Predictors of Hospital Readmission of Manitoba Newborns Within Six Weeks Postbirth Discharge: A Population-Based Study
Notice bibliographique
Résumé
OBJECTIVES: To examine the proportion, geographic variation, and predictors of infant hospital readmission within 6 weeks of the postbirth discharge. METHODS: A cross-sectional, population-based study was conducted of all infants who were born from 1997 through 2001, linkable to the birth mother, and discharged alive from the hospital (N = 68 681) using hospital discharge files in the Canadian province of Manitoba. The following predictors of readmission were examined using logistic regression: preterm, low birth weight, neighborhood income, geographic location (the North, Rural South, and Urban areas of Winnipeg and Brandon), breastfeeding status, length of stay, maternal age, and type of delivery. Using 9 non-Winnipeg regions and 12 Winnipeg subregions, ecologic correlations (1-tailed Spearman) between newborn hospital readmission rates and the following were examined: 1) a region's overall health status, measured by the premature mortality rate (PMR), or death before aged 75 years and 2) a region's socioeconomic risk, using the Socio-Economic Factor Index (SEFI). RESULTS: The proportion of infants who were readmitted to the hospital at least once within 6 weeks of postbirth hospital discharge was 3.95%, with respiratory illness the leading cause (22.3% of readmissions). Risk of readmission was higher for infants who were born preterm (adjusted odds ratio [AOR]: 1.80; 95% confidence interval [CI]: 1.55-2.10), who were of the 3 lowest income quintiles (lowest: AOR: 2.02; 95% CI: 1.77-2.32; low: AOR: 1.48; 95% CI: 1.29-1.71; middle: AOR: 1.26; 95% CI: 1.08-1.47), who resided in the North (AOR: 1.85; 95% CI: 1.66-2.07) or Rural South (AOR: 1.25; 95% CI: 1.14-1.36), who were not breastfed (AOR: 1.32; 95% CI: 1.20-1.44), whose mother's age was 17 or younger (AOR: 1.30; 95% CI: 1.10-1.55), whose mother was 18 to 19 years of age (AOR: 1.25; 95% CI: 1.09-144), or who were born by cesarean section (AOR: 1.30; 95% CI: 1.19-1.43). Regional readmission rates were correlated with PMR (9 non-Winnipeg regions: r = 0.77 for PMR and r = 0.68 for SEFI; 12 Winnipeg Community Areas: r = 0.49 for PMR and r = 0.73 for SEFI). CONCLUSIONS: Income and geography are strongly associated with newborn hospital readmission. Modifiable risk factors include increasing breastfeeding rates, decreasing cesarean section rates, and decreasing adolescent pregnancy rates (or increasing adolescent parental support), but these need additional study to establish causation.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, pas un consensus.
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