Evidence map›Paper›PMID 35003303›Full record

ArticleEvidence-based complementary and alternative medicine : eCAM2021

Medicinal Plants Used in Ethnoveterinary Practices in Adea Berga District, Oromia Region of Ethiopia.

Megersa Feyisa, Addis Kassahun, Mirutse Giday

Abstract read
In one paragraph

Article in Evidence-based complementary and alternative medicine : eCAM, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. 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

3 authors.

Megersa FeyisaFaculty of Veterinary Medicine, Hawassa University, P.O. Box 05, Hawassa, Ethiopia.
Addis KassahunFaculty of Veterinary Medicine, Hawassa University, P.O. Box 05, Hawassa, Ethiopia.
Mirutse GidayAklilu Lemma Institute of Pathobiology, Addis Ababa University, P.O. Box 1176, Addis Ababa, Ethiopia.ORCID https://orcid.org/0000-0001-7533-0379

Funding

NRSA Training CoreTL1TR002016 · NCATS · PENNSYLVANIA STATE UNIV HERSHEY MED CTR · PI THOMAS, GAIL D. · 2016 to 2025
$3.4M
NCATS NIH HHS TL1 TR002016
6 · The paper itself

Abstract

In Ethiopia, locally available materials, mainly medicinal plants, are commonly utilized to manage livestock diseases. However, this practice is currently being threatened by several factors including loss of traditional knowledge and depletion of plant resources. This calls for an urgent need to document the ethnoveterinary knowledge in the country and conserve the associated medicinal plants. The purpose of this study was, therefore, to document traditional knowledge on use of medicinal plants in the Adea Berga district, Oromia region of Ethiopia, to manage livestock ailments. Ethnobotanical data were collected largely through semistructured interviews conducted with purposively selected traditional healers of the district. The study identified 59 medicinal plants used in ethnoveterinary practices in the district. The great majority (90.4%) of the medicinal plants were used in fresh forms, which were mainly administered orally. The majority (65.4%) of the medicinal plants were gathered from the wild. Data revealed that yoke sore (wound) had the highest informant consensus factor (ICF) value (1.00), followed by leech infestation (0.92) and endoparasite infections (0.90). The highest fidelity level (FL) (100%) and rank order priority (ROP) (100%) values were obtained for the plants

Identifiers

PMID35003303
PMCPMC8739178

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.