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Enregistrement W4389234631 · doi:10.1182/blood-2023-179515

Accuracy of Reticulocyte Hemoglobin for Diagnosing Iron Deficiency in Very Preterm Infants: A Population-Based Cohort Study

2023· article· en· W4389234631 sur OpenAlexaff
Hudson Barr, Ketan Kulkarni, Balpreet Singh, Navjot Sandila, Lisa Morrison, Lori Beach, Satvinder Ghotra

Notice bibliographique

RevueBlood · 2023
Typearticle
Langueen
DomaineMedicine
ThématiqueIron Metabolism and Disorders
Établissements canadiensIzaak Walton Killam Health CentreDalhousie University
Organismes subventionnairesnon disponible
Mots-clésMedicineIron deficiencyPediatricsPopulationCohortHemoglobinFerritinAnemiaComplete blood countSoluble transferrin receptorInternal medicineIron status

Résumé

récupéré en direct d'OpenAlex

Background: Preterm born infants are at an increased risk of developing iron deficiency (ID) despite preventative iron supplementation, which can lead to long-term negative neurodevelopmental and behavioral outcomes. Serum ferritin (SF) is the commonly used test for diagnosing ID. However, SF is influenced by infection and inflammation, making it an unreliable marker in such situations. An alternative, reticulocyte hemoglobin equivalent (Ret-He), measures the iron content in newly produced red blood cells, providing an immediate assessment of iron availability. Unlike SF, Ret-He tests are automated, can be performed on the same blood sample as a complete blood count, and is not influenced by infection or inflammation like SF. However, there is limited literature on the reliability of Ret-He as an ID marker in very preterm infants (VPI) during their first year of life. This study aims to evaluate the diagnostic accuracy of Ret-He as an ID indicator in VPI at 4-6 months of corrected age (CA) compared to SF levels. Objective: To investigate the accuracy of Ret-He in detecting ID in VPI at 4-6 months CA Methods: A retrospective population-based cohort study was conducted using a population-based Provincial Perinatal Follow-Up (PFUP) database on all live VPIs born in Nova Scotia between 2012 and 2018. Infants with hematological disorders, chromosomal abnormalities, or major congenital anomalies were excluded. Prophylactic iron supplementation (2-3 mg/kg/day) starting at 2-4 weeks of chronological age was a standard of care for all included infants. Iron supplementation was recommended until 9-12 months CA. All infants underwent SF and CBC testing at either 4- or 6-months CA to assess iron stores and guide supplementation. In 2012, Ret-He was added as an additional marker of ID for clinical decision-making. Two definitions of ID were used. Definition one defined ID as SF level <20 mcg/L. Definition two defined ID as SF level <20 mcg/L at 4 months and <12 mcg/L at 6 months CA. Receiver operating characteristic curves were performed and the areas under the curves (AUC) were calculated to assess the accuracy of Ret-He in classifying patients with ID. The optimal cut-off point for Ret-He was determined using Youden's index, from which sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated. The Spearman correlation coefficient was calculated between SF and Ret-He. Statistical significance was set at a two-sided P value of < 0.05. Results: A total of 156 patients were included. Under definition one, 62 (39.7%) met the criteria for ID. Under definition two, 39 (25.0%) patients had ID. Baseline characteristics are provided in Table 1. The Spearman correlation coefficient between SF and Ret-He was 0.23 (p=0.004). Under definition one, the AUC of Ret-He for diagnosing ID was 0.64 (p=0.002) and 0.69 (p<0.001) under definition two (Figure 1). The optimal cut-off value for Ret-He in ID diagnosis was 29.4 pg irrespective of the definition. Sensitivity, specificity, PPV, and NPV for both definitions are reported in Table 1. Conclusion: Regardless of the ID definition used, the AUCs indicated a weak discriminatory ability of Ret-He for ID diagnosis. The study indicated a weak positive relationship between SF and Ret-He. Ret-He's low diagnostic accuracy in this study is comparable to other studies involving healthy pediatric populations but lower than studies involving children with chronic health conditions. Clinicians should use caution when relying on Ret-He alone to diagnose ID in VPI. Further research is needed to determine the optimal diagnostic approach for identifying ID in VPI as well as explore the clinical utility of Ret-He in combination with other ID biomarkers such as SF and transferrin saturation.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,003
score de la tête « metaresearch » (Gemma)0,010
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,085
Score d'incertitude au seuil0,169

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0030,010
Méta-épidémiologie (sens strict)0,0000,001
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0010,001
Études des sciences et des technologies0,0010,001
Communication savante0,0010,000
Science ouverte0,0010,001
Intégrité de la recherche0,0010,001
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 Opus0,013
Tête enseignante GPT0,290
Écart entre enseignants0,276 · 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 source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

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

En bref

Citations0
Publié2023
Routes d'admission1
Résumé présentoui

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