Dataset Information

A Bayesian model to estimate the cutoff value of TSH for management of preterm birth.

ABSTRACT:

Background

Determining a thyroid hormone cutoff value in pregnancy is challenging issue and several approaches have been introduced to optimize a utility function. We aimed to estimate the cutoff value of TSH using Bayesian method for prediction of preterm-birth.

Methods

This study was a secondary-analysis of the population-based data collected prospectively within the framework of the Tehran Thyroid and Pregnancy Study. A total of 1,538 pregnant women attending prenatal clinics.

Results

Using Bayesian method resulted a TSH-cutoff of (3.97mIU/L,95%CI:3.95-4.00) for distinguishing pregnant women at risk of preterm-birth. The cutoff was associated with acceptable positive predictive and negative predictive values (0.84,95% CI:0.80-0.88) and 0.92 (95%CI: 0.91-0.94), respectively). In women who were negative for thyroid peroxides antibody (TPOAb) with sufficient urinary iodine concentration (UIC), the TSH cutoff of 3.92 mIU/L(95%CI:3.70-4) had the highest predictive value; whereas in TPOAb positive women with insufficient UIC, the cutoff of 4.0 mIU/L(95%:CI 3.94-4) could better predict preterm birth. Cutoffs estimated in this study are close to the revised TSH value of 4.0mIU/L which is currently recommended by the American Thyroid Association.

Conclusion

Regardless of TPOAb status or iodine insufficiency, risk of preterm labor is increased in pregnant women with TSH value of > 3.92 mIU/L; these women may benefit from Levothyroxine (LT4) therapy for preventing preterm birth.

SUBMITTER: Rahmati M

PROVIDER: S-EPMC10058148 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature

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Publications

A Bayesian model to estimate the cutoff value of TSH for management of preterm birth.

Rahmati Maryam M Nazarpour Sima S Minooee Sonia S Behboudi-Gandevani Samira S Azizi Fereidoun F Tehrani Fahimeh Ramezani FR

PloS one 20230329 3

<h4>Background</h4>Determining a thyroid hormone cutoff value in pregnancy is challenging issue and several approaches have been introduced to optimize a utility function. We aimed to estimate the cutoff value of TSH using Bayesian method for prediction of preterm-birth.<h4>Methods</h4>This study was a secondary-analysis of the population-based data collected prospectively within the framework of the Tehran Thyroid and Pregnancy Study. A total of 1,538 pregnant women attending prenatal clinics.< ...[more]

PMID: 36989309

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Project description:BackgroundPrevious research has documented heterogeneity in the effects of maternal education on adverse birth outcomes by nativity and Hispanic subgroup in the United States. In this article, we considered the risk of preterm birth (PTB) using 9 years of vital statistics birth data from New York City. We employed finer categorizations of exposure than used previously and estimated the risk dose-response across the range of education by nativity and ethnicity.MethodsUsing Bayesian random effects logistic regression models with restricted quadratic spline terms for years of completed maternal education, we calculated and plotted the estimated posterior probabilities of PTB (gestational age < 37 weeks) for each year of education by ethnic and nativity subgroups adjusted for only maternal age, as well as with more extensive covariate adjustments. We then estimated the posterior risk difference between native and foreign born mothers by ethnicity over the continuous range of education exposures.ResultsThe risk of PTB varied substantially by education, nativity and ethnicity. Native born groups showed higher absolute risk of PTB and declining risk associated with higher levels of education beyond about 10 years, as did foreign-born Puerto Ricans. For most other foreign born groups, however, risk of PTB was flatter across the education range. For Mexicans, Central Americans, Dominicans, South Americans and "Others", the protective effect of foreign birth diminished progressively across the educational range. Only for Puerto Ricans was there no nativity advantage for the foreign born, although small numbers of foreign born Cubans limited precision of estimates for that group.ConclusionsUsing flexible Bayesian regression models with random effects allowed us to estimate absolute risks without strong modeling assumptions. Risk comparisons for any sub-groups at any exposure level were simple to calculate. Shrinkage of posterior estimates through the use of random effects allowed for finer categorization of exposures without restricting joint effects to follow a fixed parametric scale. Although foreign born Hispanic women with the least education appeared to generally have low risk, this seems likely to be a marker for unmeasured environmental and behavioral factors, rather than a causally protective effect of low education itself.

Dataset Information

A Bayesian model to estimate the cutoff value of TSH for management of preterm birth.

Background

Methods

Results

Conclusion

Publications

A Bayesian model to estimate the cutoff value of TSH for management of preterm birth.

Similar Datasets

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