Reply to Ku et al
Notice bibliographique
Résumé
To the Editor—We thank Dr Ku and colleagues for their interest in our study [1] and for contributing to existing data regarding the emerging association between influenza and invasive aspergillosis. Ku et al report influenza-associated invasive pulmonary aspergillosis (IAIPA) in 11 of 89 patients in 3 Taiwanese centers with influenza, including 8 of 52 (15.4%) in the intensive care unit (ICU). Further analysis showed that although the total incidence of IAIPA was similar in 2015–2016 and in 2018, there was marked variation in incidence of IAIPA among the subgroup of patients with influenza A(H1N1) in different years [2]. On first glance, the rate of IAIPA appears to be considerably higher than what we observed in Alberta, Canada (7.2%) [1], and similar to what has been reported elsewhere in Europe, notably in the Netherlands and Belgium (19%) [3]. However, some caution is warranted in interpreting these data. As the authors point out, their definitions of IAIPA were different from those used in other studies, limiting comparisons. First, clinical features of patients are not described, and so it is unclear whether patients met clinical or radiographic criteria for the diagnosis as published by Schauwvlieghe et al [3]. Second, mycological criteria for IAIPA are lacking in 3 of 11 patients: 2 patients in whom Aspergillus was cultured from sputum, and a third with elevated galactomannan in an endotracheal aspirate. Additional data are needed to describe the epidemiology of IAIPA, but comparisons of incidence rates in different settings could be facilitated by use of consistent research definitions. The most widely used research definitions for invasive fungal disease were recently revised by the European Organization for the Research and Treatment of Cancer (EORTC) and the Mycosis Study Group Education and Research Consortium [4]. Except when proven by histopathology, mycological data alone lack sufficient specificity for diagnosing invasive aspergillosis, necessitating the consideration of host criteria and clinical syndromes. The current EORTC/Mycosis Study Group guidelines do not consider antecedent influenza infection as a host criterion [4], and ICU patients with invasive aspergillosis may lack classic host factors. For this reason, Blot et al published an alternative algorithm (known as AspICU) for the diagnosis of invasive pulmonary aspergillosis (IPA) in this population [5], and Schauwvlieghe et al modified this to study IAIPA in ICU patients [3]. It is likely that patients with milder forms of influenza—that is, patients not requiring intensive care for respiratory failure—and without classic host factors can still develop IPA. However, studying this phenomenon may be difficult because AspICU criteria and published modifications don’t apply outside ICUs, and no current research definitions could capture this group. If further data suggest this occurs frequently, this may prompt modification to future research definitions. In an editorial accompanying our report, Rijnders et al have advised that a new consensus research definition of IAIPA is forthcoming [6]. We welcome the publication of refined standardized definitions to ensure that researchers studying the phenomenon of IAIPA in different settings are comparing the same thing to one another. Such studies are much needed to make sense of the apparent wide variation in the incidence of IAIPIA across geographic settings, and, as we found, across seasons. Potential conflicts of interest. The authors: No reported conflicts of interest. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest.
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 | 0,005 | 0,043 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,002 |
| Méta-épidémiologie (sens large) | 0,002 | 0,002 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,009 | 0,005 |
| Communication savante | 0,008 | 0,005 |
| Science ouverte | 0,003 | 0,004 |
| Intégrité de la recherche | 0,136 | 0,062 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,018 | 0,012 |
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 ».