600 A Meta-analysis of Expected In-patient Burn Mortality Rates
Notice bibliographique
Résumé
Abstract Introduction Improvements in burn care have significantly decreased burn-related mortality over the last several decades. However, a small percentage of patients admitted to burn centers still die from their burn injuries. There is a paucity of information as to the rate of burn deaths at specific time points. The purpose of this study was to determine an updated estimate of overall burn mortality as well as expected event rates within 30-, 60- and 90- days post-burn admission. Methods A search of the existing literature was conducted using PubMed and Google Scholar databases in December 2022. An additional search of relevant primary literature and review articles was performed. Title and abstract screening was performed, followed by full-text reviews. Studies related to burns including patients ≥ 16 y/o with sample sizes ≥ 250 reporting overall in-hospital mortality and mortality at 30-, 60- and/or 90- days post-admission were included in the analysis. Studies including pediatric populations in analyses and patients with non-burn etiologies were excluded. A secondary analysis of adult patients admitted to our burn centre between 2006-2021 were included. Results A total of selected 9 studies were included in the meta-analysis (4 retrospective, 1 prospective, 1 double-blind, randomized, placebo-controlled trial, and 1 Phase III, multi-center, open label, investigator-initiated, randomized trial) in addition to 2611 patients admitted to our burn centre. A total of 10,824 patients were included in our analysis. The overall mortality rate of the included studies is 8.51%. By 60-days post-admission, the overall mortality rate of 6 studies was 7.51%. By 90-days post-admission, the overall mortality rate is 11.66%. The expected mortality rate at 30 days is 6.62%, at 60 days 2.99%, and at 90 days 0.91%. The mortality rate within the first 30 days of admission is 6.6% (95% CI 6.3-6.9%). A decreasing trend in mortality is noted at 60 days of admission which is 1.64% (95% CI 1.4-2%), 90 days of admission 0.5% (95% CI 0.43-0.67%), and 120 days of admission 0.3% (95% CI 0.17-0.37%). Conclusions The meta-analysis shows a higher rate of mortality during the first 30 days of burn admission followed by a decreasing trend in mortality at 60- and 90-days post-admission. Applicability of Research to Practice Our findings suggest further inquiry into factors contributing to increased mortality within the first 30 days of hospital admission as well as the development of effective therapeutic strategies to decrease the rate of mortality.
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 | 0,026 | 0,048 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,002 |
| Méta-épidémiologie (sens large) | 0,013 | 0,067 |
| Bibliométrie | 0,008 | 0,006 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,004 | 0,002 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 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 ».