Evidence map›Paper›PMID 27864668›Full record

ReviewAdvances in therapy2017

Unproven Therapies for Diabetes and Their Implications.

Jothydev Kesavadev, Banshi Saboo, Shaukat Sadikot, Ashok Kumar Das, Shashank Joshi, Rajeev Chawla, Hemant Thacker, Arun Shankar, Lakshmy Ramachandran, Sanjay Kalra

Abstract readReview
In one paragraph

Review in Advances in therapy, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing 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

23 citing papers in PubMed.

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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

10 authors.

Jothydev KesavadevJothydev's Diabetes Research Centre, Trivandrum, Kerala, India. jothydev@gmail.com.
Banshi SabooDia Care and Hormone Clinic, Ahmedabad, Gujarat, India.
Shaukat SadikotDepartment of Endocrinology/Diabetology, Jaslok Hospital and Research Centre, Mumbai, India.
Ashok Kumar DasDepartment of Endocrinology, Jawaharlal Institute of Postgraduate Medical Education and Research, Puducherry, India.
Shashank JoshiDepartment of Diabetology, Lilavati Hospital and Research Centre, Mumbai, India.
Rajeev ChawlaNorth Delhi Diabetes Centre, New Delhi, India.
Hemant ThackerDepartment of Endocrinology, Bhatia Hospital, Mumbai, India.
Arun ShankarJothydev's Diabetes Research Centre, Trivandrum, Kerala, India.
Lakshmy RamachandranJothydev's Diabetes Research Centre, Trivandrum, Kerala, India.
Sanjay KalraDepartment of Endocrinology, Bharati Hospital, Karnal, Haryana, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Diabetes is a chronic disease and is one of the leading causes of morbidity and mortality worldwide. Being an ancient disease, many individuals follow complementary and alternative medicinal (CAM) therapies for either the cure or prevention of the disease. The popularity of these practices among the general public is in no way a testimony to their safety and efficacy. Due to the possibility of undesirable interactions with conventional medicines, it is imperative that patients are asked about CAM use during patient assessment. Patient- and physician-targeted awareness programs on various aspects of CAM use must be initiated to create a better understanding of evidence-based use of these practices. In addition, there should be guidelines in place based on clinical trial outcomes, and stricter regulations need to be enforced on CAM practices to ensure their safety and effectiveness.

Indexed as

Chronic DiseaseComplementary TherapiesDiabetes MellitusHumansAyurvedaCAMComplementary and alternative medicineDiabetesHerbal medicineSupplementsTMTraditional medicine

Identifiers

PMID27864668
PMCPMC5216071

What OpenQuestion holds

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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.