Nomogram for predicting cognitive impairment in postpartum depression patients after pharmacotherapy: Development and validation

  • Jing Chai Department of Joint Surgery, The Third hospital of Shijiazhuang, Shijiazhuang 050051, China
  • Ye Di Department of Psychiatry, The third hospital of Shijiazhuang, Shijiazhuang 050051, China
  • Jingjing Cui Department of Production, The Second People’s Hospital of Hengshui, Hengshui 053099, China
  • Longjie Yuan Department of Joint Surgery, The Third hospital of Shijiazhuang, Shijiazhuang 050051, China
  • Baibai Wang Department of Joint Surgery, The Third hospital of Shijiazhuang, Shijiazhuang 050051, China
  • Luobin Ding * Department of Joint Surgery, The Third hospital of Shijiazhuang, Shijiazhuang 050051, China
Article ID: 4579
DOI: https://doi.org/10.18282/po4579
Keywords: postpartum depression; antidepressive agents; cognitive dysfunction; selective serotonin reuptake inhibitors; nomograms; risk prediction

Abstract

Objective: To develop and validate a clinical feature-based nomogram for predicting the risk of significant cognitive impairment in postpartum depression (PPD) patients treated with selective serotonin reuptake inhibitors (SSRIs). Methods: A retrospective study was conducted on 350 PPD patients treated with SSRI monotherapy at our institution between January 2020 and December 2024. Cognitive function was assessed at week 8 using the Montreal Cognitive Assessment (MoCA), with MoCA < 26 defined as significant cognitive impairment. Predictors were screened using LASSO regression, and a multivariate logistic regression model was built to construct the nomogram. Internal validation was performed via bootstrapping (1000 repetitions). Model discrimination, calibration, and clinical utility were evaluated using the C-statistic, calibration curve, and decision curve analysis (DCA). Results: Six predictors were identified: age, baseline depression severity (HAMD-17 score), years of education, SSRI type (paroxetine vs. others), baseline sleep quality (PSQI score), and postpartum duration. The model exhibited a C-statistic of 0.82 (95% CI: 0.78–0.86). The calibration curve demonstrated good agreement between predicted and actual risks. DCA indicated significant clinical net benefit across a wide threshold probability range (0.1–0.6). Conclusion: This nomogram effectively predicts individualized risk of significant cognitive impairment in SSRI-treated PPD patients, demonstrating good discrimination, calibration, and clinical utility. It serves as a valuable tool to aid clinical decision-making.

Published
2025-08-20

Copyright (c) 2025 Author(s)

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This work is licensed under a Creative Commons Attribution 4.0 International License.

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