Prediction Nomogram for Faltering Catch-Up Growth in Full-Term SGA Infants

1,185 full-term small-for-gestational-age (SGA) infants from a development cohort and 294 from a temporal validation cohort were analyzed in a retrospective study by Qian Hu, published on figshare in 2026. The data was used to develop a nomogram predicting faltering catch-up growth before age two, based on sex, birth weight Z score, birth length Z score, and target height Z score. The model achieved an area under the curve (AUC) of 0.810 in development and 0.784 in temporal validation.

Use Cases

• Validating the predictive performance of the published nomogram based on sex, birth weight, birth length, and target height Z scores.
• Training machine learning models for early identification of infants at risk of faltering catch-up growth.
• Conducting secondary analysis on the relationship between anthropometric Z scores at birth and subsequent growth patterns.

Strengths

• Model performance is quantified with an AUC of 0.810 and validated on a separate temporal cohort of 294 infants.
• The study includes a substantial development cohort of 1,185 full-term SGA infants.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count for the underlying patient-level data is unknown, which may limit suitability assessment.
• Data may reflect geographic or institutional bias inherent to the single hospital source.

Provenance

Source

West China Second University Hospital

Collection Method

Retrospective cohort study

Time Range

Development cohort: January 1996–December 2019; Validation cohort: January 2020–July 2023

Freshness

Last updated 2026-05-18 05:43:04; freshness should be verified.

Geography

China (likely Sichuan province, based on hospital location)