Using an EMR to assess pediatric blood pressure: Challenges and opportunities in a nephrology cohort
Notice bibliographique
Résumé
Abstract Background Hypertension is a prevalent condition in the pediatric population. Diagnosis and management can be challenging due to difficulties with accurate measurement techniques and complex diagnostic criteria. The widespread adoption of electronic medical records (EMRs) has revealed their potential for improving patient care and research. This study aims to assess the clinical utility of using EMR data to enhance the identification and evaluation of children with hypertension. Objectives The primary objectives of this research project were to utilize the EMR to extract anthropometric, demographic, and blood pressure-related data from patients seen in the nephrology clinic as well as describe and evaluate trends in hypertension assessment and treatment while also identifying areas for improvement. Design We performed a single center, retrospective cohort study using EMR data. Setting Children who had their initial visit at the nephrology clinic between January 1st, 2018, and January 1st, 2022, were included in the cohort. Methods Outpatients were identified using ICD-10 codes related to nephrology diseases. The EMR was reviewed to extract anthropometric, biochemical, and blood pressure data. A blood pressure (BP) index was calculated using systolic and diastolic BP values and the 2017 American Academy of Pediatrics (AAP) hypertension guidelines. The primary analysis categorized BP phenotypes. A secondary analysis using EMR and chart review, assessed whether elevated BP was appropriately managed, including scheduling follow-up visits, diagnosing white-coat hypertension, or initiating pharmacological or non-pharmacological interventions. Results A total of 1,469 children aged 1–18 (median age 9.8 years) were newly referred to the nephrology clinic with complete data for BP index calculation. Many children were initially diagnosed as hypertensive, but across multiple visits were normotensive. Despite being hypertensive across multiple visits, we observed that many children had missing data following EMR extraction (∼20%). Furthermore, despite meeting criteria at visit one for hypertension, many children did not have follow up visits (∼20-30%). We identified that those children presenting with isolated elevated diastolic blood pressure elevations were more likely to have fewer BP measurements and were less likely to have BP-related follow up, likely reflecting the perceived benign nature of this phenomenon. Limitations This study’s retrospective, non-randomized design limits generalizability. Conclusions This study underscores the challenges in studying pediatric hypertension using an EMR, particularly highlighting missing values and decreased measurements as problematic.
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 | 0,013 | 0,024 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,002 | 0,002 |
| 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 ».