Search Results

You are looking at 1 - 2 of 2 items for

  • Author or Editor: Gabriela D. Ruiz Colón x
  • Refine by Access: all x
Clear All Modify Search
Restricted access

Gabriela D. Ruiz Colón, Michael C. Jin, Gerald A. Grant, and Laura M. Prolo

OBJECTIVE

Craniosynostosis is characterized by the premature fusion of at least one cranial suture. Although evidence suggests that patients with both syndromic and nonsyndromic craniosynostosis may benefit from developmental, behavioral, and mental health support, data on utilization of healthcare services are lacking. In this study the authors compared utilization of mental health care, rehabilitation therapies, and other specialty medical services among children with craniosynostosis, children with plagiocephaly, and healthy controls.

METHODS

The Optum Clinformatics Data Mart database was queried to identify 1340 patients with craniosynostosis, of whom 200 had syndromic craniosynostosis. Long-term utilization of mental health care, rehabilitation therapies, and other medical services up to the age of 6 years was calculated. Rates of utilization were compared to healthy controls (n = 1577) and children with plagiocephaly (n = 1249).

RESULTS

Patients with syndromic and nonsyndromic craniosynostosis used mental health care, occupational therapy, speech–language pathology, and other medical services at similar rates (p = 0.1198, p > 0.9999, p = 0.1097, and p = 0.8119, respectively). Mental health services were used more frequently by patients with craniosynostosis (11.0% in patients with syndromic craniosynostosis and 7.5% in those with nonsyndromic craniosynostosis) compared to patients in the plagiocephaly (5.0%, p = 0.0020) and healthy control (2.9%, p < 0.0001) cohorts. Rehabilitation therapies were more frequently used by patients with syndromic craniosynostosis and plagiocephaly (16.0% and 14.1%, respectively), which was significantly higher than use by healthy controls (p < 0.0001). Other medical subspecialty services (developmental pediatrics, ophthalmology, optometry, and audiology) were used by 37.0% of patients with craniosynostosis, compared with 20.9% (p < 0.0001) and 15.1% (p < 0.0001) of patients with plagiocephaly and healthy controls, respectively. Among patients with craniosynostosis, utilization did not differ by race or household income, but it was not uniform by age. Whereas ophthalmology utilization did not differ by age (p = 0.1003), mental health care was most commonly used among older children (p = 0.0107).

CONCLUSIONS

In this study, the authors demonstrate that rates of utilization of mental health care, rehabilitation therapies, and other medical subspecialty services are similar between patients with syndromic and those with nonsyndromic craniosynostosis, but higher than in healthy controls. Although surgical correction may be considered an isolated event, providers and parents need to monitor all children with craniosynostosis—syndromic and nonsyndromic—for developmental and mental health support longitudinally. Future work should explore risk factors driving utilization, including suture involvement, repair type, and comorbidities.

Restricted access

Michael C. Jin, Jonathon J. Parker, Adrian J. Rodrigues, Gabriela D. Ruiz Colón, Cesar A. Garcia, Kelly B. Mahaney, Gerald A. Grant, and Laura M. Prolo

OBJECTIVE

Neonatal intraventricular hemorrhage (IVH) is a major cause of mortality and morbidity, particularly following premature birth. Even after the acute phase, posthemorrhagic hydrocephalus is a long-term complication, frequently requiring permanent ventriculoperitoneal shunt (VPS) placement. Currently, there are no risk classification methods integrating the constellation of clinical data to predict short- and long-term prognosis in neonatal IVH. To address this need, the authors developed a two-part machine learning approach for predicting short- and long-term outcomes after diagnosis of neonatal IVH. Integrating both maternal and neonatal characteristics, they developed a binary classifier to predict short-term mortality risk and a clinical scale to predict the long-term risk of VPS placement.

METHODS

Neonates with IVH were identified from the Optum Clinformatics Data Mart administrative claims database. Matched maternal and childbirth characteristics were obtained for all patients. The primary endpoints of interest were short-term (30 day) mortality and long-term VPS placement. Classification of short-term mortality risk was evaluated using 5 different machine learning approaches and the best-performing method was validated using a withheld validation subset. Prediction of long-term shunt risk was performed using a multivariable Cox regression model with stepwise variable selection, which was subsequently converted to an easily applied integer risk scale.

RESULTS

A total of 5926 neonates with IVH were identified. Most patients were born before 32 weeks’ gestation (67.2%) and with low birth weight (81.2%). Empirical 30-day mortality risk was 10.9% across all IVH grades and highest among grade IV IVH (34.3%). Among the neonates who survived > 30 days, actuarial 12-month postdiagnosis risk of shunt placement was 5.4% across all IVH grades and 31.3% for grade IV IVH. The optimal short-term risk classifier was a random forest model achieving an area under the receiver operating characteristic curve of 0.882 with important predictors ranging from gestational age to diverse comorbid medical conditions. Selected features for long-term shunt risk stratification were IVH grade, respiratory distress syndrome, disseminated intravascular coagulation, and maternal preeclampsia or eclampsia. An integer risk scale, termed the Shunt Prediction After IVH in Neonates (SPAIN) scale, was developed from these 4 features, which, evaluated on withheld cases, demonstrated improved risk stratification compared with IVH grade alone (Harrell’s concordance index 0.869 vs 0.852).

CONCLUSIONS

In a large cohort of neonates with IVH, the authors developed a two-pronged, integrated, risk classification approach to anticipate short-term mortality and long-term shunt risk. The application of such approaches may improve the prognostication of outcomes and identification of higher-risk individuals who warrant careful surveillance and early intervention.