Accuracy of Reticulocyte Hemoglobin for Diagnosing Iron Deficiency in Very Preterm Infants: A Population-Based Cohort Study
Notice bibliographique
Résumé
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.
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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 | 0,003 | 0,010 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| 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 ».