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Enregistrement W4383957208 · doi:10.3389/fped.2023.1245772

Editorial: Insights in pediatric critical care 2022

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

Notice bibliographique

RevueFrontiers in Pediatrics · 2023
Typeeditorial
Langueen
DomaineMedicine
ThématiqueSepsis Diagnosis and Treatment
Établissements canadiensUniversity of British Columbia
Organismes subventionnairesnon disponible
Mots-clésMedicineIntensive care medicine

Résumé

récupéré en direct d'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.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,006
score de la tête « metaresearch » (Gemma)0,029
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Éditorial · Signal consensuel: Éditorial
Score de désaccord entre enseignants0,022
Score d'incertitude au seuil0,075

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0060,029
Méta-épidémiologie (sens strict)0,0050,001
Méta-épidémiologie (sens large)0,0040,003
Bibliométrie0,0040,002
Études des sciences et des technologies0,0030,003
Communication savante0,0090,005
Science ouverte0,0040,002
Intégrité de la recherche0,0160,021
Charge utile insuffisante (le modèle a refusé de juger)0,0220,014

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,022
Tête enseignante GPT0,326
Écart entre enseignants0,304 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreÉditorial

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2023
Routes d'admission1
Résumé présentoui

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