Evidence map›Paper›PMID 42529058›Full record

ArticleCureus2026

Scanning Electron Microscopic Comparison of Emblica officinalis Extract, EDTA, and Maleic Acid for Smear Layer Removal From Root Canal Dentin.

Lakshmi Sunkara, Sunil Kumar Chennuru, Vamsee Krishna Nallagatla, Sadamsetty Sunil Kumar, Kalluru Subbarathnam Chandrababu, Ramisetty Bharathisuma

Abstract read
In one paragraph

Article in Cureus, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Lakshmi SunkaraConservative Dentistry and Endodontics, Chadalawada Krishna Srinivasa (CKS) Teja Institute of Dental Sciences and Research, Tirupati, IND.
Sunil Kumar ChennuruConservative Dentistry and Endodontics, Chadalawada Krishna Srinivasa (CKS) Teja Institute of Dental Sciences and Research, Tirupati, IND.
Vamsee Krishna NallagatlaConservative Dentistry and Endodontics, Chadalawada Krishna Srinivasa (CKS) Teja Institute of Dental Sciences and Research, Tirupati, IND.
Sadamsetty Sunil KumarConservative Dentistry and Endodontics, Chadalawada Krishna Srinivasa (CKS) Teja Institute of Dental Sciences and Research, Tirupati, IND.
Kalluru Subbarathnam ChandrababuConservative Dentistry and Endodontics, Chadalawada Krishna Srinivasa (CKS) Teja Institute of Dental Sciences and Research, Tirupati, IND.
Ramisetty BharathisumaConservative Dentistry and Endodontics, Chadalawada Krishna Srinivasa (CKS) Teja Institute of Dental Sciences and Research, Tirupati, IND.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFormation of a smear layer during canal preparation impedes the penetration of irrigants, medicaments, and sealers, posing a challenge to optimal endodontic results. This study compared the efficacy of 6.25%

methodsA total of 48 single-rooted human teeth extracted with fully developed apices were decoronated, standardized to 17 mm, and instrumented using a hybrid technique. Samples were randomly assigned to four groups of 12 (n = 12) as follows: group I - 17% EDTA, group II - 6.25%

resultsSeven percent maleic acid demonstrated significantly greater smear layer removal in the apical and middle thirds than the other irrigants (p < 0.05). Seventeen percent EDTA showed comparable efficacy in the coronal third. The 6.25% aqueous extract of

conclusionsMaleic acid at 7% emerged as the most effective irrigant for smear layer removal, surpassing 17% EDTA, 6.25% aqueous extract of

Indexed as

edtaemblica officinalismaleic acidroot canal irrigationscanning electron microscopysmear layer

Identifiers

PMID42529058
PMCPMC13416120

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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.