# Construction of a visual nomogram prediction model for post-traumatic stress disorder in mothers of very low birth weight infants

## TL;DR

This study creates a visual model to predict PTSD in mothers of very low birth weight infants, helping identify those at high risk for early intervention.

## Contribution

The novel contribution is the development of a validated visual nomogram model for predicting PTSD in mothers of VLBWIs.

## Key findings

- The PTSD detection rate among mothers of VLBWIs was 40.9%.
- Six independent risk factors for PTSD were identified, including history of miscarriage and low social support.
- The nomogram model showed excellent discrimination with an AUC of 0.969.

## Abstract

The prevalence of very low birth weight infants (VLBWIs) continues to rise globally. These infants face increased susceptibility to preterm-related complications and potential long-term chronic health conditions, creating significant psychological and economic burdens for their families. Mothers of VLBWIs demonstrate substantially higher risks of developing post-traumatic stress disorder (PTSD) compared to mothers of term infants. Maternal PTSD can impair psychosocial functioning, compromise therapeutic relationships, and disrupt early mother–infant bonding, with potentially lasting consequences for child development. These findings highlight the critical importance of early PTSD screening and intervention in this vulnerable population.

We enrolled 352 mothers of very low birth weight infants (<1,500 g) admitted to NICUs at three hospitals in Shandong Province between September 2022 and December 2023. We identified PTSD risk factors through multivariable logistic regression and developed predictive models based on these results. Model validation included ROC analysis, calibration curves, and decision curve analysis.

Among the 352 mothers of preterm infants, the PTSD detection rate was 40.9%. Logistic regression analysis identified six independent risk factors for PTSD in mothers of VLBWIs: history of miscarriage, spousal support, illness uncertainty, neurotic personality traits, negative coping styles, and perceived social support. The nomogram model developed from these factors demonstrated excellent discriminative ability, with an area under the ROC curve of 0.969 (95% CI: 0.953–0.984). Both the Hosmer–Lemeshow goodness-of-fit test (P = 0.956) and calibration curves indicated strong agreement between predicted and observed outcomes.

Understanding the prevalence of PTSD among mothers of extremely low birth weight infants, identifying its independent risk factors, and developing a visual nomogram prediction model are critical for enabling early PTSD detection and facilitating clinical screening of high-risk mothers.