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Record W2469101797 · doi:10.1055/s-2007-1012584

Asthma bronchiale - Inhalatives Fluticason weniger effektiv als orales Prednisolon

2007· article· de· W2469101797 on OpenAlexaboutno aff
Ralph Hausmann

Bibliographic record

VenuePneumologie · 2007
Typearticle
Languagede
FieldMedicine
TopicNeonatal Respiratory Health Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineGynecology

Abstract

fetched live from OpenAlex

Inhalative Corticosteroide haben sich als weniger wirksam als orale Substanzen bei der Therapie von Kindern mit akutem schwerem Asthma bronchiale erwiesen. Bei der Behandlung von eher mäßigen Exazerbationen ist die Bedeutung der inhalativen Corticosteroide wegen der widersprüchlichen Datenlage weniger eindeutig. Pediatrics 2006; 118: 644-650 In einer randomisierten doppelblinden und kontrollierten Studie gingen S. Schuh und Mitarbeiter von der Universität von Toronto, Kanada, der Frage nach, ob inhalatives Fluticason die Atemwegsobstruktion bei Kindern mit mildem bis mittelschwerem Asthma schneller bessert als orales Prednisolon. 69 bisher gesunde Kinder und Jugendliche im Alter zwischen 5 und 17 Jahren mit akutem Asthma bronchiale und einer forcierten Einsekundenkapazität (FEV 1 ) zwischen 50% und 79% waren einbezogen. 35 Studienteilnehmer erhielten 2 mg inhalatives Fluticason in der Notfallambulanz plus 500 µg 2-mal täglich (10 Dosen) nach der Entlassung. In der 2. Gruppe (n = 34) wurden die Kinder in der Notfallambulanz mit 2 mg/kg oralem Prednisolon plus 5 täglichen Dosen Prednisolon 1 mg/kg nach der Entlassung therapiert. Alle Patienten erhielten Albuterol in der Notaufnahme und Salmeterol nach der Entlassung. Die Autoren ermittelten die definierten absoluten Veränderungen in % der FEV 1 am Studienanfang und nach 4 und 48 h bei beiden Gruppen.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0170.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.071
GPT teacher head0.403
Teacher spread0.332 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2007
Admission routes1
Has abstractyes

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