An observational study in Pneumonia, Community-Acquired, COVID-19 Pneumonia and Cardiovascular Diseases, sponsored by Hellenic Institute for the Study of Sepsis. Recruiting at 19 sites in Greece. Open to participants aged 18 Years and older, including healthy volunteers. Per ClinicalTrials.gov, last updated 2026-11-06.
Sponsored by Hellenic Institute for the Study of Sepsis · Observational
Pneumonia, which can be acquired in the community (including influenza and COVID-19), is a leading cause of mortality. The risk of severe cardiovascular diseases events (stroke, myocardial infarction, pulmonary embolism) increases after infections, but causal mechanisms are not understood yet. There is an essential need for improved understanding of the relationship between pneumonia and cardiovascular diseases and early identification of patients at risk of cardiovascular events to develop tailored therapies.
The overall concept underpinning "Homi-lung" is to investigate the time course of host-microbiome interactions during \& after pneumonia to i) understand the causal relationship between trained immunity, microbiome dysbiosis and cardiovascular and respiratory diseases (CVRD) progressions, ii) define endotypes of pneumonia associated with response to treatment \& CVRD history; iii) develop biomarkers to predict the individual response to the treatment \& CVRD progression, and iv) preclinically validate therapeutical approaches for CVRD during \& after pneumonia.
Post-acute pneumonia syndrome People believe that there is a "modern pandemic" beyond the pandemic. This is called the post-acute COVID syndrome (PACS), and it is a constellation of symptoms and medical entities which emerge after acute infection by the new coronavirus SARS-CoV-2 (COVID-19). However, in this definition, people are attracted by the apparent symptomatology and ignore that long-term complications may be even more severe. In this regard, it is reported that the incidence of type 2 diabetes mellitus (T2DM) is increasing almost 1.56-fold after acute COVID-19, which may happen without any symptoms. The increase in the incidence of T2DM is supported by two large-scale meta-analyses involving more than 4.2 million patients during the post-COVID-19 follow-up period.
Recent evidence from the Hellenic Sepsis Study group suggests that circulating monocytes of patients after the acute COVID- 19 illness have increased ability for the biosynthesis of interleukin (IL)-1β, many of them do not present symptoms of PACS.
Taking into consideration the importance of IL-1β for the pathogenesis of T2DM through the destruction of β-pancreatic cell islets, it is evident that increased cardiometabolic (CV) risk may also be a counterpart of PACS. In the CANTOS randomized clinical trial published several years ago, survivors of a first myocardial infarct were randomized to treatment with a placebo or canakinumab, one monoclonal antibody targeting IL-1β, for five years. Results showed that anti-IL-1 treatment decreased by 15% the incidence of secondary cardiovascular events outscoring excess IL-1β production as a driver of CV risk. Consequently, it is reasonable to hypothesize that COVID-19 survivors who over-produce IL-1β may present with long-term CV events.
Beyond state of the art: respiratory dysbiosis, a complete reappraisal of the physiopathology of pneumonia for innovative treatments Healthy distal airways have long been considered sterile, and pneumonia was thus supposed to be caused by the contamination of the lungs by exogenous virulent pathogens (for CAP) or during micro- aspirations of the digestive contents in comatose patients (for HAP). Based on this physiopathology, numerous strategies to rapidly eliminate pathogens are recommended and widely used in Europe and worldwide. However, the limits of CAP and HAP treatments which increase bacterial or viral clearance, are highlighted in almost all randomized trials evaluating antibiotics or antiviral drugs in which the rates of treatment failure commonly exceed 30%, and by the 30%-rate of patients presenting with prolonged symptoms after pathogen clearance. A reappraisal of the physiopathology of pneumonia seemed necessary to overcome the relative failure and improve patient outcomes.
We have demonstrated that pneumonia outcomes depend on pathogen clearance and restoring healthy interactions between a weakened microbiome and altered immunity. Since CVRD progression is associated with disruption of the host-microbiome interactions, we hypothesize that the dysbiosis induced by pneumonia participates in the CVRD progression reported after the infection recovery. We thus propose to perform i) a longitudinal follow-up of host-microbiome interactions in large cohorts of patients cured of pneumonia to demonstrate clinically meaningful associations between immune reprogramming, microbiome dysbiosis and CVRD progression, and ii) preclinical investigations in calibrated mice models to demonstrate causality between dysbiosis and CVRD progression.
It is now well established that airways harbour a rich and diverse microbiome in healthy controls. Respiratory tract invasion by pathogens rapidly causes a loss of microbiome diversity and an impoverishment of host-microbiome interactions. These respiratory microbiome alterations play an essential role in the development of lung inflammation during pneumonia and reflect variation in baseline lung innate immunity. In published studies of mechanically ventilated patients, it has been demonstrated that lung microbiota are correlated with alveolar inflammation and that disruption of the gut microbiome (via anti-anaerobic antibiotics) increases patients risk of prolonged mechanical ventilation and mortality. These studies demonstrate the clinical significance of the microbiome in recovery from lung injury. Alterations of the gut microbiome derived metabolites also participate in the long-term immune reprogramming observed after sepsis.
In the healthy state, respiratory mucosal immunity actively controls the commensal bacterial agents in the airways. Numerous studies have revealed profound immune alterations in septic patients, considered immunocompetent" at the time of hospitalization. Partner Nantes Université has demonstrated that pneumonia induces prolonged immune reprogramming, characterized by the formation of paralyzed dendritic cells (DCs) and low phagocytic alveolar macrophages (MAC), that lasts for months in humans and is associated with prolonged susceptibility to bacterial and viral respiratory infections. These results demonstrate that the required immune response to contain respiratory pathogens and interact with the microbiome is rapidly dampened during pneumonia and that this immune reprogramming lasts for years.
Critically ill patients are highly variable in their recovery from lung injury. Much of this variation is attributable to the differential recovery of alveolar epithelial cell integrity and function. An improved understanding of lung epithelial recovery will be necessary to identify therapeutic targets for resolving lung injury and preventing CVRD progression. Lung epithelial cells are subject to constant exposure to 1) microbiota within the respiratory tract and 2) metabolites and translocated bacterial products from the lower gut microbiome. Yet the role of the microbiome in alveolar epithelial recovery is undetermined.
As a summary, we propose a reappraisal of the physiopathology of pneumonia based on the concept of dysbiosis between a weakened microbiome and sepsis-induced immunosuppression, which have the potential to explain the prolonged susceptibility to non-communicable diseases, notably by sustaining epithelial injuries.
Role of host-microbiome interactions in CVRD progression Current pharmaceutical interventions designed to slow the progression of atherosclerosis focus almost exclusively on reducing plasma cholesterol levels. However, clinical and experimental data support an additional critical role for inflammation in atherothrombosis. Notably, inflammation inhibition targeting the central NLRP3 inflammasome to IL-1 to IL-6 pathway of innate immunity is an emerging method for atherosclerosis treatment and prevention. Macrophage accumulation within the vascular wall is a hallmark of atherosclerosis, and in atherosclerotic lesions, macrophages respond to various environmental stimuli, such as modified lipids and cytokines. We have demonstrated that trained immunity develops early during pneumonia, correlates with the inflammatory response, and can help to predict long-term outcomes after viral pneumonia.
This innate immune reprogramming, lasts for months after sepsis recovery and is characterized by exacerbated inflammatory response and prolonged decrease phagocytic activity of monocytes and macrophages during secondary immune stimulation. We thus propose that the functional reprogramming of monocytes and macrophages observed after pneumonia, can alter the control of atherosclerosis plaques, increasing the risk of major CVD events. The gut microbiome has also emerged as a central factor affecting type 2 diabetes, obesity and the progression of atherosclerotic cardiovascular disease.
Integration of host-microbiome interactions to model the response to pneumonia and identify patients at risk of unfavourable outcomes early Each patient likely responds differently to therapeutic intervention and might recover differently after pneumonia. Indeed, some subgroups of patients suffer rapid CVRD progression, and others return to baseline conditions. Several biomarkers have been associated with pneumonia outcomes, but none have reached the accuracy required for clinical implementation. This is mainly because they are usually developed in small mono-centre cohorts and analyzed separately in the microbiome and host status. So, pneumonia treatments and rehabilitation care are "one-fits-all patients" approach leading to a large proportion of treatment failures and CVRD progression.
There is a critical need for reliable biomarkers for the stratification of patients predicting therapy success/failure and risk of CVRD progression/severe. The gold standard to reach these objectives is to use large cohorts of patients, bar coding of the samples, and high-throughput analysis followed by unbiased algorithm-guided analysis. In this setting, the description that the integration of the host response and the microbiome composition have a fair accuracy for the diagnosis of pneumonia demonstrates the potential of protocols investigating the host/microbiome interactions for the development of personalized treatment for respiratory infections.
The development and validation of endotypes to better understand the functional mechanisms associated with CVRD progression will help clinicians to adapt treatment and better prevent these conditions. The definition of phenotypes will also help identify patients at risk early. We thus propose to combine host background (sex/gender, age, ethnicity, medical history and genetic susceptibility, vaccination), CVRD risk factors (dyslipidemia, diabetes, obesity), inflammation and soluble mediators (metabolome, cytokines), immune status (epigenetic regulation) and microbiome composition during and after pneumonia to capture the complexity of the hostmicrobiome interaction time course and define endotypes and phenotypes associating pneumonia with CVRD.
324 studies on the registry are indexed under Community-Acquired Pneumonia; 77 are open to participants now.
This study's planned enrollment of 650 is close to the median of 650 across 111 observational studies indexed under Community-Acquired Pneumonia.
Browse Community-Acquired Pneumonia studies →Hellenic Institute for the Study of Sepsis is the lead sponsor of 32 studies on the registry; 7 are open to participants now.
Counted across the registry records on this site, refreshed daily.
The study needs to enroll four groups of patients to cover the magnitude of the spectrum of community-acquired pneumonia and enroll the required controls:
Go through the criteria one by one — yes, no or not sure — and take the list to your doctor or the study team. Kept in this browser only.
Group A (healthy controls)
Group B (CVRD controls)
Group C (COVID-19 survivors)
Group D (sCAP survivors)
Exclusion Criteria:
Group A (healthy controls)
Group B (CVRD controls)
Group C (COVID-19 survivors)
Group D (sCAP survivors)
Underlined terms in the criteria open these too. Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
Weight in kilograms divided by height in metres squared. Example: 70 kg and 1.75 m gives 70 ÷ (1.75 × 1.75) ≈ 22.9.
What counts as overweight or obesity differs between countries (some use lower cut-offs), so go by the range the study states.
The New York Heart Association’s four classes of how much heart failure limits physical activity.
Studies set their own limit — many outside heart failure leave out class III–IV, while heart failure studies may ask for a particular class. Check the class this study names.
BMI (body mass index)
Weight in kilograms divided by height in metres squared. Example: 70 kg and 1.75 m gives 70 ÷ (1.75 × 1.75) ≈ 22.9.
What counts as overweight or obesity differs between countries (some use lower cut-offs), so go by the range the study states.
Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
NYHA class (heart failure)
The New York Heart Association’s four classes of how much heart failure limits physical activity.
Studies set their own limit — many outside heart failure leave out class III–IV, while heart failure studies may ask for a particular class. Check the class this study names.
Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
Controls with no or one comorbidity, predisposing to significant CV events and without a medical history of severe pneumonia.
Other: Blood samples and Oropharyngeal swab
Controls with comorbidities predisposing to major CV events and without a medical history of severe pneumonia
Other: Blood samples and Oropharyngeal swab · Other: Six-minute walk test, Spirometry, ECG, Heart ultrasound and cardiopulmonary exercise stress testing, Completion of questionnaires of symptoms
Patients cured of acute COVID-19
Other: Blood samples and Oropharyngeal swab · Other: Six-minute walk test, Spirometry, ECG, Heart ultrasound and cardiopulmonary exercise stress testing, Completion of questionnaires of symptoms
Patients cured of severe community-acquired pneumonia
Other: Blood samples and Oropharyngeal swab · Other: Six-minute walk test, Spirometry, ECG, Heart ultrasound and cardiopulmonary exercise stress testing, Completion of questionnaires of symptoms
Blood samples: EDTA-plasma (proteome, metabolome and lipidome) and PBMCs (transcriptome, epigenome, immune-phenotype and genetic polymorphism)
* Spirometry for forced expiratory volume in the first, second, total lung capacity and diffusion capacity of carbon monoxide. * ECG, Heart ultrasound and cardiopulmonary exercise stress testing: * NYHA * Rhythm or conduction abnormality (yes/no) * Left ventricular ejection fraction (%) * VO2Max
The first primary outcome is the rates of major cardiovascular disease event at 6 months.
Major CVD events are all-cause mortality, stroke, non-fatal acute coronary syndrome, pulmonary embolism or venous thrombosis
Time frame: From enrollment to Month 6.
The second primary endpoint is poor cardiorespiratory fitness at 36 months.
Poor fitness is a VO2max lower than normal values for age.
Time frame: From enrollment to Month 36.
Rates of unplanned hospitalisation
Rates of unplanned hospitalisation
Time frame: From enrollment to Month 36.
Rates of COPD exacerbation, hospitalization for respiratory failure and/or respiratory-related mortality at 3 years
Rates of COPD exacerbation, hospitalization for respiratory failure and/or respiratory-related mortality at 3 years
Time frame: From enrollment to Month 36.
Rates of secondary episodes of pneumonia, the incidence of non-respiratory infections
Rates of secondary episodes of pneumonia, the incidence of non-respiratory infections
Time frame: From enrollment to Month 36.
The rates of major cardiovascular disease event and of poor cardiorespiratory fitness
The rates of major cardiovascular disease event at 6 months and of poor cardiorespiratory fitness at 36 months according to the microbiology of sCAP (viral vs bacterial vs mixed etiology)
Time frame: At 6 and 36 months
The rates of major cardiovascular disease event and of poor cardiorespiratory fitness
The rates of major cardiovascular disease event at 6 months and of poor cardiorespiratory fitness at 36 months according to the antibiotic treatments for sCAP
Time frame: At 6 and 36 months
Changes in health-related quality of life (HRQoL)
Changes in health-related quality of life (HRQoL) from six (M6) to eighteen months (M18) after hospital discharge measured with the Short Form (SF)-36 scale validated in Greek and Spanish
Time frame: From six (M6) to eighteen months (M18) after hospital discharge
Changes in anxiety and depression
Changes in anxiety and depression from M6 to M18, measured with the Hospital Anxiety and Depression Scale (HADS) validated in Greek and Spanish
Time frame: From Month 6 to Month 18
Changes in subjective well-being
Changes in subjective well-being from M6 to M18 measured with the Satisfaction With Life Scale (SWLS) validated in Greek and Spanish.
Time frame: From Month 6 to Month 18
New metabolic disease
New metabolic disease, as evaluated by laboratory tests: diabetes (HbA1c \> 6.5%), dyslipidemia, denutrition (pre-albumin and albumin blood levels) at hospital discharge, M6 and M18
Time frame: At hospital discharge (i.e. an average of 1 Month after enrollment), Month 6 and Month18
Distance at the 6-min walk-test
Distance at the 6-min walk-test at hospital discharge, M6 and M18
Time frame: At hospital discharge (i.e. an average of 1 Month after enrollment), Month 6 and Month18
Mean values of lung functions
Mean values of lung functions (maximum expiratory volume per second, vital capacity, expiratory reserve volume and inspiratory reserved volume, DLC50) at hospital discharge, M6 and M18
Time frame: At hospital discharge (i.e. an average of 1 Month after enrollment), Month 6 and Month18
Cardiopulmonary exercise stress testing
Cardiopulmonary exercise stress testing: VO2Max at hospital discharge, M6 and M18
Time frame: At hospital discharge (i.e. an average of 1 Month after enrollment), Month 6 and Month18
ECG: Percentages of patients with rhythm cardiac alterations, repolarisation abnormality
ECG: Percentages of patients with rhythm cardiac alterations, repolarisation abnormality at hospital discharge, M6 and M18
Time frame: At hospital discharge (i.e. an average of 1 Month after enrollment), Month 6 and Month18
Mean values of left ventricular ejection fraction
Mean values of left ventricular ejection fraction at hospital discharge, M6 and M18
Time frame: At hospital discharge (i.e. an average of 1 Month after enrollment), Month 6 and Month18
From the registry record's own update history. This site started tracking changes on Sep 25, 2026; for anything earlier, see the record history on ClinicalTrials.gov ↗
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