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

NCT07660757 | Completed DMC

• 1 other identifier: FADOI.01.2021
• Study Type: observational
• Target: 4,500
• Locations: 1 country
• Sites: 1

Brief 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 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.

Conditions

Heart Failure; Chronic Obstructive Pulmonary Disease (COPD); Chronic Kidney Disease (CKD)

Keywords

Internal Medicine; disease clusters

Outcome Measures

Primary Outcomes (1)

• 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: 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

  14 Months

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

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

You may qualify if:

• 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

You may not qualify if:

• Patients who do not consent to participate in the study

Sponsors & Collaborators

• Fadoi Foundation, Italy: lead

Study Sites (1)

Antonella Valerio

Roma, Italy

Location

Related Publications (4)

• 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.

  PMID: 21209965 BACKGROUND

• Mannucci 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.

  PMID: 30171585 BACKGROUND

• Bisquera 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.

  PMID: 34557797 BACKGROUND

• Whitty 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.

  PMID: 32210388 BACKGROUND

MeSH Terms

Conditions

Heart Failure; Pulmonary Disease, Chronic Obstructive; Renal Insufficiency, Chronic

Condition Hierarchy (Ancestors)

Heart Diseases; Cardiovascular Diseases; Lung Diseases, Obstructive; Lung Diseases; Respiratory Tract Diseases; Chronic Disease; Disease Attributes; Pathologic Processes; Pathological Conditions, Signs and Symptoms; Renal Insufficiency; Kidney Diseases; Urologic Diseases; Female Urogenital Diseases; Female Urogenital Diseases and Pregnancy Complications; Urogenital Diseases; Male Urogenital Diseases

Study Officials

• Ombretta Para, PhD

  Department of Medicine, AOU Careggi, Firenze

  STUDY CHAIR

• Francesco Dentali, Prof.

  Department of Medicine, ASST-Settelaghi, Varese

  STUDY DIRECTOR

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: June 16, 2026
• First Posted: June 22, 2026
• Study Start: January 2, 2023
• Primary Completion: June 3, 2024
• Study Completion: November 19, 2024
• Last Updated: June 24, 2026

Record last verified: 2026-06

Locations

IT (1)