Does Cocaine Use Increase Medication Noncompliance in Bipolar Disorders? A United States Nationwide Inpatient Cross-Sectional Study.

Introduction Medication noncompliance among bipolar disorder (BD) is often linked with comorbid substance use disorders. This study aims to investigate cocaine use (CU) association with medication noncompliance in hospitalized BD patients. Methods Using data on 266,303 BD hospitalizations between 2010-2014 from the US Nationwide Inpatient Sample database, we obtained medication noncompliance rates stratified by demographics and cocaine use. Logistic regression was used to evaluate factors associated with medication noncompliance. Results Overall mean age, the prevalence of CU, and medication noncompliance were 41.58 (+0.11) years, 8.34%, and 16.08%, respectively. More than half of BD patients with comorbid CU were between 40-64 years (54.4%), while more male patients with BD were in the CU group (53.9%). With univariable logistic regression, CU (odds ratio [OR]: 1.77, 95% CI: 1.66-1.88) increased the odds of medication noncompliance among BD patients, and after adjusting for other variables there was sustained increased odds (adjusted odds ratio [aOR]: 1.40, 95% CI: 1.32-1.50). Conclusion This study showed that CU is associated with medication noncompliance among hospitalized BD patients. This highlights the importance of addressing CU among BD patients. Given the possible association of CU with medication noncompliance among BD patients, collaborative work between general adult psychiatry and addiction services is imperative in improving the management outcome of BD patients with comorbid CU.

Evaluating the National Surgical Quality Improvement Program-Pediatric Surgical Risk Calculator for Pediatric Craniosynostosis Surgery.

BACKGROUND: The American College of Surgeons' National Surgical Quality Improvement Program-Pediatric (NSQIP-P) risk calculator was developed based on national data. There have been no studies assessing the risk calculator's performance in pediatric neurosurgery. The authors aimed to evaluate the predictions from the risk calculator compared to our single institution experience in craniosynostosis surgery. METHODS: Outcomes from craniosynostosis surgeries performed between 2012 and 2016 at our academic pediatric hospital were evaluated using the NSQIP-P risk calculator. Descriptive statistics were performed comparing predicted 30-day postoperative events and clinically observed outcomes. The performance of the calculator was evaluated using the Brier score and receiver operating characteristic curve (ROC). RESULTS: A total of 202 craniosynostosis surgeries were included. Median age was 0.74 years (range 0.15-6.32); 66% were males. Blood transfusion occurred in 162/202 patients (80%). The following clinical characteristics were statistically correlated with surgical complications: American Society of Anesthesiologists physical status classification >1 (P < 0.001), central nervous system abnormality (P < 0.001), syndromic craniosynostosis (P = 0.001), and redo operations (P = 0.002). Postoperative events occurred in <3%, including hardware breakage, tracheal-cartilaginous sleeve associated with critical airway, and surgical site infection. The calculator performed well in predicting any complication (Brier = 0.067, ROC = 73.9%), and for pneumonia (Brier = 0.0049, ROC 99%). The calculator predicted a low rate of cardiac complications, venous thromboembolism, renal failure, reintubation, and death; the observed rate of these complications was 0. CONCLUSIONS: The risk calculator demonstrated reasonable ability to predict the low number of perioperative complications in patients undergoing craniosynostosis surgery with a composite complications outcome. Efforts to improve the calculator may include further stratification based on procedure-specific risk factors.