Going back for more: an evaluation of clinical outcomes and characteristics of readmissions to a pediatric intensive care unit

Development and validation of a nomogram for predicting hospitalization longer than 14 days in pediatric patients with ventricular septal defect-a study based on the PIC database

Background: Ventricular septal defect is a common congenital heart disease. As the disease progresses, the likelihood of lung infection and heart failure increases, leading to prolonged hospital stays and an increased likelihood of complications such as nosocomial infections. We aimed to develop a nomogram for predicting hospital stays over 14 days in pediatric patients with ventricular septal defect and to evaluate the predictive power of the nomogram. We hope that nomogram can provide clinicians with more information to identify high-risk groups as soon as possible and give early treatment to reduce hospital stay and complications. Methods: The population of this study was pediatric patients with ventricular septal defect, and data were obtained from the Pediatric Intensive Care Database. The resulting event was a hospital stay longer than 14 days. Variables with a variance inflation factor (VIF) greater than 5 were excluded. Variables were selected using the least absolute shrinkage and selection operator (Lasso), and the selected variables were incorporated into logistic regression to construct a nomogram. The performance of the nomogram was assessed by using the area under the receiver operating characteristic curve (AUC), Decision Curve Analysis (DCA) and calibration curve. Finally, the importance of variables in the model is calculated based on the XGboost method. Results: A total of 705 patients with ventricular septal defect were included in the study. After screening with VIF and Lasso, the variables finally included in the statistical analysis include: Brain Natriuretic Peptide, bicarbonate, fibrinogen, urea, alanine aminotransferase, blood oxygen saturation, systolic blood pressure, respiratory rate, heart rate. The AUC values of nomogram in the training cohort and validation cohort were 0.812 and 0.736, respectively. The results of the calibration curve and DCA also indicated that the nomogram had good performance and good clinical application value. Conclusion: The nomogram established by BNP, bicarbonate, fibrinogen, urea, alanine aminotransferase, blood oxygen saturation, systolic blood pressure, respiratory rate, heart rate has good predictive performance and clinical applicability. The nomogram can effectively identify specific populations at risk for adverse outcomes.

Risk Factors of Readmission to Pediatric Intensive Care Unit Within 1 Year: A Case-Control Study

BACKGROUND

Research on pediatric intensive care unit (PICU) readmission is lacking in China. This study was conducted to describe the risk factors associated with PICU readmission within 1 year after PICU discharge.

METHODS

This retrospective case-control study included patients aged from 1 month to 16 years who were discharged between January 2018 and May 2020. The case group included readmitted patients with two or more PICU admissions within 1 year during the study period. The control group included survivors with only one PICU admission during the same study period, and the controls were matched on age and sex. Demographic and clinical variables were collected from the electronic administrative database. Risk factors were analyzed by univariate and multivariate analyses.

RESULTS

From January 2018 to May 2020, 2,529 patients were discharged from the PICU, and 103 (4.07%) were readmitted within 1 year. In the univariate analysis, PICU readmission within 1 year was associated with lower weight, the presence of chronic conditions, a higher StrongKids score on admission, length of PICU stay of more than 2 weeks, the presence of dysfunction at discharge, sedation medications use, vasopressor use, and invasive mechanical ventilation in the first PICU stay. Patients had a higher StrongKids score as a surrogate for increased risk of malnutrition. In the multivariate analysis, the factors most significantly associated with PICU readmission within 1 year were the presence of chronic conditions, a higher StrongKids score on admission, and length of PICU stay of more than 2 weeks in the first PICU stay. In the subgroup analysis, compared with the control group, the factors most significantly associated with readmission within 48 h of discharge were the presence of chronic conditions, a higher StrongKids score on admission, and vasopressor use during the first PICU stay. The mortality rate was 8.74% (9/103) in patients with PICU readmission. The overall PICU mortality rate was 7.39% (201/2,721) during the study period.

CONCLUSIONS

Patients with chronic conditions, a higher StrongKids score on admission, and length of PICU stay of more than 2 weeks were at much higher risk for PICU readmission within 1 year. Patients with vasopressor use during the first PICU hospitalization were more likely to be readmitted within 48 h of discharge.

Resources and Costs Associated With Repeated Admissions to PICUs

Supplemental Digital Content is available in the text.

To determine the costs and hospital resource use from all PICU patients readmitted with a PICU stay within 12 months of hospital index discharge.

Is Unplanned PICU Readmission a Proper Quality Indicator? A Systematic Review and Meta-analysis

CONTEXT

Unplanned PICU readmissions within 48 hours of discharge (to home or a different hospital setting) are considered a quality metric of critical care.

OBJECTIVE

We sought to determine identifiable risk factors associated with early unplanned PICU readmissions.

DATA SOURCES

A comprehensive search of Medline, Embase, the Cochrane Database of Systematic Reviews, and Scopus was conducted from each database's inception to July 16, 2018.

STUDY SELECTION

Observational studies of early unplanned PICU readmissions (<48 hours) in children (<18 years of age) published in any language were included.

DATA EXTRACTION

Two reviewers selected and appraised studies independently and abstracted data. A meta-analysis was performed by using the random-effects model.

RESULTS

We included 11 observational studies in which 128 974 children (mean age: 5 years) were evaluated. The presence of complex chronic diseases (odds ratio 2.42; 95% confidence interval 1.06 to 5.55; I ² 79.90%) and moderate to severe disability (odds ratio 2.85; 95% confidence interval 2.40 to 3.40; I ² 11.20%) had the highest odds of early unplanned PICU readmission. Other significant risk factors included an unplanned index admission, initial admission to a general medical ward, spring season, respiratory diagnoses, and longer initial PICU stay. Readmission was less likely after trauma- and surgery-related index admissions, after direct admission from home, or during the summer season. Modifiable risk factors, such as evening or weekend discharge, revealed no statistically significant association. Included studies were retrospective, which limited our ability to account for all potential confounders and establish causality.

CONCLUSIONS

Many risk factors for early unplanned PICU readmission are not modifiable, which brings into question the usefulness of this quality measure.

Dynamic Electronic Tracking and Escalation to reduce Critical care Transfers (DETECT): the protocol for a stepped wedge mixed method study to explore the clinical effectiveness, clinical utility and cost-effectiveness of an electronic physiological surveillance system for use in children

Background

Active monitoring of hospitalised adults, using handheld electronic physiological surveillance systems, is associated with reduced in-patient mortality in the UK. Potential also exists to improve the recognition and response to deterioration in hospitalised children. However, the clinical effectiveness, the clinical utility, and the cost-effectiveness of this technology to reduce paediatric critical deterioration, have not been evaluated in an NHS environment.

Method

This is a non-randomised stepped-wedge prospective mixed methods study. Participants will be in-patients under the age of 18 years, at a tertiary children’s hospital. Day-case, neonatal surgery and Paediatric Intensive Care Unit (PICU) patients will be excluded.

The intervention is the implementation of Careflow Vitals and Connect (System C) to document vital signs and sepsis screening. The underpinning age-specific Paediatric Early Warning Score (PEWS) risk model calculates PEWS and provides associated clinical decision support. Real-time data of deterioration risk are immediately visible to the entire clinical team to optimise situation awareness, the chronology of the escalation and response are captured with automated reporting of the organisational safety profile.

Baseline data will be collected prospectively for 1 year preceding the intervention. Following a 3 month implementation period, 1 year of post-intervention data will be collected.

The primary outcome is unplanned transfers to critical care (HDU and/or PICU). The secondary outcomes are critical deterioration events (CDE), the timeliness of critical care transfer, the critical care interventions required, critical care length of stay and outcome.

The clinical effectiveness will be measured by prevalence of CDE per 1000 hospital admissions and per 1000 non-PICU bed days.

Observation, field notes, e-surveys and focused interviews will be used to establish the clinical utility of the technology to healthcare professionals and the acceptability to in-patient families. The cost-effectiveness will be analysed using Health Related Group costs per day for the critical care and hospital stay for up to 90 days post CDE.

Discussion

If the technology is effective at reducing CDE in hospitalised children it could be deployed widely, to reduce morbidity and mortality, and associated costs.

Trial registration

Current Controlled Trials ISRCTN61279068, date of registration 03.06.19, retrospectively registered.

Variation in Case-Mix Adjusted Unplanned Pediatric Cardiac ICU Readmission Rates

OBJECTIVES

To identify modifiable factors leading to unplanned readmission and characterize differences in adjusted unplanned readmission rates across hospitals.

DESIGN

Retrospective cohort study using prospectively collected clinical registry data SETTING:: Pediatric Cardiac Critical Care Consortium clinical registry.

PATIENTS

Patients admitted to a pediatric cardiac ICU at Pediatric Cardiac Critical Care Consortium hospitals.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

We examined pediatric cardiac ICU encounters in the Pediatric Cardiac Critical Care Consortium registry from October 2013 to March 2016. The primary outcomes were early (< 48 hr from pediatric cardiac ICU transfer) and late (2-7 d) unplanned readmission. Generalized logit models identified independent predictors of unplanned readmission. We then calculated observed-to-expected ratios of unplanned readmission and identified higher-than or lower-than-expected unplanned readmission rates for those with an observed-to-expected ratios greater than or less than 1, respectively, and a 95% CI that did not cross 1. Of 11,301 pediatric cardiac ICU encounters (16 hospitals), 62% were surgical, and 18% were neonates. There were 175 (1.6%) early unplanned readmission, and 300 (2.7%) late unplanned readmission, most commonly for respiratory (31%), or cardiac (28%) indications. In multivariable analysis, unique modifiable factors were associated with unplanned readmission. Although shorter time between discontinuation of vasoactive infusions and pediatric cardiac ICU transfer was associated with early unplanned readmission, nighttime discharge was independently associated with a greater likelihood of late unplanned readmission. Two hospitals had lower-than-expected unplanned readmission in both the early and late categories, whereas two other hospitals were higher-than-expected in both.

CONCLUSIONS

This analysis demonstrated time from discontinuation of critical care therapies to pediatric cardiac ICU transfer as a significant, modifiable predictor of unplanned readmission. We identified two hospitals with lower-than-expected adjusted rates of both early and late unplanned readmission, suggesting that their systems are well designed to prevent unplanned readmission. This offers the possibility of disseminating best practices to other hospitals through collaborative learning.

Epidemiology of Readmissions After Sepsis Hospitalization in Children

BACKGROUND AND OBJECTIVES

The decline in hospital mortality in children hospitalized with sepsis has increased the number of survivors. These survivors are at risk for adverse long-term outcomes, including readmission and recurrent or unresolved infections. We described the epidemiology of 90-day readmissions after sepsis hospitalization in children. We tested the hypothesis that a sepsis hospitalization increases odds of 90-day readmissions.

METHODS

Retrospective cohort analysis of the Nationwide Readmissions Database. We included index unplanned admissions of non-neonatal pediatric patients and described the proportion of readmissions, including those involving infection or sepsis. We performed multivariable analysis to determine the odds of readmission after a sepsis and nonsepsis admission and compared costs of readmission after sepsis and nonsepsis admissions.

RESULTS

Of 562 817 pediatric admissions, 7634 (1.4%) and 555 183 (98.6%) were discharged alive after admissions with and without sepsis. The rate of 90-day readmission after sepsis was 21.4%: 7.2% and 25.5% in previously healthy and chronically ill patients. The adjusted mean cost during readmission was $7385. Half of readmissions (52.9%) involved recurrent infection or sepsis. Sepsis admissions were associated with higher odds of readmission at 90 days compared with nonsepsis admissions (adjusted odds ratio 1.15, 95% confidence interval 1.08-1.23). The results remained unchanged for 30-day and 6-month readmissions.

CONCLUSIONS

Readmissions occur after 1 in 5 pediatric sepsis hospitalizations and increase health care costs. Sepsis hospitalization increased odds of readmission and commonly involved recurrent infection or sepsis. Clinicians caring for these patients should consider surveillance for recurrent or unresolved infection, and researchers should explore underlying mechanisms and potential interventions to reduce readmissions.

Survival after PICU admission: The impact of multiple admissions and complex chronic conditions

OBJECTIVE

Factors predicting survival over time after pediatric intensive care unit (PICU) admissions are not fully understood. The primary aim of the current study was to investigate whether multiple admissions (MADM) compared to single PICU admissions (SADM) were associated with poor survival over time after being admitted to PICU facilities. Our secondary aim was to investigate if the presence of a complex chronic condition (CCC) would further impair prognosis.

DESIGN

A closed cohort of all children up to 16 years of age admitted to the three PICUs in Sweden between 2008 and 2010 was prospectively collected and followed until 2012, providing survival data for at least one but up to four years of follow-up.

SETTING

Three Swedish tertiary referral centers for pediatric intensive care and extracorporeal membrane oxygenation (ECMO) care were used.

PATIENTS

In total, 3,688 Swedish children with 5,019 PICU admissions were included.

INTERVENTIONS

No interventions were conducted.

MEASUREMENTS

An extensive data set was recorded, including up to four-year survival information following first PICU admission. The patients were assigned to seven admission diagnostic groups, which were then divided into SADM or MADM groups. The difference in survival over time and mortality rates (MR) and mortality rate ratios (MRR) were calculated. SADM and MADM groups with and without an existing CCC were formed. The difference in survival over time between groups was calculated.

MAIN RESULTS

A highly significant difference in survival over time was noted between SADM and MADM patients (p<0.0001), which was intensified by the presence of a CCC. MADM patients with a CCC had the worst outcome, while SADM patients without a CCC had the best outcome. MADM patients with no CCC demonstrated decreased survival over time compared to SADM patients with a CCC. Survival over time was statistically worsened for patients with MADM compared to SADM for the following admission diagnostic groups: Cardiovascular, Gastrointestinal/Renal, Respiratory, Neurological, and Miscellaneous. The mortality rate (deaths/patient year of follow-up) during the time of follow-up was 0.023 for SADM and 0.062 for MADM patients. The mortality rate ratio (MRR) between these groups was 2.69.

CONCLUSION

Compared to single admissions, multiple admissions to PICU were associated with a significant decrease in survival over time in some but not all diagnostic groups. Regarding our secondary aim, we found that when the presence of a CCC is factored into the survival analysis, survival over time is further impaired.

Repeated Critical Illness and Unplanned Readmissions Within 1 Year to PICUs

OBJECTIVES

To determine the occurrence rate of unplanned readmissions to PICUs within 1 year and examine risk factors associated with repeated readmission.

DESIGN

Retrospective cohort analysis.

SETTING

Seventy-six North American PICUs that participated in the Virtual Pediatric Systems, LLC (VPS, LLC, Los Angeles, CA).

PATIENTS

Ninety-three thousand three hundred seventy-nine PICU patients discharged between 2009 and 2010.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Index admissions and unplanned readmissions were characterized and their outcomes compared. Time-to-event analyses were performed to examine factors associated with readmission within 1 year. Eleven percent (10,233) of patients had 15,625 unplanned readmissions within 1 year to the same PICU; 3.4% had two or more readmissions. Readmissions had significantly higher PICU mortality and longer PICU length of stay, compared with index admissions (4.0% vs 2.5% and 2.5 vs 1.6 d; all p < 0.001). Median time to readmission was 30 days for all readmissions, 3.5 days for readmissions during the same hospitalization, and 66 days for different hospitalizations. Having more complex chronic conditions was associated with earlier readmission (adjusted hazard ratio, 2.9 for one complex chronic condition; hazard ratio, 4.8 for two complex chronic conditions; hazard ratio, 9.6 for three or more complex chronic conditions; all p < 0.001 compared no complex chronic condition). Most specific complex chronic condition conferred a greater risk of readmission, and some had considerably higher risk than others.

CONCLUSIONS

Unplanned readmissions occurred in a sizable minority of PICU patients. Patients with complex chronic conditions and particular conditions were at much higher risk for readmission.

A Modified Delphi Study to Identify Factors Associated With Clinical Deterioration in Hospitalized Children

OBJECTIVE

Hospitalized children who are admitted to the inpatient ward can deteriorate and require unplanned transfer to the PICU. Studies designed to validate early warning scoring systems have focused mainly on abnormalities in vital signs in patients admitted to the inpatient ward. The objective of this study was to determine the patient and system factors that experienced clinicians think are associated with progression to critical illness in hospitalized children.

METHODS

We conducted a modified Delphi study with 3 iterations, administered electronically. The expert panel consisted of 11 physician and nonphysician health care providers from hospitals in Canada and the United States.

RESULTS

Consensus was reached that 21 of the 57 factors presented are associated with clinical deterioration in hospitalized children. The final list of variables includes patient characteristics, signs and symptoms in the emergency department, emergency department management, and system factors.

CONCLUSIONS

We generated a list of variables that can be used in future prospective studies to determine if they are predictors of clinical deterioration on the inpatient ward.

Pediatric Medical Emergency Team Events and Outcomes: A Report of 3647 Events From the American Heart Association's Get With the Guidelines-Resuscitation Registry

OBJECTIVES

To describe the clinical characteristics and outcomes of a large, multicenter cohort of pediatric medical emergency team (MET) events occurring in US hospitals reported to the American Heart Association's Get With the Guidelines-Resuscitation registry.

METHODS

We analyzed consecutive pediatric (<18 years) MET events reported to the registry from January 2006 to February 2012.

RESULTS

We identified 3647 MET events from 151 US hospitals: 3080 (84%) ward and 567 (16%) telemetry/step-down unit events; median age 3.0 years (interquartile range: 0.0-11.0); 54% male; median duration 29 minutes (interquartile range: 18-49). Triggers included decreased oxygen saturation (32%), difficulty breathing (26%), and staff concern (24%). Thirty-seven percent (1137/3059) were admitted within 24 hours before MET event. Within 24 hours before the MET event, 16% were transferred from a PICU, 24% from an emergency department, and 7% from a pediatric anesthesia care unit. Fifty-three percent of MET events resulted in transfer to a PICU; 3251 (89%) received nonpharmacologic interventions, 2135 (59%) received pharmacologic interventions, 223 (6.1%) progressed to an acute respiratory compromise event, and 17 events (0.5%) escalated to cardiopulmonary arrest during the event. Survival to hospital discharge was 93.3% (n=3299/3536).

CONCLUSIONS

Few pediatric MET events progress to respiratory or cardiac arrest, but most require nonpharmacologic and pharmacologic intervention. Median duration of MET event was 29 minutes (interquartile range: 18-49), and 53% required transfer to a PICU. Events often occurred within 24 hours after hospital admission or transfer from the PICU, emergency department, or pediatric anesthesia care unit and may represent an opportunity to improve triage and other systems of care.

Assessing the utility of ICU readmissions as a quality metric: an analysis of changes mediated by residency work-hour reforms

BACKGROUND

ICU readmissions are associated with increased mortality and costs; however, it is unclear whether these outcomes are caused by readmissions or by residual confounding by illness severity. An assessment of temporal changes in ICU readmission in response to a specific policy change could help disentangle these possibilities. We sought to determine whether ICU readmission rates changed after 2003 Accreditation Council for Graduate Medical Education Resident Duty Hours reform ("reform") and whether there were temporally corresponding changes in other ICU outcomes.

METHODS

We used a difference-in-differences approach using Project IMPACT (Improved Methods of Patient Information Access of Core Clinical Tasks). Piecewise regression models estimated changes in outcomes immediately before and after reform in 274,491 critically ill medical and surgical patients in 151 community and academic US ICUs. Outcome measures included ICU readmission, ICU mortality, and in-hospital post-ICU-discharge mortality.

RESULTS

In ICUs with residents, ICU readmissions increased before reform (OR, 1.5; 95% CI, 1.22-1.84; P < .01), and decreased after (OR, 0.85; 95% CI, 0.73-0.98; P = .03). This abrupt decline in ICU readmissions after reform differed significantly from an increase in readmissions observed in ICUs without residents at this time (difference-in-differences P < .01). No comparable changes in mortality were observed between ICUs with vs without residents.

CONCLUSIONS

The changes in ICU readmission rates after reform, without corresponding changes in mortality, suggest that ICU readmissions are not causally related to other untoward patient outcomes. Instead, ICU readmission rates likely reflect operational aspects of care that are not patient-centered, making them less useful indicators of ICU quality.

Frequency, risk factors, and outcomes of early unplanned readmissions to PICUs

OBJECTIVES

To determine the rate of unplanned PICU readmissions, examine the characteristics of index admissions associated with readmission, and compare outcomes of readmissions versus index admissions.

DESIGN

Retrospective cohort analysis.

SETTING

Ninety North American PICUs that participated in the Virtual Pediatric Intensive Care Unit Systems.

PATIENTS

One hundred five thousand four hundred thirty-seven admissions between July 2009 and March 2011.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Unplanned PICU readmission within 48 hours of index discharge was the primary outcome. Summary statistics, bivariate analyses, and mixed-effects logistic regression model with random effects for each hospital were performed.There were 1,161 readmissions (1.2%). The readmission rate varied among PICUs (0-3.3%), and acute respiratory (56%), infectious (35%), neurological (28%), and cardiovascular (20%) diagnoses were often present on readmission. Readmission risk increased in patients with two or more complex chronic conditions (adjusted odds ratio, 1.72; p < 0.001), unscheduled index admission (adjusted odds ratio, 1.37; p < 0.001), and transfer to an intermediate unit (adjusted odds ratio, 1.29; p = 0.004, compared with ward). Trauma patients had a decreased risk of readmission (adjusted odds ratio, 0.67; p = 0.003). Gender, race, insurance, age more than 6 months, perioperative status, and nighttime transfer were not associated with readmission. Compared with index admissions, readmissions had longer median PICU length of stay (3.1 vs 1.7 d, p < 0.001) and higher mortality (4% vs 2.5%, p = 0.002).

CONCLUSIONS

Unplanned PICU readmissions were relatively uncommon, but were associated with worse outcomes. Several patient and admission characteristics were associated with readmission. These data help identify high-risk patient groups and inform risk-adjustment for standardized readmission rates.

Unplanned pediatric intensive care unit readmissions: a single-center experience

PURPOSE

The purpose of the study was to compare patients readmitted to the pediatric intensive care unit (PICU) unexpectedly within 48 hours (early), more than 48 hours from transfer (late), or not readmitted during the same hospitalization.

MATERIALS AND METHODS

A retrospective study (2007-2009) was performed at a tertiary care pediatric academic hospital. Readmitted at-risk patients were grouped by timing of readmission, and a sample of nonreadmitted patients was randomly selected. Early readmissions were compared to late readmissions and to nonreadmissions.

RESULTS

Of 3805 eligible patients, 3.9% had an unplanned PICU readmission with almost half occurring within 48 hours. Median times to readmission were 21.5 hours (early) and 7 days (late). Compared with late readmissions, early readmissions were more often admitted from and transferred to a surgical service, transferred on a weekend, and readmitted with the same primary diagnosis. Compared with nonreadmitted patients, independent risk factors for early readmission were admission source and respiratory support at PICU transfer. Readmitted patients had longer total PICU and hospital lengths of stay than nonreadmitted patients. Late readmissions had a higher mortality than early readmissions.

CONCLUSIONS

Patients requiring an unplanned PICU readmission had worse outcomes than those without a readmission. Future studies should focus on identifying modifiable risk factors for targeted interventions.

Frequency, characteristics, and outcomes of pediatric patients readmitted to the cardiac critical care unit

PURPOSE

To describe the characteristics and outcomes of patients readmitted to a pediatric cardiac critical care unit (CCCU) from the ward within 72 h of their first discharge.

METHODS

This was a retrospective analysis of data collected on patients admitted to the CCCU between January 1, 2000 and January 31, 2007. The setting was an 18-bed pediatric CCCU in a tertiary care university hospital. No interventions were performed.

RESULTS

Among the 4,625 patients admitted to the CCCU, 112 (2.4 %) were readmitted from the ward within 72 h of their discharge. The most common cause for readmission was respiratory symptoms (42.9 %). Significant changes in the chest X-ray prior to discharge were identified retrospectively in 12.5 % of these patients. Cardiovascular symptoms were similarly frequent (40.2 %) among these patients. Nine (8 %) of the patients died during the readmission period, a rate which is considerably higher than the overall CCCU mortality rate (3.8 %) in the same period of time.

CONCLUSIONS

Respiratory reasons are the most common cause for early CCCU readmission among pediatric cardiac patients. The readmitted patients have higher rates of death compared to the overall pediatric cardiac critical care population. The development of objective predischarge scores might help planning appropriately for discharge to the ward and avoid readmission to the CCU.