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Enregistrement W4230367182 · doi:10.1097/inf.0b013e318241f6ea

CARESS

2012· article· en· W4230367182 sur OpenAlexaffabout
Ian Mitchell, Bosco Paes, Abby Li, Krista L. Lanctôt

Notice bibliographique

RevueThe Pediatric Infectious Disease Journal · 2012
Typearticle
Langueen
DomaineMedicine
ThématiqueRespiratory viral infections research
Établissements canadiensHealth Sciences CentreSunnybrook Health Science Centre
Organismes subventionnairesnon disponible
Mots-clésMedicineConfidence intervalPediatricsGestational agePopulationRandomized controlled trialInternal medicinePregnancy

Résumé

récupéré en direct d'OpenAlex

Reply Thank you for the opportunity to respond to the letter by Dr. Taylor. We agree with Dr. Taylor that follow-up data of infants who have received prophylaxis is important. As he points out, those infants who experience a respiratory syncytial virus (RSV)-positive hospitalization represent the failure rate of the product when the product is used in a real-life setting—a measure of effectiveness. That proportion is not necessarily expected to be the same as the values found in randomized controlled clinical trials, in which recruited patients and procedures are not always representative of the reference population. Thus, efficacy and effectiveness estimates may vary substantially. Dr. Taylor also expressed surprise that the calculated admission rate of 0.2% for RSV infections in infants with a gestational age (GA) of 33 to 35 completed weeks1 was not considered significantly different from that found in other groups (1.34% for <29 completed weeks and 1.25% for 29–32 completed weeks GA). In the CARESS study, a total of 588 infants were prophylaxed for prematurity and had GA of 33 to 35 completed weeks. Of those, 14 were hospitalized for any respiratory illness, 12 were tested for RSV, and only 1 was positive for an RSV infection (1/12 × 14/588 = 0.2%). While the proportion looks numerically lower, an estimate based on a single RSV-positive hospitalization gives a wide confidence interval around that estimate. As shown by a χ2 test, the 3 proportions were not statistically significantly different from each other (χ2 = 1.859, df = 2, P = 0.395). As can be seen in Table 1, the expected count in that cell is 5.3, which is not statistically different from the single RSV-positive case detected and the proportions in the other cells.Table 1: χ2 analysis of RSV-positive hospitalizations in premature infantsDr. Taylor compares this result with that of the Palivizumab Outcomes Registry, which found an overall RSV hospitalization rate of 0.8% in the 32 to 35 weeks' GA group.2 He states that the overall RSV hospitalization rate in this group is 1.1%; however, this is incorrect since the quoted percentage applies to infants who were >35 completed weeks' GA. However, there are several differences between the 2 studies that could attribute to the different rates of hospitalization for RSV infection. First, there is a large difference in the number of patients included in the calculation. As well, the 32 to 35 completed weeks' GA group in the Palivizumab Outcomes Registry included infants with other risk factors such as congenital airway anomalies, neuromuscular disease, and other underlying conditions that predisposed the infants to respiratory infection. The CARESS registry premature group did not include any infants with underlying medical illnesses; instead, the latter patients were classified by their specific underlying comorbidities. The differences in classification by the 2 studies make comparisons between the CARESS registry and the Palivizumab Outcomes Registry difficult. In summary, we would like to reassure Dr. Taylor and other readers that the calculated percentage of 0.2% is correct and represents the true rate of RSV positive hospitalization in the 33 to 35 weeks' GA prophylaxed group. We would also point out that the estimate is based on a single admission and that the true admission risk for those who were not prophylaxed in this population cannot be determined in the CARESS registry. Ian Mitchell, MB ChB, FCCP, FRCPC Bosco Paes, MB BS, FRCPI, FRCPC Abby Li, MSc Krista L. Lanctôt, PhD Sunnybrook Health Sciences Centre University of Toronto Toronto, Canada

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)0,003
score de la tête « metaresearch » (Gemma)0,020
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 enseignants0,271
Score d'incertitude au seuil0,000

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0030,020
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0010,001
Études des sciences et des technologies0,0030,001
Communication savante0,0030,003
Science ouverte0,0020,002
Intégrité de la recherche0,0080,009
Charge utile insuffisante (le modèle a refusé de juger)0,2710,130

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 GPT0,342
Écart entre enseignants0,312 · 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'admission2
Résumé présentoui

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