Risk prediction tool for use and predictors of duration of postoperative oxygen therapy in children undergoing non-cardiac surgery: a case-control study

Oofuvong, Maliwan; Ratprasert, Siriwimol; Chanchayanon, Thavat

doi:10.1186/s12871-018-0595-4

Cited by 5 publications

(3 citation statements)

References 22 publications

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“…The tool demonstrated high predictive ability. The common risk factors for oxygen requirement postoperatively were probable difficult airway, ASA physical status ≥ 3, and surgeries involving the airway, thorax, and abdomen [ 162 ].…”

Section: Postoperative Respiratory Concernsmentioning

confidence: 99%

Recognizing Risks and Optimizing Perioperative Care to Reduce Respiratory Complications in the Pediatric Patient

Egbuta

Mason

2020

JCM

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There have been significant advancements in the safe delivery of anesthesia as well as improvements in surgical technique; however, the perioperative period can still be high risk for the pediatric patient. Perioperative respiratory complications (PRCs) are some of the most common critical events that can occur in pediatric surgical patients and they can lead to increased length of hospitalization, worsened patient outcomes, and higher hospital and postoperative costs. It is important to determine the various factors that put pediatric patients at increased risk of PRCs. This will allow for more detailed and accurate informed consent, optimized perioperative management strategy, improved allocation of clinical resources, and, hopefully, better patient experience. There are only a few risk prediction models/scoring tools developed for and validated in the pediatric patient population, but they have been useful in helping identify the key factors associated with a high likelihood of developing PRCs. Some of these factors are patient factors, while others are procedure-related factors. Some of these factors may be modified such that the patient’s clinical status is optimized preoperatively to decrease the risk of PRCs occurring perioperatively. Fore knowledge of the factors that are not able to be modified can help guide allocation of perioperative clinical resources such that the negative impact of these non-modifiable factors is buffered. Additional training in pediatric anesthesia or focused expertise in pediatric airway management, vascular access and management of massive hemorrhage should be considered for the perioperative management of the less than 3 age group. Intraoperative ventilation strategy plays a key role in determining respiratory outcomes for both adult and pediatric surgical patients. Key components of lung protective mechanical ventilation strategy such as low tidal volume and moderate PEEP used in the management of acute respiratory distress syndrome (ARDS) in pediatric intensive care units have been adopted in pediatric operating rooms. Adequate post-operative analgesia that balances pain control with appropriate mental status and respiratory drive is important in reducing PRCs.

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Section: Postoperative Respiratory Concernsmentioning

confidence: 99%

Recognizing Risks and Optimizing Perioperative Care to Reduce Respiratory Complications in the Pediatric Patient

Egbuta

Mason

2020

JCM

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“…We also added other factors associated with potentially difficult airways, as these tend to increase intubation time, and potentially prolong the postoperative intubation course. 16 The adult MeNTS variable "cardiovascular disease" was changed to reflect the greater impact of congenital heart disease in vulnerable children. "Pediatric congenital heart disease" was categorized by severity and baseline risk to the patient.…”

Section: Patient Factorsmentioning

confidence: 99%

Pediatric Modification of the Medically Necessary, Time-Sensitive Scoring System for Operating Room Procedure Prioritization During the COVID-19 Pandemic

Slidell

Kandel

Prachand

et al. 2020

Journal of the American College of Surgeons

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BACKGROUND:The COVID-19 pandemic forced surgeons to reconsider concepts of "elective" operations.Perceptions about the time sensitivity and medical necessity of a procedure have taken on greater significance during the pandemic. The evolving ethical and clinical environment requires reappraisal of perioperative factors, such as personal protective equipment conservation; limiting the risk of exposure to COVID-19 for patients, families, and healthcare workers; preservation of hospital beds and ICU resources; and minimizing COVID-19-related perioperative risk to patients. STUDY DESIGN: A scaffold for the complex decision-making required for prioritization of medically necessary, time-sensitive (MeNTS) operations was developed for adult patients by colleagues at the University of Chicago. Although adult MeNTS scoring can be applied across adult surgical specialties, some variables were irrelevant in a pediatric population. Pediatric manifestations of chronic diseases and congenital anomalies were not accounted for. To account for the unique challenges children face, we modified the adult MeNTS system for use across pediatric subspecialties. RESULTS:This pediatric MeNTS scoring system was applied to 101 cases both performed and deferred between March 23 and April 19, 2020 at the University of Chicago Comer Children's Hospital. The pediatric MeNTS scores provide a safe, equitable, transparent, and ethical strategy to prioritize children's surgical procedures. CONCLUSIONS: This process is adaptable to individual institutions and we project it will be useful during the acute phase of the pandemic (maximal limitations), as well as the anticipated recovery phase.

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“…Examples of adverse respiratory and airway events include laryngospasm, bronchospasm, airway obstruction, stridor, and oxygen desaturation . Numerous studies have been undertaken to determine the risk factors for adverse airway outcomes in children to improve patient safety throughout the perioperative stages . However, many of these studies have relied upon traditional statistical models to determine relevant outcomes and risk factors.…”

Section: Machine Learning In Predicting Airway Outcomesmentioning

confidence: 99%

Artificial intelligence, machine learning and the pediatric airway

Matava

Pankiv

Ahumada

et al. 2020

Pediatric Anesthesia

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Artificial intelligence and machine learning are rapidly expanding fields with increasing relevance in anesthesia and, in particular, airway management. The ability of artificial intelligence and machine learning algorithms to recognize patterns from large volumes of complex data makes them attractive for use in pediatric anesthesia airway management. The purpose of this review is to introduce artificial intelligence, machine learning, and deep learning to the pediatric anesthesiologist. Current evidence and developments in artificial intelligence, machine learning, and deep learning relevant to pediatric airway management are presented. We critically assess the current evidence on the use of artificial intelligence and machine learning in the assessment, diagnosis, monitoring, procedure assistance, and predicting outcomes during pediatric airway management. Further, we discuss the limitations of these technologies and offer areas for focused research that may bring pediatric airway management anesthesiology into the era of artificial intelligence and machine learning.

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Risk prediction tool for use and predictors of duration of postoperative oxygen therapy in children undergoing non-cardiac surgery: a case-control study

Cited by 5 publications

References 22 publications

Recognizing Risks and Optimizing Perioperative Care to Reduce Respiratory Complications in the Pediatric Patient

Recognizing Risks and Optimizing Perioperative Care to Reduce Respiratory Complications in the Pediatric Patient

Pediatric Modification of the Medically Necessary, Time-Sensitive Scoring System for Operating Room Procedure Prioritization During the COVID-19 Pandemic

Artificial intelligence, machine learning and the pediatric airway

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