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Record W2900640173 · doi:10.1097/ccm.0000000000003545

Extracorporeal Cardiopulmonary Resuscitation: One-Year Survival and Neurobehavioral Outcome Among Infants and Children With In-Hospital Cardiac Arrest*

2018· article· en· W2900640173 on OpenAlexaffabout
Kathleen L. Meert, Anne-Marie Guerguerian, Ryan P. Barbaro, Beth S. Slomine, James R. Christensen, John Berger, Alexis Topjian, Melania M. Bembea, Sarah Tabbutt, Ericka L. Fink, Steven M. Schwartz, Vinay Nadkarni, Russell Telford, Jay B. Dean, Frank W. Moler

Bibliographic record

VenueCritical Care Medicine · 2018
Typearticle
Languageen
FieldMedicine
TopicCardiac Arrest and Resuscitation
Canadian institutionsHospital for Sick ChildrenUniversity of Toronto
FundersNational Center for Advancing Translational SciencesNational Center for Research ResourcesEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Heart, Lung, and Blood Institute
KeywordsMedicineExtracorporeal cardiopulmonary resuscitationCardiopulmonary resuscitationResuscitationExtracorporealClinical deathAnesthesiaEmergency medicineInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: To describe neurobehavioral outcomes and investigate factors associated with survival and survival with good neurobehavioral outcome 1 year after in-hospital cardiac arrest for children who received extracorporeal cardiopulmonary resuscitation. DESIGN: Secondary analysis of the Therapeutic Hypothermia after Pediatric Cardiac Arrest In-Hospital trial. SETTING: Thirty-seven PICUs in the United States, Canada, and the United Kingdom. PATIENTS: Children (n = 147) resuscitated with extracorporeal cardiopulmonary resuscitation following in-hospital cardiac arrest. INTERVENTIONS: Neurobehavioral status was assessed using the Vineland Adaptive Behavior Scales, Second Edition, at prearrest baseline and 12 months postarrest. Norms for Vineland Adaptive Behavior Scales, Second Edition, are 100 (mean) ± 15 (SD). Higher scores indicate better functioning. Outcomes included 12-month survival, 12-month survival with Vineland Adaptive Behavior Scales, Second Edition, decreased by less than or equal to 15 points from baseline, and 12-month survival with Vineland Adaptive Behavior Scales, Second Edition, greater than or equal to 70. MEASUREMENTS AND MAIN RESULTS: Of 147 children receiving extracorporeal cardiopulmonary resuscitation, 125 (85.0%) had a preexisting cardiac condition, 75 (51.0%) were postcardiac surgery, and 84 (57.1%) were less than 1 year old. Duration of chest compressions was greater than 30 minutes for 114 (77.5%). Sixty-one (41.5%) survived to 12 months, 32 (22.1%) survived to 12 months with Vineland Adaptive Behavior Scales, Second Edition, decreased by less than or equal to 15 points from baseline, and 39 (30.5%) survived to 12 months with Vineland Adaptive Behavior Scales, Second Edition, greater than or equal to 70. On multivariable analyses, open-chest cardiac massage was independently associated with greater 12-month survival with Vineland Adaptive Behavior Scales, Second Edition, decreased by less than or equal to 15 points and greater 12-month survival with Vineland Adaptive Behavior Scales, Second Edition, greater than or equal to 70. Higher minimum postarrest lactate and preexisting gastrointestinal conditions were independently associated with lower 12-month survival with Vineland Adaptive Behavior Scales, Second Edition, decreased by less than or equal to 15 points and lower 12-month survival with Vineland Adaptive Behavior Scales, Second Edition, greater than or equal to 70. CONCLUSIONS: About one third of children survived with good neurobehavioral outcome 1 year after receiving extracorporeal cardiopulmonary resuscitation for in-hospital arrest. Open-chest cardiac massage and minimum postarrest lactate were associated with survival with good neurobehavioral outcome at 1 year.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.304
Teacher spread0.286 · 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 designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations57
Published2018
Admission routes2
Has abstractyes

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