Laboratory, clinical, neurological and neuropsychological features of the course of post-COVID syndrome in patients with cerebrovascular disease
Notice bibliographique
Résumé
A review of the literature reveals a wide range of terms for conditions after coronavirus disease (COVID-19): post-COVID syndrome, post-acute COVID syndrome, chronic COVID-19, long-term complications of COVID-19, long COVID-19, and post-acute sequelae of severe acute respiratory syndrome coronavirus 2 infection. All these terms and others indicate that after COVID-19, a person does not return to his/her usual state of health. Many scientists are researching and looking for the causes of these symptoms, why and when they occur, and how to diagnose and treat them. Therefore, the aim of the study was to improve the diagnosis of post-COVID syndrome in patients with cerebrovascular disease (CVD) by studying clinical, neurological, laboratory and neuropsychological markers. Materials and methods. The study uses psychometric methods — Beck Anxiety Inventory, Hamilton Depression Rating Scale, Fatigue Assessment Scale; neuropsychological — Montreal Cognitive Assessment; clinical — neurological status; laboratory — hemoglobin, C-reactive protein, fibrinogen, albumin, ferritin, lactate dehydrogenase. All patients were divided into four groups: the first group included 20 people with post-COVID syndrome and CVD, the second — 15 individuals with post-COVID syndrome without CVD, the third — 15 patients without post-COVID syndrome with CVD, and the fourth — 15 people without post-COVID syndrome and without CVD. Results. In the group of patients with post-COVID syndrome with cerebrovascular disease (n1 = 20), the average level of hemoglobin (M = 115.15 ± 4.93) and albumin (M = 32.15 ± 1.53) was below the normal range; the content of fibrinogen (M = 6.04 ± 0.82), C-reactive protein (M = 5.50 ± 0.68) was above normal. Data of the Hamilton Depression Rating Scale indicate that patients with post-COVID syndrome and cerebrovascular disease Data of the Hamilton Depression Rating Scale indicate that patients with post-COVID syndrome and cerebrovascular disease (n1 = 20) had a mild depression (M = 6.75 ± 3.90; M = 8.60 ± ± 3.06). Correlation analysis revealed a direct relationship between cognitive functions and hemoglobin (r = 0.455, p ≤ 0.01), albumin (r = 0.571, p ≤ 0.01) and an inverse relationship between cognitive functions and fibrinogen (r = –0.605, p ≤ 0.01), C-reactive protein (r = –0.547, p ≤ 0.01), ferritin (r = 0.408, p ≤ 0.01). There was an inverse correlation between anxiety and hemoglobin (r = –0.619, p ≤ 0.01) and albumin (r = –0.567, p ≤ 0.01) and a direct relationship between anxiety and fibrinogen (r = 0.550, p ≤ 0.01) and C-reactive protein (r = 0.537, p ≤ 0.01). The depression scale negatively correlates with the level of hemoglobin (r = –0.597, p ≤ 0.01), albumin (r = –0.543, p ≤ 0.01) and directly with the content of fibrinogen (r = 0.433, p ≤ 0.01), C-reactive protein (r = 0.383, p ≤ 0.01) and lactate dehydrogenase (r = 0.276, p ≤ 0.05). The indicators of fibrinogen, C-reactive protein, and ferritin were the highest in the group of patients with post-COVID syndrome and cerebrovascular disease. According to the obtained data, there are statistically significant differences between four groups in cognitive functions (χ2 = 36.419, p ≤ 0.01), fatigue (χ2 = 37.251, p ≤ 0.01), anxiety (χ2 = 37.981, p ≤ 0.01) and depression (χ2 = 37.171, p ≤ 0.01). The highest rate of fatigue, anxiety, and depression was found in patients with post-COVID syndrome and cerebrovascular disease.
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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 | 0,001 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 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 ».