Evaluating Hemoglobin Thresholds on the Basis of Sex: Preliminary Insights from a Systematic Review
Notice bibliographique
Résumé
Introduction: World Health Organization hemoglobin thresholds to define anemia are identical for males and females until menarche after which they diverge to 130 g/L and 120 g/L, respectively. There is increasing concern that sex-defined hemoglobin lower limits of normal (LLN) are predicated on sampling females with untreated iron deficiency given its extremely high prevalence and relative under-prioritization in medicine. Inclusion of women with iron deficiency would, in and of itself, result in inappropriately low LLN. We therefore conducted a systematic review to evaluate the published literature to date on sex-based hemoglobin reference intervals (RIs). Methods: A systematic review was conducted using a comprehensive search of MEDLINE, EMBASE, CINAHL and Web of Science from inception to November 2022. Two reviewers independently screened and performed data extraction. A third reviewer adjudicated decisions when a consensus could not be reached. We excluded studies that only evaluated hemoglobin RIs in a state of know disease (e.g. untreated iron deficiency, bone marrow pathology, inherited red blood cell disorders, chronic systemic diseases). A priori defined quality assessment of all manuscripts was performed and included the following criteria: the manner in which “health” was defined in the sampled population, whether there was adherence to Clinical and Laboratory Standards (CLSI) guidelines for RI establishment studies, methodological rigour applied and transparent reporting of results. Results: 6411 articles were identified for title/abstract review. 885 articles were selected for full-text analysis, of which 143 extractions have been completed. We report the results of this convenience sample of the first 143 articles. Sixty-two articles aimed to establish hemoglobin RIs or thresholds to define anemia. The remainder of the studies (n=81) were establishing a hemoglobin mean. 32/143 articles evaluated a female population only, 9/143 were male-only and 102/143 presented both. Of those that sought to establish a RI, 42/62 (67.8%) adhered to CLSI guidelines. 110/143 articles included people with known iron deficiency or were at risk of iron deficiency. Of the 82 articles that considered iron status in the study design, 57 used ferritin as the screening laboratory parameter with variation in the definition of a normal ferritin to exclude iron deficiency (21 articles used a ferritin LLN of 12.0 ug/L,15 used a LLN of 16.0 ug/L, 7 used a LLN between 16.0-30.0 ug/L, and 1 used a LLN of 50 ug/L). Conclusion: 77% of the sample of studies evaluated failed to explicitly exclude individuals with known iron deficiency or its risk factors when deriving their LLN. Moreover, in studies that considered iron status of the sampled population, the majority used a ferritin LLN below conventional standards to define iron deficiency. Based on our preliminary findings, we suspect we will identify an overwhelming lack of consideration of the potential for iron deficiency to be present in patients used to define the LLN despite its well-established impact on erythropoiesis and its extremely high prevalence, particularly in females of reproductive age. At the annual meeting we will present more complete results, including a further exploration of the impact of excluding individuals with or at risk of iron deficiency from the cohort used to establish the LLN.
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 | 0,043 | 0,187 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,002 |
| Méta-épidémiologie (sens large) | 0,010 | 0,010 |
| Bibliométrie | 0,022 | 0,025 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,005 | 0,005 |
| Science ouverte | 0,003 | 0,003 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 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 ».