Evidence map›Paper›PMID 22448310›Full record

ArticleInternational journal of preventive medicine2012

Establishment of Health Clinics as Mass Screening and Referral Systems for Chronic Non-communicable Diseases in Primary Health Care.

Kamal Heidari, Sayyed Ali Sajjadi, Rezvaneh Hadian, Somayeh Hadi, Ramesh Hosseinkhani, Soudabeh Amini, Zahra Kiani, Ali Ajami, Reza Fadaei, Anahita Shahriari and 1 more

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Article in International journal of preventive medicine, 2012. 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
1.2field-weighted citation impact, top 20% of its field
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

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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, 7 citations in OpenAlex.

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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

11 authors at 1 institution in 1 country.

Kamal HeidariDepartment of Health, Isfahan Provincial Health Office, Isfahan University of Medical Sciences, Isfahan, Iran.
Sayyed Ali Sajjadi
Rezvaneh Hadian
Somayeh Hadi
Ramesh Hosseinkhani
Soudabeh Amini
Zahra Kiani
Ali Ajami
Reza Fadaei
Anahita Shahriari
Kasra Keramatian
Isfahan University of Medical Sciences · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis study aimed to establish a comprehensive screening and referral system for chronic non-communicable diseases (CNCD) in the routine primary health care, and to determine the prevalence of diabetes, pre-diabetes, metabolic syndrome, and dyslipidemia in adult population invited by public announcement to the Health clinics in Isfahan, Iran.

methodsThis survey was conducted from March 2010, and the current paper presents data obtained until November 2011. To provide health services for prevention and control of CNCDs, with priority of type2 diabetes mellitus, Health clinics were established in different parts of Isfahan city with a population of approximately 2,100,000 in Iran. The general populations aged 30 years and above were invited to the Health clinics by public announcement.

resultsA total of 198972 participants were screened. The mean age of participants was 47.8 years (48.5 men, 47.3 women), with a range of 1 to 95 years old and standard deviation of 12.3 years (12.7 men, 12.1 women). Overall, 22% of participants had impaired fasting glucose, 25% had hypercholesterolemia, 31% had hypertriglyceridemia, and 20% had metabolic syndrome.

conclusionThe high prevalence of dysglycemia and diabetes in our survey may serve as confirmatory evidence about the importance of mass screening and early diagnosis of CNCDs' risk factors. Our model of establishing Health clinics, as a comprehensive referral system in the routine primary health care can be adopted by Middle Eastern countries, where CNCDs notably diabetes are an emerging health problem.

Indexed as

diabetesmetabolic syndromepreventionScreening

Identifiers

PMID22448310
PMCPMC3309631
OpenAlexW2152174795

What OpenQuestion holds

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LicenceCC BY-NC-SA
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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.