Notice bibliographique
Résumé
Since the earliest days of modern neonatology, there has been concern with regard to the outcomes of high-risk survivors after they go home from the hospital. This concern has increased with the recent improvements in survival of infants of extremely short gestation who would previously have died. These issues stimulated the development of follow-up programs by neonatologists, some of them in Canada (1), who could be said to have founded the field of outcomes research. Despite the huge obstacles involved in consistently following infants through childhood, adolescence and, now, adulthood, we have had great success. The follow-up programs have produced important information based on large samples with low attrition. As a result, some programs have shown the generally positive futures of our patients, and the resilience and adaptability of the human organism (2). We have been able to describe the extent and severity of the problems that some of the infants face in the future (3), and also identify the adverse effects of some specific interventions that only became apparent in the long term (4). Neonatal follow-up programs also serve an important clinical purpose – to identify problems early, refer patients for necessary remediation and assist with the coordination of their sometimes complex care. This function is essential, and its importance has led many jurisdictions to provide funding for follow-up programs, which are recognized as an important way of improving the medical care of babies. The current issue of Paediatrics & Child Health includes a series of articles concerning neonatal follow-up, many of them focussing on the situation in Canada. Our country, with its universal health care system, has proved itself capable of ensuring that all of its neonates have the best available care, regardless of parental resources. This system has supported neonatal follow-up programs of extremely high quality, of which we can all be proud, and with outcomes that are as good as anywhere else in the world. What about the future? Stable, secured funding will allow these essential services to focus on providing excellent care and high-quality information. An extension of follow-up programs to other categories of infants is clearly important. The improved survival of infants with congenital anomalies and complex neonatal care unrelated to prematurity requires that they also benefit from the expertise of these programs. There are as many survivors of neonatal intensive care with long-term sequelae as a result of perinatal hypoxic-ischemic encephalopathy at term as there are from prematurity (5); these infants require coordinated care, and the development of effective therapies for them (6) will require ongoing outcomes research. There is also a need for further refining what should be measured and when – both as a means of identifying the child who may benefit from specific intervention and as a way of predicting the likely outcome. Collating results from across the country to develop truly regional and national statistics will provide more essential information on the effects of neonatal diseases and the best ways to improve outcomes. Improving long-term outcomes is now recognized as the most important primary objective of neonatal clinical trials, with the quality of life of the survivors of intensive care being the critical demonstration of the usefulness of an intervention or a change in care. Interventions after the neonatal period to enhance the outcomes of at-risk infants by improving care during development have been less well investigated (7,8) but must, in the future, be thoroughly researched so that we can provide optimal outcomes for all of our patients.
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 | 0,001 | 0,012 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,004 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,014 | 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 ».