Evidence map›Paper›PMID 39342361›Full record

ArticleJournal of orthopaedic surgery and research2024

Predictive factors for deep medial collateral ligament release in adjusted mechanical alignment total knee arthroplasty.

Nimit Thongpulsawasdi, Chaiwat Achawakulthep, Tawan Intiyanaravut, Chirathit Anusitviwat, Varah Yuenyongviwat

Abstract read
In one paragraph

Article in Journal of orthopaedic surgery and research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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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

1 citing paper in PubMed.

  1. Review
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.

Nimit ThongpulsawasdiGolden jubilee medical center, Faculty of Medicine Siriraj hospital, Mahidol university, Nakhon Pathom, 73170, Thailand.
Chaiwat AchawakulthepGolden jubilee medical center, Faculty of Medicine Siriraj hospital, Mahidol university, Nakhon Pathom, 73170, Thailand.
Tawan IntiyanaravutGolden jubilee medical center, Faculty of Medicine Siriraj hospital, Mahidol university, Nakhon Pathom, 73170, Thailand.
Chirathit AnusitviwatDepartment of Orthopedics, Faculty of Medicine, Prince of Songkla University, Hat Yai, Songkhla, 90110, Thailand.
Varah YuenyongviwatDepartment of Orthopedics, Faculty of Medicine, Prince of Songkla University, Hat Yai, Songkhla, 90110, Thailand. varahortho@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTotal knee arthroplasty (TKA) demands precision in achieving optimal alignment and soft tissue balance, especially in cases of medial compartment osteoarthritis where the need for medial soft tissue release is critical yet challenging to ascertain.

objectiveThis study aims to systematically investigate the relationship between preoperative data, initial knee conditions and the necessity for deep collateral ligament (MCL) release in adjusted mechanical alignment total knee arthroplasty.

methodsWe conducted a retrospective study involving 61 TKA patients who underwent adjusted mechanical alignment robotic-assisted procedures. Soft tissue release was carried out when clinically indicated. We collected and statistically analyzed patient demographics, initial knee conditions, and surgical details.

resultsAmong the patients, 52% required deep MCL release. Notably, patients without soft tissue release exhibited lower initial hip-knee-ankle (HKA) angles, reduced varus-valgus stress test angles, and a greater range of flexion. We identified a predictive threshold HKA angle of 6.250 degrees, demonstrating high sensitivity and specificity for determining the need for deep MCL release.

conclusionThis study underscores the significance of the initial HKA angle and varus-valgus stress tests in predicting deep MCL release during TKA. The established HKA angle threshold simplifies surgical decision-making, reducing the likelihood of unnecessary soft tissue release.

Indexed as

Arthroplasty, Replacement, KneeMedial Collateral Ligament, KneeAgedAged, 80 and overFemaleHumansMaleMiddle AgedOsteoarthritis, KneeRetrospective StudiesRobotic Surgical ProceduresAdjusted mechanical alignmentOsteoarthritisRobotic-assisted total knee arthroplastySoft tissue balance

Identifiers

PMID39342361
PMCPMC11437786

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LicenceCC BY
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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.