Evaluating long-term renal outcomes after acute kidney injury in critically ill children using two approaches: administrative data and patient-oriented research
Notice bibliographique
Résumé
Background: Acute kidney injury (AKI) in the pediatric intensive care unit (PICU) is associated with poor hospital outcomes. In adults, AKI is associated with the development of chronic kidney disease (CKD) and hypertension in the long-term, both of which are cardiovascular risk factors. However, the late renal effects of child AKI are unclear. Objectives: 1. Use patient-oriented research to determine if PICU-AKI is associated with long-term hypertension and microalbuminuria. 2. Develop novel pediatric CKD and hypertension definitions using provincial administrative healthcare data to evaluate AKI-long-term renal outcomes associations. Methods: Two observational cohort studies: 1) Retrospective Database cohort: n=2499 from two Montreal PICUs; 2) Patient-oriented cohort: 101 patients in an ongoing longitudinal study, 7 years post-PICU admission. Database cohort: medical chart data was collected and merged with 5 years post-PICU provincial administrative healthcare data. Administrative health data CKD and hypertension definitions were derived iteratively (diagnostic, procedural, medication codes). Patient-oriented cohort: 24-hour ambulatory blood pressure monitoring (ABPM) and first morning urine collection were performed to ascertain hypertension and microalbuminuria. Blood samples were not collected at this study visit and therefore glomerular filtration rate was unavailable. Univariate analyses were performed to compare long-term outcomes in patients with vs. without AKI. ResultsDatabase cohort: n=2404; 24.2% (477/1973 with data available) developed AKI. Patients with AKI were younger, had a higher Pediatric Risk of Mortality (PRISM) score, were more likely to require mechanical ventilation and had a longer length of PICU stay. Within 5 years post-PICU, 8.6% had a CKD diagnosis (AKI: 15.7%, non-AKI: 6%, p<0.001); 3.9% had a hypertension diagnosis (AKI: 43/467 (9.2%) vs. non-AKI: 40/1467 (2.7%), p<0.001). Patent-oriented cohort: 32/101 (31.7%) had AKI in the PICU. Patients with AKI were more likely to be given vasopressors in the PICU and had a longer length of PICU stay. Of the 89 patients with ABPM data, 4 (4.5%) had prehypertension, 1 (1.1%) had white coat hypertension, 11 (12.4%) had hypertension (10 masked hypertension, 1 ambulatory hypertension), and 34/68 (50%) had inadequate nighttime dipping (<10% decrease from day to night). In the total population the prevalence of microalbuminuria was 9/100 (9%). There were no statistically significant differences in long-term outcomes between the AKI and non-AKI patients. However, patients with AKI had clinically significantly higher nighttime blood pressure z-scores and a higher proportion had masked hypertension. Conclusions: PICU-AKI is associated with late provincial administrative healthcare data defined CKD and hypertension in preliminary (unadjusted) analyses. The hypertension prevalence after PICU admission is about 2-8 times higher than in the general child population. Research should address measures to decrease post-PICU long-term renal and cardiovascular risk.
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 | 0,017 | 0,038 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,007 | 0,012 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,001 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 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 ».