Evidence map›Paper›PMID 41907937›Full record

ArticleBioinformation2025

Assessment of salivary biomarkers in early peri-implantitis detection.

Rashmita Nayak, Sarah Hesham Ahmed Mohamed Eweis, Rani Kumari Gupta, Rashmi Rathore, Pratiksha Tripathi, Vinita Dahiya

Abstract read
In one paragraph

Article in Bioinformation, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

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

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

  1. Pooled it
  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

6 authors.

Rashmita NayakDepartment of Periodontics & Oral Implantology, Institute of Dental Sciences, Siksha O Anusandhan University, Deemed to be University, Bhubaneswar, Odisha.
Sarah Hesham Ahmed Mohamed EweisDepartment of General Dentistry, Nova international medical complex, Jeddah, Makkah, Saudi Arabia.
Rani Kumari GuptaDepartment of Prosthodontics, CDER AIIMS New Delhi, India.
Rashmi RathoreDepartment of Periodntics, Modern Dental College and Research Center, Indore, Madhya Pradesh, India.
Pratiksha TripathiDepartment of Periodontology, Institute of Dental Studies & Technologies, Kadrabad, Uttar Pradesh, India.
Vinita DahiyaDepartment of Periodontology, Institute of Dental Studies & Technologies, Kadrabad, Uttar Pradesh, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Peri-implantitis is often detected only after significant tissue destruction, and conventional diagnostic methods fail to reliably identify early disease activity. Therefore, it is of interest to evaluate the diagnostic efficacy of salivary biomarkers-interleukin-1β (IL-1β), matrix metalloproteinase-8 (MMP-8) and tumour necrosis factor-alpha (TNF-α)-by comparing their concentrations in patients with healthy peri-implant tissues and those with peri-implantitis. Fifty participants were divided into two equal groups, saliva samples were collected and analysed using ELISA and clinical parameters such as probing depth, bleeding on probing and radiographic bone loss were recorded. Statistical analysis (t-tests and correlations, p < 0.05) revealed significantly elevated levels of IL-1β, MMP-8 and TNF-α in peri-implantitis patients, with IL-1β and MMP-8 strongly correlating with probing depth and TNF-α moderately correlating with bone loss. Thus, we show that salivary IL-1β, MMP-8 and TNF-α show strong potential as reliable, non-invasive biomarkers for early detection and monitoring of peri-implantitis.

Indexed as

biomarkersearly diagnosisinterleukin-1βMMP-8peri-implantitisSalivaTNF-α

Identifiers

PMID41907937
PMCPMC13018351

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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.