Validation of Automated Data Extraction From the Electronic Medical Record to Provide a Pediatric Risk Assessment Score.

BACKGROUND: Although the rate of pediatric postoperative mortality is low, the development and validation of perioperative risk assessment models have allowed for the stratification of those at highest risk, including the Pediatric Risk Assessment (PRAm) score. The clinical application of such tools requires manual data entry, which may be inaccurate or incomplete, compromise efficiency, and increase physicians' clerical obligations. We aimed to create an electronically derived, automated PRAm score and to evaluate its agreement with the original American College of Surgery National Surgical Quality Improvement Program (ACS NSQIP)-derived and validated score. METHODS: We performed a retrospective observational study of children <18 years who underwent noncardiac surgery from 2017 through 2021 at Boston Children's Hospital (BCH). An automated PRAm score was developed via electronic derivation of International Classification of Disease (ICD) -9 and -10 codes. The primary outcome was agreement and correlation among PRAm scores obtained via automation, NSQIP data, and manual physician entry from the same BCH cohort. The secondary outcome was discriminatory ability of the 3 PRAm versions. Fleiss Kappa, Spearman correlation (rho), and intraclass correlation coefficient (ICC) and receiver operating characteristic (ROC) curve analyses with area under the curve (AUC) were applied accordingly. RESULTS: Of the 6014 patients with NSQIP and automated PRAm scores (manual scores: n = 5267), the rate of 30-day mortality was 0.18% (n = 11). Agreement and correlation were greater between the NSQIP and automated scores (rho = 0.78; 95% confidence interval [CI], 0.76-0.79; P <.001; ICC = 0.80; 95% CI, 0.79-0.81; Fleiss kappa = 0.66; 95% CI, 0.65-0.67) versus the NSQIP and manual scores (rho = 0.73; 95% CI, 0.71-0.74; P < .001; ICC = 0.78; 95% CI, 0.77-0.79; Fleiss kappa = 0.56; 95% CI, 0.54-0.57). ROC analysis with AUC showed the manual score to have the greatest discrimination (AUC = 0.976; 95% CI, 0.959,0.993) compared to the NSQIP (AUC = 0.904; 95% CI, 0.792-0.999) and automated (AUC = 0.880; 95% CI, 0.769-0.999) scores. CONCLUSIONS: Development of an electronically derived, automated PRAm score that maintains good discrimination for 30-day mortality in neonates, infants, and children after noncardiac surgery is feasible. The automated PRAm score may reduce the preoperative clerical workload and provide an efficient and accurate means by which to risk stratify neonatal and pediatric surgical patients with the goal of improving clinical outcomes and resource utilization.

Comprehensive Risk Assessment of Morbidity in Pediatric Patients Undergoing Noncardiac Surgery: An Institutional Experience.

BACKGROUND: Utilizing the intrinsic surgical risk (ISR) and the patient's chronic and acute conditions, this study aims to develop and validate a comprehensive predictive model of perioperative morbidity in children undergoing noncardiac surgery. METHODS: Following institutional review board (IRB) approval at a tertiary care children's hospital, data for all noncardiac surgical encounters for a derivation dataset from July 2017 to December 2018 including 16,724 cases and for a validation dataset from January 2019 to December 2019 including 9043 cases were collected retrospectively. The primary outcome was a composite morbidity score defined by unplanned transfer to an intensive care unit (ICU), acute respiratory failure requiring intubation, postoperative need for noninvasive or invasive positive pressure ventilation, or cardiac arrest. Internal model validation was performed using 1000 bootstrap resamples, and external validation was performed using the 2019 validation cohort. RESULTS: A total of 1519 surgical cases (9.1%) experienced the defined composite morbidity. Using multivariable logistic regression, the Risk Assessment of Morbidity in Pediatric Surgery (RAMPS) score was developed with very good predictive ability in the derivation cohort (area under the curve [AUC] = 0.805; 95% confidence interval [CI], 0.795-0.816), very good internal validity using 1000 bootstrap resamples (bias-corrected Nagelkerke R = 0.21 and Brier score = 0.07), and good external validity (AUC = 0.783; 95% CI, 0.770-0.797). The included variables are age <5 years, critically ill, chronic condition indicator (CCI) ≥3, significant CCI ≥2, and ISR quartile ≥3. The RAMPS score ranges from 0 to 10, with the risk of composite morbidity ranging from 1.8% to 42.7%. CONCLUSIONS: The RAMPS score provides the ability to identify a high-risk cohort of pediatric patients using a 5-component tool, and it demonstrated good internal and external validity and generalizability. It also provides an opportunity to improve perioperative planning with the intent of improving both individual-patient outcomes and the appropriate allocation of health care resources.

Prospective External Validation of the Pediatric Risk Assessment Score in Predicting Perioperative Mortality in Children Undergoing Noncardiac Surgery.

BACKGROUND: Early identification of children at high risk for perioperative mortality could lead to improved outcomes; however, there is a lack of well-validated risk prediction tools. The Pediatric Risk Assessment (PRAm) score is a new model to prognosticate perioperative risk of mortality in pediatric patients undergoing noncardiac surgery. It was derived from the American College of Surgeons (ACS) National Surgical Quality Improvement Program (NSQIP) Pediatric database. In this study, we aimed to externally validate the PRAm score at 1 large institution. METHODS: A PRAm score was prospectively assigned by the primary anesthesia team to children ≤18 years of age undergoing noncardiac surgery between July 2017 and July 2018 at a tertiary care pediatric hospital. The primary outcome was the PRAm score's ability to predict 30-day mortality. The area under the receiver operating characteristic (ROC) curve was utilized to determine discriminative ability. Sensitivity and specificity at varying cutoffs were considered. Youden J index and the gray zone approach were applied to determine the optimal PRAm cutoff for predicting 30-day mortality. RESULTS: Among the 13,530 cases included in the external validation cohort, the incidence of 30-day mortality was 0.21% (29/13,530). The PRAm score was found to predict 30-day mortality with an area under the curve (AUC) of 0.956 (95% confidence interval [CI], 0.938-0.974; P < .001). Youden J index determined the optimal PRAm score threshold to be ≥5 with a sensitivity of 86% and a specificity of 91%. The gray zone identified an inconclusive risk of mortality in 6.93% (938/13,530) of patients who had PRAm scores of 4 or 5 (sensitivity or specificity <90%, respectively), therefore refining the optimal cutoff point to be a PRAm score of ≥6. The incidence of mortality for patients with an American Society of Anesthesiologists Physical Status (ASA PS) ≤3 (0.06%, 8/13,530) increased 8-fold for those with an ASA PS of ≤3 and a PRAm score of ≥6. CONCLUSIONS: The PRAm score is a simple and objective tool that has excellent ability to predict perioperative risk of mortality in pediatric patients undergoing noncardiac surgery and can be easily used by clinicians. The application of the PRAm score could have important implications on the safety and quality of care delivered to infants and children and on the resource utilization in the pediatric health care system.

Outcomes and Costs of Cardiac Surgery in Adults with Congenital Heart Disease.

Advances in pediatric cardiac surgical and medical care have led to increased survival of patients with congenital heart disease (CHD). Consequently, many CHD patients survive long enough to require cardiac surgery as adults. Using the 2013 Nationwide Inpatient Sample (NIS) database, we compared costs and outcomes for adult patients undergoing surgery for treatment of CHD to a reference population of adults undergoing CABG. Patients were identified using International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9 CM) procedure codes. We recorded the demographic characteristics, gender, ethnicity, hospital bed size, hospital length of stay, in-hospital mortality, and comorbidities. Patients with ACHD have higher incidences of in-hospital mortality (2.6 vs. 1.8%), and complication rates including neurologic complications (2.6 vs. 0.9%), thromboembolic complications (3.9 vs. 1.4%), arrhythmias (51.6 vs. 29.8%), hepatic failure (4.44 vs. 2.03%), and sepsis (7.24 vs. 4.61%) (all p < 0.001). In addition, cost is higher in patients with CHD (Coefficient = 0.116, 95% CI, 0.105-0.128; p < 0.001), Elixhauser score ≥ 7 (Coefficient = 0.114, 95% CI, 0.108-0.121; p < 0.001), neurologic complications (Coefficient = 0.169, 95% CI, 0.143-0.196; p < 0.001), thrombotic complications (Coefficient = 0.243, 95% CI, 0.222-0.265; p < 0.001), sepsis (Coefficient = 0.198, 95% CI, 0.185-0.211; p < 0.001), acute kidney injury (Coefficient = 0.056, 95% CI, 0.041-0.063; p < 0.001), elective cases (Coefficient = 0.047, 95% CI, 0.041-0.053; p < 0.001), and length of stay > 6 days (Coefficient = 0.703, 95% CI, 0.697-0.710; p < 0.001). This study shows that ACHD patients undergoing cardiac surgery experience higher hospital costs and poorer outcomes than a reference population of adult CABG patients. Recognition and treatment of comorbidities in ACHD patients undergoing cardiac surgery may provide an opportunity to improve perioperative outcomes in this growing patient population.

Development of a Pediatric Risk Assessment Score to Predict Perioperative Mortality in Children Undergoing Noncardiac Surgery.

BACKGROUND: Although there have been numerous attempts to predict perioperative mortality in adults, an objective model to predict mortality in children has not been developed. In this study, we aimed to develop a Pediatric Risk Assessment (PRAm) score to predict perioperative mortality in children undergoing noncardiac surgery. METHODS: We included all children recorded in the 2012 and 2013 American College of Surgeons National Surgical Quality Improvement Program Pediatric databases in a derivation cohort and those from the 2014 database in a validation cohort. The primary outcome was the incidence of in-hospital mortality. A total of 115,229 (63%) were included in the derivation cohort and 68,194 (37%) in the validation cohort. We used multivariable logistic regression to determine the predictors for mortality and designed the PRAm score. RESULTS: On the basis of the multivariable regression model, we created a simplified risk assessment tool (PRAm score) ranging from 0 to ≥9, including the presence of any comorbidities, factors of critical illness, age <12 months, the requirement for an urgent procedure, and the diagnosis of a neoplasm. The PRAm score showed an excellent discriminative ability with an apparent "optimistic" area under the receiver operating characteristic curve (AUC) of 0.950 (95% confidence interval [CI], 0.942-0.957) in the derivation cohort. In the validation cohort, we observed similar performances with an area under the "naive" receiver operating characteristic curve of 0.950 (95% CI, 0.938-0.961). The AUC was also calculated from a bootstrap procedure and then applied to the original derivation sample to estimate "optimism" for each bootstrap sample with an AUC of 0.943 (95% CI, 0.929-0.9956). The optimism in apparent performance was 0.007, corresponding to an optimism-corrected area of 0.943. Calibration was assessed graphically by plotting the observed outcome against the predicted mortality (Pearson correlation coefficient = 0.995, calibration in the large = 0.001 [P = .974], calibration slope = 0.927). CONCLUSIONS: In this study, we developed a simplified PRAm tool (PRAm score) as a predictor of perioperative mortality in children undergoing noncardiac surgery. The PRAm score has excellent accuracy. In patients assigned American Society of Anesthesiologists physical status classification ≥4, there is wide variability in objectively obtained PRAm scores.

Overall Hospital Cost Estimates in Children with Congenital Heart Disease: Analysis of the 2012 Kid's Inpatient Database.

This study sought to determine overall hospital cost in children with congenital heart disease (CHD) and to compare cost associated with cardiac surgical procedures, cardiac catheterizations, non-cardiac surgical procedures, and medical admissions. The 2012 Healthcare Cost and Utilization Project Kid's Inpatient Database was used to evaluate hospital cost in neonates and children with CHD undergoing cardiac surgery, cardiac catheterization, non-cardiac surgical procedures, and medical treatments. Multivariable logistic regression was applied to determine independent predictors for increased hospital cost. In 2012, total hospital cost was 28,900 M$, while hospital cost in children with CHD represented 23% of this total and accounted for only 4.4% of hospital discharges. The median cost was $51,302 ($32,088-$100,058) in children who underwent cardiac surgery, $21,920 ($13,068-$51,609) in children who underwent cardiac catheterization, $4134 ($1771-$10,253) in children who underwent non-cardiac surgery, and $23,062 ($5529-$71,887) in children admitted for medical treatments. Independent predictors for increased cost were hospital bed size <400 beds (P < 0.001), more than four procedures performed during the same hospitalization (P = 0.001), use of ECMO (P < 0.001), length of hospital stay exceeding 14 days (P < 0.001), cardiac failure (P < 0.001), sepsis (P < 0.001), acute kidney injury (P < 0.001), and neurologic (P < 0.001) and thromboembolic complications (P < 0.001). Hospital cost in children with CHD represented 23% of global cost while accounting for only 4.4% of discharges. This study identified factors associated with increased cost of cardiac surgical procedures, cardiac catheterizations, non-cardiac surgical procedures, and medical management in children with CHD.

Hospital Costs for Neonates and Children Supported with Extracorporeal Membrane Oxygenation.

OBJECTIVE: To assess the characteristics associated with high hospital cost for patients receiving extracorporeal membrane oxygenation (ECMO) to identify a cohort of high-resource users. STUDY DESIGN: Cost for hospitalization, during which ECMO support was used, was calculated from hospital charges reported in the 2012 Health Care Cost and Use Project Kid's Inpatient Database. Patients were categorized into 6 diagnostic groups: (1) cardiac surgery; (2) nonsurgical heart disease; (3) congenital diaphragmatic hernia; (4) neonatal respiratory failure; (5) pediatric respiratory failure; and (6) sepsis. We categorized cost into 4 groups based on quartiles. We compared ECMO cost with hospital cost for bone marrow, liver, and kidney transplants performed during the same year. RESULTS: Median hospital cost for children supported with ECMO (n = 1465) was $230,425 (IQR: $126,599-$420,960). In a multivariable model, lower cost was associated with neonatal respiratory failure (OR: 0.19) and sepsis (OR 0.53) compared with cardiac surgery (OR: 1.88), whereas greater cost was associated with smaller hospital bed-size <99 (OR: 3.49) and 100-399 beds (OR: 3.03) compared with hospitals >400 beds, hospital location (Midwest [OR: 1.74] and West [OR 2.18] compared with North-East), and complications such as renal failure (OR: 3.77) and thromboembolic complications (OR 1.60). Hospital cost per survivor was greater for ECMO ($519,450) than bone marrow transplantation ($207,212), liver ($231,755), or kidney transplantation ($82,008) groups. CONCLUSIONS: Hospitalization cost for children supported with ECMO is high. Diagnosis, hospital characteristics, and presence of complications are associated with increased cost.

Ability of hemostatic assessment to detect bleeding disorders and to predict abnormal surgical blood loss in children: a systematic review and meta-analysis.

BACKGROUND: Systematic preoperative coagulation testing is still widely used in children scheduled for surgery, although current guidelines recommend that a bleeding history should be the first choice for hemostatic assessment. We performed a systematic review with meta-analysis to evaluate the pertinence of bleeding questionnaire and screening laboratory testing to detect bleeding disorders (BDs) in children and to predict abnormal surgical blood loss. METHODS: A search was conducted in PubMed, EMBASE, MEDLINE(R), Cochrane Central Register of Controlled Trials, Health technology Assessment, and all EBM Reviews (Cochrane DSR, ACP Journal Club, DARE, CCTR, CMR, HTA, and NHSEED and EBM Reviews) up to October 22, 2013. Prospective trials containing 20 children or more and any tests evaluating either the ability of the test to detect a congenital BD or the ability of the test to predict increased surgical blood loss were retained. The quality of the study was judged with the Cochrane Collaboration Tool and two investigators extracted data independently. Data were combined to calculate the pooled diagnostic odds ratio (DOR) and their 95% confidence intervals (CI 95%). I(2) statistics were used to assess statistics heterogeneity. RESULTS: Data could be extracted from 16 studies. Best results for detecting a congenital abnormality at potential risk for increased surgical blood loss were obtained with the PFA-100 (DOR = 113.0; 95% CI, 22.6-566.2; I(2) = 0%) in two studies, followed by the bleeding time in two other studies (DOR = 110.7; 95% CI, 24.4-502.3; I(2) = 0%). With a high amount of heterogeneity, questionnaires showed disappointing performances (DOR = 7.9; 95% CI: 3.5-17.5; I(2) = 72.6%). CONCLUSION: Current evidence does not identify a tool that adequately predicts BDs and/or abnormal surgical blood loss in children. Questionnaires currently available do not perform well. In the setting of a pediatric coagulation clinic, the PFA-100 has the highest chance of detecting a BD. This meta-analysis highlights the weakness of the literature regarding the prediction of perioperative bleeding due to congenital hemostatic disorders in children.

Updates in the perioperative and emergency management of non-vitamin K antagonist oral anticoagulants.

Perioperative management of patients treated with the non-vitamin K antagonist oral anticoagulants is an ongoing challenge. Due to the lack of good clinical studies involving adequate monitoring and reversal therapies, management requires knowledge and understanding of pharmacokinetics, renal function, drug interactions, and evaluation of the surgical bleeding risk. Consideration of the benefit of reversal of anticoagulation is important and, for some low risk bleeding procedures, it may be in the patient's interest to continue anticoagulation. In case of major intra-operative bleeding in patients likely to have therapeutic or supra-therapeutic levels of anticoagulation, specific reversal agents/antidotes would be of value but are currently lacking. As a consequence, a multimodal approach should be taken which includes the administration of 25 to 50 U/kg 4-factor prothrombin complex concentrates or 30 to 50 U/kg activated prothrombin complex concentrate (FEIBA®) in some life-threatening situations. Finally, further studies are needed to clarify the ideal therapeutic intervention.