UNIverse - Public Research Portal
Profile Photo

Prof. Dr. med. Jörg Leuppi

Department of Clinical Research
Profiles & Affiliations

General Internal Medicine especially Respiratory Medicine

 Area of Research

 

Our main areas of interest and expertise relate to respiratory physiology and obstructive lung diseases, in particular asthma and chronic obstructive pulmonary disease (COPD). Our clinical research also encompasses clinical implications of airway hyperresponsiveness. The approach of our research is multidisciplinary and so are the qualifications and areas of expertise of our team members. We have and encourage close collaboration between general internists, respiratory physicians, clinical investigators, health scientists, public health specialists as well as pharmaceutical scientists and experts in the field of family medicine. Our research group has focused on patient-centered care and translational research with the aim to close the gap between academic research and daily clinical practice. The concept behind this is that provision of optimal treatment is not only about short-term improvement in patients’ clinical conditions and quality of life, but also about reducing long-term side-effects of treatments to a minimum. As such, our goal is to improve diagnostic accuracy as well as to deliver optimized healthcare to patients with cardiopulmonary diseases.


Our research group leads the first and largest COPD cohort in Switzerland as well as the Swiss Severe Asthma Registry. In the COPD cohort, general practitioners and respiratory physicians play a key role, because they enter data on their patients’ routine examinations anonymously into a centralized electronic database. We are particularly interested in evaluating physicians’ adherence to guidelines as well as prediction and early diagnosis of COPD-exacerbations. With the Swiss Severe Asthma Registry, we are focusing on factors associated with asthma control. More than 400 patients with severe asthma have been included. The use of biologicals clearly show an improvement in asthma control and reduction of asthma exacerbations.

 

Further, we are investigating - retrospectively as well as in randomized clinical trials - aspects of "Smarter Medicine”, such as management of general internal medical conditions in patients with chronic lung diseases (for example diabetes) focusing especially physicians’ adherence to national and international guidelines and factors influencing length of stay, rehospitalisation and mortality.


 


National Collaborations


•      Prof. Dr. med. Andreas Zeller, University Center for Family Medicine, Basel

•      Prof. Dr. med. Maria Wertli Kantonsspital Baden

•      Prof. Dr. med. Michael Brändle, Kantonsspital St. Gallen

•      Prof. Dr. med. Sabina Hunziker Schütz, MPH, University Hospital Basel

•      Prof. Dr. med. Drahomir Aujesky, Inselspital Bern

•      Prof. Dr. med. Mirjam Christ-Crain, University Hospital Basel



Konsortium im Rahmen des Swiss Severe Asthma Registry


•      Inselspital Bern (Dr. med. Nikolay Pavlov)

•      Kantonsspital St. Gallen (Dr. med. Lukas Kern)

•      Universitätsspital Zürich (Prof. Dr. med. Christian Clarenbach)

•      Kantonsspital Graubünden (PD Dr.med. Tsogyal Latshang/ Dr. med. Thomas Rothe)

•      EOC Lugano ( Dr. med. Pietro Gianella)

•      HVS Sion (Prof. Dr. med. Pierre Olivier Bridevaux)

•      HUG Genève (Dr. med. Florian Charbonnier)

•      CHUV Lausanne (Prof. Dr. med. Christophe von Garnier)

•      RhNE Neuchâtel (Prof. Dr. med. Jean-Marc Fellrath)

 

 

International Collaborations


•      SHARP- Severe Heterogeneous Asthma Research collaboration

•      Dr. Prashant Chhajed, Mumbai, India

•      Dr. John Brannan, Newcastle, Australia

•      Dr. Herbert Bachler, Tiroler Gesellschaft für Allgemeinmedizin, Austria

Selected Publications

Boesing, Maria, Ottensarendt, Nicola, Lüthi-Corridori, Giorgia, & Leuppi, Jörg D. (2023). The Management of Acute Exacerbations in COPD: A Retrospective Observational Study and Clinical Audit [Journal-article]. Journal of Clinical Medicine, 13(1), 19. https://doi.org/10.3390/jcm13010019

URLs
URLs

Leuppi, Jörg D., Schuetz, Philipp, Bingisser, Roland, Bodmer, Michael, Briel, Matthias, Drescher, Tilman, Duerring, Ursula, Henzen, Christoph, Leibbrandt, Yolanda, Maier, Sabrina, Miedinger, David, Müller, Beat, Scherr, Andreas, Schindler, Christian, Stoeckli, Rolf, Viatte, Sebastien, von Garnier, Christophe, Tamm, Michael, & Rutishauser, Jonas. (2013). Short-term vs conventional glucocorticoid therapy in acute exacerbations of chronic obstructive pulmonary disease: the REDUCE randomized clinical trial. Journal of the American Medical Association, 309(21), 2223–2231. https://doi.org/10.1001/jama.2013.5023

URLs
URLs

Leuppi JD, Salome CM, Jenkins CR, Anderson SD, Xuan W, Marks GB, Koskela H, Brannan JD, Freed R, Andersson M, Chan HK, & Woolcock AJ. (2001). Predictive markers of asthma exacerbation during stepwise dose reduction of inhaled corticosteroids. American journal of respiratory and critical care medicine, 163(2), 406–412. https://doi.org/10.1164/ajrccm.163.2.9912091

URLs
URLs

Selected Projects & Collaborations

Project cover

SHARE: Selecting and sharing Hospital dAta for Research and Evidence-based medicine

Research Project  | 2 Project Members

Enhancing Personalized Healthcare and Clinical Research through Interoperable Data Management: A Focus on Symptoms Management


BACKGROUND

 

In healthcare organizations and hospitals in particular, patient medical data are stored in a multitude of heterogeneous systems and formats. These systems are often not interconnected, and information is not transferred across interfaces. The lack of flexibility and the difficulties involved in current data systems not only impede the quality of health care providers’ work and ability to deliver personalized health care but also limit research opportunities with large amounts of data.

Existing research emphasizes the critical need for interoperability between patient information systems to enhance personalized healthcare and facilitate clinical research (1–3).

To help solve this problem at the Cantonal Hospital of Baselland (KSBL) we have developed a new concept for data selection and extraction based on an innovative approach to data management. We will use the DAWIMED software developed by ID-Berlin (main company) and ID-Suisse (Swiss subsidiary) to enable interoperability between patient information systems and make routine clinical data accessible for clinical research and quality management.

This project aims to use this innovative approach to improve personalized healthcare and clinical research, with a specific focus on symptom management.

The project includes two clinically driven research studies:

1.    Assessment of the Management of Patients Admitted with Dyspnea as Their Chief Complaint

2.    Machine Learning to Predict the Cause of Dyspnea Based on Parameters Available at Admission



RESEARCH STUDIES

  

1.    Assessment of the Management of Patients Admitted with Dyspnea as Their Chief Complaint

Dyspnea, or shortness of breath, is a prevalent symptom leading to numerous emergency department (ED) visits and hospital admissions. It can result from various conditions, including cardiac and pulmonary diseases, as well as other less common causes. Dyspnea's diverse causes necessitate a comprehensive and prompt assessment using medical history, physical exams, biomarkers, and radiological evaluations. Despite its prevalence, there is limited data on its frequency and causes in Switzerland, and patient data is often fragmented across unstructured paper documents and digital systems. Identifying relevant patient data from mixed formats (paper and digital) is complex and often requires time-consuming manual searches.

 

The study aims to:

 

·        Describe the management of patients presenting with dyspnea at the KSBL ED.

·        Assess adherence to the medStandards algorithm for dyspnea management.

Significance: Understanding and improving the management of dyspnea can enhance patient outcomes, reduce in-hospital mortality, and streamline ED processes.

 

2.    Machine Learning to Predict the Cause of Dyspnea Based on Parameters Available at Admission

Dyspnea has multifactorial causes, ranging from common conditions like respiratory infections and heart failure to rarer causes like anaphylaxis or metabolic disorders. The wide variability in patient demographics, comorbidities, and clinical presentations complicates the diagnostic process. Distinguishing between cardiac and pulmonary causes is particularly difficult due to overlapping symptoms. Accurate and rapid diagnosis is crucial for effective treatment but is often challenging due to the symptom's urgency and diverse etiologies.

The study aims to:

  • Identify parameters collected during the initial ED assessment (e.g., symptoms, vital signs, medical history) that predict the underlying cause of dyspnea.
  • Develop predictive scores or digital tools to assist physicians in making prompt and accurate diagnoses.

Significance: By leveraging machine learning, the study seeks to enhance diagnostic accuracy, reduce the need for extensive testing, and improve the timeliness and effectiveness of dyspnea management in the ED. This approach can lead to better patient outcomes and more efficient use of resources.




Project cover

QUA-DIT - Quality evaluation of hospital care through audits

Research Project  | 3 Project Members

Background: The recent increasing complexity in internal medicine and the concurrent demand for improving quality while cutting down resources represent a major challenge for healthcare providers. Disease-specific clinical guidelines for diagnostic and therapeutic management provide support in this demanding situation. However, according to previous studies, guideline adherence is often poor in clinical practice. Clinical audits are a powerful instrument in the evaluation of guideline adherence and can ultimately improve quality of hospital care.

Objectives: With the QUA-DIT project we seek to identify disease-specific areas of in-hospital management where diagnostic and/or therapeutic guideline-adherence is poor. Furthermore, we plan to investigate the effect of guideline-adherence on patient outcome related quality indicators. By establishing a sustainable quality control program addressing these areas, we intend to lay the foundation for the overall improvement of hospital care.

Methods: The QUA-DIT project consists of seven clinically driven audits in typical acute diagnoses in the department of internal medicine at the Cantonal Hospital Baselland. Recent clinical routine data concerning diagnostic workup, treatment, and other measures of care will be collected and descriptively compared to the established national and international disease-specific guidelines. Ultimately, association of guideline-adherence with quality indicators mortality, length of hospital stay, and rehospitalization will be assessed by multivariable regression models. We expect to include data of 2410 patients into our analyses.

Relevance: Establishing a series of clinical audits with the same methodology and the aim to improve quality in different fields of internal medicine is an innovative approach. Based on the audit findings, we plan to implement several measures to achieve improvement in the evidence-based management of our patients. Being transparent about the results with the intention of publication is a way of creating awareness in the internal medicine community and may serve as a motivation for other hospitals to follow the example. The QUA-DIT project represents a significant step for improvement of the overall healthcare system, and ultimately for the health of the population.

Project cover

Swiss Severe Asthma Register (SAR)

Research Project  | 2 Project Members

Asthma is a chronic respiratory airway disease that affects more than 300 million people worldwide. Severe Asthma (SA) affects around 5-10% of all asthma patients yet accounts for half of the asthma related costs and carries a high burden of disease . Since the introduction of highly targeted treatments (monoclonal antibodies) in 2005, the treatment of severe asthma has been revolutionized. Nowadays, most of the patients with a severe asthma are treated with monoclonal antibodies. However, in Switzerland as in other countries, we have had only a little knowledge about the real-life situation of patients with SA, regarding long-term clinical management and therapeutic outcomes. Recognizing that knowledge gap, multiple countries, including Switzerland, have established national registries observing severe asthma and build up an international network of clinical registries.


The overall aim of this cohort is to gain comprehensive information about severe asthma in Switzerland, with the focus on the following:

  • Describing SA Patient characteristics in Switzerland
  • Treatment regimens over time
  • Clinical course of SA patients over time including changes and influencing factors of asthma related outcomes



Project cover

COPD-Management: A clinical epidemiological observation cohort study in primary care setting

Research Project  | 2 Project Members

The objective of this project is to establish a COPD cohort database to allow high quality research on diagnosis, treatment, complication and progression of COPD on long-term course.

Spirometry should be used consistently for the diagnosis and the monitoring of the development of the disease. Using collected information such as spirometric data, disease progression’s data and therapeutic measures should help improve the management and self-management of the patients.

Patients’ follow-up visits occurs at 6-month intervals; their demographic data, history, symptoms, examination status, medical treatment and exacerbation history is recorded.

Data is entered into an online database either by the physicians or by study team after receiving the collected data questionnaires.