What did we learn about tocilizumab use against COVID-19? A single-center observational study from an intensive care unit in Serbia
Notice bibliographique
Résumé
Background Selection of effective and safe therapy for management of patients with coronavirus disease is challenging. Tocilizumab (TZB) has emerged as a potential treatment option for COVID-19. Several aspects regarding Tocilizumab treatment remain uncertain, such as the optimal timing for its administration and the safety profile, including the potential risk of infections. The aim of the study is to present the clinical characteristics of patients with COVID-19 following the application of Tocilizumab. Methods This is a retrospective analysis of 121 patients with severe forms of COVID-19 previously treated with Tocilizumab was conducted. All patients were admitted to intensive care units (ICUs). Results Of 121 patients, the majority were men 72 (59.5%) with a median age at presentation of 65 ± 13 years. Only 9 (7.43%) patients were without comorbidities, while the other 112 (92.55%) had two or more comorbidities. Almost all of the 120 patients (99.2%) needed oxygen therapy, such as nasal cannulas in 110 (90.9%) patients, high flow nasal catheter (HFNC) in 4 (3.3%) patients, and continuous positive airway pressure (CPAP) in 5 (4.1%) patients while 1 patient was intubated at the time of hospital admission. The average time from Tocilizumab application to admission to the ICU was 3 days. During clinical deterioration, almost half 57 (47.1%) of the patients were intubated, and 52 (82.5%) of these intubated patients (p < 0.001) had lethal outcomes. The most significant predictors for a lethal outcome according to multivariate analysis were diabetes mellitus (p < 0.001) followed by a subsequent elevation in C-reactive protein levels (CRP; p < 0.002) and ferritin (p < 0.013) after Tocilizumab application. Bloodstream infections were found in 20 (16.5%) patients, most frequently with Gram-negative pathogens like Acinetobacter spp. as in 12 (18.6%) patients, Klebsiella spp. in 6 (8%) patients, and Pseudomonas spp. in 2 (3.2%) patients. Urine culture isolates were found in 9 (7.43%) patients, with Candida spp. being most frequently isolated in 7 (5.8%) patients, followed by Klebsiella spp. and Pseudomonas spp. in 1 patient each (0.8%). Significantly lower survival was seen in patients with proven infection. Conclusion The benefit of tocilizumab was not found in our study. The high mortality rate among intubated patients after Tocilizumab use suggests appropriate patient selection and monitoring and emphasizes the risk of superinfections. Diabetes mellitus, increased levels of CRP, and ferritin were identified as the most significant predictors of poor outcomes in contrast to increased levels of IL-6.
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 | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
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 ».