Active and passive physical therapy in patients with chronic low-back pain: a level I Bayesian network meta-analysis

Authors

Institutions

Publication Details

Journal
Journal of Orthopaedics and Traumatology
Published
2025-10-03
DOI
https://doi.org/10.1186/s10195-025-00885-4
Citations
6
Primary Topic
Musculoskeletal pain and rehabilitation
Type
article
Field-Weighted Citation Impact
8.37
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Active and passive physical therapy in patients with chronic low-back pain: a level I Bayesian network meta-analysis

Filippo Migliorini, Alexandra Klimuch, Alice Baroncini, M. Bossa et al.
6 citations
Journal of Orthopaedics and Traumatology
Musculoskeletal pain and rehabilitation
8.37
article

Active and passive physical therapy in patients with chronic low-back pain: a level I Bayesian network meta-analysis

Filippo Migliorini, Alexandra Klimuch, Alice Baroncini, M. Bossa, Nicola Maffulli, Calogero Foti, Nicola Manocchio, Luise Schäfer
article en
6 citations

Abstract

No abstract available for this paper.
Journal of Orthopaedics and TraumatologyVol. 26(1)
University of Rome Tor Vergata (IT), Queen Mary University of London (GB), Mile End Hospital (GB), Ospedale di Bolzano (IT), Casa di Cura Columbus (IT), Universitätsklinikum Aachen (DE), Lungenklinik Hemer (DE), University Hospital in Halle (DE), Link Campus University (IT), Keele University (GB), Martin Luther University Halle-Wittenberg (DE), Sapienza University of Rome (IT), RWTH Aachen University (DE)
Openalex Percentile: Top 2%
Musculoskeletal pain and rehabilitation
8.37
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.