Item request has been placed! ×
Item request cannot be made. ×
loading  Processing Request

Diagnostic Power of Pregnancy-Associated Plasma Protein-A (PAPP-A) for Identifying Preeclampsia in Pregnant Women: A Case-Control Study.

Item request has been placed! ×
Item request cannot be made. ×
loading   Processing Request
Read Online Read More Add to Saved list
  • Additional Information
    • Subject Terms:
      Iran
    • Abstract:
      Background & Objective: Pregnancy-Associated Plasma Protein-A (PAPP-A) has emerged as a potential biomarker for assessing the risk of preeclampsia. This study was conducted with aim to assess the diagnostic power of Pregnancy-Associated Plasma Protein-A (PAPP-A) for identifying preeclampsia in pregnant women attending medical facilities in Zahedan, Iran. Materials & Methods: This case-control study was conducted on 30 pregnant women diagnosed with preeclampsia as the case group and 120 pregnant women without preeclampsia as the control group. Participants were selected from Edalat Clinic and Ali Ibn Abi Talib Hospital between 2020 and 2021. Data concerning PAPP-A levels were extracted from medical records. The diagnostic performance of PAPP-A was evaluated using the Area Under the ROC Curve (AUROC), along with sensitivity, specificity, and the Youden index. Results: The mean PAPP-A levels were significantly different between the groups, with case and control groups measuring 0.74±0.33 MoM and 1.14±0.71 MoM, respectively (P<0.001). The AUROC for PAPP-A in preeclampsia was found to be 0.72 (P<0.001). An optimal cutoff value of 0.69 MoM for PAPP-A demonstrated a sensitivity of 0.66, specificity of 0.80, and a Youden index of 0.46. Conclusion: This study revealed that PAPP-A has the potential as a serum marker for early detection of preeclampsia during the first trimester, helping to identify and manage this outcome. [ABSTRACT FROM AUTHOR]
    • Abstract:
      Copyright of Journal of Obstetrics, Gynecology & Cancer Research is the property of Iranian Society of Gynecology Oncology (IRSGO) and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)