Evidence map›Paper›PMID 29546113›Full record

ArticleAIMS public health2015

Evaluation and Use of Registry Data in a GIS Analysis of Diabetes.

Mungrue Kameel, Sankar Steven, Kamalodeen Aleem, Lalchansingh Dayna, Ramnarace Demeytri, Samodee Shanala, Sookhan Craig, Sookar Navin, Sooknanan Kristal, St George Leah and 1 more

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Article in AIMS public health, 2015. 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. Article
  2. 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

11 authors.

Mungrue KameelUniversity of the West Indies, Faculty of Medical Sciences, Department of Paraclinical Sciences, Public Health and Primary Care Unit, India.
Sankar StevenUniversity of the West Indies, Faculty of Medical Sciences, Department of Paraclinical Sciences, Public Health and Primary Care Unit, India.
Kamalodeen AleemUniversity of the West Indies, Faculty of Medical Sciences, Department of Paraclinical Sciences, Public Health and Primary Care Unit, India.
Lalchansingh DaynaUniversity of the West Indies, Faculty of Medical Sciences, Department of Paraclinical Sciences, Public Health and Primary Care Unit, India.
Ramnarace DemeytriUniversity of the West Indies, Faculty of Medical Sciences, Department of Paraclinical Sciences, Public Health and Primary Care Unit, India.
Samodee ShanalaUniversity of the West Indies, Faculty of Medical Sciences, Department of Paraclinical Sciences, Public Health and Primary Care Unit, India.
Sookhan CraigUniversity of the West Indies, Faculty of Medical Sciences, Department of Paraclinical Sciences, Public Health and Primary Care Unit, India.
Sookar NavinUniversity of the West Indies, Faculty of Medical Sciences, Department of Paraclinical Sciences, Public Health and Primary Care Unit, India.
Sooknanan KristalUniversity of the West Indies, Faculty of Medical Sciences, Department of Paraclinical Sciences, Public Health and Primary Care Unit, India.
St George LeahUniversity of the West Indies, Faculty of Medical Sciences, Department of Paraclinical Sciences, Public Health and Primary Care Unit, India.
Suruj DeonathUniversity of the West Indies, Faculty of Medical Sciences, Department of Paraclinical Sciences, Public Health and Primary Care Unit, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesto evaluate registry data routinely collected by the Chronic Disease Electronic Management System (CDEMS) in the monitoring of type 2 diabetes mellitus (T2DM) in the Eastern half of the island and use the data to describe the spatial epidemiological patterns of T2DM. DESIGN AND

methodThe starting point was access and retrival of all exsisting data on the diabetes registry. This data was subsequently validated using handwritten medical records. Several clinical indicators were selected to evaluate the registry. The address of each patient was extracted and georeferenced using ArcGIS 10.0 and several maps were created.

resultsThe registry had data for thirteen (13) out of the sixteen (16) health facilities. We found that less than 15 percent of all patients actually had diabetic indicator tests done according to World Health Organization (WHO) standards. The overall prevalence of T2DM was 20.8 per 1000 population. The highest prevalence of diabetes occurred at the northeastern tip of the island. In addition 57.58% of patients with T2DM resided inland and 40.75% of patients residing on the coastal areas.

conclusionsIn conclusion, we provide evidence that the data collected by the diabetes registry although lacking in many areas was adequate for spatial epidemiological analysis.

Indexed as

GISspatial epidemiologytype 2 diabetes mellitus

Identifiers

PMID29546113
PMCPMC5690238

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