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Enregistrement W1981445913 · doi:10.1016/j.juro.2012.02.2460

2281 HOW MANY SEMEN SAMPLES ARE REQUIRED TO MAKE THE DIAGNOSIS OF AZOOSPERMIA?

2012· article· en· W1981445913 sur OpenAlexaboutno aff
Aziz Khambati, Keith Jarvi, Kirk Lo

Notice bibliographique

RevueThe Journal of Urology · 2012
Typearticle
Langueen
DomaineMedicine
ThématiqueSperm and Testicular Function
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésAzoospermiaSpermSemenMedicineSemen analysisObstructive azoospermiaMale infertilityGynecologySperm RetrievalAndrologyInfertilityBiologyPregnancy

Résumé

récupéré en direct d'OpenAlex

You have accessJournal of UrologyInfertility: Evaluation1 Apr 20122281 HOW MANY SEMEN SAMPLES ARE REQUIRED TO MAKE THE DIAGNOSIS OF AZOOSPERMIA? Aziz M. Khambati, Keith Jarvi, and Kirk Lo Aziz M. KhambatiAziz M. Khambati Toronto, Canada More articles by this author , Keith JarviKeith Jarvi Toronto, Canada More articles by this author , and Kirk LoKirk Lo Toronto, Canada More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2012.02.2460AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Many guidelines now suggest that men are diagnosed as being azoospermic when no sperm is found in two sequential well collected and analyzed semen samples. It is well known that many men with non-obstructive azoospermia (NOA: the most common cause of azoospermia) will have sperm within the testicles. In addition, it has also been well recognized that all men have a significant degree of variability of sperm counts possibly due to variability in sperm production. This has led us to speculate that some men with NOA may also have variability in sperm production and hence on occasion might have enough sperm production to lead to sperm in the ejaculate. The study objective was to determine how many men who would typically be defined as being azoospermic (azoospermia on two sequential semen analyses) had sperm in the ejaculate on subsequent semen testing. METHODS A retrospective study was performed by using a database containing the semen analyses results of patients referred to our centre between October 2000 and June 2011. Patients with a minimum of three semen samples, each within a space of 6 months, with the first two showing azoospermia were identified. All semen analyses were performed in the same laboratory, with centrifugation of the semen samples and an extensive microscopic analysis of the pellet. Medical records were then reviewed and patients with known obstructive causes such as a vasectomy or congenital bilateral absence of vas deference were excluded. In addition, patients who had undergone a corrective procedure such as a varicocelectomy were also excluded. RESULTS In all, 120 men with a total of 420 semen analyses between them were included in the analysis. In men with two initial azoospermic samples, 27 out of 120 (22.5%) had sperm on the third sample. Eight (29.6 %) of these patients had rare non-motile sperm, whereas the mean and median spermatozoa counts in the remaining men (19/27: 70.4%) was 0.54 and 0.4 million respectively. Four of 41 (9.7%) men with three initial azoospermic samples had spermatozoa on the fourth sample. The average motility overall was 21.4%. Finally, none of the 17 men who were azoospermic after four samples had any sperm identified in their subsequent tests. CONCLUSIONS This study suggests that at least 3 and preferably 4 semen samples should be examined before making the diagnosis of azoospermia. In addition, more than 20% of men who would have originally been diagnosed as azoospermic had enough sperm in the subsequent semen specimens to use in a program of intra-cytoplasmic sperm injection. This might possibly reduce the need for surgery to retrieve sperm surgically for these men. © 2012 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 187Issue 4SApril 2012Page: e920 Advertisement Copyright & Permissions© 2012 by American Urological Association Education and Research, Inc.MetricsAuthor Information Aziz M. Khambati Toronto, Canada More articles by this author Keith Jarvi Toronto, Canada More articles by this author Kirk Lo Toronto, Canada More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...

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)0,001
score de la tête « metaresearch » (Gemma)0,009
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,096
Score d'incertitude au seuil0,320

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,009
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0020,001
Études des sciences et des technologies0,0010,001
Communication savante0,0020,001
Science ouverte0,0010,001
Intégrité de la recherche0,0020,001
Charge utile insuffisante (le modèle a refusé de juger)0,0960,032

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 Opus0,045
Tête enseignante GPT0,278
Écart entre enseignants0,233 · 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'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
Publié2012
Routes d'admission1
Résumé présentoui

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