Evidence map›Paper›PMID 38256494›Full record

ArticleJournal of clinical medicine2024

Low Response Rate to Follow-Up Using Telemedicine after Total Knee Replacement during the COVID-19 Pandemic in Italy.

Eugenio Cammisa, Matteo La Verde, Federico Coliva, Antongiulio Favero, Iacopo Sassoli, Stefano Fratini, Domenico Alesi, Giada Lullini, Stefano Zaffagnini, Giulio Maria Marcheggiani Muccioli

Abstract read
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Article in Journal of clinical medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Eugenio CammisaOperational Unit of Orthopedics and Traumatology, Imola Hospital Santa Maria della Scaletta, 40026 Imola, Italy.ORCID 0000-0001-6254-6621
Matteo La VerdeII Orthopaedic and Traumatology Clinic, IRCCS Istituto Ortopedico Rizzoli-DIBINEM, University of Bologna, 40126 Bologna, Italy.
Federico ColivaII Orthopaedic and Traumatology Clinic, IRCCS Istituto Ortopedico Rizzoli-DIBINEM, University of Bologna, 40126 Bologna, Italy.ORCID 0009-0007-8330-0314
Antongiulio FaveroII Orthopaedic and Traumatology Clinic, IRCCS Istituto Ortopedico Rizzoli-DIBINEM, University of Bologna, 40126 Bologna, Italy.
Iacopo SassoliII Orthopaedic and Traumatology Clinic, IRCCS Istituto Ortopedico Rizzoli-DIBINEM, University of Bologna, 40126 Bologna, Italy.
Stefano FratiniII Orthopaedic and Traumatology Clinic, IRCCS Istituto Ortopedico Rizzoli-DIBINEM, University of Bologna, 40126 Bologna, Italy.
Domenico AlesiII Orthopaedic and Traumatology Clinic, IRCCS Istituto Ortopedico Rizzoli-DIBINEM, University of Bologna, 40126 Bologna, Italy.ORCID 0000-0002-8841-056X
Giada LulliniIRCCS Istituto delle Scienze Neurologiche di Bologna, UOC Medicina Riabilitativa e Neuroriabilitazione, 40139 Bologna, Italy.
Stefano ZaffagniniII Orthopaedic and Traumatology Clinic, IRCCS Istituto Ortopedico Rizzoli-DIBINEM, University of Bologna, 40126 Bologna, Italy.
Giulio Maria Marcheggiani MuccioliII Orthopaedic and Traumatology Clinic, IRCCS Istituto Ortopedico Rizzoli-DIBINEM, University of Bologna, 40126 Bologna, Italy.ORCID 0000-0002-1087-2932

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis study aimed to evaluate the survival rate and medium-term outcomes of patients after cemented posterior-stabilized (PS) mobile-bearing (MB) total knee arthroplasty (TKA) using a telemedicine platform during the COVID-19 pandemic in Italy.

methodsA total of 100 consecutive patients (mean age 73.5 ± 13.2 years) who received a cemented PS MB TKA were enrolled. The mean age of patients who did not complete the telemedicine follow-up (58%) was 75.8 ± 9.7 years. A dedicated software that makes it possible to perform video calls, online questionnaires, and acquire X-rays remotely was used. Subjective clinical scores and objective range-of-motion (ROM) measurements were observed at an average follow-up of 54 ± 11.3 months.

resultsA total of 42 of 100 enrolled patients (mean age 70.3 ± 8.4 years) completed the telemedicine follow-up. The mean age of patients who did not complete the telemedicine follow-up (58%) was 75.8 ± 9.7 years. Age was found to be a statistically significant difference between the group that completed the telemedicine follow-up and the one that did not (

conclusionsSubject to small numbers, telemedicine presented as a useful instrument for performing remote monitoring after TKA. The most important factor in telemedicine success remains the patient's skill, which is usually age-related, as older patients have much more difficulty in approaching a technological tool.

Indexed as

COVIDknee arthroplastytelemedicineTKA

Identifiers

PMID38256494
PMCPMC10816610

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.