Evidence map›Paper›PMID 42087087›Full record

Trial reportBMC pregnancy and childbirth2026

Vitamin D deficiency and supplementation in pregnancy: a clinical trial using an irregular fuzzy cellular automata model.

Mostafa Kashani, Mehran Kamani, Sedigheh Barzekar, Maryam Rostami

Abstract readClinical Trial
In one paragraph

Trial report in BMC pregnancy and childbirth, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Mostafa KashaniSirjan School of Medical Sciences, Sirjan, Iran.
Mehran KamaniSirjan School of Medical Sciences, Sirjan, Iran. m6326726@gmail.com.
Sedigheh BarzekarSirjan School of Medical Sciences, Sirjan, Iran.
Maryam RostamiDepartment of Social Medicine, Faculty of Medicine, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran. mehrankamany@yahoo.com.

Funding

Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran, 9ECRIES92/10/25 9ECRIES92/10/25
6 · The paper itself

Abstract

backgroundPregnant women need enough vitamin D for healthy pregnancies, but many women in Iran's Khuzestan province don't get sufficient sunlight to produce vitamin D naturally. In this study, we aimed to determine how many pregnant women have low vitamin D levels and to test different methods of providing vitamin D supplements. We also sought to assess whether our new algorithm model, called Irregular Fuzzy Cellular Automata (IFCA), performs better than older methods for predicting pregnancy complications.

methodsWe examined 2,481 pregnant women who participated in this study in two Iranian cities between 2014 and 2016. Women with vitamin D blood levels below 20 ng/mL were considered to have low vitamin D. We selected 800 women with moderate or severe vitamin D deficiency (25(OH)D < 50 nmol/L) and assigned them to eight groups receiving different combinations of injectable and oral supplementation regimens. We assessed maternal complications such as gestational hypertension, diabetes, preterm birth, and premature rupture of membranes. For babies, we evaluated their weight, length, head size, and vitamin D levels in their cord blood. We compared how well our new IFCA model worked against older methods by evaluating its accuracy compared to them.

resultsOur results indicate that 85% of the women had low vitamin D levels, with approximately 38% exhibiting severe deficiency. After taking supplements, the average vitamin D level in mothers went up to 24.1 ± 3.2 ng/mL (p < 0.001). Mothers' vitamin D levels matched closely with their babies' levels (r = 0.82, p < 0.001). Only 0.6% of women developed high blood pressure during pregnancy, but we found that being overweight and having high blood pressure were bigger problems (OR = 2.3, p = 0.032) than low vitamin D alone. Our IFCA model worked better than older methods, achieving an accuracy of 89% with an AUC of 0.92 (p < 0.01).

conclusionLow vitamin D is very common in pregnant women who don't get much sunlight, but providing them with supplements can address this issue. Both injection and pill forms of vitamin D helped bring levels back to normal. Our new IFCA model was better at finding women who might have pregnancy problems than older methods. Doctors should monitor vitamin D levels early in pregnancy and utilize improved tools to help ensure the health of mothers and babies.

trial registrationThis study was registered in the Iranian Registry of Clinical Trials (IRCT) under the code IRCT2014102519660N1. Registered on 15 January 2014 at www.irct.ir .

Indexed as

Dietary SupplementsPregnancy ComplicationsVitamin DVitamin D DeficiencyAdultAlgorithmsFemaleFuzzy LogicHumansIranPregnancyYoung AdultVitamin DCellular AutomataPre-EclampsiaPregnancyPregnancy ComplicationsPrenatal NutritionVitamin D Deficiency

Identifiers

PMID42087087
PMCPMC13317318

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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.