The University of California Study of Outcomes in Mothers and Infants (a Population-Based Research Resource): Retrospective Cohort Study
Notice bibliographique
Résumé
BACKGROUND: Population-based databases are valuable for perinatal research. The California Department of Health Care Access and Information (HCAI) created a linked birth file covering the years 1991 through 2012. This file includes birth and fetal death certificate records linked to the hospital discharge records of the birthing person and infant. In 2019, the University of California Study of Outcomes in Mothers and Infants received approval to create similar linked birth files for births from 2011 onward, with 2 years of overlapping birth files to allow for linkage comparison. OBJECTIVE: This paper aims to describe the University of California Study of Outcomes in Mothers and Infants linkage methodology, examine the linkage quality, and discuss the benefits and limitations of the approach. METHODS: Live birth and fetal death certificates were linked to hospital discharge records for California infants between 2005 and 2020. The linkage algorithm includes variables such as birth hospital and date of birth, and linked record selection is made based on a "link score." The complete file includes California Vital Statistics and HCAI hospital discharge records for the birthing person (1 y before delivery and 1 y after delivery) and infant (1 y after delivery). Linkage quality was assessed through a comparison of linked files and California Vital Statistics only. Comparisons were made to previous linked birth files created by the HCAI for 2011 and 2012. RESULTS: Of the 8,040,000 live births, 7,427,738 (92.38%) California Vital Statistics live birth records were linked to HCAI records for birthing people, 7,680,597 (95.53%) birth records were linked to HCAI records for the infant, and 7,285,346 (90.61%) California Vital Statistics birth records were linked to HCAI records for both the birthing person and the infant. The linkage rates were 92.44% (976,526/1,056,358) for Asian and 86.27% (28,601/33,151) for Hawaiian or Pacific Islander birthing people. Of the 44,212 fetal deaths, 33,355 (75.44%) had HCAI records linked to the birthing person. When assessing variables in both California Vital Statistics and hospital records, the percentage was greatest when using both sources: the rates of gestational diabetes were 4.52% (329,128/7,285,345) in the California Vital Statistics records, 8.2% (597,534/7,285,345) in the HCAI records, and 9.34% (680,757/7,285,345) when using both data sources. CONCLUSIONS: We demonstrate that the linkage strategy used for this data platform is similar in linkage rate and linkage quality to the previous linked birth files created by the HCAI. The linkage provides higher rates of crucial variables, such as diabetes, compared to birth certificate records alone, although selection bias from the linkage must be considered. This platform has been used independently to examine health outcomes, has been linked to environmental datasets and residential data, and has been used to obtain and examine maternal serum and newborn blood spots.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».