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Enregistrement W3171607606 · doi:10.1093/pch/pxab032

Micronutrient deficiencies in autism spectrum disorder: A macro problem?

2021· article· en· W3171607606 sur OpenAlexafffund
Laura M. Kinlin, Catherine S. Birken

Notice bibliographique

RevuePaediatrics & Child Health · 2021
Typearticle
Langueen
DomaineMedicine
ThématiqueChild Nutrition and Feeding Issues
Établissements canadiensInstitute for Work & HealthInstitute for Clinical Evaluative SciencesSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
Organismes subventionnairesCanadian Institutes of Health Research
Mots-clésAutism spectrum disorderMicronutrientAutismMacroMedicinePsychiatryComputer sciencePathology

Résumé

récupéré en direct d'OpenAlex

A 7-year-old boy with autism spectrum disorder (ASD) was referred for outpatient paediatric assessment because of food selectivity and a limited food repertoire. His diet consisted exclusively of yogurt drink, pudding, and chicken nuggets. His parents had tried to give him a children’s multivitamin and encourage a more varied diet, without success. A review of systems was positive for gingival bleeding and fatigue. The physical exam was notable for gingival swelling and perifollicular petechiae in the bilateral lower extremities. The patient’s blood work identified a microcytic anemia (hemoglobin 75 g/L, mean corpuscular volume 58 fL). Hypochromia, microcytosis, and poikilocytosis were present on blood smear. Ferritin was <1 µg/L. Ascorbic acid (vitamin C) level was ultimately reported as <5 µmol/L. The patient was diagnosed with both iron deficiency anemia and scurvy. A 10-year-old boy with ASD presented to the emergency department following a generalized tonic-clonic seizure (his first known seizure). Initial blood work identified an ionized calcium level of 0.79 mmol/L. He was admitted to hospital for ongoing management of hypocalcemia, including calcium infusion. His diet was found to consist exclusively of rice, banana, and canned chicken. He had refused dairy products since early childhood and was not receiving supplemental vitamin D or calcium. In the context of the patient’s limited dietary repertoire and parental concerns regarding eye pain, an urgent ophthalmological assessment was arranged. Findings were consistent with xerophthalmia, and he was treated urgently with oral vitamin A, as per World Health Organization guidelines (1). Further blood work showed vitamin D deficiency (25-hydroxy vitamin D <5 nmol/L), elevated alkaline phosphatase (440 U/L) and elevated parathyroid hormone (132 ng/L). On x-ray, there was no radiographic evidence of rickets. As suspected, the patient’s vitamin A level was very low (0.2 µmol/L). The patient had both xerophthalmia (secondary to nutritional vitamin A deficiency), and symptomatic hypocalcemia (secondary to severe vitamin D deficiency). ASD is a neurodevelopmental disorder with onset in childhood, characterized by (i) impairments in social communication and (ii) restricted, repetitive patterns of behaviours, interests or activities (2). ASD affects approximately 1 in 66 Canadian children and youth from 5 to 17 years of age (3). Feeding problems are common in children and youth with ASD (4). Food refusal, limited dietary repertoire, and high frequency single food intake, in particular, may be seen in ASD (5). The origins of these problems are not completely understood, but likely relate, in part, to insistence on sameness and sensory differences. Restricted diet—resulting from food refusal, limited dietary repertoire and high frequency single food intake—can lead to micronutrient deficiencies. There are numerous case reports of children and youth with ASD and the following micronutrient deficiencies (6–8): Vitamin A deficiency, causing xerophthalmia (the spectrum of ophthalmologic disease caused by vitamin A deficiency) Vitamin C deficiency, causing scurvy (the disease resulting from severe vitamin C deficiency) Vitamin D deficiency, causing vitamin D-deficiency rickets (a defect in mineralization of newly formed bone) Iron deficiency, causing iron-deficiency anemia (a state of insufficient total body iron, such that normal physiologic processes, like hematopoiesis, are not maintained) Micronutrient deficiencies can result in significant morbidity, which may be compounded by invasive investigations, prolonged hospital admission and delayed diagnosis, due in part to the perceived rarity of these conditions (e.g., scurvy [9–11]). The incidence of micronutrient deficiencies in Canadian children and youth with ASD is unknown. Furthermore, very little is understood about the clinical characteristics, use of healthcare resources, and significant health complications associated with these micronutrient deficiencies. A Canadian Paediatric Surveillance Program (CPSP) study on micronutrient deficiencies in children and youth with ASD began in January 2020 and is ongoing (8). CPSP participants are being asked to report all children and youth less than 18 years of age with ASD and a new diagnosis of one or more of the following: vitamin A deficiency/xerophthalmia; scurvy; severe, symptomatic vitamin D deficiency; and severe iron-deficiency anemia. Detailed case definitions (included in the study protocol [8]) were developed to capture cases of biochemical micronutrient deficiency associated with clinical sequelae, and not biochemical deficiency alone. The primary goal of this CPSP study is to understand the burden of serious micronutrient deficiencies better in Canadian children and youth with ASD, in order to inform anticipatory guidance, screening, and prevention strategies in this population. Funding: Laura Kinlin is supported by a Fellowship Award from the Canadian Institutes of Health Research (CIHR). Potential Conflicts of Interest: All authors: No reported conflicts of interest. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed.

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)0,000
score de la tête « metaresearch » (Gemma)0,002
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Commentaire · Signal consensuel: aucune
Score de désaccord entre enseignants0,012
Score d'incertitude au seuil0,025

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,002
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0010,001
Communication savante0,0010,001
Science ouverte0,0000,001
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

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 Opus0,011
Tête enseignante GPT0,266
Écart entre enseignants0,255 · 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'étudeSans objet
Domainenon disponible
GenreCommentaire

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

En bref

Citations3
Publié2021
Routes d'admission2
Résumé présentnon

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