Heart FailureIN-CluDiMINCT07660757
Epidemiological Cluster Evaluation in Patients Admitted to Internal Medicine, With at Least One of the Following Diagnoses: Heart Failure, COPD, Renal Failure. The FADOI IN-CluDiMI Study
An observational study of Heart Failure and Chronic Obstructive Pulmonary Disease (COPD), run by Fadoi Foundation, Italy at 1 site in Italy.
Trial summary
Improved medical care has led to an increase in both the age and clinical complexity of patients admitted to Internal Medicine wards, characterized by multiple chronic diseases. Multimorbidity is a common issue in the elderly, significantly associated with higher mortality, functional decline, and poorer quality of… Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Heart Failure, Chronic Obstructive Pulmonary Disease (COPD), Chronic Kidney Disease (CKD)
- How many people
- 4,500 participants
- Where
- 1 siteItaly
- Study dates
- 2 Jan 2023to 19 Nov 2024
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: 53 Internal Medicine Units, and for each of them the enrollment of approximately 100 consecutively hospitalized adult patients affected by at least one chronic disease among heart failure, COPD and chronic renal failure in the Medicine Units is planned, for a total of at least 1500 subjects per disease group
Who may be able to join
- Patients admitted to Internal Medicine with a diagnosis of at least one of the following chronic conditions:
- heart failure
- COPD
- chronic kidney disease
- Acceptance of participation in the study by signing the informed consent
Who cannot join
- Patients who do not consent to participate in the study
Trial locations and contacts
1 site in 1 country.
About this study
Improved medical care has led to an increase in both the age and clinical complexity of patients admitted to Internal Medicine wards, characterized by multiple chronic diseases. Multimorbidity is a common issue in the elderly, significantly associated with higher mortality, functional decline, and poorer quality of life. The concept of "disease clustering" goes beyond simple multimorbidity or comorbidity by grouping statistically associated morbid conditions to understand their interconnections, shared risk factors, and pathophysiological mechanisms. The goal is to identify these clusters in relation to the most common chronic conditions in Internal Medicine: heart failure, chronic obstructive pulmonary disease (COPD), and chronic kidney disease.This is an observational, multicenter, prospective, national study sponsored by the FADOI Foundation (Federation of Associations of Internal Medicine Hospital) and this is a non-profit research project. It aims to involve about 50 Internal Medicine Units, targeting the enrollment of approximately 100 consecutive adult patients per unit, for a total of at least 1500 subjects per pathology group.
- Keywords
- Internal Medicine, disease clusters
- Medical subject headings
- Heart Failure, Pulmonary Disease, Chronic Obstructive, Renal Insufficiency, Chronic
What is being measured
The primary outcome is the main question the study is designed to answer.
Identifying disease clusters (defined as the co-presence of at least two additional diseases) in patients suffering from at least one of the following chronic diseases: heart failure, COPD, and chronic kidney disease
IN-CluDiMI study primary objective was to map the structural patterns of disease clustering around HF, COPD, and CKD, and to evaluate their prevalence, functional impacts, and geographic distribution.We also investigated the prognostic role of these clusters on mortality (in-hospital and/or follow-up mortality).
The analysis included all available comorbidities, excluding highly prevalent risk factors such as hypertension, diabetes mellitus and dyslipidaemia, which were analysed separately.
The optimal number of clusters was determined using the silhouette index, selecting a solution that maximised cluster separation and internal cohesion.
3 complementary approaches were used to investigate co-occurrence patterns:
- pairwise analyses
- hierarchical analyses
- a combinatorial analysis to identify the most prevalent triplets of co-occurring conditions within each disease-specific cohort This approach is considered the primary method for identifying recurrent multimorbidity patterns
Measured: 14 Months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted22 Jun 2026
- Study start2 Jan 2023
- Primary completion3 Jun 2024
- Study completion19 Nov 2024
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (4)Papers the sponsor has linked to this study.
- Other trials for Heart FailureStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 4,500 participants (actual)
Sponsor and investigators
- Lead sponsor
- Fadoi Foundation, Italy
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- Ombretta Para, PhD, Study chair, Department of Medicine, AOU Careggi, FirenzeFrancesco Dentali, Prof., Study director, Department of Medicine, ASST-Settelaghi, Varese
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07660757
- Sponsor's protocol ID
- FADOI.01.2021
- Acronym
- IN-CluDiMI
- Status last verified
- Jun 2026
- First submitted
- 16 Jun 2026
- Last updated
- 24 Jun 2026
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided: The following information collected for each patient: * Demographic parameters * Medical history -Pathology (home, nursing home), hospitalizations in the previous year/month, basic activities of daily living (BADL/IADL) autonomy, Barthel scale score * History of medical conditions Heart failure (NYHA class), COPD, renal failure (the severity), hypertension, asthma, diabetes mellitus (with/without organ damage), chronic anemia, dislipidemia, active solid tumor (pharmacological/radiotherapy treatment), active hematological oncology (pharmacological/radiotherapy treatment), ischemic heart disease, atrial fibrillation, cerebrovascular disease (TIA/stroke), Parkinson's disease/neurodegenerative disease, thyroid diseases * Medications/Treatments -Number and class of medications taken before hospital admission/discharge * Charlson Index Score * Hospitalization Outcome -Discharge (home/nursing home), death, transfer to intensive care * 30-day phone follow-up Mortality and rehospitalization 30days
Publications
Schafer I, von Leitner EC, Schon G, Koller D, Hansen H, Kolonko T, Kaduszkiewicz H, Wegscheider K, Glaeske G, van den Bussche H. Multimorbidity patterns in the elderly: a new approach of disease clustering identifies complex interrelations between chronic conditions. PLoS One. 2010 Dec 29;5(12):e15941. doi: 10.1371/journal.pone.0015941.
PubMed 21209965Mannucci PM, Nobili A, Pasina L; REPOSI Collaborators (REPOSI is the acronym of REgistro POliterapie SIMI, Societa Italiana di Medicina Interna). Polypharmacy in older people: lessons from 10 years of experience with the REPOSI register. Intern Emerg Med. 2018 Dec;13(8):1191-1200. doi: 10.1007/s11739-018-1941-8. Epub 2018 Aug 31.
PubMed 30171585Bisquera A, Gulliford M, Dodhia H, Ledwaba-Chapman L, Durbaba S, Soley-Bori M, Fox-Rushby J, Ashworth M, Wang Y. Identifying longitudinal clusters of multimorbidity in an urban setting: A population-based cross-sectional study. Lancet Reg Health Eur. 2021 Mar 2;3:100047. doi: 10.1016/j.lanepe.2021.100047. eCollection 2021 Apr.
PubMed 34557797Whitty CJM, Watt FM. Map clusters of diseases to tackle multimorbidity. Nature. 2020 Mar;579(7800):494-496. doi: 10.1038/d41586-020-00837-4. No abstract available.
PubMed 32210388
Study at a glance
From the registry record, last updated by the sponsor on 24 Jun 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Epidemiological Cluster Evaluation in Patients Admitted to Internal Medicine, With at Least One of the Following Diagnoses: Heart Failure, COPD, Renal Failure. The FADOI IN-CluDiMI Study
- ClinicalTrials.gov ID
- NCT07660757
- Acronym / sponsor ID
- IN-CluDiMI / FADOI.01.2021
- Keywords
- Internal Medicine, disease clusters
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 4,500 participants (actual)
- Lead sponsor
- Fadoi Foundation, ItalyUniversity, hospital or other
- Study start
- 2 Jan 2023 (actual)
- Primary completion
- 3 Jun 2024 (actual)
- Study completion
- 19 Nov 2024 (actual)
- First posted
- 22 Jun 2026 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Improved medical care has led to an increase in both the age and clinical complexity of patients admitted to Internal Medicine wards, characterized by multiple chronic diseases. Multimorbidity is a common issue in the elderly, significantly associated with higher mortality, functional decline, and poorer quality of life. The concept of "disease clustering" goes beyond simple multimorbidity or comorbidity by grouping statistically associated morbid conditions to understand their interconnections, shared risk factors, and pathophysiological mechanisms. The goal is to identify these clusters in relation to the most common chronic conditions in Internal Medicine: heart failure, chronic obstructive pulmonary disease (COPD), and chronic kidney disease.This is an observational, multicenter, prospective, national study sponsored by the FADOI Foundation (Federation of Associations of Internal Medicine Hospital) and this is a non-profit research project. It aims to involve about 50 Internal Medicine Units, targeting the enrollment of approximately 100 consecutive adult patients per unit, for a total of at least 1500 subjects per pathology group.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- 53 Internal Medicine Units, and for each of them the enrollment of approximately 100 consecutively hospitalized adult patients affected by at least one chronic disease among heart failure, COPD and chronic renal failure in the Medicine Units is planned, for a total of at least 1500 subjects per disease group
Key inclusion criteria (5 listed)
- Patients admitted to Internal Medicine with a diagnosis of at least one of the following chronic conditions:
- heart failure
- COPD
- chronic kidney disease
- Acceptance of participation in the study by signing the informed consent
Key exclusion criteria (1 listed)
- Patients who do not consent to participate in the study
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Identifying disease clusters (defined as the co-presence of at least two additional diseases) in patients suffering from at least one of the following chronic diseases: heart failure, COPD, and chronic kidney disease
Time frame: 14 Months
IN-CluDiMI study primary objective was to map the structural patterns of disease clustering around HF, COPD, and CKD, and to evaluate their prevalence, functional impacts, and geographic distribution.We also investigated the prognostic role of these clusters on mortality (in-hospital and/or follow-up mortality). The analysis included all available comorbidities, excluding highly prevalent risk factors such as hypertension, diabetes mellitus and dyslipidaemia, which were analysed separately. The optimal number of clusters was determined using the silhouette index, selecting a solution that maximised cluster separation and internal cohesion. 3 complementary approaches were used to investigate co-occurrence patterns: 1. pairwise analyses 2. hierarchical analyses 3. a combinatorial analysis to identify the most prevalent triplets of co-occurring conditions within each disease-specific cohort This approach is considered the primary method for identifying recurrent multimorbidity patterns
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 24 Jun 2026.
- Background: PubMed 21209965Schafer I, von Leitner EC, Schon G, Koller D, Hansen H, Kolonko T, Kaduszkiewicz H, Wegscheider K, Glaeske G, van den Bussche H. Multimorbidity patterns in the elderly: a new approach of disease clustering identifies complex interrelations between chronic conditions. PLoS One. 2010 Dec 29;5(12):e15941. doi: 10.1371/journal.pone.0015941.
- Background: PubMed 30171585Mannucci PM, Nobili A, Pasina L; REPOSI Collaborators (REPOSI is the acronym of REgistro POliterapie SIMI, Societa Italiana di Medicina Interna). Polypharmacy in older people: lessons from 10 years of experience with the REPOSI register. Intern Emerg Med. 2018 Dec;13(8):1191-1200. doi: 10.1007/s11739-018-1941-8. Epub 2018 Aug 31.
- Background: PubMed 34557797Bisquera A, Gulliford M, Dodhia H, Ledwaba-Chapman L, Durbaba S, Soley-Bori M, Fox-Rushby J, Ashworth M, Wang Y. Identifying longitudinal clusters of multimorbidity in an urban setting: A population-based cross-sectional study. Lancet Reg Health Eur. 2021 Mar 2;3:100047. doi: 10.1016/j.lanepe.2021.100047. eCollection 2021 Apr.
- Background: PubMed 32210388Whitty CJM, Watt FM. Map clusters of diseases to tackle multimorbidity. Nature. 2020 Mar;579(7800):494-496. doi: 10.1038/d41586-020-00837-4. No abstract available.
- Individual participant dataSharing planned: Undecided. The following information collected for each patient: * Demographic parameters * Medical history -Pathology (home, nursing home), hospitalizations in the previous year/month, basic activities of daily living (BADL/IADL) autonomy, Barthel scale score * History of medical conditions Heart failure (NYHA class), COPD, renal failure (the severity), hypertension, asthma, diabetes mellitus (with/without organ damage), chronic anemia, dislipidemia, active solid tumor (pharmacological/radiotherapy treatment), active hematological oncology (pharmacological/radiotherapy treatment), ischemic heart disease, atrial fibrillation, cerebrovascular disease (TIA/stroke), Parkinson's disease/neurodegenerative disease, thyroid diseases * Medications/Treatments -Number and class of medications taken before hospital admission/discharge * Charlson Index Score * Hospitalization Outcome -Discharge (home/nursing home), death, transfer to intensive care * 30-day phone follow-up Mortality and rehospitalization 30days
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Ombretta Para, PhD study chair
Department of Medicine, AOU Careggi, Firenze
Francesco Dentali, Prof. study director
Department of Medicine, ASST-Settelaghi, Varese
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Heart Failure and Chronic Obstructive Pulmonary Disease (COPD), run by Fadoi Foundation, Italy at 1 site in Italy.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 5 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 24 Jun 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Italy. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Identifying disease clusters (defined as the co-presence of at least two additional diseases) in patients suffering from at least one of the following chronic diseases: heart failure, COPD, and chronic kidney disease (time frame: 14 Months). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT07660757, which also lists 4 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 24 Jun 2026.