Optimizing long-term joint health in the treatment of hemophilia.

Ultrasonography cartilage hemophilia joint diseases synovitis

Journal

Expert review of hematology
ISSN: 1747-4094
Titre abrégé: Expert Rev Hematol
Pays: England
ID NLM: 101485942

Informations de publication

Date de publication:
08 Sep 2024
Historique:
medline: 9 9 2024
pubmed: 9 9 2024
entrez: 9 9 2024
Statut: aheadofprint

Résumé

The improved quality of care and increased drug availability have shifted the goal of treating people with hemophilia from life-threatening bleeding prevention to joint health preservation and quality of life amelioration. Many tools are now available to the clinician in order to optimize the management of hemophilic arthropathy. This paper reviews the pivotal role of ultrasound evaluation in early detection of joint bleeding and differential diagnosis of joint pain, with a focus on the feasibility of a long-term monitoring of joint health through the use of artificial intelligence and telemedicine. The literature search methodology included using keywords to search in PubMed and Google Scholar, and articles used were screened by the coauthors of this review. Joint ultrasound is a practical point-of-care tool with many advantages, including immediate correlation between imaging and clinical presentation, and dynamic evaluation of multiple joints. The potential of telemedicine care, coupled with a point-of-care detection device assisted by artificial intelligence, holds promises for even earlier diagnosis and treatment of joint bleeding. A multidisciplinary approach including early intervention by physical medicine and rehabilitation (PMR) physicians and physiotherapists is crucial to ensure the best possible quality of life for the patient.

Identifiants

pubmed: 39245933
doi: 10.1080/17474086.2024.2396617
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

1-10

Auteurs

Roberta Gualtierotti (R)

Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Angelo Bianchi Bonomi Hemophilia and Thrombosis Center, Milan, Italy.
Department of Pathophysiology and Transplantation, Università degli Studi di Milano, Milan, Italy.

Andrea Giachi (A)

Department of Pathophysiology and Transplantation, Università degli Studi di Milano, Milan, Italy.

Chiara Suffritti (C)

Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Angelo Bianchi Bonomi Hemophilia and Thrombosis Center, Milan, Italy.

Luca Bedogni (L)

Dipartimento di Scienze Fisiche, Informatiche e Matematiche, Università degli Studi di Modena e Reggio Emilia, Modena, Italy.

Francesco Franco (F)

Dipartimento di Scienze Fisiche, Informatiche e Matematiche, Università degli Studi di Modena e Reggio Emilia, Modena, Italy.

Francesco Poggi (F)

Institute for Cognitive Sciences and Technologies (ISTC), National Research Council (CNR), Bologna, Italy.

Sergio Mascetti (S)

Department of Computer Science, Università degli Studi di Milano, Milan, Italy.

Marco Colussi (M)

Department of Computer Science, Università degli Studi di Milano, Milan, Italy.

Dragan Ahmetovic (D)

Department of Computer Science, Università degli Studi di Milano, Milan, Italy.

Valentina Begnozzi (V)

Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Angelo Bianchi Bonomi Hemophilia and Thrombosis Center, Milan, Italy.

Elena Anna Boccalandro (EA)

Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Angelo Bianchi Bonomi Hemophilia and Thrombosis Center, Milan, Italy.

Luigi Piero Solimeno (LP)

Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Division of Orthopaedic Surgery and Traumatology, Milan, Italy.

Flora Peyvandi (F)

Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Angelo Bianchi Bonomi Hemophilia and Thrombosis Center, Milan, Italy.
Department of Pathophysiology and Transplantation, Università degli Studi di Milano, Milan, Italy.

Classifications MeSH