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Record W4383957208 · doi:10.3389/fped.2023.1245772

Editorial: Insights in pediatric critical care 2022

2023· editorial· en· W4383957208 on OpenAlexaff
Nicole Shilkofski, Niranjan Kissoon

Bibliographic record

VenueFrontiers in Pediatrics · 2023
Typeeditorial
Languageen
FieldMedicine
TopicSepsis Diagnosis and Treatment
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicineIntensive care medicine

Abstract

fetched live from OpenAlex

Optimal care of the critically ill child is best achieved by a holistic approach that goes beyond correcting or reversing abnormal physiology. This collection nicely encompasses the vast spectrum of high quality research being performed in pediatric critical care medicine, ranging from improvements in clinical care of critically ill children including the search for biomarkers to predict mortality , to addressing communication during end of life care, to implementation science approaches to improve clinical care decisions, to understanding the spectrum of available online educational interventions. This emphasizes the multifaceted scope of practice that pediatric critical care medicine entails, and we hope gives readers insight into some of the current "hot topics" worthy of further investigation and future study within this field.In the article by Carreras et al, the authors demonstrate validity of their hypothesis that non-thyroidal illness syndrome (NTIS), as defined by low levels of free thyroxine and free triiodothyronine hormones, is associated with increased prediction of mortality risk scores in a prospective observational study of 103 patients in a pediatric intensive care unit (PICU) in Spain. While Pediatric Risk of Mortality (PRISM) scores have traditionally been utilized to improve prognostic assessment of critically ill children in the first several hours after admission to the PICU, this study is one example of the recent push to improve this prognostic assessment through the use of biochemical testing that can be quickly obtained on admission and improve accuracy of predictive models. While further studies are needed to determine if NTIS is an independent predictor of mortality, the study highlights a potential systematic maladaptive response to critical illness that could impact initial evaluation and subsequent treatment of critically ill pediatric patients. Similarly, the study by Zhou et al sought to determine if serum phosphate levels before and during continuous renal replacement therapy (CRRT) are predictive of higher 90 day mortality rates in a population of critically ill children in a PICU in China. The correlation of hyperphosphatemia with higher mortality rates in this study points to yet another important potential biomarker for risk stratification of this subpopulation of children requiring CRRT.The article by Resch et al highlights use of hirudotherapy (medicinal leech therapy) in a retrospective pediatric case series of patients hospitalized in a PICU in the United States with acute refractory limb ischemia from arterial malperfusion. While the use of the enzymatic properties of leeches is not a new therapeutic modality, it is not a widely used therapy, despite being approved by the U.S. Food and Drug Administration for improving venous congestion in graft tissue. Being a case series, however, the authors conclude that further prospective studies, including consideration of bleeding manifestations as a side effect of therapy, are required prior to a systematic recommendation of hirudotherapy for use in pediatric ICUs.Reuland et al describe the use of a Systems Engineering Initiative for Patient Safety (SEIPS) framework within implementation science for the initiation of a Pediatric Early Warning Score (PEWS) system in the limited-resource setting of a pediatric hospital in the Philippines. To date, PEWS systems have been used predominantly in resource-rich settings to identify children at risk of acute clinical deterioration and to make decisions about care escalation in these environments, but have not been extensively studied in low and middle income countries (LMICs). This type of qualitative research to examine barriers and facilitators that exist in a resource-constrained context is a critical predecessor to successful adaptation and implementation of PEWS in this context.The case report by Santos et al describes two children with encephalitis secondary to parainfluenza and respiratory syncytial virus (RSV) complicated by cytokine storm and multiorgan inflammatory response. These cases highlight that further investigations are clearly needed to better understand the pathophysiologic mechanisms of brain injury and systemic inflammatory response in critically ill children.The EVOLvE study by Zanin et al is a cross-sectional observational study surveying 198 pediatric critical care professionals across different regions in Europe regarding their attitudes toward end of life (EOL) care and EOL decisions. Importantly, the study highlights differences in opinions and practices from healthcare professionals regarding optimal timing of EOL decisions and underscores the need to identify and understand cultural, religious, legal and resource differences that may be the basis for discrepancies in practices and attitudes toward EOL care.Finally, the systematic review by Daniel and Wolbrink examines the current state of evidence for online education targeting healthcare workers in PICUs. Given the widespread and sudden need for medical education to make an unprecedented pivot to online education as a primary modality during the SARS CoV-2 pandemic, this review brings timely and salient insights. The authors' conclusion that significant opportunities remain to assess impact of online educational interventions, particularly those related to patient outcomes, should be a call to action for the pediatric critical care community, in particular individuals invested in furthering the quality of medical education in pediatrics.Much needs to be done to improve outcomes for critically ill children globally. The sharing of knowledge is important to understand contributors to and methods to improve the outcomes for children globally, and this collection represents this effort.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.029
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.022
Threshold uncertainty score0.075

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.029
Meta-epidemiology (narrow)0.0050.001
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0040.002
Science and technology studies0.0030.003
Scholarly communication0.0090.005
Open science0.0040.002
Research integrity0.0160.021
Insufficient payload (model declined to judge)0.0220.014

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.022
GPT teacher head0.326
Teacher spread0.304 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEditorial

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2023
Admission routes1
Has abstractyes

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