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Record W4317567939 · doi:10.1097/pcc.0000000000003157

Outcomes of Children Surviving Pediatric Acute Respiratory Distress Syndrome: From the Second Pediatric Acute Lung Injury Consensus Conference

2023· review· en· W4317567939 on OpenAlexaff
Elizabeth Y. Killien, Aline B. Maddux, Sze Man Tse, R. Scott Watson

Bibliographic record

VenuePediatric Critical Care Medicine · 2023
Typereview
Languageen
FieldMedicine
TopicRespiratory Support and Mechanisms
Canadian institutionsUniversité de MontréalCentre Hospitalier Universitaire Sainte-Justine
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute of Child Health and Human DevelopmentNational Institutes of Health
KeywordsMedicineMEDLINECINAHLIntensive care medicineData extractionConsensus conferenceGrading (engineering)Family medicineInternal medicinePsychiatryPsychological intervention

Abstract

fetched live from OpenAlex

OBJECTIVES: To summarize the evidence for the Second Pediatric Acute Lung Injury Consensus Conference-2 (PALICC-2) recommendations for assessment of outcomes among patients surviving pediatric acute respiratory distress syndrome (PARDS). DATA SOURCES: MEDLINE (Ovid), Embase (Elsevier), and CINAHL Complete (EBSCOhost). STUDY SELECTION: We conducted a scoping review to identify studies evaluating outcomes following PARDS. We included studies of survivors of PARDS, acute respiratory failure with a high proportion of PARDS patients, or other critical illnesses if PARDS-specific outcomes could be extracted. DATA EXTRACTION: Title/abstract review, full-text review, and data extraction using a standardized data collection form. DATA SYNTHESIS: The Grading of Recommendations Assessment, Development and Evaluation approach was used to identify and summarize evidence and develop recommendations. Of 8,037 abstracts screened, we identified 20 articles for inclusion. Morbidity following PARDS was common and affected multiple domains of pulmonary and nonpulmonary function. There was insufficient evidence to generate any evidence-based recommendations. We generated eight good practice statements and five research statements. A panel of 52 experts discussed each proposed good practice statement and research statement, and the agreement rate was measured with an online voting process. Good practice statements describe the approach to clinical outcome assessment, assessment of pulmonary outcomes of children surviving PARDS, and assessment of nonpulmonary outcomes of children surviving PARDS including health-related quality of life and physical, neurocognitive, emotional, family, and social functioning. The five research statements relate to assessment of patient preillness status, use of postdischarge endpoints for clinical trials, the association between short-term and longer term outcomes, the trajectory of recovery following PARDS, and practices to optimize follow-up. CONCLUSIONS: There is increasing evidence that children are at risk for impairments across a range of pulmonary and nonpulmonary health domains following hospitalization for PARDS. The results of this extensive scoping review and consensus conference involving experts in PARDS research, clinical care, and outcomes assessment provide guidance to clinicians and researchers on postdischarge follow-up to optimize the long-term health of patients surviving PARDS.

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)0.117
metaresearch head score (Gemma)0.221
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.117
Threshold uncertainty score0.617

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1170.221
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0090.012
Bibliometrics0.0250.014
Science and technology studies0.0020.001
Scholarly communication0.0070.006
Open science0.0070.009
Research integrity0.0070.007
Insufficient payload (model declined to judge)0.0040.001

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 head0.052
GPT teacher head0.377
Teacher spread0.324 · 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
GenreReview

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

Citations15
Published2023
Admission routes1
Has abstractyes

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