Screening for Thyroid Disorder in First Trimester of Pregnancy: A Cross-Sectional Study
Bibliographic record
Abstract
Background: Alteration in thyroid function is very common among females, in particular during pregnancy. The majority of them are clinically veiled, and with considerable differences in outcome of mother and fetus, even more serious maternal and fetal outcome if present during the first trimester. So, we conducted this study to explore the magnitude of thyroid problems during first trimester of pregnancy at a tertiary health care facility in Nepal and highlight the benefits of its early diagnosis. Methods: This was a cross-sectional study conducted over a period of 1 year among 160 pregnant females in their first trimester, attending to the outpatient department of a tertiary care center. Blood samples were collected from all the patients for thyroid function test which included measurement of serum levels of thyroid-stimulating hormone (TSH), free thyroxine (fT4), and free tri-iodothyronine (fT3). Pregnant females with previously diagnosed thyroid disorders or currently under medications were excluded. Results: Among the 160 patients included in the study, 25.83 years was the mean age. The mean body mass index (BMI) was 24.62 kg/m 2 and most of the patients were overweight (40.625%). Of the patients 53.12% were primigravida and 46.87% were multigravida. Based on the thyroid function tests, 91.25% were found to be euthyroid, 3.125% were hyperthyroid and 5.625% were hypothyroid. The prevalence of subclinical hyperthyroidism and overt hyperthyroidism was found to be 60% and 40% respectively and that of subclinical hypothyroidism and overt hypothyroidism was 55.6% and 44.4% respectively. None of the patients had symptoms of thyroid disorder (neither hyperthyroidism nor hypothyroidism). The correlation between BMI and TSH among the pregnant females included in the study was statistically significant when tested by using Karl Pearson correlation coefficient (r = 0.164, P = 0.038). Conclusions: Based on this study, around one in every 12 pregnant women had thyroid disorder. Early identification of thyroid disorders and prompt initiation of treatment is very essential for the health of mother and fetus due to the significant maternal or fetal morbidity and mortality associated with thyroid disorders. Thus, routine screening for thyroid disorder should be considered during pregnancy. J Clin Gynecol Obstet. 2023;12(2):52-58 doi: https://doi.org/10.14740/jcgo880
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".