Evidence map›Paper›PMID 35794524›Full record

ArticleBMC pregnancy and childbirth2022

Simple method for identification of women at risk of gestational diabetes mellitus in Arusha urban, Tanzania.

Safiness Simon Msollo, Haikael David Martin, Akwilina Wendelin Mwanri, Pammla Petrucka

Open access · goldAbstract read
In one paragraph

Article in BMC pregnancy and childbirth, 2022. 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
0.7field-weighted citation impact, top 29% 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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Observational
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 3 institutions in 2 countries.

Safiness Simon MsolloDepertment of Food Technology, Nutrition and Consumer Sciences, Sokoine University of Agriculture, Morogoro, Tanzania. msollosafiness@yahoo.co.uk.
Haikael David MartinSchool of Life Sciences, Nelson Mandela African Institution of Science and Technology, Arusha, Tanzania.
Akwilina Wendelin MwanriDepertment of Food Technology, Nutrition and Consumer Sciences, Sokoine University of Agriculture, Morogoro, Tanzania.
Pammla PetruckaCollege of Nursing, University of Saskatchewan, Saskatoon, Canada.
Sokoine University of Agriculture · TZNelson Mandela African Institution of Science and Technology · TZUniversity of Saskatchewan · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundScreening for gestational diabetes mellitus in Tanzania is challenged by limited resources. Therefore, this study aimed to develop a simple method for identification of women at risk of gestational diabetes mellitus in Arusha urban, Tanzania.

methodsThis study used data from a cross sectional study, that was conducted between March and December 2018 in Arusha District involving 468 pregnant women who were not known to have diabetes before pregnancy. Urine glucose was tested using urine multistics and blood glucose levels by Gluco-Plus™ and diagnosed in accordance with the World Health Organization's criteria. Anthropometrics were measured using standard procedures and maternal characteristics were collected through face-to-face interviews using a questionnaire with structured questions. Univariate analysis assessed individual variables association with gestational diabetes mellitus where variables with p-value of < 0.05 were included in multivariable analysis and predictors with p-value < 0.1 remained in the final model. Each variable was scored based on its estimated coefficients and risk scores were calculated by multiplying the corresponding coefficients by ten to get integers. The model's performance was assessed using c-statistic. Data were analyzed using Statistical Package for Social Science™.

resultsThe risk score included body fat ≥ 38%, delivery to macrosomic babies, mid-upper arm circumference ≥ 28 cm, and family history of type 2 diabetes mellitus. The score correctly identified 98% of women with gestational diabetes with an area under the receiver operating characteristic curve of 0.97 (95% CI 0.96-0.99, p < 0.001), sensitivity of 0.98, and specificity of 0.46.

conclusionThe developed screening tool is highly sensitive and correctly differentiates women with and without gestational diabetes mellitus in a Tanzanian sub-population.

Indexed as

Diabetes, GestationalDiabetes Mellitus, Type 2Cross-Sectional StudiesFemaleHumansPregnancyRisk FactorsTanzaniaChecklistGestational diabetes mellitusRisk scoreTanzania

Identifiers

PMID35794524
PMCPMC9258134
OpenAlexW4283831529

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.