Factors associated with the follow-up of high risk infants discharged from a neonatal intensive care unit

Developing a practical neurodevelopmental prediction model for targeting high-risk very preterm infants during visit after NICU: a retrospective national longitudinal cohort study

BACKGROUND

Follow-up visits for very preterm infants (VPI) after hospital discharge is crucial for their neurodevelopmental trajectories, but ensuring their attendance before 12 months corrected age (CA) remains a challenge. Current prediction models focus on future outcomes at discharge, but post-discharge data may enhance predictions of neurodevelopmental trajectories due to brain plasticity. Few studies in this field have utilized machine learning models to achieve this potential benefit with transparency, explainability, and transportability.

METHODS

We developed four prediction models for cognitive or motor function at 24 months CA separately at each follow-up visits, two for the 6-month and two for the 12-month CA visits, using hospitalized and follow-up data of VPI from the Taiwan Premature Infant Follow-up Network from 2010 to 2017. Regression models were employed at 6 months CA, defined as a decline in The Bayley Scales of Infant Development 3rd edition (BSIDIII) composite score > 1 SD between 6- and 24-month CA. The delay models were developed at 12 months CA, defined as a BSIDIII composite score < 85 at 24 months CA. We used an evolutionary-derived machine learning method (EL-NDI) to develop models and compared them to those built by lasso regression, random forest, and support vector machine.

RESULTS

One thousand two hundred forty-four VPI were in the developmental set and the two validation cohorts had 763 and 1347 VPI, respectively. EL-NDI used only 4-10 variables, while the others required 29 or more variables to achieve similar performance. For models at 6 months CA, the area under the receiver operating curve (AUC) of EL-NDI were 0.76-0.81(95% CI, 0.73-0.83) for cognitive regress with 4 variables and 0.79-0.83 (95% CI, 0.76-0.86) for motor regress with 4 variables. For models at 12 months CA, the AUC of EL-NDI were 0.75-0.78 (95% CI, 0.72-0.82) for cognitive delay with 10 variables and 0.73-0.82 (95% CI, 0.72-0.85) for motor delay with 4 variables.

CONCLUSIONS

Our EL-NDI demonstrated good performance using simpler, transparent, explainable models for clinical purpose. Implementing these models for VPI during follow-up visits may facilitate more informed discussions between parents and physicians and identify high-risk infants more effectively for early intervention.

Previous missed visits and independent risk of loss to follow-up in the high-risk neonatal follow-up clinic

BACKGROUND

Neonatal intensive care unit (NICU) patients are at high risk for developmental delays. As a result, many are seen in neonatal follow-up (NFU) clinics. Disparities in NFU follow-up rates by social determinants of health exist.

AIMS

Determine how the number of missed visits (composed of patient-canceled visits and no-show visits) relates to risk of loss to follow-up in the NFU clinic.

STUDY DESIGN

Retrospective cohort study at a regional specialty center in the United States.

SUBJECTS

262 patients born between January 1, 2014, and December 31, 2017, who were referred to the NFU clinic.

OUTCOME MEASURES

Logistic binomial regression was used to model risk ratio of loss to follow-up over two years, defined as not attending a recommended follow-up visit and not informing the clinic of a reason for discontinued care.

RESULTS

Of 262 infants, 220 patients (84 %) were seen for at least one visit and 143 (65 %) completed follow-up. Younger maternal age, maternal smoking during pregnancy, maternal drug use during pregnancy, and public insurance were all associated with missing more visits. For each additional missed visit, the risk of loss to follow-up was 1.73 times higher unadjusted (95 % CI: 1.33, 2.26) and 1.81 times higher (95 % CI: 1.36, 2.40) after adjusting for confounders. The risk ratio of loss to follow-up for no-show visits was three times higher than that for patient-canceled visits.

CONCLUSIONS

Each missed visit was independently associated with higher risk of loss to follow-up from NFU clinic, even after adjusting for other risk factors.