Evidence map›Paper›PMID 42898140›Full record

SynthesisFrontiers in medicine2026

Nurse-led rehabilitation after total hip or knee arthroplasty: a systematic review and meta-analysis of functional recovery, self-efficacy, and quality of life.

Ying Xu, Yan Chen, Yuan Yin, Mengxia Tang, Qin Luo

Abstract readSystematic Review
In one paragraph

Synthesis in Frontiers in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Ying XuDepartment of Rehabilitation, Taixing People's Hospital, Taixing, Jiangsu, China.
Yan ChenDepartment of Rehabilitation, Taixing People's Hospital, Taixing, Jiangsu, China.
Yuan YinDepartment of Rehabilitation, Taixing People's Hospital, Taixing, Jiangsu, China.
Mengxia TangDepartment of Rehabilitation, Taixing People's Hospital, Taixing, Jiangsu, China.
Qin LuoDepartment of Rehabilitation, Taixing People's Hospital, Taixing, Jiangsu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Nurse-led rehabilitation is increasingly embedded in postdischarge care after total hip or knee arthroplasty, but its effect on patient-reported recovery has not been quantified through meta-analysis. Objective: The aim of this study was to evaluate the effects of nurse-led rehabilitation versus usual care on functional recovery, self-efficacy, and quality of life after total hip or knee arthroplasty. Methods: PubMed, Scopus, Web of Science, and ClinicalTrials.gov were searched (2010-2026; English only) for randomized controlled trials comparing nurse-led rehabilitation with usual care. Standardized mean differences (Hedges Results: Eleven trials (1,107 participants) were included. Nurse-led rehabilitation improved functional recovery (10 trials; Conclusions: Nurse-led rehabilitation after hip or knee arthroplasty was associated with improved function, self-efficacy, and quality of life, consistently favoring nurse-led care in direction but with evidence of low certainty, substantial between-study heterogeneity, prediction intervals that crossed the null, and possible small-study effects. Therefore, the magnitude of benefit remains uncertain. Adequately powered, outcome-blinded trials are needed. Systematic Review Registration: https://www.crd.york.ac.uk/PROSPERO/view/CRD420261425216, PROSPERO CRD420261425216.

Indexed as

nurse-led rehabilitationquality of lifeself-efficacytotal hip arthroplastytotal knee arthroplasty

Identifiers

PMID42898140
PMCPMC13677350

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.