Prävalenz der nicht-invasiven Beatmung in deutschen Notaufnahmen
Notice bibliographique
Résumé
Background and objectives: Non-invasive Ventilation (NIV) is one of the main treatment methods of acute respir-atory insufficiency. So far there is no prevalence data regarding the provision of this kind of ventilation in Germany and in German emergency departments. This thesis focuses on obtaining an overview of the prevalence of non-invasive ventilation in German emergency departments. Materials: A list of emergency departments was created for this purpose and nearly a quarter of all German emergency departments were interviewed with an online questionnaire during September and October of 2017. The questionnaire contained 62 items, struc-tured into 5 categories: Organizational matters, NIV-availability, application, NIV on patients with AECOPD (acute exacerbation of chronic obstructive pulmonary dis-ease), NIV on patients with ACPE (acute cardiogenic pulmonary edema). Results: The response rate was 125 out of 276 emergency departments (nearly 50%) treating about 5 million patients a year. As a result over 80% of the participating hospitals are able to offer NIV in their emergency departments. More than a half of them established NIV in the last five years. In average 120 NIV-applications are performed in each emergency department yearly. The two main indications for NIV are AECOPD (acute exacerbation of chronic ob-structive pulmonary disease) and ACPE (acute cardiogenic pulmonary edema). In third place the community acquired pneumonia is mentioned. The respirator-settings usually are the physicians duty, but nearly in a quarter of all situations the nursing staff is instructed to take care of this task. Sedation is applied by nearly 80% of the participants as supportive medication. Morphin is most commonly used while Midazolam was selected as a second choice. Sedation based on specific diagnoses only plays a minor role. Only while using Ketanest as a sedative for patients with AECOPD and Fentanyl as a sedative for pa-tients with ACPE, significant differences appear. A bronchodilatation mostly is achieved by means of Salbutamol. The acceptance of NIV is highest among the group of leading physicians such as the medical superintendents or the heads of the emergency departments. House officers on duty hesitantly accept this form of therapy. Quality assurance measures are not implemented in nearly 40% of the participating hospitals, clinical standard operation procedures for applying NIV are only available in less than half of the emergency departments. Conclusion: In spite of a current NIV-proportion of 40% in German emergency departments there are no clinical studies for this special setting. The heterogeneous point of view of the participants concerning indications and contraindications of NIV clarifies this state-ment. Furthermore it is necessary to establish external quality assurance programs with a higher measure of standardization. There is less heterogeneity in sedation of NIV-patients, however other recommenda-tions in contrast to the daily practice can be observed.
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 | 0,002 | 0,018 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
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 ».