The Fetal Alert Network: Surveying congenital anomalies
Notice bibliographique
Résumé
To the Editor; Meschino (1) has commented on the innovative nature of the Fetal Alert Network (FAN) in Ontario as was reviewed previously (2); however, we would like to point out that there are only two provinces in Canada that have population-based congenital anomaly (birth defect) registries or surveillance systems, namely British Columbia and Alberta. The remaining provinces that Meschino listed, as did Kim et al (3), have very limited systems such as the maternal serum screen programs of Manitoba and Ontario, perinatal databases of Ontario and Nova Scotia (Nova Scotia also has a fetal anomaly registry) and the Newfoundland provincial medical genetics program with a short ascertainment period. The latter depends on referral to their program and is, therefore, not population-based and would not necessarily have any information on stillbirths or terminations of pregnancy. We agree that it is a serious deficiency not to have a good congenital anomaly surveillance system in Ontario, where 40% of Canada's births take place. The FAN depends on a patient being referred for prenatal diagnosis to one of the five collaborating centres, but they do not state how they will capture cases who are not referred, who are stillborn or who die with a congenital anomaly after the perinatal period. In our opinion, Ontario could use the FAN as an excellent start but they will need to do much more than that if they are to have a comprehensive population-based surveillance system for birth defects. The FAN's one-year study of 832 cases comprises only 0.63% of Ontario's annual births (approximately 132,000) (4). Having a central clearinghouse with the FAN as its base, collecting data from many other sources including the Ontario perinatal system and the maternal serum screen system as well as from genetics clinics, would be a good start. Ontario has also had a problem in the past with the denominator because not all births were registered, but we understand Ontario Vital Statistics is rectifying that. Meschino should realize that ‘traditional surveillance systems’ have not stood still but are, in fact, ascertaining prenatally diagnosed cases and terminations of pregnancy and also have plans to use record linkage methods to perinatal programs. Consequently, data on maternal health, weight, exposure to teratogens and other risk factors can be linked to the congenital anomaly in question. Ethnicity is not necessarily easy to obtain because Canada has decided that it is not to be collected. We also agree with Meschino that congenital anomalies surveillance systems are not adequate if they cannot ascertain prenatally diagnosed cases and terminations, as is the case with the Public Health Agency of Canada's system (Canadian Congenital Anomalies Surveillance System). We submit that the data from the FAN alone will not allow comparisons with other provinces and countries except for a limited number of sentinel anomalies. The longer an ascertainment period exists, the better the data, but a reasonable compromise is a minimum of one year of age.
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 | 0,010 | 0,062 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,003 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,003 | 0,003 |
| Science ouverte | 0,004 | 0,001 |
| Intégrité de la recherche | 0,007 | 0,007 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,002 |
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 ».