Development and validation of a prediction model for hypotension after neuraxial anesthesia in preeclamptic parturients: a multicenter retrospective study
Year: 2025
Type: article
Study design: Observational Study
Abstract: Objective To develop and validate a multivariate prediction model for hypotension following neuraxial anesthesia in preeclamptic parturients. Methods This multicenter retrospective study analyzed 1,402 preeclamptic parturients (gestational age ≥28 weeks) from three tertiary centers (2013–2024). After exclusions (n = 569), 833 patients were allocated to training (n = 495), internal validation (n = 213), and external validation (n = 125) cohorts. Multivariable logistic regression identified independent predictors, with subsequent nomogram construction. Model performance was assessed via discrimination (AUC), calibration (Hosmer-Lemeshow), and clinical utility [decision curve analysis (DCA), clinical impact curves (CIC)]. Results Seven independent predictors were identified: platelet count (OR 0.920, 95%CI 0.876–0.966), sFlt-1/PlGF ratio (OR 1.039, 95%CI 1.002–1.078), baseline perfusion index (OR 0.221, 95%CI 0.101–0.485), T6 anesthesia level (OR 11.353, 95%CI 1.408–29.320), local anesthetic dose (OR 29.391, 95%CI 4.792–38.270), fetal weight (OR 1.004, p = 0.045), and umbilical artery S/D ratio (OR 9.319, p < 0.001). The nomogram demonstrated robust discrimination (training AUC 0.851; internal validation AUC 0.836; external validation AUC 0.810) and calibration (mean absolute errors: 0.013–0.038). DCA confirmed clinical utility at a 45% risk threshold (net benefit 0.62), capturing 85% of events with 32% false positives. Conclusion This validated prediction model accurately stratifies hypotension risk in preeclamptic parturients receiving neuraxial anesthesia. The nomogram facilitates targeted prophylactic interventions, optimizing resource allocation and maternal hemodynamic stability.
Source: Frontiers in Medicine
Authors: Jie Su, Qumin Chen, Xiuhong Ye, Huan Lu
Language: English
Subfield: Obstetrics and Gynecology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,801
OpenAlex ID: W4415097722
