Evidence map›Paper›PMID 34258069›Full record

ArticleAdvances in orthopedics2021

Comparison of Functional Outcome of Total and Unicompartmental Knee Arthroplasty Using Computer-Assisted Patient-Specific Templating.

Atef Mohamed Morsy, Emad Gaber Elbana, Ahmed Gaber Mostafa, Mark Ashraf Edward, Mahmoud A Hafez

Open access · goldAbstract read
In one paragraph

Article in Advances in orthopedics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
0.6field-weighted citation impact, top 32% of its field
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

4 citing papers in PubMed, 1 synthesis or guideline pooled it, 5 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Article
  4. Article
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 at 2 institutions in 1 country.

Atef Mohamed MorsyThe Orthopaedic Department, Beni-Suef University, Beni-Suef, Egypt.ORCID https://orcid.org/0000-0003-4880-3972
Emad Gaber ElbanaThe Orthopaedic Department, Beni-Suef University, Beni-Suef, Egypt.ORCID https://orcid.org/0000-0002-0892-1643
Ahmed Gaber MostafaThe Orthopaedic Department, Beni-Suef University, Beni-Suef, Egypt.ORCID https://orcid.org/0000-0002-2409-1985
Mark Ashraf EdwardThe Orthopaedic Department, Faculty of Medicine, October 6 University, Giza, Egypt.ORCID https://orcid.org/0000-0002-6925-5701
Mahmoud A HafezThe Orthopaedic Department, Faculty of Medicine, October 6 University, Giza, Egypt.ORCID https://orcid.org/0000-0002-6285-5720
Beni-Suef University · EGOctober 6 University · EG

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundKnee arthroplasty surgeries are in ever-increasing demand. With unicompartmental knee arthroplasty (UKA), patients may benefit from a higher range of flexion and a better Knee Society Score (KSS).

aimIn this study, we compared the short-term clinical outcomes of total knee arthroplasty (TKA) and UKA using the patient-specific templating (PST) technique.

methodsTwo groups of 20 knees each were divided into UKA and TKA groups depending on the Oxford criteria of UKA. Only patients with medial compartmental osteoarthritis were included. KSS, functional knee score (FKS), and ROF were assessed preoperatively and at 6 months postoperatively.

resultsThe TKA group has shown a significant improvement compared to the UKA group in KSS (MD = 39.35 vs. 31.2, respectively,

conclusionPreoperatively, the TKA group had lower KSS and ROF compared to UKA. The improvement of KSS from preoperative to postoperative was more significant in TKA. However, the TKA group has shown less range of flexion postoperatively.

Identifiers

PMID34258069
PMCPMC8253625
OpenAlexW3176182534

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Registered trials

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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.