Evidence map›Paper›PMID 31011514›Full record

ArticleJournal of bone and joint infection2019

Fever and Erythema are Specific Findings in Detecting Infection Following Total Knee Arthroplasty.

Noam Shohat, Karan Goswami, Timothy L Tan, Brian Henstenburg, Gabriel Makar, Alexander J Rondon, Javad Parvizi

Open access · goldAbstract read
In one paragraph

Article in Journal of bone and joint infection, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 2 pooled it
2.2field-weighted citation impact, top 13% 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

19 citing papers in PubMed, 2 syntheses or guidelines pooled it, 23 citations in OpenAlex.

  1. Machine Learning Based Diagnostic Models for Hip and Knee Prosthetic Joint Infection: A Systematic Review.Journal of orthopaedic research : official publication of the Orthopaedic Research Society · 2026
    Pooled it
  2. Pooled it
  3. Review
  4. Article
  5. Evaluating chronic bone and soft tissue infections with [European journal of nuclear medicine and molecular imaging · 2026
    Article
  6. Observational
  7. Review
  8. Review
  9. Article
  10. Review
  11. Review
  12. Review
  13. Review
  14. Imaging joint infections using D-methyl-European journal of nuclear medicine and molecular imaging · 2022
    Article
  15. Diagnosing Periprosthetic Joint Infection: a Scoping Review.Current reviews in musculoskeletal medicine · 2022
    Article
  16. Article
  17. Progress in Prevention, Diagnosis, and Treatment of Periprosthetic Joint Infection.Evidence-based complementary and alternative medicine : eCAM · 2021
    Review
  18. Article
  19. 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

7 authors at 2 institutions in 2 countries.

Noam ShohatThe Rothman Institute at Thomas Jefferson University, Philadelphia, PA 19107.
Karan GoswamiThe Rothman Institute at Thomas Jefferson University, Philadelphia, PA 19107.
Timothy L TanThe Rothman Institute at Thomas Jefferson University, Philadelphia, PA 19107.
Brian HenstenburgThe Rothman Institute at Thomas Jefferson University, Philadelphia, PA 19107.
Gabriel MakarThe Rothman Institute at Thomas Jefferson University, Philadelphia, PA 19107.
Alexander J RondonThe Rothman Institute at Thomas Jefferson University, Philadelphia, PA 19107.
Javad ParviziThe Rothman Institute at Thomas Jefferson University, Philadelphia, PA 19107.
Thomas Jefferson University · USRothman Institute · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Current diagnostic modalities are based almost exclusively on laboratory findings and the role of clinical presentation remains unknown. The purpose of this study was to examine the diagnostic value of clinical presentation in detecting periprosthetic joint infection (PJI). This study evaluated 279 patients undergoing revision surgery for failed total knee arthroplasty (TKA) between 2001-2016. Patients were classified as undergoing septic revisions based on major MSIS criteria. Aseptic revisions were defined as cases of single stage revision that did not have suspected PJI, fulfill MSIS criteria, or subsequently fail within one year of follow-up. Clinical presentation included pain, fever, presence of joint effusion or erythema, and reduced range of motion. Serum and synovial laboratory markers were also evaluated. The diagnostic value of each test was assessed and a Fagan's nomogram was constructed. A subset of MSIS-negative patients was used to demonstrate the value of various clinical presentations in detecting PJI. Post-test probability for infection was calculated taking into account clinical presentation together with serum and synovial markers. Our results show that fever and erythema are the most important signs for diagnosing PJI with a positive likelihood ratio (LR) of 10.78 and 8.08, respectively. Effusion had a LR of 2.42. Pain and reduced ROM were not as strongly correlated with PJI diagnosis; LR was 1.02 and 1.51. Of the 35 MSIS-negative patients treated for PJI, 33 had a post-test probability of infection greater than 90% when taking clinical presentation into account. Clinical presentation should be used to guide which future diagnostic tests should be ordered and in the interpretation of their results. Our results indicate that pain, fever, presence of joint effusion or erythema, and reduced range of motion should prompt further workup for infection. We propose a nomogram that may be used in interoperating their individual weight together with laboratory findings. Fever and erythema are highly specific findings in patients with PJI and future studies should assess whether they may be added as minor criteria to current definitions for infection.

Identifiers

PMID31011514
PMCPMC6470654
OpenAlexW2923249676

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.