Evidence map›Paper›PMID 37576764›Full record

ArticleVeterinary world2023

Effectiveness of ozone-laser photodynamic combination therapy for healing wounds infected with methicillin-resistant

Suryani Dyah Astuti, Wahyu Intan Pertiwi, Sri Puji Astuti Wahyuningsih, Perwira Annissa Dyah Permatasari, Dezy Zahrotul Istiqomah Nurdin, Ardiansyah Syahrom

Abstract read
In one paragraph

Article in Veterinary world, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

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

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. 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.

Suryani Dyah AstutiDepartment of Physics, Faculty of Science and Technology, Airlangga University, Surabaya, 60115, Indonesia.
Wahyu Intan PertiwiDepartment of Physics, Faculty of Science and Technology, Airlangga University, Surabaya, 60115, Indonesia.
Sri Puji Astuti WahyuningsihDepartment of Biology, Faculty of Science and Technology, Airlangga University, Surabaya, 60115, Indonesia.
Perwira Annissa Dyah PermatasariDepartment of Mathematics, Faculty of Science and Technology, Airlangga University, Surabaya, 60115, Indonesia.
Dezy Zahrotul Istiqomah NurdinDepartment of Physics, Faculty of Science and Technology, Airlangga University, Surabaya, 60115, Indonesia.
Ardiansyah SyahromDepartment of Applied Mechanics and Design, Faculty of Mechanical Engineering, Universiti Teknologi Malaysia, Johor Bahru, 81310, Malaysia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and Aim: According to 2013 data from the Ministry of Health of the Republic of Indonesia, there were 8.2% more wounds than typical in Indonesia; 25.4% were open wounds, 70.9% were abrasions and bruises, and 23.2% were lacerations. A wound is defined as damage or loss of body tissue. This study aimed to determine the effectiveness of wound healing using red-laser therapy (650 nm, 3.5 J/cm Materials and Methods: One hundred and twelve mice were given incision wounds and infected with methicillin-resistant Results: Acceleration of wound healing was significantly different between treatments with a laser or a laser-ozone combination and treatment using 95% sodium chloride (NaCl) and Sofra-tulle Conclusion: The blue- and red-laser combined with ozone treatments effectively accelerated the healing of incisional wounds infected with MRSA bacteria.

Indexed as

Blue-lasermethicillin-resistant Staphylococcus aureusozone therapyred-laser

Identifiers

PMID37576764
PMCPMC10420723

What OpenQuestion holds

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LicenceCC BY
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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.