Impact of muscle mass, muscle density and obesity on clinical outcomes in critically ill patients with COVID-19
Notice bibliographique
Résumé
OBJECTIVE: Obesity is generally recognized as an independent risk factor for poor outcomes in Coronavirus Disease 2019 (COVID-19); however, some studies report a paradoxical protective effect. Findings may be mediated by low muscle mass, a relevant predictor of poor clinical outcomes in critically ill patients. We aimed to investigate the association of body mass index (BMI), baseline low muscle mass index (SMI) and low muscle density (SMD) with clinical outcomes in critically ill patients with COVID-19. DESIGN: This retrospective cohort study was conducted at a tertiary care center in São Paulo, Brazil. We included all consecutive patients admitted to the intensive care unit (ICU) from March 1st, 2020, to May 31st, 2021, with a confirmed diagnosis of COVID-19 and who had a measured SMI and SMD by thoracic computed tomography (CT) at admission. SMI and SMD were assessed from a transverse image at the level of the 12th thoracic vertebra (T12), and BMI at admission was calculated. The association between coprimary exposures BMI, low SMI, low SMD and hospital mortality was assessed through multivariable analysis accounting for confounding factors such as age, sex, Simplified Acute Physiology Score 3 (SAPS 3) and comorbidities. RESULTS: A total of 962 patients were included; 63.7 (±15.3) years; 75.8 % males. SMI was assessed in all patients; however, 33 with contrast CTs were excluded from the SMD analysis. The prevalence of low SMI was 21.6 % (208/962). The prevalence of low SMD was 22.7 % (211/929). A total of 391 (40.6 %) patients were classified as overweight, and 393 (40.8 %) as having obesity. Hospital mortality was 14.3 %, increasing to 26.2 % for patients aged ≥65 years. We found no significant association between BMI, SMI or SMD and hospital mortality. Patients with low SMI were more likely to undergo extracorporeal membrane oxygenation (P = 0.045), required longer duration of mechanical ventilation (MV) (p < 0.001), and had prolonged ICU and hospital stays (p < 0.001). Low SMD was independently associated only with ICU readmission (p = 0.034) and longer hospital stay (p < 0.001). Patients with a higher BMI were more likely to be intubated and placed under MV (p < 0.001). Higher BMI was also associated with longer ICU (p = 0.001) and hospital stays (p = 0.049). Patients with obesity and low SMI had longer ICU (p = 0.033), and hospital (p < 0.001) stays, and extended MV duration compared to those with obesity and normal SMI (p = 0.003). CONCLUSIONS: BMI, low SMI, and low SMD were not associated with in-hospital mortality in this cohort. However, these parameters were important predictors of morbidity, including longer ICU and hospital stays, greater need for mechanical ventilation, and ICU readmissions. These findings highlight the importance of assessing body composition parameters in critically ill patients with COVID-19.
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 | 0,004 |
| 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 | 0,000 |
| 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) | 0,003 | 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 ».