Evidence map›Paper›PMID 40448336›Full record

Observational studyJournal of evidence-based integrative medicine

Efficacy and Safety of an Ayurveda Herbal Formulation in Uncomplicated Type 2 Diabetes mellitus.

Bilesha Perera, Colvin Goonaratna, Hettiarchchige Ariyawansa, Nirmala Senaratna, Jennifer Perera

Abstract readObservational Study
In one paragraph

Observational study in Journal of evidence-based integrative medicine. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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

2 citing papers in PubMed.

  1. Review
  2. Review
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.

Bilesha PereraDepartment of Community Medicine, Faculty of Medicine, University of Ruhuna, Galle, Sri Lanka.ORCID 0000-0001-5398-710X
Colvin GoonaratnaFaculty of Medicine, University of Colombo, Colombo, Sri Lanka.
Hettiarchchige AriyawansaInstitute of Indigenous Medicine, University of Colombo, Sri Lanka.
Nirmala SenaratnaDistrict Ayurveda Hospital, Western Province, Sri Lanka.ORCID 0009-0002-7324-704X
Jennifer PereraFaculty of Medicine, University of Colombo, Colombo, Sri Lanka.ORCID 0000-0002-7450-5672

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BackgroundMedicinal plants and herbal preparations have been used in Ayurveda medicine to treat diabetes for centuries. Link Gluconorm (LG) is a standardized solid formulation comprising seven medicinal herbs that have been used as herbal ingredients in Ayurveda for treating type 2 diabetes mellitus (T2DM). This study evaluated the efficacy and safety of the solid form of LG, and its effect on the quality of life (QoL) in T2DM patients.Materials and methodsAn observational study was conducted on 37 newly diagnosed uncomplicated T2DM patients aged between 35 and 65 years, whose fasting blood glucose levels ranged between 110 and 160 mg/dL. They were being treated for diabetes using the LG herbal formulation as the sole treatment. Laboratory tests for assessing glycemic control and safety were done at baseline and repeated at 4-weekly intervals for 24-weeks. A validated diabetes-specific QoL inventory was administered every 2 weeks.ResultsThe mean age was 48 ± 9y, and the mean body mass index was 25.0 ± 4.4 kg/m

Indexed as

Diabetes Mellitus, Type 2Hypoglycemic AgentsMedicine, AyurvedicPhytotherapyPlant ExtractsPlant PreparationsAdultAgedBlood GlucoseFemaleGlycated HemoglobinHumansMaleMiddle AgedQuality of LifeTreatment OutcomeBlood GlucoseGlycated HemoglobinHypoglycemic AgentsPlant ExtractsPlant Preparationsayurvedaefficacypolyherbalquality of lifesafetytype 2 diabetes

Identifiers

PMID40448336
PMCPMC12125513

What OpenQuestion holds

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Registered trials

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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.