BOLD: Blood-gas and Oximetry Linked Dataset – Open Source Research Article Swipe
João Matos
,
Tristan Struja
,
Jack Gallifant
,
Luis Filipe Nakayama
,
Marie‐Laure Charpignon
,
Xiaoli Liu
,
Nicoleta Economou-Zavlanos
,
Jaime S. Cardoso
,
Kimberly S. Johnson
,
Nrupen A. Bhavsar
,
Judy Wawira Gichoya
,
Leo Anthony Celi
,
An-Kwok Ian Wong
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1101/2023.10.03.23296485
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1101/2023.10.03.23296485
Pulse oximeters measure peripheral arterial oxygen saturation (SpO 2 ) noninvasively, while the gold standard (SaO 2 ) involves arterial blood gas measurement. There are known racial and ethnic disparities in their performance. BOLD is a new comprehensive dataset that aims to underscore the importance of addressing biases in pulse oximetry accuracy, which disproportionately affect darker-skinned patients. The dataset was created by harmonizing three Electronic Health Record databases (MIMIC-III, MIMIC-IV, eICU-CRD) comprising Intensive Care Unit stays of US patients. Paired SpO 2 and SaO 2 measurements were time-aligned and combined with various other sociodemographic and parameters to provide a detailed representation of each patient. BOLD includes 49,099 paired measurements, within a 5-minute window and with oxygen saturation levels between 70-100%. Minority racial and ethnic groups account for ∼25% of the data – a proportion seldom achieved in previous studies. The codebase is publicly available. Given the prevalent use of pulse oximeters in the hospital and at home, we hope that BOLD will be leveraged to develop debiasing algorithms that can result in more equitable healthcare solutions.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.1101/2023.10.03.23296485
- https://www.medrxiv.org/content/medrxiv/early/2023/10/03/2023.10.03.23296485.full.pdf
- OA Status
- green
- References
- 18
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4387337641
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4387337641Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1101/2023.10.03.23296485Digital Object Identifier
- Title
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BOLD: Blood-gas and Oximetry Linked Dataset – Open Source ResearchWork title
- Type
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2023Year of publication
- Publication date
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2023-10-03Full publication date if available
- Authors
-
João Matos, Tristan Struja, Jack Gallifant, Luis Filipe Nakayama, Marie‐Laure Charpignon, Xiaoli Liu, Nicoleta Economou-Zavlanos, Jaime S. Cardoso, Kimberly S. Johnson, Nrupen A. Bhavsar, Judy Wawira Gichoya, Leo Anthony Celi, An-Kwok Ian WongList of authors in order
- Landing page
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https://doi.org/10.1101/2023.10.03.23296485Publisher landing page
- PDF URL
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https://www.medrxiv.org/content/medrxiv/early/2023/10/03/2023.10.03.23296485.full.pdfDirect link to full text PDF
- Open access
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YesWhether a free full text is available
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greenOpen access status per OpenAlex
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https://www.medrxiv.org/content/medrxiv/early/2023/10/03/2023.10.03.23296485.full.pdfDirect OA link when available
- Concepts
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Pulse oximetry, Ethnic group, Medicine, Neonatal intensive care unit, Arterial blood, Oxygen saturation, Emergency medicine, Internal medicine, Pediatrics, Political science, Oxygen, Psychiatry, Law, Organic chemistry, ChemistryTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
- References (count)
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18Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.underscore | 43 |
| abstract_inverted_index.(MIMIC-III, | 69 |
| abstract_inverted_index.disparities | 30 |
| abstract_inverted_index.harmonizing | 63 |
| abstract_inverted_index.measurement. | 23 |
| abstract_inverted_index.measurements | 86 |
| abstract_inverted_index.performance. | 33 |
| abstract_inverted_index.time-aligned | 88 |
| abstract_inverted_index.comprehensive | 38 |
| abstract_inverted_index.measurements, | 109 |
| abstract_inverted_index.darker-skinned | 56 |
| abstract_inverted_index.noninvasively, | 11 |
| abstract_inverted_index.representation | 101 |
| abstract_inverted_index.sociodemographic | 94 |
| abstract_inverted_index.disproportionately | 54 |
| cited_by_percentile_year | |
| corresponding_author_ids | https://openalex.org/A5073759003 |
| countries_distinct_count | 6 |
| institutions_distinct_count | 13 |
| corresponding_institution_ids | https://openalex.org/I182534213, https://openalex.org/I4210166615, https://openalex.org/I63966007 |
| citation_normalized_percentile.value | 0.15553119 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |