Evidence map›Paper›PMID 42159445›Full record

Observational studyPediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies2026

Real-Time Assessment of Factors Impacting Prognostic Predictions After Pediatric Cardiac Arrest: A Single-Center Prospective Study.

Megan L McSherry, Bingqing Zhang, Lauren Louderback, Aubree Little, Kathleen E Walsh, Craig A Press, Jennifer McGuire, Rebecca Ichord, Matthew P Kirschen, Charlotte Woods-Hill and 1 more

Abstract readObservational Study
In one paragraph

Observational study in Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Megan L McSherryDepartment of Anesthesiology and Critical Care Medicine, Children's Hospital of Philadelphia, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA.ORCID 0009-0003-8930-1490
Bingqing ZhangDepartment of Biomedical and Health Informatics, Data Science and Biostatistics Unit, Children's Hospital of Philadelphia, Philadelphia, PA.
Lauren LouderbackDepartment of Anesthesiology and Critical Care Medicine, Children's Hospital of Philadelphia, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA.
Aubree LittleDepartment of Anesthesiology and Critical Care Medicine, Children's Hospital of Philadelphia, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA.
Kathleen E WalshDivision of Neurology, Department of Pediatrics, Children's Hospital of Philadelphia, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA.
Craig A PressDivision of Neurology, Department of Pediatrics, Children's Hospital of Philadelphia, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA.
Jennifer McGuireDivision of Neurology, Department of Pediatrics, Children's Hospital of Philadelphia, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA.
Rebecca IchordDivision of Neurology, Department of Pediatrics, Children's Hospital of Philadelphia, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA.
Matthew P KirschenDepartment of Anesthesiology and Critical Care Medicine, Children's Hospital of Philadelphia, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA.
Charlotte Woods-HillDepartment of Anesthesiology and Critical Care Medicine, Children's Hospital of Philadelphia, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA.
Alexis TopjianDepartment of Anesthesiology and Critical Care Medicine, Children's Hospital of Philadelphia, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA.

Funding

Physician Postdoctoral Research Training in Perioperative Medicine (PPRTPM)T32GM112596 · NIGMS · UNIVERSITY OF PENNSYLVANIA · PI Roderic G Eckenhoff, Max Kelz · 2015 to 2026
$3.4M
Cerebral autoregulation and MRI measures of brain injury after pediatric-post cardiac arrestK23NS116120 · NINDS · CHILDREN'S HOSP OF PHILADELPHIA · PI KIRSCHEN, MATTHEW P · 2021 to 2025
$966k
Leveraging implementation and behavioral science to reduce harmful overuse of diagnostic testing in critically ill childrenK23HL151381 · NHLBI · CHILDREN'S HOSP OF PHILADELPHIA · PI WOODS-HILL, CHARLOTTE Z · 2021 to 2025
$890k
NHLBI NIH HHS K23 HL151381NIGMS NIH HHS T32 GM112596NINDS NIH HHS K23 NS116120
6 · The paper itself

Abstract

objectivesChildren who suffer cardiac arrest are at risk of mortality and morbidity, with survivors often experiencing a severe decline in neurobehavioral function. Despite challenges in neuroprognostication, providers frequently make predictions regarding patient recovery that influence outcomes. We aimed to determine the clinical factors providers report using in real time to predict patient survival and neurologic outcomes at discharge, and how these factors differ by provider and patient characteristics, and time from arrest.

designSingle center prospective observational study.

settingThe Children's Hospital of Philadelphia PICU over 12 months, 2023-2024. PATIENTS: Children resuscitated from in-hospital cardiac arrest and out-of-hospital cardiac arrest (OHCA) who received post-arrest care in the PICU. SUBJECTS: Multidisciplinary providers of post-cardiac arrest patients.

interventionsNone. MEASUREMENTS AND MAIN

resultsMultidisciplinary team members completed questionnaires on post-arrest days 1, 2, 3, and 7, eliciting demographic data and factors used to form their prediction. Descriptive statistics summarized patient characteristics, provider demographics, and survey data. Mixed-effect models explored changes in factors used for the prediction of patient discharge outcome over survey time points, as well as differences by provider and patient characteristics. Overall, 64 patients (median age, 4.1 yr [interquartile range, 1.2-9.4 yr]; 60% OHCA; and 55% pre-arrest Pediatric Cerebral Performance Category = 1) were analyzed. Five hundred forty-eight questionnaires were completed by 245 unique providers. Across all time points, baseline neurologic function and clinical neurologic examination were the most frequently reported factors used to inform prognosis. Use of intra-arrest factors decreased, while reliance on neuromonitoring and neuroimaging increased over time. Factor use varied by provider discipline and patient and arrest characteristics.

conclusionsPrognostic predictions after pediatric cardiac arrest were dynamic and influenced by both patient characteristics and provider discipline. Future efforts should aim to understand how the integration of patient data impacts prognostic accuracy and clarify how prognostic impressions shape communication and decision-making with caregivers.

Indexed as

Heart ArrestOut-of-Hospital Cardiac ArrestCardiopulmonary ResuscitationChildChild, PreschoolFemaleHumansInfantIntensive Care Units, PediatricMalePrognosisProspective StudiesTime Factorscardiac arrestgoals-of-care conversationsneuroprognosticationpredictionprognosis

Identifiers

PMID42159445
PMCPMC13682271

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.