Diagnostic Accuracy of Female Pelvic Ultrasonography in Differentiating Precocious Puberty From Premature Thelarche: A Systematic Review and Meta-analysis

Nguyen, Nam Nhat; Huynh, Linh Ba Phuong; M, Duc; Yang, Tien Yun; Tsai, Meng‐Che; Chen, Yang Ching

doi:10.3389/fendo.2021.735875

Cited by 10 publications

(9 citation statements)

References 34 publications

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“…Ovarian volume and the quantity of large follicles are generally inferior markers of puberty onset compared with uterine parameters 11 , 33 . On the other hand, a recent systematic review and meta-analysis of 13 studies found that girls with CPP had significantly greater uterine and ovarian measurements, and a uterine length greater than 3.20 cm was a reliable marker to differentiate CPP from IPT with a diagnostic odds ratio of 19.62 and an area under the curve of 0.820 34 . However, the PI was not evaluated in this meta-analysis.…”

Section: Discussionmentioning

confidence: 99%

Accuracy of doppler assessment of the uterine arteries for the diagnosis of pubertal onset in girls: a scoping review

Cheuiche

Moro

Lucena

et al. 2023

Sci Rep

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The uterine artery pulsatility index (PI) assessed by Doppler ultrasound reflects the impedance to the blood flow in the vessel distal to the sampling point. We aimed to assess the accuracy of the uterine artery PI for the diagnosis of puberty in girls. A PRISMA-ScR-compliant scoping review was performed in the MEDLINE and Embase databases with the search terms “puberty” and “Doppler ultrasonography”. Studies that included girls aged 0–18 years who underwent pelvic Doppler ultrasound with calculation of uterine artery PI were eligible. Ten studies comprising 1385 girls aged 1.2–18 years were included. The selected studies included participants from Italy, Brazil, Iran, Belgium and Denmark, and were published between 1996 and 2021. Six studies selected girls who were referred for evaluation of pubertal disorders, while four studies included only healthy girls. Nine studies found a significant difference in Doppler signal pattern and PI according to pubertal stage, with PI cutoff points ranging from 2.5 to 4.6 for the diagnosis of puberty, with a sensitivity of 77%–94%, specificity of 85%–100%, and accuracy of 79%–98%. Doppler assessment of the uterine arteries with PI calculation is a useful noninvasive tool in the diagnosis of pubertal onset in girls.

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Section: Discussionmentioning

confidence: 99%

Accuracy of doppler assessment of the uterine arteries for the diagnosis of pubertal onset in girls: a scoping review

Cheuiche

Moro

Lucena

et al. 2023

Sci Rep

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“…uterine and ovarian measurements could help to distinguish girls with CPP and isolated premature thelarche [ 14 , 32 , 33 ]. A recent meta-analysis noted that uterine length and volume are important markers for differentiating CPP from premature thelarche, e.g., a uterine length of 3.2 cm had a diagnostic AUC of 0.82, with a sensitivity and specificity of 81.8% and 82.0%, respectively [ 11 ]. FCR is regarded as a crucial indicator of puberty.…”

Section: Discussionmentioning

confidence: 99%

“…Magnetic resonance imaging (MRI) of the brain can be used to determine the presence of brain lesions causing premature pubertal development. [ 10 , 11 ]. The possibility of replacing the GnRHa stimulation test with basal pubertal hormones, such as luteinizing hormone (LH) and routine imaging tests has been continuously reviewed [ 12 – 14 ].…”

Section: Introductionmentioning

confidence: 99%

Basal gonadotropin levels combine with pelvic ultrasound and pituitary volume: a machine learning diagnostic model of idiopathic central precocious puberty

Chen,

Zhang

2023

BMC Pediatr

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Objective The current diagnosis of central precocious puberty (CPP) relies on the gonadotropin-releasing hormone analogue (GnRHa) stimulation test, which requires multiple invasive blood sampling procedures. The aim of this study was to construct machine learning models incorporating basal pubertal hormone levels, pituitary magnetic resonance imaging (MRI), and pelvic ultrasound parameters to predict the response of precocious girls to GnRHa stimulation test. Methods This retrospective study included 455 girls diagnosed with precocious puberty who underwent transabdominal pelvic ultrasound, brain MRI examinations and GnRHa stimulation testing were retrospectively reviewed. They were randomly assigned to the training or internal validation set in an 8:2 ratio. Four machine learning classifiers were developed to identify girls with CPP, including logistic regression, random forest, light gradient boosting (LightGBM), and eXtreme gradient boosting (XGBoost). The accuracy, sensitivity, specificity, positive predictive value, negative predictive value, area under receiver operating characteristic (AUC) and F1 score of the models were measured. Results The participates were divided into an idiopathic CPP group (n = 263) and a non-CPP group (n = 192). All machine learning classifiers used achieved good performance in distinguishing CPP group and non-CPP group, with the area under the curve (AUC) ranging from 0.72 to 0.81 in validation set. XGBoost had the highest diagnostic efficacy, with sensitivity of 0.81, specificity of 0.72, and F1 score of 0.80. Basal pubertal hormone levels (including luteinizing hormone, follicle-stimulating hormone, and estradiol), averaged ovarian volume, and several uterine parameters were predictors in the model. Conclusion The machine learning prediction model we developed has good efficacy for predicting response to GnRHa stimulation tests which could help in the diagnosis of CPP.

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“…Ovarian volume and the quantity of large follicles are generally inferior markers of puberty onset compared with uterine parameters [11,32]. On the other hand, a recent systematic review and meta-analysis of 13 studies found that girls with CPP had signi cantly greater uterine and ovarian measurements, and a uterine length greater than 3.20 cm was a reliable marker to differentiate CPP from IPT with a diagnostic odds ratio of 19.62 and an area under the curve of 0.820 [33]. However, the PI was not evaluated in this meta-analysis.…”

Section: Discussionmentioning

confidence: 99%

Accuracy of Doppler Assessment of the Uterine Arteries for the Diagnosis of Pubertal Onset in Girls: A Scoping Review

Cheuiche

Moro

Lucena

et al. 2022

Preprint

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The uterine artery pulsatility index (PI) assessed by Doppler ultrasound reflects blood flow impedance in the vessel distal to the sampling point. We aimed to evaluate the accuracy of the uterine artery PI for the diagnosis of puberty in girls. A PRISMA-ScR-compliant scoping review was performed in the MEDLINE and Embase databases with “puberty” and “Doppler ultrasonography” as the search terms. Studies that included girls aged 0–18 years who underwent pelvic Doppler ultrasound with calculation uterine artery PI were considered eligible. Ten studies comprising 1385 girls aged 1.2–18 years were included. The selected studies were published between 1996 and 2021 and included participants from Italy, Brazil, Iran, Belgium, and Denmark. Six studies included girls who were referred for evaluation of pubertal disorders, while four studies selected only healthy girls. Nine studies found a significant difference in Doppler and PI according to pubertal stage, with PI cutoff points ranging from 2.5 to 4.6 for the diagnosis of puberty onset, with a sensitivity of 77–94%, specificity of 85–100%, and accuracy of 79–98%. Doppler assessment of the uterine arteries with PI calculation is a useful noninvasive tool in the diagnosis of secondary sexual characteristic onset in girls.

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Diagnostic Accuracy of Female Pelvic Ultrasonography in Differentiating Precocious Puberty From Premature Thelarche: A Systematic Review and Meta-analysis

Cited by 10 publications

References 34 publications

Accuracy of doppler assessment of the uterine arteries for the diagnosis of pubertal onset in girls: a scoping review

Accuracy of doppler assessment of the uterine arteries for the diagnosis of pubertal onset in girls: a scoping review

Basal gonadotropin levels combine with pelvic ultrasound and pituitary volume: a machine learning diagnostic model of idiopathic central precocious puberty

Accuracy of Doppler Assessment of the Uterine Arteries for the Diagnosis of Pubertal Onset in Girls: A Scoping Review

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