Cohort of the Specialist Network Infectious Diseases (SNID)

Goethe University

Status: Not yet enrolling

Conditions: Infectious Diseases and Manifestations

Study type: Observational

Funder types: Other

Identifiers

NCT06879184

01KX2121 (Other Identifier)

SNID.msp.2025-01

Details and patient eligibility

About

This observational study aims to collect standardized clinical data and biosamples from adults in university hospitals across Germany. The main goals are to create a cohort that combines clinical data, pathogen samples, and biosamples, with consent for future research. A pre-screening program tracks infection-related hospitalizations, helping detect pathogen changes early and respond quickly. Participants will be recruited if they have respiratory, bloodstream, gastrointestinal, emerging, or central nervous system infections. Data and biosamples will be collected at the start and end of the hospital stay, with additional visits if needed.

Full description

As part of the European concept of ever-warm recruiting infrastructures in case of future public health hazards, but also as instrument for answering pressing questions in the field of major infectious diseases, the cohort of the Specialist Network Infectious Diseases (SNID) collects clinical patient data and biosamples in a standardized and quality-assured manner. In this sense, the SNID manifests itself as a structured data and decentralized biobank within the German Network University Medicine (NUM).

The main objectives of the SNID cohort are: 1) To collect clinical patient data and biosamples from major infectious diseases to accelerate translational and outcomes research with the aim of improving diagnosis and treatment strategies for future patients, 2) To establish pandemic preparedness by initiating and maintaining an ever-warm recruitment network in the field of infectious diseases, 3) To establish a sentinel programme to observe and monitor outbreaks of severe infections requiring hospitalization of patients.

The study will identify and recruit patients across different specific modules, each providing a sub-protocol to this master study protocol. These modules focus on major areas of infectious diseases ("entities") and will describe research questions and priorities as well as specific requirements for the observation of the respective affected patients. They will also denominate specific sub-types ("sub-entities") of these diseases that are or may become a focus of the SNID cohort. As an example, the module "respiratory infections" may have an entity "community-acquired pneumonia" that in turn may have sub-entities like "community-acquired pneumonia caused by legionella pneumophila".

A base of sociodemographic, epidemiologic, and clinical patient data is documented, including information on possible pre-existing conditions, medical diagnoses, and therapies.

The documentation is supplemented by residual or non-invasive biosampling, depending on the study tier. Three different tiers establish different levels of sampling and data collection in terms of frequency or depth of assessment. The Tiers have been adapted mainly from the International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC).

Tier 2: Serial collection of data and biosamples (additional non-invasive collection of biosamples and residual samples) at the baseline visit, once a week starting on day 3 until the final visit (corresponding to tier 2, sampling schedule 4 by ISARIC).

Tier 1: Collection of data and biosamples (additional non-invasive collection of biosamples and residual samples) at baseline visit and final visit (corresponding to tier 1 by ISARIC).

Tier 0: Only documentation of data and preservation of residual samples (routine clinical care) at baseline visit and final visit (corresponding to tier 0 by ISARIC).

For tier 1 and 2, additional non-invasive biosamples may be collected as part of the study. Non-invasive is defined as no new tissue penetration or other harm to the patient, allowing for swabbing, collection of spontaneously ejectable fluids/substances, or usage of permanent devices or non-invasive access to materials.

Enrollment: 15,000 estimated patients

Sex: All

Ages: 18+ years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• Fulfillment of all inclusion and no exclusion criteria for at least one module
• Ability to perform all baseline visit data and biosample collections according to the study requirements no later than 48 hours (with an additional 48-hour period for weekends) after fulfilling all study and specific module inclusion and exclusion criteria
• Signed informed consent form from all patients capable of giving consent and understanding all contents of the informed consent
• Age ≥ 18 years.

Exclusion criteria

There are no generic exclusion criteria in the master study protocol.

Trial design

15,000 participants in 5 patient groups

Module Bloodstream Infections

Description:

This sub-cohort focuses on the characterization of patients with both nosocomial and community-acquired bloodstream infections (BSI), serving as a foundation for future prospective randomized controlled clinical trials. The study will explore the evolution of BSI caused by multidrug-resistant or emerging pathogens and assess the prognosis and long-term outcomes of patients with BSI in Germany. Additionally, the cohort will evaluate patient- and pathogen-related risk factors associated with BSI.

Module Emerging Infections

Description:

The sub-cohort includes identifying and monitoring emerging pathogens to stay ahead of potential health threats, as well as developing a targeted screening program to detect infections caused by established pathogens like Mpox and Candida auris. The sub-cohort will also expand detection efforts to include pathogens not yet established in Germany, such as dengue virus, particularly in regions where this is not yet addressed by other modules. Additionally, the study team will perform an extended risk and exposure assessment for participating patients according to a defined protocol.

Module Respiratory Infections

Description:

The sub-cohort includes the creation of a searchable data and biosample repository for community-acquired respiratory tract infections (CARTI), not limited to pneumonia, enabling research on pathogens, clinical presentations, treatments, and patient outcomes. The biosamples will support future studies on pathogen identification, immune responses, and therapeutic efficacy. It will also document a range of pathogens, including emerging ones, and their frequencies across various CARTI, allowing analysis of associations with factors like age, gender, and comorbidities. Therapeutic data will track primary anti-infective treatments and adjustments based on resistogram results or clinical needs to assess their impact on outcomes. Key clinical outcomes, such as hospital mortality, length of stay, and complications, will be tracked to explore the effects of pathogen type, comorbidities, and treatments on patient outcomes.

Module Gastrointestinal Infections

Description:

The sub-cohort enrolls patients with bacterial, viral, and parasitic gastrointestinal (GI) infections identified through routine diagnostics, including those from hematology units screened for GI colonization with multidrug-resistant pathogens like MRGN or Vancomycin-resistant enterococci (VRE). A key focus is comparing GI pathogen translocation into the bloodstream with the bloodstream infection module, identifying risk factors and transmission routes. The study also assesses antimicrobial resistance (AMR) in enteric pathogens and colonizing enterobacteria, while systematically biobanking stool samples for resistance analysis and pathogen characterization, such as hypervirulent Clostridioides difficile ribotypes or Giardia intestinalis resistance mechanisms. Outcome data collection includes complex Salmonella infections and rare parasitic infections like Cryptosporidium parvum.

Module CNS Infections

Description:

The sub-cohort focuses on Central Nervous System (CNS) infections, which are a major public health concern due to their potential to cause severe neurological damage and high mortality. The goal of this project is to create a searchable dataset derived from routine clinical data and biobanked biosamples, which will facilitate future research into CNS infections. The dataset will support studies on pathogen profiles, diagnostic pathways, and clinical outcomes, helping to understand the underlying mechanisms of CNS infections. Additionally, the project aims to explore prognostic markers, treatment responses, and outcomes, with the goal of improving risk stratification and informing personalized treatment strategies for CNS infections.