Back

Beta-HCG levels and ovarian ultrasonography results among non-pregnant women of reproductive age in Port Harcourt, Nigeria

Agonsi, C. C.; Anacletus, F.; Aluko, J.; Eleke, C.; Samuel, J.

2023-07-13 nursing
10.1101/2023.07.05.23292265 medRxiv
Show abstract

BackgroundCertain ovarian cancers previously more common in postmenopausal women are now increasingly observed in women of reproductive age. The research on using {beta}-HCG as a diagnostic biomarker for ovarian cancer in women of reproductive age is ongoing. This particular study assessed the level of serum {beta}-HCG in non-pregnant women of reproductive age and determined its potential association with suspicious ovarian ultrasonography results in Port Harcourt, Nigeria. Material and methodsThis study utilized a descriptive-analytic design on a quota sample of 224 diagnostic case notes of women aged 18-40 years obtained from eight diagnostic centres. Data collection involved a data extraction form. Data analysis employed descriptive statistics, Chi-square, Fishers exact test, and Odds Ratio at 95% confidence and 5% significance levels. ResultsAbout 5.8% of the participants exhibited detectable levels of serum {beta}-HCG above 5 IU/L (World Health Organization reference) at a mean concentration of 5.87 ({+/-}1.75) IU/L. About 4.0% of the participants had suspicious ovarian lesions identified through ultrasonography. Participants with elevated serum {beta}-HCG levels above the WHO reference were 59 times more likely to have suspicious ovarian lesions, with an odds ratio of 59.4 (95%CI: 12.3-287.8, p = 0.001). There was a significant association between serum {beta}-HCG level and age (p = 0.041) as well as parity (p < 0.001). ConclusionsThis study demonstrated that Serum {beta}-HCG levels above the WHO reference were associated with suspicious ovarian lesions. Non-pregnant women should undergo serum {beta}-HCG testing at least yearly to facilitate the early detection of ovarian anomalies.

Matching journals

The top 1 journal accounts for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.