Evidence map›Paper›PMID 39007012›Full record

ReviewSensors & diagnostics2024

Point-of-care diagnostic devices for periodontitis - current trends and urgent need.

Alexandra Griffith, Charmi Chande, Sahitya Kulkarni, Josuel Morel, Yu-Hsuan Cheng, Emi Shimizu, Carla Cugini, Sagnik Basuray, Vivek Kumar

Abstract readReview
In one paragraph

Review in Sensors & diagnostics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
–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

14 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
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  4. Antibiotic Resistance in Dentistry: A Review.Antibiotics (Basel, Switzerland) · 2025
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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.

Alexandra GriffithDepartment of Biomedical Engineering, New Jersey Institute of Technology Newark NJ 07102 USA sbasuray@njit.edu vak@njit.edu.
Charmi ChandeDepartment of Biomedical Engineering, New Jersey Institute of Technology Newark NJ 07102 USA sbasuray@njit.edu vak@njit.edu.
Sahitya KulkarniDepartment of Biological Sciences, New Jersey Institute of Technology Newark NJ 07102 USA.
Josuel MorelDepartment of Biomedical Engineering, New Jersey Institute of Technology Newark NJ 07102 USA sbasuray@njit.edu vak@njit.edu.
Yu-Hsuan ChengDepartment of Chemical and Materials Engineering, New Jersey Institute of Technology Newark NJ 07102 USA.
Emi ShimizuDepartment of Endodontics, Rutgers School of Dental Medicine Newark NJ 07103 USA.
Carla CuginiDepartment of Oral Biology, Rutgers School of Dental Medicine Newark NJ 07103 USA.
Sagnik BasurayDepartment of Biomedical Engineering, New Jersey Institute of Technology Newark NJ 07102 USA sbasuray@njit.edu vak@njit.edu.
Vivek KumarDepartment of Biomedical Engineering, New Jersey Institute of Technology Newark NJ 07102 USA sbasuray@njit.edu vak@njit.edu.ORCID https://orcid.org/0000-0001-7536-9281

Funding

New Jersey Alliance for Clinical Translational Science: NJ ACTSUL1TR003017 · NCATS · RUTGERS BIOMEDICAL/HEALTH SCIENCES-RBHS · PI PANETTIERI, REYNOLD ALEXANDER · 2019 to 2023
$28.9M
Bioactive Scaffold for TMJ Disc Regeneration by Endogenous Stem/Progenitor CellsR01DE029321 · NIDCR · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI LEE, CHANG HUN · 2020 to 2024
$3.5M
Diversity Supplement for Angiogenic and anti-microbial supports for pulp regenerationR01DE031812 · NIDCR · UNIVERSITY OF HOUSTON · PI Vivek Kumar · 2022 to 2026
$3.3M
Treatment and Mechanisms of Diabetic Fracture HealingR01AR080895 · NIAMS · UNIVERSITY OF PENNSYLVANIA · PI DANA T GRAVES, Shuying Yang · 2023 to 2026
$2.0M
Acellular composite hydrogel scaffolds for volumetric muscle regenerationR21AR079708 · NIAMS · NEW JERSEY INSTITUTE OF TECHNOLOGY · PI GRASMAN, JONATHAN M., KUMAR, VIVEK · 2022 to 2023
$467k
NCATS NIH HHS UL1 TR003017NIAMS NIH HHS R01 AR080895NIAMS NIH HHS R21 AR079708NIDCR NIH HHS R01 DE029321NIDCR NIH HHS R01 DE031812
6 · The paper itself

Abstract

Point of care (POC) diagnostic devices provide a method for rapid accurate identification of disease through analysis of biologically relevant substances. This review focuses on the utility of POC testing for early detection of periodontitis, a critical factor in treating the disease. Accessing the oral cavity for biological sampling is less invasive when compared to other internal test sites, and oral fluids contain biomarkers indicative of periodontitis. The ease of access makes the mouth an excellent target location for the development of POC devices. In this review, accepted standards in industry by which these devices must adhere, provided by the World Health Organization such as REASSURED and CLIA, are discussed. An overview is provided for many periodontal biomarkers currently being investigated as a means of predicting periodontal disease and its progression. POC devices currently being investigated for the identification and monitoring of periodontal disease such as paper-based and lab-on-a-chip based devices are outlined. Limitations of current POC devices on the market are provided and future directions in leveraging biomarkers as an adjunctive method for oral diagnosis along with AI-based analysis systems are discussed. Here, we present the ESSENCE sensor platform, which combines a porous non-planar electrode with enhanced shear flow to achieve unprecedented sensitivity and selectivity. The combination of the ESENCE chip with an automated platform allows us to meet the WHO's ASSURED criteria. This platform promises to be an exciting POC candidate for early detection of periodontitis.

Identifiers

PMID39007012
PMCPMC11238172

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.