Evidence map›Paper›PMID 36143226›Full record

ReviewJournal of personalized medicine2022

Impact of the COVID-19 Pandemic on Mortality Following Hip and Knee Joint Arthroplasty Surgeries: A Systematic Review and Meta-Analysis.

Eic Ju Lim, Minboo Kim, Chul-Ho Kim

Abstract readReview
In one paragraph

Review in Journal of personalized medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Observational
  2. Article
  3. 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

3 authors.

Eic Ju LimDepartment of Orthopaedic Surgery, Chungbuk National University Hospital, Chungbuk National University College of Medicine, Cheongju 28644, Korea.ORCID 0000-0001-8095-6173
Minboo KimDepartment of Orthopaedic Surgery, Chungbuk National University Hospital, Chungbuk National University College of Medicine, Cheongju 28644, Korea.ORCID 0000-0002-3719-7711
Chul-Ho KimDepartment of Orthopaedic Surgery, Chung-Ang University Hospital, Chung-Ang University College of Medicine, Seoul 06973, Korea.ORCID 0000-0001-9233-5358

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We performed a meta-analysis comparing the mortality rates after hip and knee joint arthroplasty between the coronavirus 2019 (COVID-19) pandemic and pre-pandemic periods. The purpose of present study was to investigate the impact of the COVID-19 pandemic on mortality rates after hip and knee joint arthroplasty. We systematically searched the MEDLINE, Embase, and Cochrane Library databases for studies published up to 28 March 2022. We included studies which directly compared mortality rates after hip and knee joint arthroplasty between the COVID-19 pandemic and pre-pandemic periods. The methodological quality of the included studies was assessed using the Methodological Index for Nonrandomized Studies (MINORS). We compared the overall mortality rate as the primary outcome. For the subgroup analysis, the mortality rates included were: within 30 days and unrelated to COVID-19; we excluded studies with only elective arthroplasties. Readmission rates following arthroplasties were also compared. We included five studies with 3044 patients, of which 838 patients underwent surgeries during the pandemic period and 2206 patients underwent surgeries in the pre-pandemic period. The mean MINORS score was 15.4/24 (range: 15-16). The overall mortality rate showed no significant differences between the pandemic and pre-pandemic periods (OR, 2.71; 95% CI, 0.78-9.35;

Indexed as

arthroplastyCOVID-19mortalityreadmissionSARS-CoV-2

Identifiers

PMID36143226
PMCPMC9504603

What OpenQuestion holds

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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.