970 Predictors and risk factors for infants presenting to the accident and emergency department: results of a systematic review
Notice bibliographique
Résumé
Aims Paediatric use of hospital urgent care is rising in all age groups but particularly for infants under the age of 1 year. Providing optimal care to this vulnerable group of patients in a busy accident and emergency (A&E) department can be a challenge. We conducted a systematic review to identify clinical, demographic and cultural risk factors associated with an increased likelihood of A&E attendance for infants under the age of 1 year across high income countries. Methods This review has been conducted in accordance with the 2020 Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA). An electronic search of multiple databases (EMBASE, EMCARE, Medline and CINHAL) was conducted to identify records published from January 2000 to October 2021 reporting on risk factors for presentation to A&E in infants under the age of 1 year. Studies with less than 10 participants or no extractable data, carried out in low and middle-income countries and conference or dissertation abstracts were excluded. Citations of relevant studies were reviewed to identify any additional studies and recommendations were sought from subject experts. The quality of the studies was assessed using the National Institute for Health Research Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies. Studies which were rated ‘poor’ were excluded. Results The search identified 2039 records of which 192 were identified for title and abstract screening. Full text screening and a manual search of the citations and recommendations from subject experts resulted in a total of 35 studies included for quality assessment. 3 studies were rated as ‘poor’ after quality assessment, hence excluded from the review. A total of 32 studies from 6 countries (United Kingdom, United States, Canada, Portugal, Australia and Italy) were analysed. Key demographic, cultural and clinical risk factors were identified. These included maternal factors (socio-economic deprivation, ethnicity, younger age and a diagnosis of a mental health disorder), infant factors (low birthweight (LBW), prematurity, medical complexity, socio-economic deprivation in association with LBW) and healthcare related factors (delivery by Caesarean section, antenatal or perinatal complications, longer postnatal stay). We found limited evidence on the impact of paternal or wider family factors on infant presentation to A&E. Comparable studies were put forward for meta-analysis. This identified maternal risk factors as significant predictive factors for infants presenting to A&E. Conclusion The key predictors of infant presentations to A&E from this review included maternal, infant and healthcare factors. Maternal factors were most commonly mentioned in the reports with an emphasis on maternal mental health factors. We hope our findings inform future interventions to target these risk factors and prevent avoidable A&E attendances through family support and education. This would ultimately improve the overall quality of care for families and their infants. In addition, future research work should focus on the role of paternal factors as well as wider social support networks on infants’ presentation to A&E.
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 | 0,011 | 0,053 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,009 | 0,014 |
| Bibliométrie | 0,011 | 0,014 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,008 | 0,001 |
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 ».