Evidence map›Paper›PMID 20217177›Full record

ArticleInternational journal of public health2010

San Antonio heart study diabetes prediction model applicable to a Middle Eastern population? Tehran glucose and lipid study.

Mohammadreza Bozorgmanesh, Farzad Hadaegh, Azadeh Zabetian, Fereidoun Azizi

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Article in International journal of public health, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
0.9field-weighted citation impact, top 23% 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

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

5 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.

  1. Pooled it
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  3. Article
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  5. Survival Regression Modeling Strategies in CVD Prediction.International journal of endocrinology and metabolism · 2016
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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

4 authors at 2 institutions in 1 country.

Mohammadreza BozorgmaneshPrevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Islamic Republic of Iran. mr_bozorgmanesh@endocrine.ac.ir
Farzad Hadaegh
Azadeh Zabetian
Fereidoun Azizi
Research Institute for Endocrine Sciences · IRShahid Beheshti University of Medical Sciences · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo assess the validity of the San Antonio heart study (SAHS) diabetes prediction model in a large representative Iranian population.

methodsA risk function derived from data in the SAHS to predict the 7.5-year risk of diabetes, was tested for its ability to predict incident diabetes in 3,242 individuals aged >or=20 years. The performance or ability to accurately predict diabetes risk, of the SAHS function compared with the performance of risk functions developed specifically from the Tehran lipid and glucose study. Comparisons included goodness of fit, discrimination, and calibration.

resultsThe participants were followed for 6.3 years. The area under the receiver operating characteristic curve (AROC) for diabetes of SAHS model was 0.83 (95% CI 0.80-0.86). The model overestimated the risk of diabetes in TLGS population with the overall bias of 111%. After the recalibration, the model-predicted probability agreed well with the actual observed 6-year risk of diabetes. DISCUSSION AND

conclusionThe American SAHS was a prediction model for diabetes with good discrimination in an Iranian target population after calibration.

Indexed as

Blood GlucoseModels, StatisticalAdultAge DistributionBody Weights and MeasuresDiabetes Mellitus, Type 2FemaleHumansIranLipidsMaleMiddle AgedPredictive Value of TestsROC CurveSex DistributionTexasBlood GlucoseLipids

Identifiers

PMID20217177
OpenAlexW2114310978

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.