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Wilson HC, Gunsaulus ME, Owens GE, Goldstein SA, Yu S, Lowery RE, Olive MK. Failed Extubation in Neonates After Cardiac Surgery: A Single-Center, Retrospective Study. Pediatr Crit Care Med 2023; 24:e547-e555. [PMID: 37219966 DOI: 10.1097/pcc.0000000000003283] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/25/2023]
Abstract
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.
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Affiliation(s)
- Hunter C Wilson
- Division of Pediatric Cardiology, Department of Pediatrics, C. S. Mott Children's Hospital, University of Michigan, Ann Arbor, MI
| | - Megan E Gunsaulus
- Division of Cardiology, Department of Pediatrics, University of Pittsburgh Medical Center, Pittsburgh, PA
| | - Gabe E Owens
- Division of Pediatric Cardiology, Department of Pediatrics, C. S. Mott Children's Hospital, University of Michigan, Ann Arbor, MI
| | - Stephanie A Goldstein
- Division of Pediatric Critical Care, Department of Pediatrics, University of Utah, Salt Lake City, UT
| | - Sunkyung Yu
- Division of Pediatric Cardiology, Department of Pediatrics, C. S. Mott Children's Hospital, University of Michigan, Ann Arbor, MI
| | - Ray E Lowery
- Division of Pediatric Cardiology, Department of Pediatrics, C. S. Mott Children's Hospital, University of Michigan, Ann Arbor, MI
| | - Mary K Olive
- Division of Pediatric Cardiology, Department of Pediatrics, C. S. Mott Children's Hospital, University of Michigan, Ann Arbor, MI
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Gaies M, Olive MK, Owens GE, Charpie JR, Zhang W, Pasquali SK, Klugman D, Costello JM, Schwartz SM, Banerjee M. Methods to Enhance Causal Inference for Assessing Impact of Clinical Informatics Platform Implementation. Circ Cardiovasc Qual Outcomes 2023; 16:e009277. [PMID: 36727516 DOI: 10.1161/circoutcomes.122.009277] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
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.
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Affiliation(s)
- Michael Gaies
- Heart Institute, Cincinnati Children's Hospital Medical Center, OH (M.G.)
| | - Mary K Olive
- Department of Pediatrics, University of Michigan Medical School, Ann Arbor, MI (M.K.O., G.E.O., J.R.C., S.K.P.)
| | - Gabe E Owens
- Department of Pediatrics, University of Michigan Medical School, Ann Arbor, MI (M.K.O., G.E.O., J.R.C., S.K.P.)
| | - John R Charpie
- Department of Pediatrics, University of Michigan Medical School, Ann Arbor, MI (M.K.O., G.E.O., J.R.C., S.K.P.)
| | - Wenying Zhang
- Michigan Congenital Heart Outcomes Research and Discovery Unit, PC4 Data Coordinating Center, University of Michigan, Ann Arbor, MI (W.Z.)
| | - Sara K Pasquali
- Department of Pediatrics, University of Michigan Medical School, Ann Arbor, MI (M.K.O., G.E.O., J.R.C., S.K.P.)
| | - Darren Klugman
- Department of Anesthesia and Critical Care, Johns Hopkins University School of Medicine, Baltimore, MD (D.K.)
| | - John M Costello
- Department of Pediatrics, Medical University of South Carolina, Charleston, SC (J.M.C.)
| | - Steven M Schwartz
- Department of Paediatrics, Temerty Faculty of Medicine, The University of Toronto, ON (S.M.S.)
| | - Mousumi Banerjee
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI (M.B.)
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Alten J, Cooper DS, Klugman D, Raymond TT, Wooton S, Garza J, Clarke-Myers K, Anderson J, Pasquali SK, Absi M, Affolter JT, Bailly DK, Bertrandt RA, Borasino S, Dewan M, Domnina Y, Lane J, McCammond AN, Mueller DM, Olive MK, Ortmann L, Prodhan P, Sasaki J, Scahill C, Schroeder LW, Werho DK, Zaccagni H, Zhang W, Banerjee M, Gaies M. Preventing Cardiac Arrest in the Pediatric Cardiac Intensive Care Unit Through Multicenter Collaboration. JAMA Pediatr 2022; 176:1027-1036. [PMID: 35788631 PMCID: PMC9257678 DOI: 10.1001/jamapediatrics.2022.2238] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/03/2022] [Accepted: 04/28/2022] [Indexed: 12/14/2022]
Abstract
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.
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Affiliation(s)
- Jeffrey Alten
- Department of Pediatrics, University of Cincinnati School of Medicine, Heart Institute, Cincinnati Children’s Hospital, Cincinnati, Ohio
| | - David S. Cooper
- Department of Pediatrics, University of Cincinnati School of Medicine, Heart Institute, Cincinnati Children’s Hospital, Cincinnati, Ohio
| | - Darren Klugman
- Division of Cardiac Critical Care Medicine, Children’s National Hospital, Washington, DC
- Division of Anesthesia, Critical Care Medicine, Johns Hopkins Children’s Center, Baltimore, Maryland
| | - Tia Tortoriello Raymond
- Department of Pediatrics, Cardiac Critical Care, Medical City Children’s Hospital, Dallas, Texas
| | - Sharyl Wooton
- James M. Anderson Center for Health Systems Excellence, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio
| | - Janie Garza
- Department of Pediatrics, Cardiac Critical Care, Medical City Children’s Hospital, Dallas, Texas
| | - Katherine Clarke-Myers
- Department of Pediatrics, Heart Institute, Cincinnati Children’s Hospital, Cincinnati, Ohio
| | - Jeffrey Anderson
- Department of Pediatrics, University of Cincinnati School of Medicine, Heart Institute, Cincinnati Children’s Hospital, Cincinnati, Ohio
| | - Sara K. Pasquali
- Division of Pediatric Cardiology, Department of Pediatrics, University of Michigan Medical School, C.S. Mott Children’s Hospital, Ann Arbor
| | - Mohammed Absi
- Department of Pediatrics, Heart Institute, University of Tennessee, Le Bonheur Children’s Hospital, Memphis
| | - Jeremy T. Affolter
- Department of Pediatrics, Critical Care Medicine, University of Missouri, Children’s Mercy Hospital, Kansas City
- Department of Pediatrics, University of Texas at Austin-Dell Medical School, Dell Children’s Medical Center of Central Texas, Austin
| | - David K. Bailly
- Division of Pediatric Critical Care, Department of Pediatrics, University of Utah, Primary Children’s Hospital, Salt Lake City
| | - Rebecca A. Bertrandt
- Department of Pediatric Critical Care, Medical College of Wisconsin, Children’s Wisconsin, Milwaukee
| | - Santiago Borasino
- Department of Pediatrics, University of Alabama at Birmingham, Cardiac Critical Care, Birmingham
| | - Maya Dewan
- Department of Pediatrics, University of Cincinnati School of Medicine, Division of Critical Care Medicine, Cincinnati Children’s Hospital, Cincinnati, Ohio
| | - Yuliya Domnina
- Division of Cardiac Critical Care Medicine, Children’s National Hospital, Washington, DC
- Department of Pediatrics and Critical Care Medicine, Cardiac Intensive Care Unit, Children’s Hospital of Pittsburgh, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania
| | - John Lane
- Division of Cardiovascular Intensive Care, Phoenix Children’s Hospital, Phoenix Arizona
| | - Amy N. McCammond
- Department of Pediatrics, Pediatric Cardiac Intensive Care, University of California San Francisco, Benioff Children’s Hospital, San Francisco
| | - Dana M. Mueller
- Department of Pediatrics, Division of Critical Care, University of Washington, Seattle Children’s Hospital, Seattle
- Division of Cardiology, Department of Pediatrics, University of California San Diego, Rady Children’s Hospital, San Diego
| | - Mary K. Olive
- Division of Pediatric Cardiology, Department of Pediatrics, University of Michigan Medical School, C.S. Mott Children’s Hospital, Ann Arbor
| | - Laura Ortmann
- Department of Pediatrics, University of Nebraska Medical Center, Children’s Hospital and Medical Center, Omaha
| | - Parthak Prodhan
- Division of Pediatric Cardiology, Department of Pediatrics, University of Arkansas for Medical Sciences, Arkansas Children’s Hospital, Little Rock
| | - Jun Sasaki
- Division of Cardiac Critical Care Medicine, Nicklaus Children’s Hospital, Miami, Florida
- Division of Critical Care Medicine, Department of Pediatrics, Weill Cornell Medicine, New York, New York
| | - Carly Scahill
- Department of Pediatrics, Heart Institute, Children’s Hospital Colorado, Aurora
| | - Luke W. Schroeder
- Department of Pediatrics, Medical University of South Carolina, Charleston
| | - David K. Werho
- Division of Cardiology, Department of Pediatrics, University of California San Diego, Rady Children’s Hospital, San Diego
| | - Hayden Zaccagni
- Department of Pediatrics, University of Alabama at Birmingham, Cardiac Critical Care, Birmingham
| | - Wenying Zhang
- Center for Healthcare Outcomes and Policy, University of Michigan, Ann Arbor
| | - Mousumi Banerjee
- Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor
- Department of Biostatistics, University of Michigan, Ann Arbor
| | - Michael Gaies
- Department of Pediatrics, University of Cincinnati School of Medicine, Heart Institute, Cincinnati Children’s Hospital, Cincinnati, Ohio
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Tossas-Betancourt C, Li NY, Shavik SM, Afton K, Beckman B, Whiteside W, Olive MK, Lim HM, Lu JC, Phelps CM, Gajarski RJ, Lee S, Nordsletten DA, Grifka RG, Dorfman AL, Baek S, Lee LC, Figueroa CA. Data-driven computational models of ventricular-arterial hemodynamics in pediatric pulmonary arterial hypertension. Front Physiol 2022; 13:958734. [PMID: 36160862 PMCID: PMC9490558 DOI: 10.3389/fphys.2022.958734] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Accepted: 08/01/2022] [Indexed: 11/13/2022] Open
Abstract
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.
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Affiliation(s)
| | - Nathan Y. Li
- Department of Pharmaceutical Sciences, University of Michigan, Ann Arbor, MI, United States
| | - Sheikh M. Shavik
- Department of Mechanical Engineering, Bangladesh University of Engineering and Technology, Dhaka, Bangladesh
| | - Katherine Afton
- Department of Pediatrics, Division of Pediatric Cardiology, University of Michigan, Ann Arbor, MI, United States
| | - Brian Beckman
- Department of Pediatrics, Nationwide Children’s Hospital, Columbus, OH, United States
| | - Wendy Whiteside
- Department of Pediatrics, Division of Pediatric Cardiology, University of Michigan, Ann Arbor, MI, United States
| | - Mary K. Olive
- Department of Pediatrics, Division of Pediatric Cardiology, University of Michigan, Ann Arbor, MI, United States
| | - Heang M. Lim
- Department of Pediatrics, Division of Pediatric Cardiology, University of Michigan, Ann Arbor, MI, United States
| | - Jimmy C. Lu
- Department of Pediatrics, Division of Pediatric Cardiology, University of Michigan, Ann Arbor, MI, United States
| | - Christina M. Phelps
- Department of Pediatrics, Nationwide Children’s Hospital, Columbus, OH, United States
| | - Robert J. Gajarski
- Department of Pediatrics, Nationwide Children’s Hospital, Columbus, OH, United States
| | - Simon Lee
- Department of Pediatrics, Nationwide Children’s Hospital, Columbus, OH, United States
| | - David A. Nordsletten
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, United States
- Department of Surgery, University of Michigan, Ann Arbor, MI, United States
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Ronald G. Grifka
- Department of Pediatrics, Division of Pediatric Cardiology, University of Michigan, Ann Arbor, MI, United States
| | - Adam L. Dorfman
- Department of Pediatrics, Division of Pediatric Cardiology, University of Michigan, Ann Arbor, MI, United States
| | - Seungik Baek
- Department of Mechanical Engineering, Michigan State University, East Lansing, MI, United States
| | - Lik Chuan Lee
- Department of Mechanical Engineering, Michigan State University, East Lansing, MI, United States
| | - C. Alberto Figueroa
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, United States
- Department of Surgery, University of Michigan, Ann Arbor, MI, United States
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Lasa JJ, Banerjee M, Zhang W, Bailly DK, Sasaki J, Bertrandt R, Raymond TT, Olive MK, Smith A, Alten J, Gaies M. Critical Care Unit Organizational and Personnel Factors Impact Cardiac Arrest Prevention and Rescue in the Pediatric Cardiac Population. Pediatr Crit Care Med 2022; 23:255-267. [PMID: 35020714 DOI: 10.1097/pcc.0000000000002892] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
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.
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Affiliation(s)
- Javier J Lasa
- Division of Critical Care Medicine, Texas Children's Hospital, Baylor College of Medicine, Houston, TX
- Division of Cardiology, Texas Children's Hospital, Baylor College of Medicine, Houston, TX
| | - Mousumi Banerjee
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI
| | - Wenying Zhang
- PC 4 Data Coordinating Center, Michigan Congenital Heart Outcomes Research and Discovery Unit, University of Michigan, Ann Arbor, MI
| | - David K Bailly
- Primary Children's, Department of Pediatrics, Division of Critical Care, University of Utah, Salt Lake City, UT
| | - Jun Sasaki
- Department of Cardiology, Nicklaus Children's Hospital, Miami, FL
| | - Rebecca Bertrandt
- Division of Pediatric Critical Care, Children's Wisconsin, Milwaukee, WI
| | - Tia T Raymond
- Cardiac Critical Care, Department of Pediatrics, Medical City Children's Hospital, Dallas, TX
| | - Mary K Olive
- Department of Pediatrics, University of Michigan Medical School, Ann Arbor, MI
| | - Andrew Smith
- Monroe Carell Jr Children's Hospital at Vanderbilt, Divisions of Cardiology and Critical Care Medicine, Department of Pediatrics, Vanderbilt University School of Medicine, Nashville, TN
| | - Jeffrey Alten
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati Children's Hospital Medical Center, Cincinnati, OH
| | - Michael Gaies
- Monroe Carell Jr Children's Hospital at Vanderbilt, Divisions of Cardiology and Critical Care Medicine, Department of Pediatrics, Vanderbilt University School of Medicine, Nashville, TN
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Olive MK, Fraser CD, Kutty S, McKenzie ED, Hammel JM, Krishnamurthy R, Dodd NA, Maskatia SA. Infundibular sparing versus transinfundibular approach to the repair of tetralogy of Fallot. CONGENIT HEART DIS 2020; 14:1149-1156. [DOI: 10.1111/chd.12863] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/13/2019] [Revised: 11/10/2019] [Accepted: 11/18/2019] [Indexed: 11/28/2022]
Affiliation(s)
- Mary K. Olive
- Department of Pediatrics, Section of Pediatric Cardiology Congenital Heart Center, C.S. Mott Children’s Hospital, University of Michigan Ann Arbor Michigan
| | - Charles D. Fraser
- Department of Surgery and Perioperative Care, Texas Center for Pediatric and Congenital Heart Disease University of Texas Dell Medical School, Dell Children’s Medical Center Austin Texas
| | - Shelby Kutty
- Department of Pediatrics Taussig Congenital Heart Center, Johns Hopkins University Baltimore Maryland
| | - Emmett D. McKenzie
- Section of Congenital Heart Surgery Texas Children’s Hospital, Baylor College of Medicine Houston Texas
| | - James M. Hammel
- Section of Cardiovascular Surgery University of Nebraska College of Medicine Omaha Nebraska
| | - Rajesh Krishnamurthy
- Section of Diagnostic Radiology Nationwide Children’s Hospital, Ohio State University Columbus Ohio
| | - Nicolas A. Dodd
- Section of Pediatric Radiology Texas Children’s Hospital, Baylor College of Medicine Houston Texas
| | - Shiraz A. Maskatia
- Section of Pediatric Cardiology Stanford University Palo Alto California
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Gaies M, Olive MK, Owens G, Charpie J, Zhang W, Pasquali S, Klugman D, Costello J, Hammel J, Gaynor JW, Banerjee M, Schwartz S. PEDIATRIC CARDIAC CRITICAL CARE OUTCOMES IMPROVE FOLLOWING IMPLEMENTATION OF A COMMERCIAL DATA AGGREGATION AND VISUALIZATION SOFTWARE PLATFORM. J Am Coll Cardiol 2019. [DOI: 10.1016/s0735-1097(19)31170-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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Abstract
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.
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Affiliation(s)
- Mary K Olive
- Division of Pediatric Cardiology, C.S. Mott Children's Hospital, University of Michigan, Ann Arbor, MI, USA
| | - Gabe E Owens
- Division of Pediatric Cardiology, C.S. Mott Children's Hospital, University of Michigan, Ann Arbor, MI, USA
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Maskatia S, Olive MK, Dodd NA, Krishnamurthy R, Fraser CD, McKenzie ED, Hammel JM, Kutty S. Improved right ventricular outflow tract function in patients with Tetralogy of Fallot after infundibular sparing compared to transventricular repair. J Cardiovasc Magn Reson 2015. [PMCID: PMC4328596 DOI: 10.1186/1532-429x-17-s1-q81] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
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Lara DA, Olive MK, George JF, Brown RN, Carlo WF, Colvin EV, Steenwyck BL, Pearce FB. Systemic effects of intracoronary nitroglycerin during coronary angiography in children after heart transplantation. Tex Heart Inst J 2014; 41:21-5. [PMID: 24512395 DOI: 10.14503/thij-12-2704] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
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.
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Affiliation(s)
- Diego A Lara
- Departments of Pediatrics (Drs. Lara and Olive) and Anesthesiology (Dr. Steenwyck), and Divisions of Cardiothoracic Surgery (Dr. George and Mr. Brown) and Pediatric Cardiology (Drs. Carlo, Colvin, and Pearce), University of Alabama School of Medicine, Birmingham, Alabama 35294
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