Risk Factors of In-hospital Death in COVID-19 Patients: a Meta-analysis
Notice bibliographique
Résumé
Background The worldwide COVID-19 pandemic has turned into a global catastrophic public health crisis, and the conclusion about the risk factors of hospital death in COVID-19 patients is not uniform. Objective To explore risk factors of in-hospital death in patients with COVID-19 by a meta-analysis. Methods Case-control studies about risk factors of in-hospital death in COVID-19 patients were searched from databases of the Cochrane Library, ScienceDirect, PubMed, Medline, Wanfang Data, CNKI and CQVIP from inception to October 1, 2021. Literature screening, data extraction and methodological quality assessment were conducted. Meta-analysis was performed using Stata 15.1. Meta-regression was used to explore the potential sources of heterogeneity. Results Eighty studies were included which involving 405 157 cases〔349 923 were survivors (86.37%) , and 55 234 deaths (13.63%) 〕, that were rated as being of high quality by the Newcastle-Ottawa Scale. Meta-analysis showed that being male〔OR=1.49, 95%CI (1.41, 1.57) , P<0.001) , older age〔WMD=10.44, 95%CI (9.79, 11.09) , P<0.001〕, dyspnoea〔OR=2.09, 95%CI (1.80, 2.43) , P<0.001〕, fatigue〔OR=1.49, 95%CI (1.31, 1.69) , P<0.001〕, obesity〔OR=1.46, 95%CI (1.43, 1.50) , P<0.001〕, smoking〔OR=1.18, 95%CI (1.14, 1.23) , P<0.001〕, stroke〔OR=2.26, 95%CI (1.41, 3.62) , P<0.001〕, kidney disease〔OR=3.62, 95%CI (3.26, 4.03) , P<0.001〕, cardiovascular disease〔OR=2.34, 95%CI (2.21, 2.47) , P<0.001〕, hypertension〔OR=2.23, 95%CI (2.10, 2.37) , P<0.001〕, diabetes〔OR=1.84, 95%CI (1.74, 1.94) , P<0.001〕, cancer〔OR=1.86, 95%CI (1.69, 2.05) , P<0.001〕, pulmonary disease〔OR=2.38, 95%CI (2.19, 2.58) , P<0.001〕, liver disease〔OR=1.65, 95%CI (1.36, 2.01) , P<0.001〕, elevated levels of white blood cell count〔WMD=2.03, 95%CI (1.74, 2.32) , P<0.001〕, neutrophil count〔WMD=1.77, 95%CI (1.49, 2.05) , P<0.001〕, total bilirubin〔WMD=3.19, 95%CI (1.96, 4.42) , P<0.001〕, aspartate transaminase〔WMD=13.02, 95%CI (11.70, 14.34) , P<0.001〕, alanine transaminase〔WMD=2.76, 95%CI (1.68, 3.85) , P<0.001〕, lactate dehydrogenase〔WMD=166.91, 95%CI (150.17, 183.64) , P<0.001〕, blood urea nitrogen〔WMD=3.11, 95%CI (2.61, 3.60) , P<0.001〕, serum creatinine〔WMD=22.06, 95%CI (19.41, 24.72) , P<0.001〕, C-reactive protein〔WMD=76.45, 95%CI (71.33, 81.56) , P<0.001〕, interleukin-6〔WMD=28.21, 95%CI (14.98, 41.44) , P<0.001〕, and erythrocyte sedimentation rate〔WMD=8.48, 95%CI (5.79, 11.17) , P<0.001〕 were associated with increased risk of in-hospital death for patients with COVID-19, while myalgia〔OR=0.73, 95%CI (0.62, 0.85) , P<0.001〕, cough〔OR=0.87, 95%CI (0.78, 0.97) , P=0.013〕, vomiting〔OR=0.73, 95%CI (0.54, 0.98) , P=0.030〕, diarrhoea〔OR=0.79, 95%CI (0.69, 0.92) , P=0.001〕, headache〔OR=0.55, 95%CI (0.45, 0.68) , P<0.001〕, asthma〔OR=0.73, 95%CI (0.69, 0.78) , P<0.001〕, low body mass index〔WMD=-0.58, 95%CI (-1.10, -0.06) , P=0.029〕, decreased lymphocyte count〔WMD=-0.36, 95%CI (-0.39, -0.32) , P<0.001〕, decreased platelet count〔WMD=-38.26, 95%CI (-44.37, -32.15) , P<0.001〕, increased D-dimer〔WMD=0.79, 95%CI (0.63, 0.95) , P<0.001〕, longer prothrombin time〔WMD=0.78, 95%CI (0.61, 0.94) , P<0.001〕, lower albumin〔WMD=-1.88, 95%CI (-2.35, -1.40) , P<0.001〕, increased procalcitonin〔WMD=0.27, 95%CI (0.24, 0.31) , P<0.001〕, and increased cardiac troponin〔WMD=0.04, 95%CI (0.03, 0.04) , P<0.001〕were associated with decreased risk of in-hospital death due to COVID-19. According to the meta-regression result, the heterogeneity in gender, renal disease, cardiovascular diseases, asthma, white blood cell count, neutrophil count, platelet count, hemoglobin, and urea nitrogen differed siangificnatly by country (P<0.05) . Conclusion The risk of in-hospital death due to COVID-19 may be increased by 25 factors (including being male, older age, dyspnoea, fatigue, obesity, smoking, stroke, kidney disease, cardiovascular disease, hypertension, diabetes, cancer, pulmonary disease, liver disease, elevated levels of white blood cells, neutrophil count, total bilirubin, aspartate transaminase, alanine transaminase, lactate dehydrogenase, blood urea nitrogen, serum creatinine, C-reactive protein, interleukin-6, and erythrocyte sedimentation rate) , and may be decreased by 13 factors (including myalgia, cough, vomiting, diarrhoea, headache, asthma, low body mass index, decreased lymphocyte count and platelet count, increased D-dimer, longer prothrombin time, lower albumin, increased procalcitonin and cardiac troponin) . The conclusion drawn from this study needs to be further confirmed by high-quality, multicenter, large-sample, real-world studies.
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 | 0,015 | 0,028 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,002 |
| Méta-épidémiologie (sens large) | 0,017 | 0,065 |
| Bibliométrie | 0,006 | 0,006 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,004 | 0,002 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,003 | 0,002 |
| 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 ».