Impact of optimizing the serum ferritin threshold for diagnosis of iron deficiency: A pre- and post-intervention study using EHR data
Notice bibliographique
Résumé
Abstract Background Iron deficiency (ID), with or without anemia (IDA or IDWA) is one of the most prevalent and underdiagnosed conditions globally, particularly in women. Ferritin is the primary biomarker used to assess iron stores, but historically, sex-specific lower limits of normal (LLNs) have underestimated ID prevalence in females. Recent guidelines recommend a unified ferritin threshold of <30 ng/mL for diagnosing iron deficiency. In September 2023, Rochester Regional Health (RRH) laboratories adopted this evidence-based, sex-independent LLN for ferritin from 10 ng/mL in women and 22 ng/mL in men, to a unified threshold of 30 ng/mL. This study evaluates the impact of this clinical laboratory intervention on IDWA/IDA diagnosis and treatment patterns. Methods We conducted a retrospective cohort study using Epic’s SlicerDicer tool to analyze RRH patient data across two 1.5-year periods: before (March 21, 2022–September 20, 2023) and after (September 21, 2023–March 20, 2025) the ferritin LLN update. Patients with ferritin <30 ng/mL were included. The primary outcome was the diagnosis rate of IDWA or IDA. Secondary outcomes included diagnosis rates by sex, iron prescriptions (oral and IV), hematology referrals, number of patients undergoing endoscopy procedures, and pRBC transfusions. Relative risks (RR) with multiplicity corrected confidence intervals (CI) were calculated for the primary and secondary outcomes. Subgroup analyses were performed by age, sex, ferritin level, and ordering department. Changes in ferritin and hematocrit levels at 3–6 months post-test were also assessed. Results Among patients with ferritin levels <30 ng/mL, 22,478 were identified in the pre- intervention period and 27,699 in the post-intervention. The proportion of ferritin tests flagged as low increased from 13% to 32% following the LLN change (p<0.001). The rate of IDWA or IDA diagnosis increased from 51.0% to 58.5% (RR 1.15; CI 1.12–1.17; p<0.001), with the largest increase among females (49.4% to 58.0%; RR 1.17) compared with males (57.0% to 60.2%; RR 1.06). Diagnosis of IDWA rose by 47% (RR 1.47; CI 1.37–1.57; p<0.001) and IDA diagnosis increased by 7% (RR 1.07; CI 1.03–1.10). Oral iron prescriptions rose by 15%, and IV iron administration increased by 17%. Hematology referrals for IDWA or IDA rose by 14% (CI 1.00–1.31), while endoscopy procedures increased by 23% (CI 1.12–1.35). There was no change in rate of packed red blood cell transfusions (RR 0.93; CI 0.79–1.11). Subgroup analyses showed the most pronounced diagnostic increase occurred among patients with ferritin levels 10-29 ng/ml in women and 22-29 ng/ml in men (newly reclassified as low), with a 33% rise in diagnoses (RR 1.33; CI 1.29–1.36). Surgical specialties had the greatest relative increase in diagnosis of IDWA/IDA —from 40.5% to 54.3% (RR 1.34; CI 1.21–1.49). Trends in iron prescriptions mirrored diagnostic patterns across departments and demographic groups. Ferritin levels increased more post-intervention vs. pre-intervention at 3–6 months follow-up (mean difference: 6.9 ng/mL; 95% CI: 5.7–8.1). Females had substantial greater increase (mean difference: 8.2 ng/mL; 95% CI: 6.9–9.5) compared with males (mean difference: 4.0 ng/mL; 95% CI: 1.4–6.6). Hematocrit also increased in both periods, the difference between the two periods was not clinically significant. Conclusion Adopting a unified, evidence-based lower limit of normal for ferritin improved the recognition and management of iron deficiency, especially in women and individuals without anemia. These results underscore the clinical value of updating ferritin thresholds and support the widespread implementation of standardized, sex-independent reference ranges to promote earlier diagnosis and treatment of iron deficiency in routine practice.
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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 | 0,009 | 0,042 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».