Prognosis of COVID-19 patients with type 2 diabetes
Notice bibliographique
Résumé
Background: The pandemic of COVID-19, a disease caused by novel coronavirus SARS-CoV-2, is associated with significant morbidity and mortality. Recent data showed that hypertension, diabetes mellitus, cardiovascular diseases, and chronic obstructive pulmonary disease were the most prevalent comorbidities in COVID-19 patients. Additionally, data indicate that hypertension, diabetes and cardiovascular diseases are important risk factors for progression and unfavourable outcome in COVID-19 patients. Poorly controlled Type 2 diabetes mellitus was associated with severe progression of disease. Hence, large studies with comprehensive analysis of all risk factors and longer follow-up are necessary. Methods and analysis: A single-centre retrospective cross-sectional study of 300 patients that were SARS-CoV-2 positive from May to October 2020 was done. Data was entered into Microsoft excel data sheet and was analysed using SPSS 22 version software. Chi-square test or Fischer’s exact test (for 2x2 tables only) was used as test of significance for qualitative data. Independent t test was used as test of significance to identify the mean difference between two quantitative variables. ANOVA (Analysis of Variance) was used as test of significance to identify the mean difference between more than two quantitative variables. P value (Probability that the result is true) of <0.05 was considered as statistically significant after assuming all the rules of statistical tests. Data collected was analyzed in a group of patients who were sub divided into 2 groups diabetics and Non diabetics. The parameters studied included laboratory markers: D dimer, CRP, Lactate Dehydrogenase, Ferritin levels. To assess the glycemic control HbA1C levels were assessed. The outcome parameters considered were Oxygen requirement, assessing the requirement of intensive care and duration of stay in the hospital Conclusion: The patients with higher HbA1c values were found to have higher CRP and D-dimer values and required ICU shift and prolonged hospital stay. Hence, good control of diabetes will reduce the worsening of disease. In a country like India, where most of the population do not have health insurance cover proper control of diabetes, can reduce the burden on family. Hence, large studies with comprehensive analysis of all risk factors and longer follow-up are necessary.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,061 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».