Evidence map›Paper›PMID 32712786›Full record

ArticleInternational orthopaedics2020

Combined serum biomarker analysis shows no benefit in the diagnosis of periprosthetic joint infection.

S M Klim, F Amerstorfer, G Glehr, G Hauer, M A Smolle, L Leitner, A Leithner, M Glehr

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in International orthopaedics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 3 pooled it
3.1field-weighted citation impact, top 8% 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

13 citing papers in PubMed, 3 syntheses or guidelines pooled it, 25 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Article
  5. Article
  6. Review
  7. Review
  8. Review
  9. Review
  10. Article
  11. Review
  12. Article
  13. 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 at 1 institution in 2 countries.

S M KlimDepartment of Orthopaedics and Trauma, Medical University of Graz, Auenbruggerplatz 5, 8036, Graz, Austria.
F AmerstorferDepartment of Orthopaedics and Trauma, Medical University of Graz, Auenbruggerplatz 5, 8036, Graz, Austria.
G GlehrStatistical Bioinformatics Department, University of Regensburg, Am BioPark 9, 93053, Regensburg, Germany.
G HauerDepartment of Orthopaedics and Trauma, Medical University of Graz, Auenbruggerplatz 5, 8036, Graz, Austria.
M A SmolleDepartment of Orthopaedics and Trauma, Medical University of Graz, Auenbruggerplatz 5, 8036, Graz, Austria.
L LeitnerDepartment of Orthopaedics and Trauma, Medical University of Graz, Auenbruggerplatz 5, 8036, Graz, Austria. lukas.leitner@medunigraz.at.ORCID 0000-0002-5534-7605
A LeithnerDepartment of Orthopaedics and Trauma, Medical University of Graz, Auenbruggerplatz 5, 8036, Graz, Austria.
M GlehrDepartment of Orthopaedics and Trauma, Medical University of Graz, Auenbruggerplatz 5, 8036, Graz, Austria.
Medical University of Graz · AT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeIn many cases, the diagnosis of a periprosthetic joint infection (PJI) consisting of the clinical appearance, laboratory tests, and other diagnostic tools remains a difficult task. Single serum biomarkers are easy to collect, are suitable for periodical assessment, and are a crucial tool in PJI diagnosis, but limited sensitivity or specificity is reported in literature. The aim of this study was to combine the best-performing single serum biomarkers into a multi-biomarker model aiming to improve the diagnostic properties.

methodsWithin a 27-month period, 124 surgical procedures (aseptic or septic revision total knee arthroplasty (TKA) or total hip arthroplasty (THA)) were prospectively included. The serum leukocyte count, C-reactive protein (CRP), interleukin-6, procalcitonin, interferon alpha, and fibrinogen were assessed 1 day prior to surgery. Logistic regression with lasso-regularization was used for the biomarkers and all their ratios. After randomly splitting the data into a training (75%) and a test set (25%), the multi-biomarker model was calculated and validated in a cross-validation approach.

resultsCRP (AUC 0.91, specificity 0.67, sensitivity 0.90, p value 0.03) and fibrinogen (AUC 0.93, specificity 0.73, sensitivity 0.94, p value 0.02) had the best single-biomarker performances. The multi-biomarker model including fibrinogen, CRP, the ratio of fibrinogen to CRP, and the ratio of serum thrombocytes to CRP showed a similar performance (AUC 0.95, specificity 0.91, sensitivity 0.72, p value 0.01).

conclusionIn this study, multiple biomarkers were tested for their diagnostic performance, with CRP and fibrinogen showing the best results regarding the AUC, accuracy, sensitivity, and specificity. It was not possible to further increase the diagnostic accuracy by combining multiple biomarkers using sophisticated statistical methods.

Indexed as

Arthroplasty, Replacement, HipArthroplasty, Replacement, KneeProsthesis-Related InfectionsBiomarkersC-Reactive ProteinHumansSensitivity and SpecificitySynovial FluidBiomarkersC-Reactive ProteinBiomarkerDiagnosticsPeriprosthetic joint infectionRevision joint arthroplasty

Identifiers

PMID32712786
PMCPMC7679358
OpenAlexW3045121827

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.