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Enregistrement W2029635564 · doi:10.1111/j.1469-8749.2009.03374.x

Socio–economic achievements of individuals born very preterm at the age of 27 to 29 years

2009· letter· en· W2029635564 sur OpenAlexaffabout
Saroj Saigal, David L. Streiner

Notice bibliographique

RevueDevelopmental Medicine & Child Neurology · 2009
Typeletter
Langueen
DomaineMedicine
ThématiqueInfant Development and Preterm Care
Établissements canadiensUniversity of TorontoMcMaster University
Organismes subventionnairesnon disponible
Mots-clésRemedial educationMedicinePsychologyCohort studyEpidemiologyPediatricsClinical psychologyDevelopmental psychology

Résumé

récupéré en direct d'OpenAlex

Follow-up studies on outcomes of preterm infants have received increasing attention owing to the remarkable improvements in the survival of very preterm (VPT) infants. These studies have shown that children born preterm have high prevalences of neurodevelopmental disabilities, behavioural and emotional difficulties, higher rates of dysfunction in cognition and executive functioning, poorer academic achievement, grade failure, and increased utilization of remedial education that persists to adolescence. With these pessimistic observations, it is not surprising that some investigators predicted that nearly half of children born very preterm would not become fully independent adults. However, over the last decade there are a number of outcome studies of preterm infants at adulthood that are fairly positive, using two different designs. The most common design is descriptive cohort studies with matched controls followed longitudinally, with meticulous efforts to gain compliance, administration of standardized tests and validated self-completed questionnaires, and access to databases collected prospectively.1, 2 These studies are expensive and time-consuming, but provide accurate and valuable information on the severity of disabilities, functional abilities, emotional and behavioural concerns, and self-perception of quality of life. Although most studies show a somewhat lower rate of educational achievement, employment, independent living, dating, and sexual activity, the preterm group has also been reported to have decreased rates of risk-seeking behaviours than term controls.1 Recently, researchers in Europe have taken an innovative approach and published large epidemiological studies to adulthood with data from national registers.3, 4 The databases have unique identifiers linking birth data to subsequent vital statistics of the individual, including education, employment, income, marriage, children, and even contact with enforcement agents law. So far, such studies have been reported in Sweden3 and Norway,4 and now in this study by Mathiasen et al. in Denmark.5 The message is the same: the majority of young adult survivors born VPT appear to do reasonably well in terms of education, employment, and independent living. However, in all these studies, with some variations, statistically significant differences were observed, with the VPT group having a higher prevalence of impairments, more young adults living at home, lower levels of education, lower income, and a higher level of unemployment and dependence on social benefits. These disadvantages were greater with decreasing gestational age. In another Norwegian study,6 stillbirth rates were higher and reproductive rates significantly lower among the preterm cohort. Further, females born preterm showed a gestational age dose response, with the more immature females having a higher risk of delivering a preterm offspring. These large epidemiological studies provide a wealth of information and are extremely cost-effective. Other advantages are that the data are readily available, with minimal losses due to missing data. However, there are some limitations: lack of information regarding severity of impairments and functional abilities, and the inability to collect data on emotional issues and depression. For two reasons, we prefer to have the largest feasible sample size: more accurate parameter estimation, and to allow for sub-group analyses. However, the downside to large sample sizes is that it dooms us to statistical significance. With a large sample size, even trivial differences or relationships are unlikely to have arisen by chance. For example, with a sample size of 1400 in this study,5 a correlation of 0.053 (accounting for ¼ of 1% of the variance) would be significant; and group differences smaller that 1/10th of a standard deviation are significant. Consequently, it is necessary to temper interpretations of statistical significance with questions about clinical importance. As the authors state, despite the statistical differences, the public health impact is small.5 Similarly, many analyses lead to the problem of multiplicity; inflating the probability of significant results by chance. If 10 analyses are done, the probability of at least one significant chance finding is 40%; and it is over 78% if 30 analyses are run. This assumes that the analyses are independent. When they are not, as with education or income in this paper, the probability of finding significance by chance escalates considerably. Usually, we correct for this by adopting a more conservative alpha level, using either the Bonferroni correction, or a sequential testing procedure. However, this is rarely done.2 Other differences between European and North American studies are that the majority of survivors, as in this study, are between 30 and 32 weeks’ gestation, and therefore do not represent the most immature infants who are at highest risk. Unlike the Cleveland study,1 the European population is also more racially homogeneous, socioeconomically more advantaged, and with access to national health services. Despite the greater immaturity and higher rates of impairments in the US1 and Canadian cohorts,2 a significant proportion was reported to doing reasonably well. Ultimately, had these studies to adulthood not been undertaken we would never have known the extent of recovery. It appears that despite disabilities, a large proportion of young adults are doing better than expected, and that the earlier dire predictions are not borne out.

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: aucune
Score de désaccord entre enseignants0,542
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0020,000
Bibliométrie0,0010,000
Études des sciences et des technologies0,0000,001
Communication savante0,0000,000
Science ouverte0,0010,001
Intégrité de la recherche0,0010,002
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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.

Tête enseignante Opus0,014
Tête enseignante GPT0,249
Écart entre enseignants0,235 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreCommentaire

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations11
Publié2009
Routes d'admission2
Résumé présentoui

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