Taiwanese Journal of Obstetrics & Gynecology (Jun 2014)

Correlation of plasma osteopontin and neutrophil gelatinase-associated lipocalin levels with the severity and clinical outcome of pelvic inflammatory disease

  • Yi-Torng Tee,
  • Po-Hui Wang,
  • Shun-Fa Yang,
  • Hsiu-Ting Tsai,
  • Shu-Kuei Lee,
  • Jiunn-Liang Ko,
  • Long-Yau Lin,
  • Shiuan-Chih Chen

DOI
https://doi.org/10.1016/j.tjog.2014.04.006
Journal volume & issue
Vol. 53, no. 2
pp. 158 – 161

Abstract

Read online

Objective: To investigate the correlation of two important inflammatory biomarkers, plasma osteopontin and neutrophil gelatinase-associated lipocalin (NGAL), with the severity and outcome of pelvic inflammatory disease (PID). Materials and methods: Sixty-one patients with PID, including 25 patients with tubo-ovarian abscess (TOA), were consecutively recruited. Their blood samples were tested for the concentrations of plasma osteopontin and NGAL using enzyme-linked immunosorbent assay. The associations of these biomarkers with TOA, length of hospitalization, and incidence of surgery were also analyzed. Results: Plasma osteopontin level was significantly increased in PID patients with TOA compared to PID patients without TOA (median 107.77 ng/mL vs. 72.39 ng/mL, p = 0.004). However, there was no significant difference for plasma NGAL. If the cutoff level of plasma osteopontin was set at 81.1 ng/mL, there was a 76.0% sensitivity and a 24.0% false negative rate in predicting TOA in PID patients. Plasma osteopontin significantly correlated with length of hospital stay (r = 0.467, p < 0.001), and this correlation was better than that of NGAL. However, neither biomarker was associated with incidence of surgery. Conclusion: Plasma osteopontin has a better correlation with TOA and length of hospitalization compared to NGAL. If plasma osteopontin level falls below 81.1 ng/mL, PID patients will have about a 20% chance of developing TOA. Incorporating plasma osteopontin, but not NGAL, will allow for an adjuvant diagnostic biomarker for TOA and predictor of length of hospital stay.

Keywords