Failed Extubation in Neonates After Cardiac Surgery: A Single-Center, Retrospective Study

OBJECTIVES

To describe factors associated with failed extubation (FE) in neonates following cardiovascular surgery, and the relationship with clinical outcomes.

DESIGN

Retrospective cohort study.

SETTING

Twenty-bed pediatric cardiac ICU (PCICU) in an academic tertiary care children's hospital.

PATIENTS

Neonates admitted to the PCICU following cardiac surgery between July 2015 and June 2018.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Patients who experienced FE were compared with patients who were successfully extubated. Variables associated with FE ( p < 0.05) from univariate analysis were considered for inclusion in multivariable logistic regression. Univariate associations of FE with clinical outcomes were also examined. Of 240 patients, 40 (17%) experienced FE. Univariate analyses revealed associations of FE with upper airway (UA) abnormality (25% vs 8%, p = 0.003) and delayed sternal closure (50% vs 24%, p = 0.001). There were weaker associations of FE with hypoplastic left heart syndrome (25% vs 13%, p = 0.04), postoperative ventilation greater than 7 days (33% vs 15%, p = 0.01), Society of Thoracic Surgeons-European Association for Cardio-Thoracic Surgery (STAT) category 5 operations (38% vs 21%, p = 0.02), and respiratory rate during spontaneous breathing trial (median 42 vs 37 breaths/min, p = 0.01). In multivariable analysis, UA abnormalities (adjusted odds ratio [AOR] 3.5; 95% CI, 1.4-9.0), postoperative ventilation greater than 7 days (AOR 2.3; 95% CI, 1.0-5.2), and STAT category 5 operations (AOR 2.4; 95% CI, 1.1-5.2) were independently associated with FE. FE was also associated with unplanned reoperation/reintervention during hospital course (38% vs 22%, p = 0.04), longer hospitalization (median 29 vs 16.5 d, p < 0.0001), and in-hospital mortality (13% vs 3%, p = 0.02).

CONCLUSIONS

FE in neonates occurs relatively commonly following cardiac surgery and is associated with adverse clinical outcomes. Additional data are needed to further optimize periextubation decision-making in patients with multiple clinical factors associated with FE.

Methods to Enhance Causal Inference for Assessing Impact of Clinical Informatics Platform Implementation

BACKGROUND

Hospitals are increasingly likely to implement clinical informatics tools to improve quality of care, necessitating rigorous approaches to evaluate effectiveness. We leveraged a multi-institutional data repository and applied causal inference methods to assess implementation of a commercial data visualization software in our pediatric cardiac intensive care unit.

METHODS

Natural experiment in the University of Michigan (UM) Cardiac Intensive Care Unit pre and postimplementation of data visualization software analyzed within the Pediatric Cardiac Critical Care Consortium clinical registry; we identified N=21 control hospitals that contributed contemporaneous registry data during the study period. We used the platform during multiple daily rounds to visualize clinical data trends. We evaluated outcomes-case-mix adjusted postoperative mortality, cardiac arrest and unplanned readmission rates, and postoperative length of stay-most likely impacted by this change. There were no quality improvement initiatives focused specifically on these outcomes nor any organizational changes at UM in either era. We performed a difference-in-differences analysis to compare changes in UM outcomes to those at control hospitals across the pre versus postimplementation eras.

RESULTS

We compared 1436 pre versus 779 postimplementation admissions at UM to 19 854 (pre) versus 14 160 (post) at controls. Admission characteristics were similar between eras. Postimplementation at UM we observed relative reductions in cardiac arrests among medical admissions, unplanned readmissions, and postoperative length of stay by -14%, -41%, and -18%, respectively. The difference-in-differences estimate for each outcome was statistically significant (P<0.05), suggesting the difference in outcomes at UM pre versus postimplementation is statistically significantly different from control hospitals during the same time.

CONCLUSIONS

Clinical registries provide opportunities to thoroughly evaluate implementation of new informatics tools at single institutions. Borrowing strength from multi-institutional data and drawing ideas from causal inference, our analysis solidified greater belief in the effectiveness of this software across our institution.

Preventing Cardiac Arrest in the Pediatric Cardiac Intensive Care Unit Through Multicenter Collaboration

Importance

Preventing in-hospital cardiac arrest (IHCA) likely represents an effective strategy to improve outcomes for critically ill patients, but feasibility of IHCA prevention remains unclear.

Objective

To determine whether a low-technology cardiac arrest prevention (CAP) practice bundle decreases IHCA rate.

Design, Setting, and Participants

Pediatric cardiac intensive care unit (CICU) teams from the Pediatric Cardiac Critical Care Consortium (PC4) formed a collaborative learning network to implement the CAP bundle consistent with the Institute for Healthcare Improvement framework; 15 hospitals implemented the bundle voluntarily. Risk-adjusted IHCA incidence rates were analyzed across 2 time periods, 12 months (baseline) and 18 months after CAP implementation (intervention) using difference-in-differences (DID) regression to compare 15 CAP and 16 control PC4 hospitals that chose not to participate in CAP but had IHCA rates tracked in the PC4 registry. Patients deemed at high risk for IHCA, based on a priori evidence-based criteria and empirical hospital-specific criteria, were selected to receive the CAP bundle. Data were collected from July 2018 to December 2019, and data were analyzed from March to August 2020.

Interventions

CAP bundle included 5 elements developed to promote increased situational awareness and communication among bedside clinicians to recognize and mitigate deterioration in high-risk patients.

Main Outcomes and Measures

Risk-adjusted IHCA incidence rate across all CICU admissions (IHCA events divided by all admissions).

Results

The bundle was activated in 2664 of 10 510 CAP hospital admissions (25.3%); admission characteristics were similar across study periods. There was a 30% relative reduction in risk-adjusted IHCA incidence rate at CAP hospitals (intervention period: 2.6%; 95% CI, 2.2-2.9; baseline: 3.7%; 95% CI, 3.1-4.0), but no change at control hospitals (intervention period: 2.7%; 95% CI, 2.3-2.9; baseline: 2.7%; 95% CI, 2.2-3.0). DID analysis confirmed significantly reduced odds of IHCA among all admissions at CAP hospitals compared with control hospitals during the intervention period vs baseline (odds ratio, 0.72; 95% CI, 0.56-0.91; P = .01). DID odds ratios were 0.72 (95% CI, 0.53-0.98) for the surgical subgroup, 0.74 (95% CI, 0.48-1.14) for the medical subgroup, and 0.72 (95% CI, 0.50-1.03) for the high-risk admission subgroup at CAP hospitals after intervention. All-cause risk-adjusted mortality rate did not change after intervention.

Conclusions and Relevance

Implementation of this CAP bundle led to significant IHCA reduction across multiple pediatric CICUs. Future studies may determine if this bundle can be effective in other critically ill populations.

Data-driven computational models of ventricular-arterial hemodynamics in pediatric pulmonary arterial hypertension

Pulmonary arterial hypertension (PAH) is a complex disease involving increased resistance in the pulmonary arteries and subsequent right ventricular (RV) remodeling. Ventricular-arterial interactions are fundamental to PAH pathophysiology but are rarely captured in computational models. It is important to identify metrics that capture and quantify these interactions to inform our understanding of this disease as well as potentially facilitate patient stratification. Towards this end, we developed and calibrated two multi-scale high-resolution closed-loop computational models using open-source software: a high-resolution arterial model implemented using CRIMSON, and a high-resolution ventricular model implemented using FEniCS. Models were constructed with clinical data including non-invasive imaging and invasive hemodynamic measurements from a cohort of pediatric PAH patients. A contribution of this work is the discussion of inconsistencies in anatomical and hemodynamic data routinely acquired in PAH patients. We proposed and implemented strategies to mitigate these inconsistencies, and subsequently use this data to inform and calibrate computational models of the ventricles and large arteries. Computational models based on adjusted clinical data were calibrated until the simulated results for the high-resolution arterial models matched within 10% of adjusted data consisting of pressure and flow, whereas the high-resolution ventricular models were calibrated until simulation results matched adjusted data of volume and pressure waveforms within 10%. A statistical analysis was performed to correlate numerous data-derived and model-derived metrics with clinically assessed disease severity. Several model-derived metrics were strongly correlated with clinically assessed disease severity, suggesting that computational models may aid in assessing PAH severity.

Critical Care Unit Organizational and Personnel Factors Impact Cardiac Arrest Prevention and Rescue in the Pediatric Cardiac Population

OBJECTIVES

Patient-level factors related to cardiac arrest in the pediatric cardiac population are well understood but may be unmodifiable. The impact of cardiac ICU organizational and personnel factors on cardiac arrest rates and outcomes remains unknown. We sought to better understand the association between these potentially modifiable organizational and personnel factors on cardiac arrest prevention and rescue.

DESIGN

Retrospective analysis of the Pediatric Cardiac Critical Care Consortium registry.

SETTING

Pediatric cardiac ICUs.

PATIENTS

All cardiac ICU admissions were evaluated for cardiac arrest and survival outcomes.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Successful prevention was defined as the proportion of admissions with no cardiac arrest (inverse of cardiac arrest incidence). Rescue was the proportion of patients surviving to cardiac ICU discharge after cardiac arrest. Cardiac ICU organizational and personnel factors were captured via site questionnaires. The associations between organizational and personnel factors and prevention/rescue were analyzed using Fine-Gray and multinomial regression, respectively, accounting for clustering within hospitals. We analyzed 54,521 cardiac ICU admissions (29 hospitals) with 1,398 cardiac arrest events (2.5%) between August 1, 2014, and March 5, 2019. For both surgical and medical admissions, lower average daily cardiac ICU occupancy was associated with better cardiac arrest prevention. Better rescue for medical admissions was observed for higher registered nursing hours per patient day and lower proportions of "part time" cardiac ICU physician staff (< 6 service weeks/yr). Increased registered nurse experience was associated with better rescue for surgical admissions. Increased proportion of critical care certified nurses, full-time intensivists with critical care fellowship training, dedicated respiratory therapists, quality/safety resources, and annual cardiac ICU admission volume were not associated with improved prevention or rescue.

CONCLUSIONS

Our multi-institutional analysis identified cardiac ICU bed occupancy, registered nurse experience, and physician staffing as potentially important factors associated with cardiac arrest prevention and rescue. Recognizing the limitations of measuring these variables cross-sectionally, additional studies are needed to further investigate these organizational and personnel factors, their interrelationships, and how hospitals can modify structure to improve cardiac arrest outcomes.

Current monitoring and innovative predictive modeling to improve care in the pediatric cardiac intensive care unit

The objectives of this review are (I) to describe the challenges associated with monitoring patients in the pediatric cardiac intensive care unit (PCICU) and (II) to discuss the use of innovative statistical and artificial intelligence (AI) software programs to attempt to predict significant clinical events. Patients cared for in the PCICU are clinically fragile and at risk for fatal decompensation. Current monitoring modalities are often ineffective, sometimes inaccurate, and fail to detect a deteriorating clinical status in a timely manner. Predictive models created by AI and machine learning may lead to earlier detection of patients at risk for clinical decompensation and thereby improve care for critically ill pediatric cardiac patients.

Systemic effects of intracoronary nitroglycerin during coronary angiography in children after heart transplantation

Coronary spasm during coronary angiography for vasculopathy in children can be prevented by the intracoronary administration of nitroglycerin. We reviewed the anesthesia and catheterization reports and charts for pediatric transplant recipients who underwent angiography from 2005 through 2010. Correlation analysis was used to study the relation of post-injection systolic blood pressure (SBP) to nitroglycerin dose. Forty-one angiographic evaluations were performed on 25 patients (13 male and 12 female). Mean age was 9.9 ± 3.2 years (range, 3.3-16.1 yr). The mean total dose of nitroglycerin was 2.93 ± 1.60 µg/kg (range, 1-8 µg/kg). There was a significant drop between the baseline SBP (mean, 106 ± 21.6 mmHg) and the lowest mean SBP before nitroglycerin administration (78 ± 13.2, P <0.0001, paired t test). There was no significant additional change in SBP (mean after nitroglycerin administration, 80.7 ± 13.1 mmHg; P = 0.2). There was a significant drop in lowest heart rate between baseline (109 ± 16.5 beats/min) and before nitroglycerin administration (89 ± 14.3 beats/min; P <0.0001, paired t test). There was no significant additional change in heart rate (mean heart rate after nitroglycerin, 84 ± 17.7 beats/min; P = 0.09). There were 2 interventions for SBP before nitroglycerin and 2 after nitroglycerin. One child experienced a transient ST-T-segment change during angiography after nitroglycerin. In the highest dose range, the additional decrease in SBP was 7.2 mmHg (P=0.03). Routine intracoronary nitroglycerin administration in this dose range produced no significant changes in SBP or heart rate in children.