Intermediate and long-term outcomes of a bowel management program for children with severe constipation or fecal incontinence.

PURPOSE: We sought to examine the long-term clinical success rates of a bowel management program (BMP) for children with severe constipation or fecal incontinence. METHODS: A single center review was conducted of children (≤18 years) enrolled in a BMP and followed in a colorectal specialty clinic (2011-2017). All patients who completed an initial week of the BMP were included. Patients enrolled in a BMP after 2018 were excluded. Success was defined as no accidents and <2 stool smears per week. RESULTS: A total of 285 patients were reviewed. BMP was initiated at a median age of 7 years (9 months-17 years). Primary diagnoses included functional constipation (112), anorectal malformation (ARM) (104), Hirschsprung Disease (HD) (41), rectal prolapse (14), spina bifida (6), fecal incontinence (3) and other (5; 4 sacral coccygeal teratomas and a GSW to the buttocks). Initial bowel regimen included large volume enema in 54% and high dose stimulant laxative in 46%. The initial Bowel Management Week (BMW) was successful in 233 (87% of adherent patients) patients with 17 (6%) non-adherent. One hundred twenty-two patients had follow-up at 12 months (72% success amongst adherent patients, 7% of patient non-adherent) and 98 patients had follow-up at 24 months (78% success amongst adherent patients, 10% of patients non-adherent). 21/154 (14%) patients started on enemas were later successfully transitioned to laxatives and 13/132 (10%) patients started on laxatives subsequently required enemas in order to stay clean. Clinic phone contact occurred outside of scheduled visits for adjustment to the BMP in 44% of patients. 33% of patients had surgery to aid bowel management (antegrade colonic enema (ACE) = 81, resection + ACE = 13, diverting stoma = 4). Median follow up was 2.5 years (5 weeks-7 years). CONCLUSION: Children who follow a structured BMP with readily available personnel to provide outpatient assistance can experience successful treatment of severe constipation or fecal incontinence long-term. A multi-institutional collaboration is necessary to identify factors which predict failure of a BMP and non-adherence. TYPE OF STUDY: Single-center retrospective chart review. LEVEL OF EVIDENCE: 3.

Predicting ICU readmission among surgical ICU patients: Development and validation of a clinical nomogram.

BACKGROUND: Unplanned intensive care unit readmission within 72 hours is an established metric of hospital care quality. However, it is unclear what factors commonly increase the risk of intensive care unit readmission in surgical patients. The objective of this study was to evaluate predictors of readmission among a diverse sample of surgical patients and develop an accurate and clinically applicable nomogram for prospective risk prediction. METHODS: We retrospectively evaluated patient demographic characteristics, comorbidities, and physiologic variables collected within 48 hours before discharge from a surgical intensive care unit at an academic center between April 2010 and July 2015. Multivariable regression models were used to assess the association between risk factors and unplanned readmission back to the intensive care unit within 72 hours. Model selection was performed using lasso methods and validated using an independent data set by receiver operating characteristic area under the curve analysis. The derived nomogram was then prospectively assessed between June and August 2017 to evaluate the correlation between perceived and calculated risk for intensive care unit readmission. RESULTS: Among 3,109 patients admitted to the intensive care unit by general surgery (34%), transplant (9%), trauma (43%), and vascular surgery (14%) services, there were 141 (5%) unplanned readmissions within 72 hours. Among 179 candidate predictor variables, a reduced model was derived that included age, blood urea nitrogen, serum chloride, serum glucose, atrial fibrillation, renal insufficiency, and respiratory rate. These variables were used to develop a clinical nomogram, which was validated using 617 independent admissions, and indicated moderate performance (area under the curve: 0.71). When prospectively assessed, intensive care unit providers' perception of respiratory risk was moderately correlated with calculated risk using the nomogram (ρ: 0.44; P < .001), although perception of electrolyte abnormalities, hyperglycemia, renal insufficiency, and risk for arrhythmias were not correlated with measured values. CONCLUSION: Intensive care unit readmission risk for surgical patients can be predicted using a simple clinical nomogram based on 7 common demographic and physiologic variables. These data underscore the potential of risk calculators to combine multiple risk factors and enable a more accurate risk assessment beyond perception alone.