Evidence map›Paper›PMID 36628030›Full record

ArticleCureus2022

Short- to Mid-Term Outcomes in Arthroscopic Debridement of the Knee: A Prospective Case Series.

Nachappa Sivanesan Uthraraj, Ravali Suguru, Fitzgerald Anazor, Ali Hussain, Anand B Divekar, Kumar Gaddam Raddy, Raj Shrivastava, Jai Relwani

Abstract read
In one paragraph

Article in Cureus, 2022. 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
–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

1 citing paper in PubMed.

  1. 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

8 authors.

Nachappa Sivanesan UthrarajTrauma and Orthopaedics, William Harvey Hospital, Ashford, GBR.
Ravali SuguruTrauma and Orthopaedics, Gandhi Medical College and Hospital, Hyderabad, IND.
Fitzgerald AnazorTrauma and Orthopaedics, William Harvey Hospital, Ashford, GBR.
Ali HussainTrauma and Orthopaedics, William Harvey Hospital, Ashford, GBR.
Anand B DivekarTrauma and Orthopaedics, William Harvey Hospital, Ashford, GBR.
Kumar Gaddam RaddyTrauma and Orthopaedics, William Harvey Hospital, Ashford, GBR.
Raj ShrivastavaTrauma and Orthopaedics, William Harvey Hospital, Ashford, GBR.
Jai RelwaniTrauma and Orthopaedics, William Harvey Hospital, Ashford, GBR.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction Osteoarthritis of the knee is a common debilitating disease in the elderly population. There are many treatment options available including physiotherapy, analgesics, steroid injections, arthroscopic debridement, high tibial osteotomy (HTO) and arthroplasty. Arthroscopic debridement is beneficial when patients are chosen with certain characteristics. This is a prospective case series where we have correlated the patient and disease characteristics, with the pre- and post-operative Oxford Knee Scores (OKS). Methods This study was done in a single centre with appropriate ethical committee approval and consent. Forty-nine patients were enrolled in the study. The scores were recorded pre-operatively and at 12 months after the interventions. Analysis was done for correlation of the outcome with patient characteristics, radiological and arthroscopic grading. Results Patients below the age of 56 years, with partial thickness chondral lesions, grade I-III Kellgren-Lawrence (KL) radiological grading and grade I-II Outerbridge arthroscopic grading showed significant improvement at 12 months. Conclusion Arthroscopic debridement is effective in younger patients with mild to moderate arthroscopic and radiologically graded osteoarthritis of the knee joint.

Indexed as

arthroscopydebridement and lavageknee jointosteoarthritisoxford knee score

Identifiers

PMID36628030
PMCPMC9826627

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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.