Child and Family Outcomes After PICU Admission: Creation of an Open Access Literature Database Using a Global Team of PICU Specialists Integrated With Machine Learning Article Swipe
Rebecca E. Hay
,
David J. Zorko
,
Katie O’Hearn
,
Christopher Finn McQuaid
,
Geneviève Du Pont Thibodeau
,
Gonzalo Garcia Guerra
,
Jérémy Olivier
,
Laurence Ducharme-Crevier
,
Laurie A. Lee
,
Michael J. Del Bel
,
Karen Choong
,
James Dayre McNally
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1097/pcc.0000000000003780
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1097/pcc.0000000000003780
OBJECTIVES: As research examining child health outcomes after PICU admission grows, so does the need for the identification and synthesis of a large body of literature. We aimed to create an open-access scoping repository of literature describing longer-term health outcomes after PICU admission, using a large multinational team (crowdsourcing) and a machine learning (ML) algorithm. DATA SOURCES: We performed a registered scoping review (OSF DOI10.17605/OSF.IO/HE5VB; Registered November 21, 2022) using MEDLINE, Embase, CINAHL, and CENTRAL databases, 2000–2022, with no language restrictions. STUDY SELECTION: Observational or interventional studies describing outcomes of children (0–17 yr old) and their families or caregivers measured greater than 2 weeks post-PICU discharge. Titles and abstracts and full texts were initially screened by a large team of PICU healthcare workers and researchers who were recruited as part of an Evidence Hackathon event at the 2022 World Federation of Pediatric Intensive and Critical Care Societies conference. Initial screening results from 5000 citations were used to develop and validate an ML algorithm, after which a hybrid human crowdsourcing and ML approach was used to screen the remaining 11,055 studies. DATA EXTRACTION: Not applicable. DATA SYNTHESIS: Of 16,055 eligible citations, 1,301 met the criteria at full text for inclusion in the database. The screening was completed in just under 2 months while adhering to the gold standard systematic review methodology. Sensitivity for the hybrid human crowdsourcing and ML was 98%. CONCLUSIONS: A collaborative, global PICU team integrated with ML was successful in efficient and accurate large data synthesis, producing a scoping open-access database of studies reporting on post-PICU outcomes. The development of this repository has implications for future reviews, providing opportunities for networking and collaborative engagement in research. The next steps should examine database maintenance, utilization, and dissemination of research findings.
Related Topics
Concepts
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1097/pcc.0000000000003780
- OA Status
- hybrid
- References
- 17
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4411625863
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4411625863Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1097/pcc.0000000000003780Digital Object Identifier
- Title
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Child and Family Outcomes After PICU Admission: Creation of an Open Access Literature Database Using a Global Team of PICU Specialists Integrated With Machine LearningWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-06-25Full publication date if available
- Authors
-
Rebecca E. Hay, David J. Zorko, Katie O’Hearn, Christopher Finn McQuaid, Geneviève Du Pont Thibodeau, Gonzalo Garcia Guerra, Jérémy Olivier, Laurence Ducharme-Crevier, Laurie A. Lee, Michael J. Del Bel, Karen Choong, James Dayre McNallyList of authors in order
- Landing page
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https://doi.org/10.1097/pcc.0000000000003780Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
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hybridOpen access status per OpenAlex
- OA URL
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https://doi.org/10.1097/pcc.0000000000003780Direct OA link when available
- Concepts
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CINAHL, Medicine, Crowdsourcing, MEDLINE, Data extraction, Observational study, Health care, Medical education, Nursing, Psychological intervention, Computer science, World Wide Web, Economic growth, Pathology, Economics, Law, Political scienceTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
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17Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.health | 5, 38 |
| abstract_inverted_index.hybrid | 166, 223 |
| abstract_inverted_index.months | 210 |
| abstract_inverted_index.review | 62, 218 |
| abstract_inverted_index.screen | 175 |
| abstract_inverted_index.should | 281 |
| abstract_inverted_index.(0–17 | 91 |
| abstract_inverted_index.CENTRAL | 74 |
| abstract_inverted_index.CINAHL, | 72 |
| abstract_inverted_index.Embase, | 71 |
| abstract_inverted_index.Initial | 148 |
| abstract_inverted_index.develop | 157 |
| abstract_inverted_index.examine | 282 |
| abstract_inverted_index.greater | 100 |
| abstract_inverted_index.machine | 51 |
| abstract_inverted_index.results | 150 |
| abstract_inverted_index.scoping | 32, 61, 250 |
| abstract_inverted_index.studies | 86, 254 |
| abstract_inverted_index.workers | 122 |
| abstract_inverted_index.Critical | 144 |
| abstract_inverted_index.Evidence | 132 |
| abstract_inverted_index.MEDLINE, | 70 |
| abstract_inverted_index.November | 66 |
| abstract_inverted_index.SOURCES: | 56 |
| abstract_inverted_index.accurate | 244 |
| abstract_inverted_index.adhering | 212 |
| abstract_inverted_index.approach | 171 |
| abstract_inverted_index.children | 90 |
| abstract_inverted_index.criteria | 193 |
| abstract_inverted_index.database | 252, 283 |
| abstract_inverted_index.eligible | 188 |
| abstract_inverted_index.families | 96 |
| abstract_inverted_index.language | 79 |
| abstract_inverted_index.learning | 52 |
| abstract_inverted_index.measured | 99 |
| abstract_inverted_index.outcomes | 6, 39, 88 |
| abstract_inverted_index.research | 2, 289 |
| abstract_inverted_index.reviews, | 268 |
| abstract_inverted_index.screened | 114 |
| abstract_inverted_index.standard | 216 |
| abstract_inverted_index.studies. | 179 |
| abstract_inverted_index.validate | 159 |
| abstract_inverted_index.Hackathon | 133 |
| abstract_inverted_index.Intensive | 142 |
| abstract_inverted_index.Pediatric | 141 |
| abstract_inverted_index.Societies | 146 |
| abstract_inverted_index.abstracts | 108 |
| abstract_inverted_index.admission | 9 |
| abstract_inverted_index.citations | 153 |
| abstract_inverted_index.completed | 205 |
| abstract_inverted_index.database. | 201 |
| abstract_inverted_index.efficient | 242 |
| abstract_inverted_index.examining | 3 |
| abstract_inverted_index.findings. | 290 |
| abstract_inverted_index.inclusion | 198 |
| abstract_inverted_index.initially | 113 |
| abstract_inverted_index.outcomes. | 258 |
| abstract_inverted_index.performed | 58 |
| abstract_inverted_index.post-PICU | 104, 257 |
| abstract_inverted_index.producing | 248 |
| abstract_inverted_index.providing | 269 |
| abstract_inverted_index.recruited | 127 |
| abstract_inverted_index.remaining | 177 |
| abstract_inverted_index.reporting | 255 |
| abstract_inverted_index.research. | 277 |
| abstract_inverted_index.screening | 149, 203 |
| abstract_inverted_index.synthesis | 19 |
| abstract_inverted_index.Federation | 139 |
| abstract_inverted_index.Registered | 65 |
| abstract_inverted_index.SELECTION: | 82 |
| abstract_inverted_index.SYNTHESIS: | 185 |
| abstract_inverted_index.admission, | 42 |
| abstract_inverted_index.algorithm, | 162 |
| abstract_inverted_index.algorithm. | 54 |
| abstract_inverted_index.caregivers | 98 |
| abstract_inverted_index.citations, | 189 |
| abstract_inverted_index.databases, | 75 |
| abstract_inverted_index.describing | 36, 87 |
| abstract_inverted_index.discharge. | 105 |
| abstract_inverted_index.engagement | 275 |
| abstract_inverted_index.healthcare | 121 |
| abstract_inverted_index.integrated | 236 |
| abstract_inverted_index.literature | 35 |
| abstract_inverted_index.networking | 272 |
| abstract_inverted_index.registered | 60 |
| abstract_inverted_index.repository | 33, 263 |
| abstract_inverted_index.successful | 240 |
| abstract_inverted_index.synthesis, | 247 |
| abstract_inverted_index.systematic | 217 |
| abstract_inverted_index.EXTRACTION: | 181 |
| abstract_inverted_index.OBJECTIVES: | 0 |
| abstract_inverted_index.Sensitivity | 220 |
| abstract_inverted_index.applicable. | 183 |
| abstract_inverted_index.conference. | 147 |
| abstract_inverted_index.development | 260 |
| abstract_inverted_index.literature. | 25 |
| abstract_inverted_index.longer-term | 37 |
| abstract_inverted_index.open-access | 31, 251 |
| abstract_inverted_index.researchers | 124 |
| abstract_inverted_index.2000–2022, | 76 |
| abstract_inverted_index.CONCLUSIONS: | 230 |
| abstract_inverted_index.implications | 265 |
| abstract_inverted_index.maintenance, | 284 |
| abstract_inverted_index.methodology. | 219 |
| abstract_inverted_index.utilization, | 285 |
| abstract_inverted_index.Observational | 83 |
| abstract_inverted_index.collaborative | 274 |
| abstract_inverted_index.crowdsourcing | 168, 225 |
| abstract_inverted_index.dissemination | 287 |
| abstract_inverted_index.multinational | 46 |
| abstract_inverted_index.opportunities | 270 |
| abstract_inverted_index.restrictions. | 80 |
| abstract_inverted_index.collaborative, | 232 |
| abstract_inverted_index.identification | 17 |
| abstract_inverted_index.interventional | 85 |
| abstract_inverted_index.(crowdsourcing) | 48 |
| abstract_inverted_index.DOI10.17605/OSF.IO/HE5VB; | 64 |
| cited_by_percentile_year | |
| countries_distinct_count | 2 |
| institutions_distinct_count | 12 |
| citation_normalized_percentile.value | 0.37556947 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |