Long-stay pediatric patients in Japanese intensive care units: their significant presence and a newly developed, simple predictive score

A Snapshot of Chronic Critical Illness in Pediatric Intensive Care Units

Children with chronic critical illness (CCI) represent the sickest subgroup of children with medical complexity. In this article, we applied a proposed definition of pediatric CCI to assess point prevalence in medical, cardiovascular, and combined pediatric intensive care units (PICUs), screening all patients admitted to six academic medical centers in the United States on May 17, 2017, for pediatric CCI (PCCI) eligibility. We gathered descriptive data to understand medical complexity and resource needs of children with PCCI in PICUs including data regarding hospitalization characteristics, previous admissions, medical technology, and chronic multiorgan dysfunction. Descriptive statistics were used to characterize the study population and hospital data. The study cohort was divided between PICU-prolonged (stay > 14 days) and PICU-exposed (any time in PICU); comparative analyses were conducted. On the study day, 185 children met inclusion criteria, 66 (36%) PICU-prolonged and 119 (64%) PICU-exposed. Nearly all had home medical technology and most ( n  = 152; 82%) required mechanical ventilation in the PICU. The PICU-exposed cohort mirrored the PICU-prolonged with a few exceptions as follows: they were older, had fewer procedures and surgeries, and had more recurrent hospitalizations. Most ( n  = 44; 66%) of the PICU-prolonged cohort had never been discharged home. Children with PCCI were a sizable proportion of the unit census on the study day. We found that children with PCCI are a prevalent population in PICUs. Dividing the cohorts between PICU-prolonged and PICU-exposed helps to better understand the care needs of the PCCI population. Identifying and studying PCCI, including variables relevant to PICU-prolonged and PICU-exposed, could inform changes to PICU care models and training programs to better enable PICUs to meet their unique needs.

Preoperative low muscle mass and early postoperative outcomes in children undergoing living donor liver transplantation: A retrospective study

Low skeletal muscle mass may develop in children with end-stage liver disease, affecting postoperative outcomes. We retrospectively investigated whether preoperative low muscle mass was associated with early postoperative outcomes in pediatric patients undergoing living donor liver transplantation (LDLT). Electronic medical records of children (age below 12 y) who underwent LDLT between February 1, 2007, and January 31, 2018, were reviewed. The cross-sectional areas of psoas, quadratus lumborum, and erector spinae muscles at the level of fourth-fifth lumbar intervertebral disks were measured using abdominal CT images, divided by the square of the height and were added to obtain the total skeletal muscle index (TSMI). The patients were divided into two groups according to the median TSMI in the second quintile (1859.1 mm 2 /m 2 ). Complications in the early postoperative period (within 30 d after surgery) classified as Clavien-Dindo grade 3 or higher were considered major complications. Logistic regression analyses were performed to determine the association between preoperative low muscle mass and early postoperative outcomes. In the study population of 123 patients (median age, 14 mo; range, 8-38 mo) who underwent LDLT, 29% and 71% were classified in the low (mean TSMI, 1642.5 ± 187.0 mm 2 /m 2 ) and high (mean TSMI 2188.1 ± 273.5 mm 2 /m 2 ) muscle mass groups, respectively. The rates of major complications, mechanical ventilation >96 hours, intensive care unit stay >14 days, hospital stay >30 days, and in-hospital mortality were not significantly different between the 2 groups. Additionally, adverse outcomes according to pediatric end-stage liver disease scores and sex were not significantly different between the 2 groups. In conclusion, preoperative low muscle mass defined by TSMI was not associated with early postoperative outcomes in pediatric patients undergoing LDLT.

Comparing the Outcomes of Pediatric Liver Transplantation

BACKGROUND

Liver transplantation is a life-saving treatment for end-stage pediatric liver failure. We aimed to present the results of pediatric liver transplants performed in our center in the last 11 years (between 2012 and March 2022) in association with prognostic factors affecting survival.

METHODS

Demographic characteristics, etiologic reasons, previous operations (Kasai procedure), morbidity, mortality, survival, and bilio-vascular complication rates were determined, and outcomes were evaluated. In the postoperative period, the duration of mechanical ventilation and intensive care unit stay and surgical and other complications were evaluated. Graft and patient survival rates were determined, and univariate and multivariate factors affecting these rates were evaluated.

RESULTS

In the last 10 years, 229 pediatric liver transplantaion (Pe-LT)/1513 adult liver taransplantation (Ad-LT) (21.35%) were performed in our center. This ratio (Pe-LT/Ad-LT ratio) is 1741/15,886 (10.95%) for our country. A total of 229 liver transplants were performed in 214 pediatric patients. Retransplantation was performed in 15 patients (6.55%). Cadaveric liver transplantation was performed in 9 patients. Graft survival rates were 87%, 83%, 78%, 78%, 78%, and 78% at <30 days, 30 to 90 days, 91 to 364 days, 1 to 3 years, and >3 years, respectively. Patient survival rates for <30 days, 30 to 90 days, 91 to 364 days, 1 to 3 years, and >3 years were 91.5%, 85.7%, 82%, 81.5%, and 81.5%, respectively. Our 5-year survival rates in metabolic diseases and the acute fulminant failure group are 93.8% and 100%, respectively.

CONCLUSIONS

The fact that the 1- and 5-year survival rates are the same shows that when patients overcome biliary vascular and infectious problems, their survival is prolonged.

Defining Pediatric Chronic Critical Illness: A Scoping Review

OBJECTIVES

Children with chronic critical illness (CCI) are hypothesized to be a high-risk patient population with persistent multiple organ dysfunction and functional morbidities resulting in recurrent or prolonged critical care; however, it is unclear how CCI should be defined. The aim of this scoping review was to evaluate the existing literature for case definitions of pediatric CCI and case definitions of prolonged PICU admission and to explore the methodologies used to derive these definitions.

DATA SOURCES

Four electronic databases (Ovid Medline, Embase, CINAHL, and Web of Science) from inception to March 3, 2021.

STUDY SELECTION

We included studies that provided a specific case definition for CCI or prolonged PICU admission. Crowdsourcing was used to screen citations independently and in duplicate. A machine-learning algorithm was developed and validated using 6,284 citations assessed in duplicate by trained crowd reviewers. A hybrid of crowdsourcing and machine-learning methods was used to complete the remaining citation screening.

DATA EXTRACTION

We extracted details of case definitions, study demographics, participant characteristics, and outcomes assessed.

DATA SYNTHESIS

Sixty-seven studies were included. Twelve studies (18%) provided a definition for CCI that included concepts of PICU length of stay (n = 12), medical complexity or chronic conditions (n = 9), recurrent admissions (n = 9), technology dependence (n = 5), and uncertain prognosis (n = 1). Definitions were commonly referenced from another source (n = 6) or opinion-based (n = 5). The remaining 55 studies (82%) provided a definition for prolonged PICU admission, most frequently greater than or equal to 14 (n = 11) or greater than or equal to 28 days (n = 10). Most of these definitions were derived by investigator opinion (n = 24) or statistical method (n = 18).

CONCLUSIONS

Pediatric CCI has been variably defined with regard to the concepts of patient complexity and chronicity of critical illness. A consensus definition is needed to advance this emerging and important area of pediatric critical care research.

Comparison of Four Machine Learning Techniques for Prediction of Intensive Care Unit Length of Stay in Heart Transplantation Patients

Background

Post-operative heart transplantation patients often require admission to an intensive care unit (ICU). Early prediction of the ICU length of stay (ICU-LOS) of these patients is of great significance and can guide treatment while reducing the mortality rate among patients. However, conventional linear models have tended to perform worse than non-linear models.

Materials and Methods

We collected the clinical data of 365 patients from Wuhan Union Hospital who underwent heart transplantation surgery between April 2017 and August 2020. The patients were randomly divided into training data (N = 256) and test data (N = 109) groups. 84 clinical features were collected for each patient. Features were validated using the Least Absolute Shrinkage and Selection Operator (LASSO) regression’s fivefold cross-validation method. We obtained Shapley Additive explanations (SHAP) values by executing package “shap” to interpret model predictions. Four machine learning models and logistic regression algorithms were developed. The area under the receiver operating characteristic curve (AUC-ROC) was used to compare the prediction performance of different models. Finally, for the convenience of clinicians, an online web-server was established and can be freely accessed via the website https://wuhanunion.shinyapps.io/PredictICUStay/.

Results

In this study, 365 consecutive patients undergoing heart transplantation surgery for moderate (NYHA grade 3) or severe (NYHA grade 4) heart failure were collected in Wuhan Union Hospital from 2017 to 2020. The median age of the recipient patients was 47.2 years, while the median age of the donors was 35.58 years. 330 (90.4%) of the donor patients were men, and the average surgery duration was 260.06 min. Among this cohort, 47 (12.9%) had renal complications, 25 (6.8%) had hepatic complications, 11 (3%) had undergone chest re-exploration and 19 (5.2%) had undergone extracorporeal membrane oxygenation (ECMO). The following six important clinical features were selected using LASSO regression, and according to the result of SHAP, the rank of importance was (1) the use of extracorporeal membrane oxygenation (ECMO); (2) donor age; (3) the use of an intra-aortic balloon pump (IABP); (4) length of surgery; (5) high creatinine (Cr); and (6) the use of continuous renal replacement therapy (CRRT). The eXtreme Gradient Boosting (XGBoost) algorithm presented significantly better predictive performance (AUC-ROC = 0.88) than other models [Accuracy: 0.87; sensitivity: 0.98; specificity: 0.51; positive predictive value (PPV): 0.86; negative predictive value (NPV): 0.93].

Conclusion

Using the XGBoost classifier with heart transplantation patients can provide an accurate prediction of ICU-LOS, which will not only improve the accuracy of clinical decision-making but also contribute to the allocation and management of medical resources; it is also a real-world example of precision medicine in hospitals.

Association between off-hour admission of critically ill children to intensive care units and mortality in a Japanese registry

Limited information exists regarding the effect of off-hour admission among critically ill children. To evaluate whether children admitted to intensive care units (ICUs) in off-hour have worse outcomes, we conducted a cohort study in 2013–2018 in a multicenter registry in Japan. Pediatric (age < 16 years) unplanned ICU admissions were divided into regular-hour (daytime on business days) or off-hour (others). Mortality and changes in the functional score at discharge from the unit were compared between the two groups. We established multivariate logistic regression models to examine the independent association between off-hour admission and outcomes. Due to the small number of outcomes, two different models were used. There were 2512 admissions, including 757 for regular-hour and 1745 for off-hour. Mortality rates were 2.4% (18/757) and 1.9% (34/1745) in regular-hour and off-hour admissions, respectively. There was no significant association between off-hour admission and mortality both in model 1 adjusting for age, sex, and Pediatric Index of Mortality 2 (adjusted odds ratio [aOR] 0.89, 95% confidence interval [CI] 0.46–1.72) and in model 2 adjusting for propensity score predicting off-hour admission (aOR 1.05, 95% CI 0.57–1.91). In addition, off-hour admission did not show an independent association with deterioration of functional score.

Pediatric living donor liver transplantation decade progress in Shanghai: Characteristics and risks factors of mortality

BACKGROUND

Pediatric living donor liver transplantation (LDLT) has become the gold standard for patients with end-stage liver disease. With improvements in organ preservation, immunosuppression, surgical and anesthesia techniques, the survival rates and long-term outcomes of patients after LDLT have significantly improved worldwide. However, data on anesthetic management and postoperative survival rate of pediatric LDLT in China are rare.

AIM

To review the status of pediatric LDLT in Shanghai and investigate the factors related to anesthetic management and survival rate in pediatric LDLT.

METHODS

We conducted a retrospective observational study to investigate the status of pediatric LDLT in Shanghai by reviewing 544 records of patients who underwent pediatric LDLT since the first operation on October 21, 2006 until August 10, 2016 at Renji Hospital and Huashan Hospital.

RESULTS

The 30-d, 90-d, 1-year, and 2-year survival rates were 95.22%, 93.38%, 91.36%, and 89.34%, respectively. The 2-year patient survival rate after January 1, 2011 significantly improved compared with the previous period (74.47% vs 90.74%; hazard ratio: 2.92; 95% confidence interval (CI): 2.16–14.14; P = 0.0004). Median duration of mechanical ventilation in the intensive care unit (ICU) was 18 h [interquartile range (IQR), 15.25–20.25], median ICU length of stay was 6 d (IQR: 4.80–9.00), and median postoperative length of stay was 24 d (IQR: 18.00–34.00). Forty-seven (8.60%) of 544 patients did not receive red blood cell transfusion during the operation.

CONCLUSION

Pediatric end-stage liver disease (PELD) score, anesthesia duration, operation duration, intraoperative blood loss, and ICU length of stay were independent predictive factors of in-hospital patient survival. Pediatric end-stage liver disease score, operation duration, and ICU length of stay were independent predictive factors of 1-year and 3-year patient survival.