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DELAYS IN DIAGNOSIS OF NEPHROTIC SYNDROME IN CHILDREN

2014· article· en· W2162849490 sur OpenAlexaffvenueabout
Asha Hollis

Notice bibliographique

RevueJournal of undergraduate research in Alberta · 2014
Typearticle
Langueen
DomaineMedicine
ThématiqueRenal Diseases and Glomerulopathies
Établissements canadiensUniversity of Calgary
Organismes subventionnairesnon disponible
Mots-clésNephrotic syndromeMedicinePediatricsProteinuriaDiseaseHealth careIntensive care medicineInternal medicineKidney
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

INTRODUCTION Nephrotic syndrome is a common childhood acquired kidney disease, characterized by proteinuria and edema. It can have a variety of complications, including thromboembolic events and end-stage renal failure. Despite knowledge of symptoms, treatment and complications, the clinical experience of nephrologists at the Alberta Children’s Hospital suggests that there are delays in diagnosis and mistakes in treatment, due to the relative non-specificity of the symptoms. Delays and mistakes in treatment could have consequences including increased complications, higher costs of treatment and alteration of the clinical course of the syndrome. As it is unclear why these errors occur, it is important to determine what factors impact delays in diagnosis, whether or not any of these factors are modifiable and what actions could be taken to avoid misdiagnoses and delays. The objective of this study was to determine what healthcare use occurred prior to diagnosis of nephrotic syndrome to see what factors impact delays in diagnosis and whether these factors are modifiable. METHODS The study design was a phone or in-person survey, approximately 15 minutes in length, conducted with the legal guardians of children between the ages of 1 and 18 who have been diagnosed with nephrotic syndrome in the Calgary area and have been seen at the Alberta Children’s Hospital Nephrology Clinic within the past 12 months. The survey was composed of 3 sections, examining patient level variables, healthcare history, and information specific to the family. RESULTS The study showed a diagnosis delay range of 1 day to approximately 110 days. All families reported that once a urine test was completed, a correct diagnosis was obtained. A total of 12 participants were included, with an age range 2.8-11.4 years. The majority of the participants were male, had no pre-existing food allergies, and came from a family where the combined household income before taxes was greater than $100,000. Additionally, participants were of varying ethnic origins. When comparing number of visits to specific healthcare locations and number of wrong diagnoses given, results showed a high rate of diagnostic success in the ER: 11% of patients were given a wrong diagnosis. In contrast, family doctor achieved a low rate of diagnostic success: 100% of patients were given a wrong diagnosis. These wrong diagnoses varied, including constipation and pink eye, but the most common error was diagnosis of allergies, which constituted 61% of faulty diagnoses. DISCUSSION AND CONCLUSIONS Nephrotic syndrome is commonly misdiagnosed by family doctors, resulting in delayed treatment. Given the results that diagnostic success was high in the ER, where a urinalysis was almost always used, the low rate of successful diagnosis by family doctors can be avoided.  There appears to be a need to further educate physicians on the importance of using a urine analysis. Furthermore, future research may explore the value of tools as a reminder to physicians and families that symptoms such as puffy eyes can be indicator of nephrotic syndrome and not necessarily allergies.

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,002
Version: codex-gemma-dda1882f352aStatut 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 enseignants0,038
Score d'incertitude au seuil0,785

Scores Codex et Gemma par catégorie

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

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 Opus0,029
Tête enseignante GPT0,335
Écart entre enseignants0,306 · 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 tête enseignante, 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
Publié2014
Routes d'admission3
Résumé présentoui

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