Evidence map›Paper›PMID 35885583›Full record

ArticleDiagnostics (Basel, Switzerland)2022

Detecting and Monitoring Periprosthetic Joint Infection by Using Electrical Bioimpedance Spectroscopy: A Preliminary Case Study.

Marco Balato, Carlo Petrarca, Pasquale Arpaia, Nicola Moccaldi, Francesca Mancino, Giusy Carleo, Simone Minucci, Massimo Mariconda, Giovanni Balato

Abstract readCase Reports
In one paragraph

Article in Diagnostics (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

9 authors.

Marco BalatoDepartment of Electrical Engineering and Information Technologies (DIETI), University of Naples "Federico II", 80125 Napoli, Italy.ORCID 0000-0003-0649-645X
Carlo PetrarcaDepartment of Electrical Engineering and Information Technologies (DIETI), University of Naples "Federico II", 80125 Napoli, Italy.ORCID 0000-0002-0986-6025
Pasquale ArpaiaDepartment of Electrical Engineering and Information Technologies (DIETI), University of Naples "Federico II", 80125 Napoli, Italy.ORCID 0000-0002-5192-5922
Nicola MoccaldiDepartment of Electrical Engineering and Information Technologies (DIETI), University of Naples "Federico II", 80125 Napoli, Italy.
Francesca MancinoDepartment of Electrical Engineering and Information Technologies (DIETI), University of Naples "Federico II", 80125 Napoli, Italy.
Giusy CarleoDepartment of Neuroscience and Reproductive and Odontostomatological Sciences, University of Naples "Federico II", 80131 Napoli, Italy.
Simone MinucciDepartment of Economics, Engineering, Society and Business Organization (DEIM), University of Tuscia, 01100 Viterbo, Italy.
Massimo MaricondaInterdepartmental Research Center on Management and Innovation in Healthcare, (CIRMIS), University of Naples "Federico II", 80131 Napoli, Italy.
Giovanni BalatoDepartment of Public Health, University of Naples "Federico II", 80131 Napoli, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A method to detect the presence of infection after Total Joint Arthroplasty is presented. The method is based on Electrical Bioimpedance Spectroscopy and guarantees low latency, non-invasiveness, and cheapness with respect to the state of art. Experimental measurements were carried out on a singular patient who had already undergone bilateral Total Knee Arthroplasty. He was affected by a hematogenous Periprosthetic Joint Infections on the left knee. The right knee was adopted as the reference. Measurements were acquired once before the surgical procedure (Diagnosis Phase) and twice in the postoperative phases (Monitoring Phase). The most relevant frequency range, for diagnosis and monitoring phases, was found to be between 10 kHz to 50 kHz. The healing trend predicted by the decrease of impedance magnitude spectrum was reflected in clinical and laboratory results. In addition, one month after the last acquisition (two months after the surgery), the patient fully recovered, confirming the prediction of the Electrical Bioimpedance Spectroscopy technique.

Indexed as

biofilm infectionsdiagnostic methodsdiseases diagnosticelectrical bioimpedance spectroscopyprediction

Identifiers

PMID35885583
PMCPMC9323083

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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.