Antimicrobial resistance (AMR) refers to the ability of microorganisms like bacteria, viruses, fungi and parasites to resist the effects of antimicrobial drugs (such as antibiotics) which are widely used as treatment. AMR poses an escalating global health threat, contributing to difficult-to-treat infections associated with increased disease spread, disability and death, as well as a substantial economic burden.\n\nIn chronic lung diseases, such as bronchiectasis, Cystic fibrosis or chronic obstructive lung disease (COPD), there is a higher risk of AMR due to the exposure to frequent or prolonged courses of antibiotics to treat recurrent lung infections and exacerbations (flares of the disease), to reduce lung inflammation or to control chronic infection within the lung with suppression of colonising microbes.\n\nMost data on AMR in chronic lung diseases derive from analysing pre-existing routinely collected health data collected on a national basis which is often incomplete. Hence a prospective study is crucial to better understand and address AMR in chronic lung diseases. Prospective studies follow patients forward in time, collecting data on outcomes and allowing researcher to observe the natural history of AMR development, monitor trends and evaluate interventions.\n\nThis multicentre prospective study, as part of the European Respiratory Society (ERS) Clinical Research Collaboration on Antimicrobial Resistance in Lung Disease (CRC - AMR Lung), aims to investigate the patterns of AMR in chronic lung diseases through a fully anonymous registry alongside a prospective sub-cohort study tracking individuals with chronic lung disease and known colonisation with high-priority AMR pathogens (microorganisms). This study will enable analysis of prevalence and burden of AMR within chronic lung disease alongside understand the genetic drivers of resistance, the link between the microbial genotype and antimicrobial resistance and how transmission of resistance occurs in chronic lung disease.",[25],"Chronic Lung Diseases",[27,28],"antimicrobial resistance","chronic lung disease","NOT_YET_RECRUITING","2026-06-17",{"date":32,"type":33},"2026-06-22","ACTUAL",{"date":35,"type":21},"2026-07-01",{"date":37,"type":21},"2028-12-01",{"name":39,"class":40},"Imperial College London","OTHER",{"id":42,"slug":43,"hasResults":11,"nctId":44,"briefTitle":45,"officialTitle":46,"acronym":4,"eligibilityCriteria":47,"healthyVolunteers":11,"sex":17,"minAge":18,"maxAge":4,"enrollmentInfo":48,"targetDuration":4,"studyType":22,"phases":4,"briefSummary":50,"conditions":51,"keywords":56,"overallStatus":29,"whyStopped":4,"lastUpdateSubmitDate":58,"lastUpdatePostDateStruct":59,"startDateStruct":61,"completionDateStruct":63,"leadSponsor":65,"locationsCount":67},"100640196","clinical-information-system-impact-on-hospitalized-patients-with-chronic-disease-100640196","NCT07609381","Clinical Information System Impact on Hospitalized Patients With Chronic Disease","Evaluating the Impact of Alberta Health Services' New Provincial Clinical Information System on Patient Outcomes and Experiences With Chronic Diseases - Study Protocol for a Multi-center Interrupted Time Series Analysis","Inclusion Criteria:\n\n* Adults aged 18 years or older at the time of hospital admission.\n* Residents of Alberta eligible to receive acute-care services in AHS facilities.\n* Hospitalized for any cause during the study period (5 years pre-implementation and 2 years post-implementation of the CIS).\n* Meet the validated case definition for one or more of the five key NCDs (diabetes mellitus, chronic kidney disease, coronary artery disease, heart failure, or chronic lung disease) based on ICD codes, laboratory measures, or pharmacy records during standardized lookback periods (up to 5 years for diagnoses; up to 1 year for labs\u002Fpharmacy).\n* Have a qualifying date for the NCD(s) that occurs prior to or during the index hospital admission.\n* Eligible for inclusion in the primary and patient experience outcomes if they survive to hospital discharge.\n* May enter multiple sub-cohorts if more than one NCD is present.\n\nExclusion Criteria:\n\n* Individuals younger than 18 years at the time of hospital admission.\n* Non-residents of Alberta or individuals not eligible for care within AHS facilities.\n* Hospitalizations that end in death (excluded from analyses of the primary outcome and patient experience measures).\n* Patients without evidence of any of the five key NCDs during the lookback period or at the index hospital admission.\n* Admissions outside the study period or admissions for which necessary administrative, laboratory, or pharmacy data are unavailable.",{"count":49,"type":21},124240,"This is a retrospective, observational study using routinely collected information collected by Alberta Health Services. The study will identify patients with chronic disease, defined by one or more of the following conditions; diabetes mellitus, heart failure, coronary artery disease, chronic kidney disease, or chronic lung disease. Adult residents of Alberta with a chronic disease of interest present upon hospital admission and who survive to hospital discharge will be included in the study cohort. The primary outcome will be the composite of hospital readmission or death within 30 days of discharge. Secondary outcomes will include components of the composite, length of stay, patient experiences related to their hospital to home transition of care, and processes of care. Multi-level interrupted time series analysis will be used to compare outcomes before versus after implementation of the Connect Care CIS.",[52,53,54,55,25],"Diabete Mellitus","Kidney Disease","Heart Failure","Coronary Artery Disease",[57],"Clinical Information System","2026-05-19",{"date":60,"type":33},"2026-05-27",{"date":62,"type":21},"2026-06-01",{"date":64,"type":21},"2027-12-31",{"name":66,"class":40},"University of Calgary",1,{"id":69,"slug":70,"hasResults":11,"nctId":71,"briefTitle":72,"officialTitle":73,"acronym":74,"eligibilityCriteria":75,"healthyVolunteers":11,"sex":17,"minAge":18,"maxAge":4,"enrollmentInfo":76,"targetDuration":4,"studyType":22,"phases":4,"briefSummary":78,"conditions":79,"keywords":4,"overallStatus":29,"whyStopped":4,"lastUpdateSubmitDate":85,"lastUpdatePostDateStruct":86,"startDateStruct":87,"completionDateStruct":88,"leadSponsor":90,"locationsCount":4},"100640455","clinical-utility-of-libs-multi-element-imaging-and-the-iff-algorithm-in-chronic-lung-diseases-100640455","NCT07597187","Clinical Utility of LIBS Multi-Element Imaging and the IFF Algorithm in Chronic Lung Diseases","Evaluation of the Clinical Utility of LIBS Multi-Element Imaging and the IFF Algorithm for the Etiological and Medico-Legal Management of Chronic Lung Diseases","PNEUMO-LIBS","Inclusion Criteria:\n\n* Adult patient aged 18 years or older.\n* Diagnosis or documented clinical suspicion of chronic lung disease, including interstitial lung disease, pulmonary granulomatosis such as sarcoidosis, or pulmonary emphysema.\n* Availability of a lung tissue biopsy sample obtained during routine medical care and stored as a formalin-fixed paraffin-embedded sample.\n* Sufficient medical record information to document the clinical context, occupational or environmental exposure history, smoking status, imaging, pathology reports, and other relevant routine-care data.\n* No documented objection to the secondary use of health data and biological samples for this research.\n\nExclusion Criteria:\n\n* Documented objection to participation in the study or to the secondary use of health data or biological samples for research.\n* Missing, unavailable, degraded, or technically unusable biopsy sample.\n* Insufficient medical record information to document the clinical context or exposure history.\n* Lung condition outside the scope of the study, such as isolated acute infection, isolated cardiac disease, or primary lung cancer.\n* Patient under legal protection when the applicable legal conditions for non-opposition cannot be fulfilled.",{"count":77,"type":21},70,"PNEUMO-LIBS is a multicenter, non-interventional observational study designed to evaluate whether multi-element tissue imaging by Laser-Induced Breakdown Spectroscopy (LIBS), combined with an artificial intelligence-based analysis tool called Interesting Features Finder (IFF), may help physicians better understand the possible causes of chronic lung diseases.\n\nThe study focuses on adult patients with chronic lung diseases for which a lung biopsy has already been performed as part of routine medical care. These diseases include diffuse interstitial lung diseases, pulmonary granulomatoses such as sarcoidosis, and emphysema, especially when an environmental or occupational exposure is suspected but not clearly demonstrated.\n\nSome chronic lung diseases may be influenced by inhaled mineral or metallic particles, such as silica, aluminum, titanium, or other metals. However, these exposures are often difficult to document at the individual patient level. Standard clinical, radiological, and pathological investigations do not usually provide direct information on the presence and distribution of such elements within lung tissue.\n\nLIBS is an imaging technique that can detect and map chemical elements directly in tissue samples, including archived formalin-fixed paraffin-embedded biopsy blocks. In this study, lung biopsy samples will be analyzed with LIBS to search for elemental signatures that may be compatible with occupational or environmental exposures. The IFF algorithm will then be used to help interpret the LIBS data and identify rare or unexpected elemental signals.\n\nThe study does not require any additional biopsy, blood test, imaging examination, treatment, or hospital visit for participants. It uses tissue samples and medical data already collected during routine care. The results of LIBS and IFF analyses will be presented to the treating physician or investigator, who will complete standardized online questionnaires at three time points: before receiving the LIBS results, after receiving the LIBS report, and after receiving the IFF-assisted interpretation.\n\nThe main objective is to assess the perceived clinical utility of LIBS imaging for physicians, particularly regarding etiological understanding, possible occupational disease recognition, and prevention-oriented reasoning. Secondary objectives include assessing the added value of the IFF algorithm and evaluating the feasibility of a centralized multicenter workflow for sample transfer, LIBS analysis, IFF processing, result reporting, and questionnaire completion.\n\nThe study aims to include approximately 70 patients across several French hospital centers. Its results may support the development of future diagnostic, occupational health, and environmental medicine approaches, without modifying the medical care of participants during the study.",[80,81,25,82,83,84],"Interstitial Lung Diseases (ILD)","Pulmonary Emphysema","Occupational Lung Diseases","Environmental Exposure","Occupational Exposure","2026-05-12",{"date":58,"type":33},{"date":35,"type":21},{"date":89,"type":21},"2027-07-01",{"name":91,"class":40},"University Hospital, Grenoble"]