A study on the correlation between albumin-to-alkaline phosphatase ratio and the severity of pelvic inflammatory disease

Objective To evaluate albumin-to-alkaline phosphatase ratio (AAPR) as a pelvic inflammatory disease (PID) severity biomarker and determine PID predictors. Methods This retrospective study included ninety-nine patients with PID, as the experimental group, further classified by severity into mild and severe PID groups. The control group included forty-nine patients who underwent elective surgery for non-inflammatory tubal-ovarian masses in the same period. Relationships between PID severity and general information, vital signs, laboratory indices, and imaging characteristics among the three groups were analyzed. Independent PID severity predictors were determined using multivariate regression analysis. Results (1) Significant differences were observed in body temperature, heart rate, respiratory rate, white blood cell count, neutrophil percentage, absolute neutrophil count, alkaline phosphatase, fibrinogen, neutrophil-to-lymphocyte ratio, and platelet-to-lymphocyte ratio among the mild PID, severe PID, and control groups ( P < 0.001). These indices were positively correlated with disease severity. Meanwhile, absolute lymphocyte count, serum albumin level, and AAPR significantly decreased with disease progression ( P < 0.001). (2) Severe PID group exhibited elevated C-reactive protein, procalcitonin, and pelvic mass diameter compared to the mild group ( P < 0.05). (3) Multivariate analysis confirmed AAPR as an independent predictor of PID severity (OR = 0.0041, 95% CI: 0.0003–0.0519, P < 0.001). (4) ROC curve analysis suggested that AAPR may serve as an indicator for diagnosing severe PID, with an AUC of 0.808 (95% CI: 0.733–0.882). The AUC of AAPR combined with neutrophil percentage was 0.947 (95% CI: 0.914–0.980). (5) The study highlights AAPR's high potential as a biomarker for dynamic treatment monitoring. Conclusions AAPR was negatively correlated with PID severity and was identified as an independent PID severity predictor, providing a new reference for clinical disease monitoring.