Failure of psychiatric referrals from the pediatric emergency department

<p>Abstract</p> <p>Background</p> <p>Recognition of mental illness in the pediatric emergency department (PED) followed by brief, problem oriented interventions may improve health-care seeking behavior and quality of life. The objective of this study was to compare the frequency of mental health follow up after an enhanced referral compared to a simple referral in children presenting to the PED with unrecognized mental health problems.</p> <p>Methods</p> <p>A prospective randomized control trial comparing an enhanced referral vs. simple referral in 56 families of children who were screened for mental health symptoms was performed in a large tertiary care PED. Children presenting to the PED with stable medical problems were approached every fourth evening for enrollment. After consent/assent was obtained, children were screened for a mental health problem using both child and parent reports of the DISC Predictive Scales. Those meeting cutoffs for a mental health problem by either parent or child report were randomized to 1) simple referral (phone number for mental health evaluation by study psychiatrist) or 2) enhanced referral (short informational interview, appointment made for child, reminder 2 days before and day of interview for an evaluation by study psychiatrist). Data analysis included descriptive statistics and Chi-Square test to calculate the proportion of children with mental health problems who completed mental health follow-up with and without the enhanced referral.</p> <p>Results</p> <p>A total of 69 families were enrolled. Overall 56 (81%) children screened positive for a mental health problem as reported by either the child (self report) or mother (maternal report of child mental health problem). Of these, 33 children were randomized into the enhanced referral arm and 23 into the simple referral arm. Overall, only 6 families with children screening positive for a mental health problem completed the psychiatric follow up evaluation, 2 in the enhanced referral arm and 4 in the simple referral arm (p = .13).</p> <p>Conclusion</p> <p>Children screened in the ED for unrecognized mental health problems are very unlikely to follow-up for a mental health evaluation with or without an enhanced referral. Understanding the role of ED based mental health screening and the timing of an intervention is key in developing ED based mental health interventions.</p

UGT1A1 sequence variants and bilirubin levels in early postnatal life: a quantitative approach

<p>Abstract</p> <p>Background</p> <p>Fundamental to definitively identifying neonates at risk of developing significant hyperbilirubinemia is a better understanding of the genetic factors associated with early bilirubin rise. Previous genetic studies have focused on the UGT1A1 gene, associating common variation in the coding or promoter regions with qualitative assessments of bilirubin (i.e. significantly elevated or not). These studies have had conflicting results and limited success. We chose to approach the problem by focusing on the quantitative (absolute) change in bilirubin levels early in post-natal life. We apply this approach to the UGT1A1 gene - exploring the contribution of both rare and common variants to early bilirubin changes.</p> <p>Methods</p> <p>We sequenced the exons, PBREM, 5'-, and 3'- regions of the UGT1A1 gene in 80 otherwise healthy term neonates who had repeat bilirubin levels measured within the first five days of life.</p> <p>Results</p> <p>Three novel coding variants were observed, but there was no clear relationship between rare coding variants and bilirubin rise. Adjusted linear regression models fit to evaluate the relationship between changing bilirubin levels and common UGT1A1variants found that among 39 neonates whose bilirubin was resampled within 33 hours, individuals homozygous for the mutant allele of a 3'UTR SNP had significantly smaller changes in bilirubin (P = 0.003) than individuals carrying the wild-type allele.</p> <p>Conclusions</p> <p>Collectively, rare UGT1A1 coding variants do not appear to play a prominent role in determining early bilirubin levels; however common variants in the 3' UTR of UGT1A1 may modulate the early bilirubin rise. A quantitative approach to evaluating early bilirubin kinetics provides a more robust framework in which to better understand the genetics of neonatal hyperbilirubinemia.</p

Predictability and stability testing to assess clinical decision instrument performance for children after blunt torso trauma

Objective The Pediatric Emergency Care Applied Research Network (PECARN) has developed a clinical-decision instrument (CDI) to identify children at very low risk of intra-abdominal injury. However, the CDI has not been externally validated. We sought to vet the PECARN CDI with the Predictability Computability Stability (PCS) data science framework, potentially increasing its chance of a successful external validation. Materials &amp; methods We performed a secondary analysis of two prospectively collected datasets: PECARN (12,044 children from 20 emergency departments) and an independent external validation dataset from the Pediatric Surgical Research Collaborative (PedSRC; 2,188 children from 14 emergency departments). We used PCS to reanalyze the original PECARN CDI along with new interpretable PCS CDIs developed using the PECARN dataset. External validation was then measured on the PedSRC dataset. Results Three predictor variables (abdominal wall trauma, Glasgow Coma Scale Score &lt;14, and abdominal tenderness) were found to be stable. A CDI using only these three variables would achieve lower sensitivity than the original PECARN CDI with seven variables on internal PECARN validation but achieve the same performance on external PedSRC validation (sensitivity 96.8% and specificity 44%). Using only these variables, we developed a PCS CDI which had a lower sensitivity than the original PECARN CDI on internal PECARN validation but performed the same on external PedSRC validation (sensitivity 96.8% and specificity 44%). Conclusion The PCS data science framework vetted the PECARN CDI and its constituent predictor variables prior to external validation. We found that the 3 stable predictor variables represented all of the PECARN CDI’s predictive performance on independent external validation. The PCS framework offers a less resource-intensive method than prospective validation to vet CDIs before external validation. We also found that the PECARN CDI will generalize well to new populations and should be prospectively externally validated. The PCS framework offers a potential strategy to increase the chance of a successful (costly) prospective validation

Predictability and stability testing to assess clinical decision instrument performance for children after blunt torso trauma

Objective The Pediatric Emergency Care Applied Research Network (PECARN) has developed a clinical-decision instrument (CDI) to identify children at very low risk of intra-abdominal injury. However, the CDI has not been externally validated. We sought to vet the PECARN CDI with the Predictability Computability Stability (PCS) data science framework, potentially increasing its chance of a successful external validation. Materials & methods We performed a secondary analysis of two prospectively collected datasets: PECARN (12,044 children from 20 emergency departments) and an independent external validation dataset from the Pediatric Surgical Research Collaborative (PedSRC; 2,188 children from 14 emergency departments). We used PCS to reanalyze the original PECARN CDI along with new interpretable PCS CDIs developed using the PECARN dataset. External validation was then measured on the PedSRC dataset. Results Three predictor variables (abdominal wall trauma, Glasgow Coma Scale Score Conclusion The PCS data science framework vetted the PECARN CDI and its constituent predictor variables prior to external validation. We found that the 3 stable predictor variables represented all of the PECARN CDI’s predictive performance on independent external validation. The PCS framework offers a less resource-intensive method than prospective validation to vet CDIs before external validation. We also found that the PECARN CDI will generalize well to new populations and should be prospectively externally validated. The PCS framework offers a potential strategy to increase the chance of a successful (costly) prospective validation. Author summary Do predictability and stability testing inform how a clinical decision instrument for identifying children at low risk of intra-abdominal injuries undergoing intervention after blunt torso trauma will perform prior to external validation? The PECARN instrument has high prediction performance and stable predictor variables. The Predictability, Computability, Stability (PCS) framework identified high performing instruments after development but before external validation. The PECARN instrument has high predictability and stability for children after blunt torso trauma and should therefore undergo prospective external validation. PCS is an effective method for evaluating clinical decision instruments after development but prior to external validation

Predictability and stability testing to assess clinical decision instrument performance for children after blunt torso trauma.

ObjectiveThe Pediatric Emergency Care Applied Research Network (PECARN) has developed a clinical-decision instrument (CDI) to identify children at very low risk of intra-abdominal injury. However, the CDI has not been externally validated. We sought to vet the PECARN CDI with the Predictability Computability Stability (PCS) data science framework, potentially increasing its chance of a successful external validation.Materials & methodsWe performed a secondary analysis of two prospectively collected datasets: PECARN (12,044 children from 20 emergency departments) and an independent external validation dataset from the Pediatric Surgical Research Collaborative (PedSRC; 2,188 children from 14 emergency departments). We used PCS to reanalyze the original PECARN CDI along with new interpretable PCS CDIs developed using the PECARN dataset. External validation was then measured on the PedSRC dataset.ResultsThree predictor variables (abdominal wall trauma, Glasgow Coma Scale Score ConclusionThe PCS data science framework vetted the PECARN CDI and its constituent predictor variables prior to external validation. We found that the 3 stable predictor variables represented all of the PECARN CDI's predictive performance on independent external validation. The PCS framework offers a less resource-intensive method than prospective validation to vet CDIs before external validation. We also found that the PECARN CDI will generalize well to new populations and should be prospectively externally validated. The PCS framework offers a potential strategy to increase the chance of a successful (costly) prospective validation