Evidence map›Paper›PMID 29211197›Full record

ReviewRevista latino-americana de enfermagem2017

Development and validation of an algorithm for laser application in wound treatment.

Diequison Rite da Cunha, Geraldo Magela Salomé, Marcelo Renato Massahud, Bruno Mendes, Lydia Masako Ferreira

Abstract readReviewValidation Study
In one paragraph

Review in Revista latino-americana de enfermagem, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. 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

5 authors.

Diequison Rite da CunhaMSc, Adjunct Professor, Phisiotherapy Department, Centro Universitário de Formiga , Formiga, MG, Brasil.
Geraldo Magela SaloméPhD, Associate Professor, Universidade do Vale do Sapucaí, Pouso Alegre, MG, Brazil.
Marcelo Renato MassahudMSc, Adjunct Professor, Phisiotherapy Department, Universidade do Vale do Sapucaí, Pouso Alegre, MG, Brazil.
Bruno MendesMSc, Adjunct Professor, Phisiotherapy Department, Universidade do Vale do Sapucaí, Pouso Alegre, MG, Brazil.
Lydia Masako FerreiraPós-Doctoral degree, Full Professor, Plastic Surgery discipline, Universidade Federal de São Paulo, São Paulo, SP, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo develop and validate an algorithm for laser wound therapy.

methodMethodological study and literature review. For the development of the algorithm, a review was performed in the Health Sciences databases of the past ten years. The algorithm evaluation was performed by 24 participants, nurses, physiotherapists, and physicians. For data analysis, the Cronbach's alpha coefficient and the chi-square test for independence was used. The level of significance of the statistical test was established at 5% (p<0.05).

resultsThe professionals' responses regarding the facility to read the algorithm indicated: 41.70%, great; 41.70%, good; 16.70%, regular. With regard the algorithm being sufficient for supporting decisions related to wound evaluation and wound cleaning, 87.5% said yes to both questions. Regarding the participants' opinion that the algorithm contained enough information to support their decision regarding the choice of laser parameters, 91.7% said yes. The questionnaire presented reliability using the Cronbach's alpha coefficient test (α = 0.962).

conclusionThe developed and validated algorithm showed reliability for evaluation, wound cleaning, and use of laser therapy in wounds.

Indexed as

AlgorithmsLaser TherapyWound HealingHumans

Identifiers

PMID29211197
PMCPMC5738875

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.