Publications by authors named "Howard E Jeffries"

27 Publications

  • Page 1 of 1

Characteristics and Symptoms of App Users Seeking COVID-19-Related Digital Health Information and Remote Services: Retrospective Cohort Study.

J Med Internet Res 2020 10 20;22(10):e23197. Epub 2020 Oct 20.

K Health Inc, New York, NY, United States.

Background: Patient-facing digital health tools have been promoted to help patients manage concerns related to COVID-19 and to enable remote care and self-care during the COVID-19 pandemic. It has also been suggested that these tools can help further our understanding of the clinical characteristics of this new disease. However, there is limited information on the characteristics and use patterns of these tools in practice.

Objective: The aims of this study are to describe the characteristics of people who use digital health tools to address COVID-19-related concerns; explore their self-reported symptoms and characterize the association of these symptoms with COVID-19; and characterize the recommendations provided by digital health tools.

Methods: This study used data from three digital health tools on the K Health app: a protocol-based COVID-19 self-assessment, an artificial intelligence (AI)-driven symptom checker, and communication with remote physicians. Deidentified data were extracted on the demographic and clinical characteristics of adults seeking COVID-19-related health information between April 8 and June 20, 2020. Analyses included exploring features associated with COVID-19 positivity and features associated with the choice to communicate with a remote physician.

Results: During the period assessed, 71,619 individuals completed the COVID-19 self-assessment, 41,425 also used the AI-driven symptom checker, and 2523 consulted with remote physicians. Individuals who used the COVID-19 self-assessment were predominantly female (51,845/71,619, 72.4%), with a mean age of 34.5 years (SD 13.9). Testing for COVID-19 was reported by 2901 users, of whom 433 (14.9%) reported testing positive. Users who tested positive for COVID-19 were more likely to have reported loss of smell or taste (relative rate [RR] 6.66, 95% CI 5.53-7.94) and other established COVID-19 symptoms as well as ocular symptoms. Users communicating with a remote physician were more likely to have been recommended by the self-assessment to undergo immediate medical evaluation due to the presence of severe symptoms (RR 1.19, 95% CI 1.02-1.32). Most consultations with remote physicians (1940/2523, 76.9%) were resolved without need for referral to an in-person visit or to the emergency department.

Conclusions: Our results suggest that digital health tools can help support remote care and self-management of COVID-19 and that self-reported symptoms from digital interactions can extend our understanding of the symptoms associated with COVID-19.
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http://dx.doi.org/10.2196/23197DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7609191PMC
October 2020

Reclassifying by highest complexity operation rather than first operation influences mortality after pediatric heart surgery.

J Thorac Cardiovasc Surg 2018 11 18;156(5):1961-1967.e9. Epub 2018 Jul 18.

Division of Pediatric Critical Care, Department of Pediatrics, Medical College of Wisconsin, Milwaukee, Wis.

Objective: To evaluate the effect on mortality of reclassifying patients undergoing pediatric heart reoperations of varying complexity by operation of highest complexity instead of by first operation.

Methods: Data from the Virtual Pediatric Systems Database on children aged < 18 years who underwent heart surgery (with or without cardiopulmonary bypass) were included (2009-2015). Only patients who underwent reoperations during the same hospitalization were included. Patients were classified based on the first cardiovascular operation (the index operation), and on the complexity of the operation (the operation with the highest Society of Thoracic Surgeons-European Association for Cardio-Thoracic Surgery [STAT] mortality category of each hospital admission) performed.

Results: Of 51,047 patients (73 centers), 22,393 met inclusion criteria. Using index operation as the classifying operation, the number of patients classified in the STAT 1 category increased by approximately 2.5 times compared with the highest-complexity operation (index, 7,077 and highest complexity, 2,654). In contrast, when the highest-complexity classification was used, we noted an increase in the number of patients in other STAT categories. We also noted higher mortality in all STAT categories when patients were classified by index operation instead of by highest complexity (index vs highest STAT category 1, 0.6% vs 0.2%; category 2, 2.4% vs 0.8%; category 3, 3.1% vs 2.1%; category 4, 5.8% vs 5.6%; and category 5, 16.7% vs 16.5%).

Conclusions: This study demonstrates differences in the reported number of patients and reported mortality in each STAT category among children undergoing various heart reoperations during the same hospitalization by classifying patients based on index operation compared with the operation of highest complexity.
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http://dx.doi.org/10.1016/j.jtcvs.2018.06.035DOI Listing
November 2018

The American College of Critical Care Medicine Clinical Practice Parameters for Hemodynamic Support of Pediatric and Neonatal Septic Shock: Executive Summary.

Pediatr Crit Care Med 2017 09;18(9):884-890

1No institution affiliation. 2Department of Critical Care Medicine and Pediatrics, University of Pittsburgh School of Medicine, Pittsburgh, PA. 3Department of Critical Care Medicine and Pediatrics, University of Pittsburgh School of Medicine, Pittsburgh, PA. 4Department of Pediatric Critical Care, Riley Hospital for Children, Indiana University, Bloomington, IN. 5Department of Pediatrics, Washington University School of Medicine, St. Louis, MO. 6Department of Pediatrics, Baylor College of Medicine/Texas Children's Hospital, Houston, TX. 7Department of Pediatrics, Baylor College of Medicine/Texas Children's Hospital, Houston, TX. 8Pediatric Critical Care Medicine, Covenant Women and Children's Hospital, Texas Tech University, Lubbock, TX. 9Department of Pediatrics, Division of Pediatric Critical Care Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL. 10Division of Pediatric Critical Care, University of British Columbia, Vancouver, BC, Canada. 11Department of Pediatrics, Division of Pediatric Critical Care Medicine, Medical College of Wisconsin, Milwaukee, WI. 12Department of Pediatrics, Baylor College of Medicine, Houston, TX. 13Department of Pediatrics, Saint Barnabas Medical Center, Livingston, NJ. 14Division of Emergency Medicine and Center for Pediatric Clinical Effectiveness, Children's Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA. 15Intensive Care & Bioethics, Great Ormond St Hospital for Sick Children, London, United Kingdom. 16Pediatric Critical Care Medicine, Department of Pediatrics, Stollery Children's Hospital/University of Alberta, Edmonton, AB, Canada. 17Department of Pediatrics, Division of Pediatric Critical Care Medicine, Duke Children's, Durham, NC. 18Departments of Pediatrics and Critical Care, Clinical Epidemiology and Biostatistics, McMaster University, Pediatric Intensive Care Unit, McMaster Children's Hospital, Hamilton, ON, Canada. 19Beth Israel Medical Center, Hartsdale, NY. 20Department of Pediatrics and Communicable Diseases, University of Michigan, Ann Arbor, MI. 21Departments of Pediatrics and Biochemistry, Washington University in Saint Louis School of Medicine, St. Louis, MO. 22Department of Pediatrics, Centre mère-enfant Soleil du CHU de Québec-Université Laval, Québec City, QC, Canada. 23Department of Inpatient Pediatrics, Kaiser Santa Clara Medical Center, Santa Clara, CA. 24Department of Anesthesiology and Critical Care Medicine, University of Pennsylvania Perelman School of Medicine and The Children's Hospital of Philadelphia, Philadelphia, PA. 25Division of Pediatric Critical Care Medicine, Department of Pediatrics, University of Mott C.S. Children's Hospital, Ann Arbor, MI. 26Division of Critical Care, Department of Pediatrics, Emory University School of Medicine, Atlanta, GA. 27Department of Pediatrics-Critical Care Medicine, University of Maryland School of Medicine, Baltimore, MD. 28Division of Pediatric Critical Care Medicine, Weill Cornell Medical College, New York, NY. 29Department of Pediatrics, Division of Critical Care Medicine, Nationwide Children's Hospital, Columbus, OH. 30Department of Critical Care Medicine, Children's Mercy Hospital, Kansas City, MO. 31Department of Pediatrics, Texas Tech University Health Sciences Center, El Paso, TX. 32Division of Pediatric Critical Care, University of Florida, Jacksonville, FL 33Bon Secours St. Mary's Hospital, Glen Allen, VA. 34Department of Pediatrics/Division of Pediatric Critical Care, University of Rochester School of Medicine and Dentistry, Rochester, NY. 35Department of Pediatrics, University of Washington School of Medicine, Seattle, WA. 36Department of Pediatrics, Division of Critical Care, Stanford University School of Medicine, Palo Alto, CA. 37Pediatric Critical Care Medicine, The Children's Hospital at Montefiore, The Pediatric Hospital for Albert Einstein College of Medicine, Bronx, NY. 38Department of Pediatrics, University of British Columbia, Vancouver, BC, Canada. 39Department of Pediatrics, Naval Medical Center San Diego and University of California San Diego School of Medicine, San Diego, CA. 40Department of Pediatrics and Pediatric Critical Care Medicine, The Valley Hospital, Ridgewood, NJ. 41Cardiothoracic ICU, National University Hospital, Singapore. 42Paediatric ICU, The Royal Children's Hospital, Parkville, VIC, Australia. 43Department of Paediatrics, University of Melbourne, Melbourne, VIC, Australia. 44Children's Hospital of Pittsburgh, Pittsburgh, PA. 45Department of Pediatrics, Medical College of Georgia at Augusta University, Augusta, GA. 46Department of Pediatrics, Division of Critical Care Medicine, University of Michigan, Ann Arbor, MI. 47Department of Pharmacy Practice, Loma Linda University School of Pharmacy, Loma Linda, CA. 48Division of Emergency Medicine, Ann and Robert Lurie Children's Hospital of Chicago, Feinberg School of Medicine at Northwestern University, Chicago, IL. 49UCL Great Ormond Street Institute of Child Health and Paediatric Intensive Care Unit, Great Ormond Street Hospital for Children, NHS Trust, London, United Kingdom. 50Pediatric Intensive Care and Emergency Services, Apollo Children's Hospital, Chennai, India. 51Department of Pediatrics, Division of Pediatric Critical Care, Duke University School of Nursing and School of Medicine, Durham, NC. 52Pediatrics School of Medicine, Austral University, Pcia de Buenos Aires, Argentina. 53Departments of Pediatrics and Emergency Medicine, University of Colorado School of Medicine, Aurora, CO. 54Critical Care and Transport, Nemours Children's Hospital, Orlando, FL. 55Department of Pediatrics, Critical Care Medicine, Albert Einstein College of Medicine, Bronx, NY. 56Department of Anesthesiology and Critical Care, The Children's Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA. 57Department of Pediatrics, Division of Pediatric Critical Care Medicine, University of Washington School of Medicine, Seattle, WA. 58Departments of Pediatrics & Anesthesiology, Sinai Hospital/NAPA, Baltimore, MD. 59Department of Pediatrics, University of Maryland Medical School, Baltimore, MD.

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http://dx.doi.org/10.1097/PCC.0000000000001259DOI Listing
September 2017

Performance of Pediatric Risk of Mortality Score Among Critically Ill Children With Heart Disease.

World J Pediatr Congenit Heart Surg 2017 07;8(4):427-434

5 Division of Pediatric Cardiology, Department of Pediatrics, College of Medicine, Arkansas Children's Hospital, University of Arkansas for Medical Sciences, Little Rock, AR, USA.

Objective: To evaluate the performance of the Pediatric Risk of Mortality 3 (PRISM-3) score in critically ill children with heart disease.

Methods: Patients <18 years of age admitted with cardiac diagnoses (cardiac medical and cardiac surgical) to one of the participating pediatric intensive care units in the Virtual Pediatric Systems, LLC, database were included. Performance of PRISM-3 was evaluated with discrimination and calibration measures among both cardiac surgical and cardiac medical patients.

Results: The study population consisted of 87,993 patients, of which 49% were cardiac medical patients (n = 43,545) and 51% were cardiac surgical patients (n = 44,448). The ability of PRISM-3 to distinguish survivors from nonsurvivors was acceptable for the entire cohort (c-statistic 0.86). However, PRISM-3 did not perform as well when stratified by varied severity of illness categories. Pediatric Risk of Mortality 3 underpredicted mortality among patients with lower severity of illness categories (quintiles 1-4) whereas it overpredicted mortality among patients with greatest severity of illness category (fifth quintile). When stratified by Society of Thoracic Surgeons-European Association for Cardiothoracic Surgery (STS-EACTS) categories, PRISM-3 overpredicted mortality among the STS-EACTS mortality categories 1, 2, and 3 and underpredicted mortality among the STS-EACTS mortality categories 4 and 5. Pediatric Risk of Mortality 3 overpredicted mortality among centers with high cardiac surgery volume whereas it underpredicted mortality among centers with low cardiac surgery volume.

Conclusion: Data from this large multicenter study do not support the use of PRISM-3 in cardiac surgical or cardiac medical patients. In this study, the ability of PRISM-3 to distinguish survivors from nonsurvivors was fair at best, and the accuracy with which it predicted death was poor.
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http://dx.doi.org/10.1177/2150135117704656DOI Listing
July 2017

American College of Critical Care Medicine Clinical Practice Parameters for Hemodynamic Support of Pediatric and Neonatal Septic Shock.

Crit Care Med 2017 06;45(6):1061-1093

1No institution affiliation. 2Department of Critical Care Medicine and Pediatrics, University of Pittsburgh School of Medicine, Pittsburgh, PA. 3Department of Pediatric Critical Care, Riley Hospital for Children, Indiana University, IN. 4Department of Pediatrics, Washington University School of Medicine, St. Louis, MO. 5Department of Pediatrics, Baylor College of Medicine/Texas Children's Hospital, Houston, TX. 6Pediatric Critical Care Medicine, Covenant Women and Children's Hospital, Texas Tech University, Lubbock, TX. 7Division of Pediatric Critical Care Medicine, Department of Pediatrics, Feinberg School of Medicine, Northwestern University, Chicago, IL. 8Division of Pediatric Critical Care, University of British Columbia, Vancouver, BC, Canada. 9Division of Pediatric Critical Care Medicine, Department of Pediatrics, Medical College of Wisconsin, Milwaukee, WI. 10Department of Pediatrics, Baylor College of Medicine, Houston, TX. 11Department of Pediatrics, Saint Barnabas Medical Center, Livingston, NJ. 12Division of Emergency Medicine and Center for Pediatric Clinical Effectiveness, University of Pennsylvania Perelman School of Medicine, Children's Hospital of Philadelphia, Philadelphia, PA. 13Intensive Care & Bioethics, Great Ormond St Hospital for Sick Children, London, United Kingdom. 14Pediatric Critical Care Medicine, Department of Pediatrics, Stollery Children's Hospital/University of Alberta, Edmonton, AB, Canada. 15Division of Pediatric Critical Care Medicine, Department of Pediatrics, Duke Children's, Durham, NC. 16Departments of Pediatrics and Critical Care, Clinical Epidemiology and Biostatistics, McMaster University, Pediatric Intensive Care Unit, McMaster Children's Hospital, Hamilton, ON, Canada. 17Beth Israel Medical Center, Hartsdale, NY. 18Department of Pediatrics and Communicable Diseases, University of Michigan, Ann Arbor, MI. 19Departments of Pediatrics and Biochemistry, Washington University in Saint Louis School of Medicine, Saint Louis, MO. 20Department of Pediatrics, Centre mère-enfant Soleil du CHU de Québec-Université Laval, Québec City, QC, Canada. 21Department of Inpatient Pediatrics, Kaiser Santa Clara Medical Center, Santa Clara, CA. 22Department of Anesthesiology and Critical Care Medicine, University of Pennsylvania Perelman School of Medicine, Children's Hospital of Philadelphia, Philadelphia, PA. 23Division of Pediatric Critical Care Medicine, Department of Pediatrics, University of Mott C.S. Children's Hospital, Ann Arbor, MI. 24Division of Critical Care, Department of Pediatrics, Emory University School of Medicine, Atlanta, GA. 25Department of Pediatrics-Critical Care Medicine, University of Maryland School of Medicine, Baltimore, MD. 26Division of Pediatric Critical Care Medicine, Weill Cornell Medical College, New York, NY. 27Division of Critical Care Medicine, Department of Pediatrics, Nationwide Children's Hospital, Columbus, OH. 28Department of Critical Care Medicine, Children's Mercy Hospital, Kansas City, MO. 29Department of Pediatrics, Texas Tech University Health Sciences Center, El Paso, TX. 30Division of Pediatric Critical Care, University of Florida, Jacksonville, FL. 31Bon Secours St. Mary's Hospital, Glen Allen, VA. 32Division of Pediatric Critical Care, Department of Pediatrics, University of Rochester School of Medicine and Dentistry, Rochester, NY. 33Department of Pediatrics, University of Washington School of Medicine, Seattle, WA. 34Division of Critical Care, Department of Pediatrics, Stanford University School of Medicine, Palo Alto, CA. 35Pediatric Critical Care Medicine, The Children's Hospital at Montefiore, The Pediatric Hospital for Albert Einstein College of Medicine, Bronx, NY. 36Department of Pediatrics, University of British Columbia, UBC & BC Children's Hospital Professor in Critical Care-Global Child Health, Vancouver, BC, Canada. 37Department of Pediatrics, Naval Medical Center San Diego and University of California San Diego School of Medicine, San Diego, CA. 38Department of Pediatrics and Pediatric Critical Care Medicine, The Valley Hospital, Ridgewood, NJ. 39Cardiothoracic ICU, National University Hospital, Singapore. 40Paediatric ICU, The Royal Children's Hospital, Melbourne, Australia. 41Department of Paediatrics, University of Melbourne, Melbourne, Australia. 42Children's Hospital of Pittsburgh, Pittsburgh, PA. 43Department of Pediatrics, Medical College of Georgia at Augusta University, Augusta, GA. 44Division of Critical Care Medicine, Department of Pediatrics, University of Michigan, Ann Arbor, MI. 45Department of Pharmacy Practice, Loma Linda University School of Pharmacy, Loma Linda, CA. 46Division of Emergency Medicine, Ann and Robert Lurie Children's Hospital of Chicago, Feinberg School of Medicine at Northwestern University, Chicago, IL. 47UCL Great Ormond Street Institute of Child Health and Paediatric Intensive Care Unit, Great Ormond Street Hospital for Children, NHS Trust, London, United Kingdom. 48Pediatric Intensive Care and Emergency Services, Apollo Children's Hospital, Chennai, India. 49Division of Pediatric Critical Care, Department of Pediatrics, Duke University School of Nursing and School of Medicine, Durham, NC. 50Pediatrics School of Medicine, Austral University, Pcia de Buenos Aires, Argentina. 51Departments of Pediatrics and Emergency Medicine, University of Colorado School of Medicine, Aurora, CO. 52Critical Care and Transport, Nemours Children's Hospital, Orlando, FL. 53Department of Pediatrics, Critical Care Medicine, Albert Einstein College of Medicine, Bronx, NY. 54Division of Pediatric Critical Care Medicine, Department of Pediatrics, University of Washington School of Medicine, Seattle, WA. 55Departments of Pediatrics & Anesthesiology, Sinai Hospital/NAPA, Baltimore, MD. 56Department of Pediatrics, University of Maryland Medical School, Baltimore, MD.

Objectives: The American College of Critical Care Medicine provided 2002 and 2007 guidelines for hemodynamic support of newborn and pediatric septic shock. Provide the 2014 update of the 2007 American College of Critical Care Medicine "Clinical Guidelines for Hemodynamic Support of Neonates and Children with Septic Shock."

Design: Society of Critical Care Medicine members were identified from general solicitation at Society of Critical Care Medicine Educational and Scientific Symposia (2006-2014). The PubMed/Medline/Embase literature (2006-14) was searched by the Society of Critical Care Medicine librarian using the keywords: sepsis, septicemia, septic shock, endotoxemia, persistent pulmonary hypertension, nitric oxide, extracorporeal membrane oxygenation, and American College of Critical Care Medicine guidelines in the newborn and pediatric age groups.

Measurements And Main Results: The 2002 and 2007 guidelines were widely disseminated, translated into Spanish and Portuguese, and incorporated into Society of Critical Care Medicine and American Heart Association/Pediatric Advanced Life Support sanctioned recommendations. The review of new literature highlights two tertiary pediatric centers that implemented quality improvement initiatives to improve early septic shock recognition and first-hour compliance to these guidelines. Improved compliance reduced hospital mortality from 4% to 2%. Analysis of Global Sepsis Initiative data in resource rich developed and developing nations further showed improved hospital mortality with compliance to first-hour and stabilization guideline recommendations.

Conclusions: The major new recommendation in the 2014 update is consideration of institution-specific use of 1) a "recognition bundle" containing a trigger tool for rapid identification of patients with septic shock, 2) a "resuscitation and stabilization bundle" to help adherence to best practice principles, and 3) a "performance bundle" to identify and overcome perceived barriers to the pursuit of best practice principles.
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http://dx.doi.org/10.1097/CCM.0000000000002425DOI Listing
June 2017

Outcomes Analysis and Quality Improvement in Children With Congenital and Acquired Cardiovascular Disease.

Pediatr Crit Care Med 2016 08;17(8 Suppl 1):S362-6

1Department of Pediatrics, Section of Critical Care Medicine, University of Washington School of Medicine, Seattle Children's Hospital, Seattle, WA. 2Department of Pediatrics, Section of Cardiology, University of Michigan Medical School, C.S. Mott Children's Hospital, Ann Arbor, MI.

Objectives: In this review, the current state of outcomes analysis and quality improvement in children with acquired and congenital cardiovascular disease will be discussed, with an emphasis on defining and measuring outcomes and quality in pediatric cardiac critical care medicine and risk stratification systems.

Data Source: MEDLINE and PubMed

Conclusion: : Measuring quality and outcomes in the pediatric cardiac critical care environment is challenging owing to many inherent obstacles, including a diverse patient mix, difficulty in determining how the care of the ICU team contributes to outcomes, and the lack of an adequate risk-adjustment method for pediatric cardiac critical care patients. Despite these barriers, new solutions are emerging that capitalize on lessons learned from other quality improvement initiatives, providing opportunities to build upon previous successes.
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http://dx.doi.org/10.1097/PCC.0000000000000785DOI Listing
August 2016

Association of 24/7 In-House Intensive Care Unit Attending Physician Coverage With Outcomes in Children Undergoing Heart Operations.

Ann Thorac Surg 2016 Dec 18;102(6):2052-2061. Epub 2016 Jun 18.

Division of Cardiology, Department of Pediatrics, Nationwide Children's Hospital, Columbus, Ohio.

Background: Multicenter data regarding the around-the-clock (24/7) presence of an in-house critical care attending physician with outcomes in children undergoing cardiac operations are limited.

Methods: Patients younger than 18 years of age who underwent operations (with or without cardiopulmonary bypass [CPB]) for congenital heart disease at 1 of the participating intensive care units (ICUs) in the Virtual PICU Systems (VPS, LLC) database were included (2009-2014). The study population was divided into 2 groups: the 24/7 group (14,737 patients; 32 hospitals), and the No 24/7 group (10,422 patients; 22 hospitals). Propensity-score matching was performed to match patients 1:1 in the 24/7 group and in the No 24/7 group.

Results: Overall, 25,159 patients from 54 hospitals qualified for inclusion. By propensity matching, 9,072 patients (4,536 patient pairs) from 51 hospitals were matched 1:1 in the 2 groups. After matching, mortality at ICU discharge was lower among the patients treated in hospitals with 24/7 coverage (24/7 versus No 24/7, 2.8% versus 4.0%; p = 0.002). The use of extracorporeal membrane oxygenation (ECMO), the incidence of cardiac arrest, extubation within 48 hours after operation, the rate of reintubation, and the duration of arterial line and central venous line use after operation were significantly improved in the 24/7 group. When stratified by surgical complexity, survival benefits of 24/7 coverage persisted among patients undergoing both high-complexity and low-complexity operations.

Conclusions: The presence of 24-hour in-ICU attending physician coverage in children undergoing cardiac operations is associated with improved outcomes, including ICU mortality. It is possible that 24-hour in-ICU attending physician coverage may be a surrogate for other factors that may bias the results. Further study is warranted.
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http://dx.doi.org/10.1016/j.athoracsur.2016.04.042DOI Listing
December 2016

Risk factors and outcomes of in-hospital cardiac arrest following pediatric heart operations of varying complexity.

Resuscitation 2016 08 13;105:1-7. Epub 2016 May 13.

Virtual PICU Systems, LLC, Los Angeles, CA, United States; Division of Critical Care Medicine, Department of Pediatrics and Anesthesiology, Children's Hospital Los Angeles, USC Keck School of Medicine, Los Angeles, CA, United States.

Background: Multi center data regarding cardiac arrest in children undergoing heart operations of varying complexity are limited.

Methods: Children <18 years undergoing heart surgery (with or without cardiopulmonary bypass) in the Virtual Pediatric Systems (VPS, LLC) Database (2009-2014) were included. Multivariable mixed logistic regression models were adjusted for patient's characteristics, surgical risk category (STS-EACTS Categories 1, 2, and 3 classified as "low" complexity and Categories 4 and 5 classified as "high" complexity), and hospital characteristics.

Results: Overall, 26,909 patients (62 centers) were included. Of these, 2.7% had cardiac arrest after cardiac surgery with an associated mortality of 31%. The prevalence of cardiac arrest was lower among patients undergoing low complexity operations (low complexity vs. high complexity: 1.7% vs. 5.9%). Unadjusted outcomes after cardiac arrest were significantly better among patients undergoing low complexity operations (mortality: 21.6% vs. 39.1%, good neurological outcomes: 78.7% vs. 71.6%). In adjusted models, odds of cardiac arrest were significantly lower among patients undergoing low complexity operations (OR: 0.55, 95% CI: 0.46-0.66). Adjusted models, however, showed no difference in mortality or neurological outcomes after cardiac arrest regardless of surgical complexity. Further, our results suggest that incidence of cardiac arrest and mortality after cardiac arrest are a function of patient characteristics, surgical risk category, and hospital characteristics. Presence of around the clock in-house attending level pediatric intensivist coverage was associated with lower incidence of post-operative cardiac arrest, and presence of a dedicated cardiac ICU was associated with lower mortality after cardiac arrest.

Conclusions: This study suggests that the patients undergoing high complexity operations are a higher risk group with increased prevalence of post-operative cardiac arrest. These data further suggest that patients undergoing high complexity operations can be rescued after cardiac arrest with a high survival rate.
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http://dx.doi.org/10.1016/j.resuscitation.2016.04.022DOI Listing
August 2016

Risk factors for mechanical ventilation and reintubation after pediatric heart surgery.

J Thorac Cardiovasc Surg 2016 Feb 28;151(2):451-8.e3. Epub 2015 Sep 28.

Virtual PICU Systems, LLC, Los Angeles, Calif; Division of Critical Care Medicine, Department of Pediatrics and Anesthesiology, Children's Hospital Los Angeles, USC Keck School of Medicine, Los Angeles, Calif.

Objective: To determine the prevalence of and risk factors associated with the need for mechanical ventilation in children following cardiac surgery and the need for subsequent reintubation after the initial extubation attempt.

Methods: Patients younger than 18 years who underwent cardiac operations for congenital heart disease at one of the participating pediatric intensive care units (ICUs) in the Virtual PICU Systems (VPS), LLC, database were included (2009-2014). Multivariable logistic regression models were fitted to identify factors likely associated with mechanical ventilation and reintubation.

Results: A total of 27,398 patients from 62 centers were included. Of these, 6810 patients (25%) were extubated in the operating room (OR), whereas 20,588 patients (75%) arrived intubated in the ICU. Of the patients who were extubated in the OR, 395 patients (6%) required reintubation. In contrast, 2054 patients (10%) required reintubation among the patients arriving intubated postoperatively in the ICU. In adjusted models, patient characteristics, patients undergoing high-complexity operations, and patients undergoing operations in lower-volume centers were associated with higher likelihood for the need for postoperative mechanical ventilation and need for reintubation. Furthermore, the prevalence of mechanical ventilation and reintubation was lower among the centers with a dedicated cardiac ICU in propensity-matched analysis among centers with and without a dedicated cardiac ICU.

Conclusions: This multicenter study suggests that proportion of patients extubated in the OR after heart operation is low. These data further suggest that extubation in the OR can be done successfully with a low complication rate.
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http://dx.doi.org/10.1016/j.jtcvs.2015.09.080DOI Listing
February 2016

Pediatric Index of Cardiac Surgical Intensive Care Mortality Risk Score for Pediatric Cardiac Critical Care.

Pediatr Crit Care Med 2015 Nov;16(9):846-52

1Department of Pediatrics, Seattle Children's Hospital, University of Washington School of Medicine, Seattle, WA. 2Virtual PICU System, LLC, Los Angeles, CA. 3Department of Pediatrics, Children's Hospital of Wisconsin, Medical College of Wisconsin, Milwaukee, WI. 4Department of Anesthesiology & Critical Care Medicine, Children's Hospital Los Angeles, University of Southern California School of Medicine, Los Angeles, CA.

Objective: Comparison of clinical outcomes is imperative in the evaluation of healthcare quality. Risk adjustment for children undergoing cardiac surgery poses unique challenges, due to its distinct nature. We developed a risk-adjustment tool specifically focused on critical care mortality for the pediatric cardiac surgical population: the Pediatric Index of Cardiac Surgical Intensive care Mortality score.

Design: Retrospective analysis of prospectively collected pediatric critical care data.

Setting: Pediatric critical care units in the United States.

Patients: Pediatric cardiac intensive care surgical patients.

Interventions: Prospectively collected data from consecutive patients admitted to ICUs were obtained from The Virtual PICU System (VPS, LLC, Los Angeles, CA), a national pediatric critical care database. Thirty-two candidate physiologic, demographic, and diagnostic variables were analyzed for inclusion in the development of the Pediatric Index of Cardiac Surgical Intensive care Mortality model. Multivariate logistic regression with stepwise selection was used to develop the model.

Measurements And Main Results: A total of 16,574 cardiac surgical patients from the 55 PICUs across the United States were included in the analysis. Thirteen variables remained in the final model, including the validated Society of Thoracic Surgeons-European Association of Cardio-Thoracic Surgery Congenital Heart Surgery Mortality (STAT) score and admission time with respect to cardiac surgery, which identifies whether the patient underwent the index surgical procedure before or after admission to the ICU. Pediatric Index of Cardiac Surgical Intensive Care Mortality (PICSIM) performance was compared with the performance of Pediatric Risk of Mortality-3 and Pediatric Index of Mortality-2 risk of mortality scores, as well as the STAT score and STAT categories by calculating the area under the curve of the receiver operating characteristic from a validation dataset: PICSIM (area under the curve = 0.87) performed better than Pediatric Index of Mortality-2 (area under the curve = 0.81), Pediatric Risk of Mortality-3 (area under the curve = 0.82), STAT score (area under the curve = 0.77), STAT category (area under the curve = 0.75), and Risk Adjustment for Congenital Heart Surgery-1 (area under the curve = 0.74).

Conclusions: This newly developed mortality score, PICSIM, consisting of 13 risk variables encompassing physiology, cardiovascular condition, and time of admission to the ICU showed better discrimination than Pediatric Index of Mortality-2, Pediatric Risk of Mortality-3, and STAT score and category for mortality in a multisite cohort of pediatric cardiac surgical patients. The introduction of the variable "admission time with respect to cardiac surgery" allowed prediction of mortality when patients are admitted to the ICU either before or after the index surgical procedure.
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http://dx.doi.org/10.1097/PCC.0000000000000489DOI Listing
November 2015

Vasoactive-inotropic score is associated with outcome after infant cardiac surgery: an analysis from the Pediatric Cardiac Critical Care Consortium and Virtual PICU System Registries.

Pediatr Crit Care Med 2014 Jul;15(6):529-37

1Department of Pediatrics and Communicable Diseases, Division of Cardiology, C.S. Mott Children's Hospital, University of Michigan Medical School, Ann Arbor, MI. 2Pediatric Cardiac Critical Care Consortium Data Coordinating Center, Michigan Congenital Heart Outcomes Research and Discovery Unit, Ann Arbor, MI. 3Department of Pediatrics, Seattle Children's Hospital, University of Washington School of Medicine, Seattle, WA. 4Department of Pediatrics, Section of Critical Care, Children's Hospital of Wisconsin, Medical College of Wisconsin, Milwaukee, WI. 5Virtual PICU Systems (VPS, LLC), Los Angeles, CA. 6Department of Cardiology, Boston Children's Hospital, Harvard Medical School, Boston, MA.

Objective: To empirically derive the optimal measure of pharmacologic cardiovascular support in infants undergoing cardiac surgery with bypass and to assess the association between this score and clinical outcomes in a multi-institutional cohort.

Design: Prospective, multi-institutional cohort study.

Setting: Cardiac ICUs at four academic children's hospitals participating in the Pediatric Cardiac Critical Care Consortium during the study period.

Patients: Children younger than 1 year at the time of surgery treated postoperatively in the cardiac ICU.

Interventions: None.

Measurements And Main Results: Three hundred ninety-one infants undergoing surgery with bypass were enrolled consecutively from November 2011 to April 2012. Hourly doses of all vasoactive agents were recorded for the first 48 hours after cardiac ICU admission. Multiple derivations of an inotropic score were tested, and maximum vasoactive-inotropic score in the first 24 hours was further analyzed for association with clinical outcomes. The primary composite "poor outcome" variable included at least one of mortality, mechanical circulatory support, cardiac arrest, renal replacement therapy, or neurologic injury. High vasoactive-inotropic score was empirically defined as more than or equal to 20. Multivariable logistic regression was performed controlling for center and patient characteristics. Patients with high vasoactive-inotropic score had significantly greater odds of a poor outcome (odds ratio, 6.5; 95% CI, 2.9-14.6), mortality (odds ratio, 13.2; 95% CI, 3.7-47.6), and prolonged time to first extubation and cardiac ICU length of stay compared with patients with low vasoactive-inotropic score. Stratified analyses by age (neonate vs infant) and surgical complexity (low vs high) showed similar associations with increased morbidity and mortality for patients with high vasoactive-inotropic score.

Conclusions: Maximum vasoactive-inotropic score calculated in the first 24 hours after cardiac ICU admission was strongly and significantly associated with morbidity and mortality in this multi-institutional cohort of infants undergoing cardiac surgery. Maximum vasoactive-inotropic score more than or equal to 20 predicts an increased likelihood of a poor composite clinical outcome. The findings were consistent in stratified analyses by age and surgical complexity.
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http://dx.doi.org/10.1097/PCC.0000000000000153DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4159673PMC
July 2014

Relationship between risk-adjustment tools and the pediatric logistic organ dysfunction score.

World J Pediatr Congenit Heart Surg 2014 Jan;5(1):16-21

Department of Pediatrics, Medical College of Wisconsin, Milwaukee, WI, USA.

Background: The Risk-Adjusted Classification for Congenital Heart Surgery (RACHS-1) method and Aristotle Basic Complexity (ABC) scores correlate with mortality. However, low mortality rates in congenital heart disease (CHD) make use of mortality as the primary outcome measure insufficient. Demonstrating correlation between risk-adjustment tools and the Pediatric Logistic Organ Dysfunction (PELOD) score might allow for risk-adjusted comparison of an outcome measure other than mortality.

Methods: Data were obtained from the Virtual PICU Systems database. Patients with postoperative CHD between 2009 and 2010 were included. Correlation between RACHS-1 category and PELOD score and between ABC level and PELOD score was examined using Spearman rank correlation. Consistency of PELOD scores across institutions for given levels of case complexity was examined using Kruskal-Wallis nonparametric analysis of variance.

Results: A total of 1,981 patient visits among 12 institutions met inclusion criteria. Positive correlations between PELOD score and RACHS-1 category (r s = .353, P < .0001) as well as between PELOD score and ABC level (r s = .328, P < .0001) were demonstrated. Variability in PELOD scores across individual centers for given levels of case complexity was observed (P < .04).

Conclusions: Risk-Adjusted Classification for Congenital Heart Surgery categories and ABC levels correlate with postoperative organ dysfunction as measured by PELOD. However, the correlation was weak, potentially due to limitations of the PELOD score itself. Identification of a more accurate metric of morbidity for the congenital heart disease population is needed.
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http://dx.doi.org/10.1177/2150135113510008DOI Listing
January 2014

Sepsis in the pediatric cardiac intensive care unit.

World J Pediatr Congenit Heart Surg 2011 Jul;2(3):393-9

Division of Critical Care Medicine, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.

The survival rate for children with congenital heart disease (CHD) has increased significantly coincident with improved techniques in cardiothoracic surgery, cardiopulmonary bypass and myocardial protection, and perioperative care. Cardiopulmonary bypass, likely in combination with ischemia-reperfusion injury, hypothermia, and surgical trauma, elicits a complex, systemic inflammatory response that is characterized by activation of the complement cascade, release of endotoxin, activation of leukocytes and the vascular endothelium, and release of proinflammatory cytokines. This complex inflammatory state causes a transient immunosuppressed state, which may increase the risk of hospital-acquired infection in these children. Postoperative sepsis occurs in nearly 3% of children undergoing cardiac surgery and has been associated with longer length of stay and mortality risks in the pediatric cardiac intensive care unit. Herein, we review the epidemiology, pathobiology, and management of sepsis in the pediatric cardiac intensive care unit.
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http://dx.doi.org/10.1177/2150135111403781DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3277844PMC
July 2011

Minimizing bleeding associated with mechanical circulatory support following pediatric heart surgery.

Eur J Cardiothorac Surg 2011 Mar;39(3):392-7

Seattle Children's Hospital, Seattle, WA 98105-0371, USA.

Objective: The use of extracorporeal membrane oxygenation (ECMO) to support patients with early postcardiotomy heart failure may be associated with catastrophic bleeding, making its use undesirable. However, postcardiotomy mechanical circulatory assistance is necessary in some patients to allow for myocardial recovery. We have assembled a centrifugal pump system (CPS) that does not require early systemic anticoagulation. This study compares postoperative bleeding in pediatric patients placed on standard ECMO versus CPS within 24h of cardiotomy.

Methods: Between November 2002 and February 2007, 25 patients (age 0 days-1.72 years) received postcardiotomy mechanical support. Fourteen patients were placed on ECMO and 11 patients were placed on CPS within 24h of surgical repair. Retrospective analysis was performed of chest-tube drainage at multiple time points following initiation of mechanical support. Additional variables, including Risk Adjustment for Congenital Heart Surgery-1 (RACHS-1) score, total time on mechanical support, 30-day mortality, activated clotting time, blood-product administration, circuit-related complications, and circuit changes were also analyzed.

Results: Patients on ECMO (0.30 ± 0.39 years) and CPS (0.40 ± 0.56 years) were of similar age (p = 0.64). Patients on ECMO (0.3 ± 0.1m(2)) and CPS (0.3 ± 0.1m(2)) had similar body surface areas (p = 0.46). Patients placed on CPS had significantly less chest-tube drainage during the first 4h of support. Activated clotting times appeared to be higher during the first 12h of ECMO versus CPS. There was no statistical difference between ECMO and CPS with respect to the following variables: RACHS-1 score, time on support, 30-day mortality, circuit-related complications, and circuit changes. Blood-product administration at 24h of support was significantly less (p = 0.04) for patients on CPS versus ECMO.

Conclusions: Mechanical circulatory support can be provided without the complication of clinically significant bleeding if a specialized circuit is used. This has important implications for the decision to use mechanical support in the immediate postoperative period in the face of ventricular failure. In addition, early mechanical support can be used with a low incidence of circuit-related complications.
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http://dx.doi.org/10.1016/j.ejcts.2010.07.027DOI Listing
March 2011

Performance of the Pediatric Index of Mortality 2 for pediatric cardiac surgery patients.

Pediatr Crit Care Med 2011 Mar;12(2):184-9

Division of Critical Care, Department of Pediatrics, Denver Children's Hospital, University of Colorado, Denver, CO, USA. czaja.angelatchden.org

Objective: To evaluate the performance of the Pediatric Index of Mortality 2 (PIM-2) for pediatric cardiac surgery patients admitted to the pediatric intensive care unit (PICU).

Design: : Retrospective cohort analysis.

Setting: Multi-institutional PICUs.

Patients: Children whose PICU admission had an associated cardiac surgical procedure.

Interventions: None.

Measurements And Main Results: Performance of the PIM-2 was evaluated with both discrimination and calibration measures. Discrimination was assessed with a receiver operating characteristic curve and associated area under the curve measurement. Calibration was measured across defined groups based on mortality risk, using the Hosmer-Lemeshow goodness-of-fit test. Analyses were performed initially, using the entire cohort, and then based on operative status (perioperative defined as procedure occurring within 24 hrs of PICU admission and preoperative as occurring >24 hrs from the time of PICU admission). A total of 9,208 patients were identified as cardiac surgery patients with 8,391 (91%) considered as perioperative. Average age of the entire cohort was 3.3 yrs (median, 10 mos, 0-18 yrs), although preoperative children tended to be younger (median, <1 month). Preoperative patients also had longer PICU median lengths of stay than perioperative patients (12 days [1-375 days] vs. 3 days [1-369 days], respectively). For the entire cohort, the PIM-2 had fair discrimination power (area under the curve, 0.80; 95% confidence interval, 0.77-0.83) and poor calibration (p < .0001). Its predictive ability was similarly inadequate for quality assessment (standardized mortality ratio, 0.81; 95% confidence interval, 0.72-0.90) with significant overprediction in the highest-decile risk group. For the subpopulations, the model continued to perform poorly with low area under the curves for preoperative patients and poor calibration for both groups. PIM-2 tended to overpredict mortality for perioperative patients and underpredict for preoperative patients (standardized mortality ratios, 0.69 [95% confidence interval, 0.59-0.78] and 1.48 [95% confidence interval, 1.27-1.70], respectively).

Conclusions: The PIM-2 demonstrated poor performance with fair discrimination, poor calibration, and predictive ability for pediatric cardiac surgery population and thus cannot be recommended in its current form as an adequate adjustment tool for quality measurement in this patient group.
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http://dx.doi.org/10.1097/PCC.0b013e3181e89694DOI Listing
March 2011

Novel pH1N1 viral cardiomyopathy requiring veno-venous extracorporeal membrane oxygenation.

Pediatr Crit Care Med 2010 Nov;11(6):714-7

Divisions of Pediatric Cardiac Surgery, Seattle Children's Hospital, Seattle, WA, USA.

Objective: To report a case of pH1N1 viral infection presenting as heart failure requiring mechanical extracorporeal life support.

Design: Case report.

Setting: Pediatric intensive care unit at a regional children's hospital.

Patient: Obese 15-yr-old boy who presented with pH1N1-related cardiomyopathy and respiratory failure that required extracorporeal membrane oxygenation.

Interventions: Extracorporeal membrane oxygenation, echocardiography, high-frequency oscillating ventilation.

Measurements And Main Results: Discovery of severe dilated cardiomyopathy and respiratory failure.

Conclusions: Patients with pH1N1 may present in profound heart failure in addition to respiratory failure. Extracorporeal membrane oxygenation may play an important role in managing these complex patients.
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http://dx.doi.org/10.1097/PCC.0b013e3181e327c9DOI Listing
November 2010

Reducing the incidence of necrotizing enterocolitis in neonates with hypoplastic left heart syndrome with the introduction of an enteral feed protocol.

Pediatr Crit Care Med 2010 May;11(3):373-7

Division of Critical Care Medicine, Department of Anesthesiology Critical Care Medicine, Children's Hospital Los Angeles, USC Keck School of Medicine, Los Angeles, CA, USA.

Objective: Neonates with hypoplastic left heart syndrome are prone to gastrointestinal complications, including necrotizing enterocolitis, during initiation or advancement of enteral feeds. A feeding protocol was developed to standardize practice across a multidisciplinary team. The purpose of this study was to examine the impact of a standardized feeding protocol on the incidence of necrotizing enterocolitis and overall postoperative gastrointestinal morbidity.

Design: Retrospective case-control study.

Setting: Cardiothoracic intensive care unit of a tertiary care children's hospital.

Patients: Ninety-eight neonates with hypoplastic left heart syndrome admitted to the cardiothoracic intensive care unit after first-stage palliation.

Intervention: A retrospective chart review was performed. Two groups were analyzed: the preprotocol group (n = 52) was examined from January 2000 through December 31, 2001, and the postprotocol group (n = 46) from February 2002 through December 31, 2003.

Measurements And Main Results: The incidence of suspected or diagnosed necrotizing enterocolitis as defined by the modified Bell staging criteria was recorded. Data were also collected regarding postoperative day of enteral feed initiation, postoperative day full feeds attained, and postoperative hospital length of stay. Necrotizing enterocolitis was detected in 14 preprotocol (27%) and three postprotocol (6.5%) patients (p < .01). Enteral feeds were initiated later in the postprotocol group (7.5 vs. 5.5 days, p < .001), and number of days to full feeds was also later in the postprotocol group (7 vs. 4 days, p = .02). Hospital length of stay tended to be shorter in the postprotocol group (21.5 vs. 28 days, p = .25).

Conclusion: Measures directed at reducing the incidence of necrotizing enterocolitis may reduce morbidity in neonates with hypoplastic left heart syndrome and reduce cost by decreasing hospital length of stay. A standardized feeding protocol instituted to address these problems likely contributed to reducing the incidence of necrotizing enterocolitis in this high-risk population.
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http://dx.doi.org/10.1097/PCC.0b013e3181c01475DOI Listing
May 2010

Infection rates following initial cerebrospinal fluid shunt placement across pediatric hospitals in the United States. Clinical article.

J Neurosurg Pediatr 2009 Aug;4(2):156-65

Divisions of Inpatient Medicine, University of Utah, Salt Lake City, Utah, USA.

Object: Reported rates of CSF shunt infection vary widely across studies. The study objective was to determine the CSF shunt infection rates after initial shunt placement at multiple US pediatric hospitals. The authors hypothesized that infection rates between hospitals would vary widely even after adjustment for patient, hospital, and surgeon factors.

Methods: This retrospective cohort study included children 0-18 years of age with uncomplicated initial CSF shunt placement performed between January 1, 2001, and December 31, 2005, and recorded in the Pediatric Health Information System (PHIS) longitudinal administrative database from 41 children's hospitals. For each child with 24 months of follow-up, subsequent CSF shunt infections and procedures were determined.

Results: The PHIS database included 7071 children with uncomplicated initial CSF shunt placement during this time period. During the 24 months of follow-up, these patients had a total of 825 shunt infections and 4434 subsequent shunt procedures. Overall unadjusted 24-month CSF shunt infection rates were 11.7% per patient and 7.2% per procedure. Unadjusted 24-month cumulative incidence rates for each hospital ranged from 4.1 to 20.5% per patient and 2.5-12.3% per procedure. Factors significantly associated with infection (p < 0.05) included young age, female sex, African-American race, public insurance, etiology of intraventricular hemorrhage, respiratory complex chronic condition, subsequent revision procedures, hospital volume, and surgeon case volume. Malignant lesions and trauma as etiologies were protective. Infection rates for each hospital adjusted for these factors decreased to 8.8-12.8% per patient and 1.4-5.3% per procedure.

Conclusions: Infections developed in > 11% of children who underwent uncomplicated initial CSF shunt placements within 24 months. Patient, hospital, and surgeon factors contributed somewhat to the wide variation in CSF shunt infection rates across hospitals. Additional factors may contribute to variation in CSF shunt infection rates between centers, but further study is needed. Benchmarking and future prospective multicenter studies of CSF shunt infection will need to incorporate these and other patient, hospital, and surgeon factors.
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http://dx.doi.org/10.3171/2009.3.PEDS08215DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2896258PMC
August 2009

Prevention of central venous catheter-associated bloodstream infections in pediatric intensive care units: a performance improvement collaborative.

Infect Control Hosp Epidemiol 2009 Jul;30(7):645-51

University of Washington School of Medicine, Division of Pediatric Critical Care, Seattle Children's Hospital, Seattle, WA 98105, USA.

Objective: The goal of this effort was to reduce central venous catheter (CVC)-associated bloodstream infections (BSIs) in pediatric intensive care unit (ICU) patients by means of a multicenter evidence-based intervention.

Methods: An observational study was conducted in 26 freestanding children's hospitals with pediatric or cardiac ICUs that joined a Child Health Corporation of America collaborative. CVC-associated BSI protocols were implemented using a collaborative process that included catheter insertion and maintenance bundles, daily review of CVC necessity, and daily goals. The primary goal was either a 50% reduction in the CVC-associated BSI rate or a rate of 1.5 CVC-associated BSIs per 1,000 CVC-days in each ICU at the end of a 9-month improvement period. A 12-month sustain period followed the initial improvement period, with the primary goal of maintaining the improvements achieved.

Results: The collaborative median CVC-associated BSI rate decreased from 6.3 CVC-associated BSIs per 1,000 CVC-days at the start of the collaborative to 4.3 CVC-associated BSIs per 1,000 CVC-days at the end of the collaborative. Sixty-five percent of all participants documented a decrease in their CVC-associated BSI rate. Sixty-nine CVC-associated BSIs were prevented across all teams, with an estimated cost avoidance of $2.9 million. Hospitals were able to sustain their improvements during a 12-month sustain period and prevent another 198 infections.

Conclusions: We conclude that our collaborative quality improvement project demonstrated that significant reduction in CVC-associated BSI rates and related costs can be realized by means of evidence-based prevention interventions, enhanced communication among caregivers, standardization of CVC insertion and maintenance processes, enhanced measurement, and empowerment of team members to enforce adherence to best practices.
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http://dx.doi.org/10.1086/598341DOI Listing
July 2009

Congenital cardiac surgical complications of the integument, vascular system, vascular-line(s), and wounds: consensus definitions from the Multi-Societal Database Committee for Pediatric and Congenital Heart Disease.

Cardiol Young 2008 Dec;18 Suppl 2:245-55

Department of Cardiovascular Surgery, Children's Hospital of Michigan, Detroit, Michigan 48201, USA.

A complication is an event or occurrence that is associated with a disease or a healthcare intervention, is a departure from the desired course of events, and may cause, or be associated with, suboptimal outcome. A complication does not necessarily represent a breech in the standard of care that constitutes medical negligence or medical malpractice. An operative or procedural complication is any complication, regardless of cause, occurring (1) within 30 days after surgery or intervention in or out of the hospital, or (2) after 30 days during the same hospitalization subsequent to the operation or intervention. Operative and procedural complications include both intraoperative/intraprocedural complications and postoperative/postprocedural complications in this time interval. The MultiSocietal Database Committee for Pediatric and Congenital Heart Disease has set forth a comprehensive list of complications associated with the treatment of patients with congenital cardiac disease, related to cardiac, pulmonary, renal, haematological, infectious, neurological, gastrointestinal, and endocrinal systems, as well as those related to the management of anaesthesia and perfusion, and the transplantation of thoracic organs. The objective of this manuscript is to examine the definitions of operative morbidity as they relate specifically to a collection of loosely related topics that include the following groups of complications: 1) Complications of the Integument, 2) Complications of the Vascular System, 3) Complications of the Vascular-Line(s), 4) Complications of Wounds. These specific definitions and terms will be used to track morbidity associated with surgical and transcatheter interventions and other forms of therapy in a common language across many separate databases. As surgical survival in children with congenital cardiac disease has improved in recent years, focus has necessarily shifted to reducing the morbidity of congenital cardiac malformations and their treatment. A comprehensive list of complications is presented. This list is a component of a systems-based compendium of complications that will standardize terminology and thereby allow the study and quantification of morbidity in patients with congenital cardiac malformations. Clinicians caring for patients with congenital cardiac disease will be able to use this list for databases, initiatives to improve quality, reporting of complications, and comparing strategies of treatment.
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http://dx.doi.org/10.1017/S1047951108003016DOI Listing
December 2008

Neurological complications associated with the treatment of patients with congenital cardiac disease: consensus definitions from the Multi-Societal Database Committee for Pediatric and Congenital Heart Disease.

Cardiol Young 2008 Dec;18 Suppl 2:234-9

Division of Pediatric Cardiology, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania 19104-4399, USA.

A complication is an event or occurrence that is associated with a disease or a healthcare intervention, is a departure from the desired course of events, and may cause, or be associated with suboptimal outcome. A complication does not necessarily represent a breech in the standard of care that constitutes medical negligence or medical malpractice. An operative or procedural complication is any complication, regardless of cause, occurring (1) within 30 days after surgery or intervention in or out of the hospital, or (2) after 30 days during the same hospitalization subsequent to the operation or intervention. Operative and procedural complications include both intraoperative/intraprocedural complications and postoperative/postprocedural complications in this time interval. The MultiSocietal Database Committee for Pediatric and Congenital Heart Disease has set forth a comprehensive list of complications associated with the treatment of patients with congenital cardiac disease, related to cardiac, pulmonary, renal, haematological, infectious, neurological, gastrointestinal, and endocrine systems, as well as those related to the management of anaesthesia and perfusion, and the transplantation of thoracic organs. The objective of this manuscript is to examine the definitions of operative morbidity as they relate specifically to the neurological system. These specific definitions and terms will be used to track morbidity associated with surgical and transcatheter interventions and other forms of therapy in a common language across many separate databases. Although neurological injury and adverse neurodevelopmental outcome can follow procedures for congenital cardiac defects, much of the variability in neurological outcome is now recognized to be more related to patient specific factors rather than procedural factors. Additionally, the recognition of pre and postoperative neurological morbidity requires procedures and imaging modalities that can be resource-intensive to acquire and analyze, and little is known or described about variations in "sampling rate" from centre to centre. The purpose of this effort is to propose an initial set of consensus definitions for neurological complications following congenital cardiac surgery and intervention. Given the dramatic advances in understanding achieved to date, and those yet to occur, this effort is explicitly recognized as only the initial first step of a process that must remain iterative. This list is a component of a systems-based compendium of complications that may help standardize terminology and possibly enhance the study and quantification of morbidity in patients with congenital cardiac malformations. Clinicians caring for patients with congenital cardiac disease may be able to use this list for databases, initiatives to improve quality, reporting of complications, and comparing strategies of treatment.
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http://dx.doi.org/10.1017/S1047951108002977DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2742973PMC
December 2008

Databases for assessing the outcomes of the treatment of patients with congenital and paediatric cardiac disease--the perspective of critical care.

Cardiol Young 2008 Dec;18 Suppl 2:130-6

Department of Paediatric Intensive Care, The Royal Brompton Hospital, London, United Kingdom.

The development of databases to track the outcomes of children with cardiovascular disease has been ongoing for much of the last two decades, paralleled by the rise of databases in the intensive care unit. While the breadth of data available in national, regional and local databases has grown exponentially, the ability to identify meaningful measurements of outcomes for patients with cardiovascular disease is still in its early stages. In the United States of America, the Virtual Pediatric Intensive Care Unit Performance System (VPS) is a clinically based database system for the paediatric intensive care unit that provides standardized high quality, comparative data to its participants [https://portal.myvps.org/]. All participants collect information on multiple parameters: (1) patients and their stay in the hospital, (2) diagnoses, (3) interventions, (4) discharge, (5) various measures of outcome, (6) organ donation, and (7) paediatric severity of illness scores. Because of the standards of quality within the database, through customizable interfaces, the database can also be used for several applications: (1) administrative purposes, such as assessing the utilization of resources and strategic planning, (2) multi-institutional research studies, and (3) additional internal projects of quality improvement or research.In the United Kingdom, The Paediatric Intensive Care Audit Network is a database established in 2002 to record details of the treatment of all critically ill children in paediatric intensive care units of the National Health Service in England, Wales and Scotland. The Paediatric Intensive Care Audit Network was designed to develop and maintain a secure and confidential high quality clinical database of pediatric intensive care activity in order to meet the following objectives: (1) identify best clinical practice, (2) monitor supply and demand, (3) monitor and review outcomes of treatment episodes, (4) facilitate strategic healthcare planning, (5) quantify resource requirements, and (6) study the epidemiology of critical illness in children.Two distinct physiologic risk adjustment methodologies are the Pediatric Risk of Mortality Scoring System (PRISM), and the Paediatric Index of Mortality Scoring System 2 (PIM 2). Both Pediatric Risk of Mortality (PRISM 2) and Pediatric Risk of Mortality (PRISM 3) are comprised of clinical variables that include physiological and laboratory measurements that are weighted on a logistic scale. The raw Pediatric Risk of Mortality (PRISM) score provides quantitative measures of severity of illness. The Pediatric Risk of Mortality (PRISM) score when used in a logistic regression model provides a probability of the predicted risk of mortality. This predicted risk of mortality can then be used along with the rates of observed mortality to provide a quantitative measurement of the Standardized Mortality Ratio (SMR). Similar to the Pediatric Risk of Mortality (PRISM) scoring system, the Paediatric Index of Mortality (PIM) score is comprised of physiological and laboratory values and provides a quantitative measurement to estimate the probability of death using a logistic regression model.The primary use of national and international databases of patients with congenital cardiac disease should be to improve the quality of care for these patients. The utilization of common nomenclature and datasets by the various regional subspecialty databases will facilitate the eventual linking of these databases and the creation of a comprehensive database that spans conventional geographic and subspecialty boundaries.
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http://dx.doi.org/10.1017/S1047951108002886DOI Listing
December 2008

An investigation of Aspergillus cardiac surgical site infections in 3 pediatric patients.

Am J Infect Control 2007 Jun;35(5):332-7

Department of Pediatrics, University of Washington, Children's Hospital and Regional Medical Center, Seattle, WA 98105, USA.

Background: Within a 3-month period, 3 pediatric patients at our hospital developed Aspergillus surgical site infections after undergoing cardiac surgery.

Methods: A multidisciplinary team conducted an epidemiologic review of the 3 patients and their infections, operative and postoperative patient care delivery, and routine maintenance of hospital equipment and air-filtration systems and investigated potential environmental exposures within the hospital that may have contributed to the development of these infections.

Results: Review of the patients and their infections, operative and postoperative patient care delivery, and routine maintenance did not reveal a source for infection. Inspection of operating room (OR) facilities identified several areas in need of repair. Of the 58 samples of air and equipment exhaust in the ORs and patient care areas, 11 revealed 2 to 4 colony-forming units of various Aspergillus species per cubic meter of air, and the remaining 47 samples were negative for Aspergillus. Eighty-three samples of surfaces and equipment water reservoirs were obtained from the OR and patient care areas. One culture of a soiled liquid nitrogen tank housed between the 2 cardiac ORs revealed 13 colony-forming units of Aspergillus.

Conclusion: No definitive source was identified, although a soiled liquid nitrogen tank contaminated with Aspergillus and kept near the OR was found and could have been a possible source.
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http://dx.doi.org/10.1016/j.ajic.2006.10.013DOI Listing
June 2007

Determining pediatric intensive care unit quality indicators for measuring pediatric intensive care unit safety.

Pediatr Crit Care Med 2007 Mar;8(2 Suppl):S3-10

Department of Pediatrics, Critical Care, Medical College of Wisconsin, Milwaukee, WI, USA.

Introduction: The measurement of quality and patient safety continues to gain increasing importance, as these measures are used for both healthcare improvement and accountability. Pediatric care, particularly that provided in pediatric intensive care units, is sufficiently different from adult care that specific metrics are required. BODY: Pediatric critical care requires specific measures for both quality and safety. Factors that may affect measures are identified, including data sources, risk adjustment, intended use, reliability, validity, and the usability of measures. The 18-month process to develop seven pediatric critical care measures proposed for national use is described. Specific patient safety metrics that can be applied to pediatric intensive care units include error-, injury-, and risk-based approaches.

Conclusion: Measurement of pediatric critical care quality and safety will likely continue to evolve. Opportunities exist for intensivists to contribute and lead in the development and refinement of measures.
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http://dx.doi.org/10.1097/01.PCC.0000257485.67821.77DOI Listing
March 2007

Computerized provider order entry implementation: no association with increased mortality rates in an intensive care unit.

Pediatrics 2006 Jul;118(1):290-5

Children's Hospital and Regional Medical Center, Mail Stop B5520, 4800 Sandpoint Way NE, Seattle, Washington 98105, USA.

Objective: Our goal was to determine if there were any changes in risk-adjusted mortality after the implementation of a computerized provider order entry system in our PICU.

Methods: Study was undertaken in a tertiary care PICU with 20 beds and 1100 annual admissions. Demographic, admission source, primary diagnosis, crude mortality, and Pediatric Risk of Mortality III risk-adjusted mortality were abstracted retrospectively on all admissions from the PICUEs database for the period October 1, 2002, to December 31, 2004. This time period reflects the 13 months before and 13 months after computerized provider order entry implementation. Pediatric Risk of Mortality III mortality risk adjustment was used to determine standardized mortality ratios.

Results: During the study period, 2533 patients were admitted to the PICU, of which 284 were transported from another facility. The 13-month preimplementation mortality rate was 4.22%, and the 13-month postimplementation mortality rate was 3.46%, representing a nonsignificant reduction in the risk of mortality in the postimplementation period. The standardized mortality ratio was 0.98 vs 0.77, respectively, and the mortality rate for the transported patients was 9.6% vs 6.29%. This yields a nonsignificant mortality risk reduction in the postimplementation period. The standardized mortality ratio was 1.10 preimplementation versus 0.70 postimplementation. Analysis of the 13-month preimplementation versus 5-month postimplementation periods showed a non-statistically significant trend in reduction of mortality for all PICU patients and for transported patients.

Conclusions: Implementation of a computerized provider order entry system, even in the early months after implementation, was not associated with an increase in mortality. Our experience suggests that careful design, build, implementation, and support can mitigate the risk of implementing new technology even in an ICU setting.
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http://dx.doi.org/10.1542/peds.2006-0367DOI Listing
July 2006

Gastrointestinal morbidity after Norwood palliation for hypoplastic left heart syndrome.

Ann Thorac Surg 2006 Mar;81(3):982-7

Department of Anesthesiology, Critical Care Medicine, Childrens Hospital Los Angeles, Los Angeles, California, USA.

Background: Neonates with hypoplastic left heart syndrome are at high risk for developing gastrointestinal complications after first stage palliation. These complications likely play a major role in their morbidity and mortality. The goal of this review was to examine the incidence and clinical impact of gastrointestinal morbidities in these newborns.

Methods: The charts of all neonates with hypoplastic left heart syndrome who underwent stage-one palliation between January 1997 and December 2001 were reviewed to determine the incidence of gastrointestinal complications. Demographic, perioperative, and procedural variables were collected and correlated with major gastrointestinal problems.

Results: There were 117 patients in our study population, and survival to discharge was 87% (102 of 117). Gastrointestinal complications occurred in 48 (41%), including 18% with necrotizing enterocolitis, 18% who required home feeding tubes, and 8% who required prolonged hospital length of stay for nutritional support. These infants had a longer length of stay (52 days versus 22 days; p < 0.0001). Multivariate logistic regression analysis revealed that weight less than 2.5 kg and development of necrotizing enterocolitis were each independently related to death. Neonates with a birth weight less than 2.5 kg had an odds ratio for death of 5.7 (95% confidence interval: 1.14 to 28.86), and the odds ratio for death with necrotizing enterocolitis was 5.6 (95% confidence interval: 1.55 to 20.67).

Conclusions: Gastrointestinal complications in infants with hypoplastic left heart syndrome are common, and necrotizing enterocolitis increases the risk of death. Measures directed at reducing the incidence of gastrointestinal complications may improve outcomes and reduce costs in this population.
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http://dx.doi.org/10.1016/j.athoracsur.2005.09.001DOI Listing
March 2006

Mesenteric blood flow velocities in the newborn with single-ventricle physiology: modified Blalock-Taussig shunt versus right ventricle-pulmonary artery conduit.

Pediatr Crit Care Med 2006 Mar;7(2):132-7

Division of Critical Care Medicine, Department of Pediatrics, Childrens Hospital Los Angeles, USC Keck School of Medicine, Los Angeles, CA, USA.

Background: Neonates with ductal-dependent single-ventricle congenital heart disease palliated with a modified Blalock-Taussig shunt (mBTS) commonly have retrograde diastolic flow in the aorta, which may place them at increased risk of mesenteric ischemia. Recently, palliation with a right ventricle-to-pulmonary artery conduit, known as the Sano procedure, has been shown to eliminate retrograde diastolic flow, theoretically leading to better systemic perfusion.

Objective: To compare the changes in superior mesenteric artery (SMA) and celiac artery velocities and flow after a bolus enteral feed in patients with single-ventricle congenital heart disease palliated with an mBTS vs. those palliated with the right ventricle-to-pulmonary artery conduit.

Design: Prospective clinical study.

Setting: Cardiothoracic intensive care unit and pediatric ward of a tertiary care children's hospital.

Patients: A total of 27 patients with single-ventricle congenital heart disease (15 with mBTS, 12 with Sano) after stage-1 palliation.

Intervention: Doppler ultrasound of the SMA and celiac artery was performed 30 mins before and after a bolus enteral feed.

Measurements And Main Results: SMA and celiac artery peak systolic flow velocity, mean flow velocity, and time-velocity integral were measured. After a bolus enteral feed, 8 of 15 infants palliated with an mBTS had retrograde diastolic flow through the SMA yet demonstrated significant increases in all variables of both the SMA and celiac artery flow velocities (SMA peak systolic flow velocity: 0.96 +/- 0.33 vs. 1.2 +/- 0.4 m/sec, p = .01). Those palliated with the Sano procedure did not demonstrate SMA retrograde diastolic flow but also did not have any significant changes in their mesenteric flow variables (SMA peak systolic flow velocity: 0.79 +/- 0.16 vs. 0.89 +/- 0.26 m/sec, p = .2).

Conclusion: Postprandial retrograde diastolic flow was observed in the majority of patients palliated with an mBTS vs. none of the patients in the Sano group. However, contrary to expectations, postprandial mesenteric blood flow velocities in those palliated with an mBTS are significantly higher than in Sano patients, although the increase is not as high as that historically seen in normal neonates. This may place this population at risk for mesenteric ischemia and feeding intolerance in the postoperative period, and the risk may be even greater for those neonates palliated with a right ventricle-to-pulmonary artery conduit.
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http://dx.doi.org/10.1097/01.PCC.0000200999.89777.92DOI Listing
March 2006