Neurological Manifestations in Hospitalized Geriatric Patients With COVID-19 at King Abdulaziz Medical City in Jeddah, Western Region, Saudi Arabia From 2020 to 2021: A Cross-Sectional Study
Notice bibliographique
Résumé
Introduction COVID-19 involvement in the nervous system has been reported in many cases. Viral neuroinvasion has multiple routes of entry. Neurological manifestations of COVID-19 can be divided into ones of the central nervous system (CNS), such as headache, dizziness, altered mental status, ataxia, and seizure, and of the peripheral nervous system (PNS), including ageusia, anosmia, acute illness demyelinating polyneuropathy, and neuralgia. Aim and objectives This study aims to observe and report the neurological manifestations in geriatric patients who were diagnosed with COVID-19 at KAMC-J and report the duration of admission to the in-patient and ICU wards. Methods This was a cross-sectional study conducted on admitted geriatric patients with PCR-confirmed COVID-19 from April 1, 2020 to June 30, 2021 at KAMC-J. Using Raosoft®, the sample size was estimated with a CI of 95% and a 36.4% prevalence of neurological symptoms in COVID-19 patients to be 289. Convenience sampling was used, and the data were collected from BESTCare EMRs. IBM SPSS Statistics for Windows, Version 20 (Released 2011) was used for descriptive and inferential statistical analysis. Results In this study, a total of 290 patients’ data were collected, 161 (55.5%) of which were males. In addition, the median age was 71 (Q1-Q3: 65-78) years; furthermore, the median body mass index (BMI) was 30 (Q1-Q3: 25-34) kg/m2. In descending order, the most prevalent comorbidities were hypertension (HTN) (70.3%), diabetes mellitus (DM) (68.6%), cardiac disease (42.1%), chronic kidney disease (26.6%), neurological disease (23.6%), cancer malignancy (13.1%), and finally chronic respiratory disease (11.4%). Regarding typical COVID-19 manifestations, 181 patients claimed to have experienced cough (62.4%), dyspnea by 164 (56.7%), fever by 154 (53.5%), fatigue by 93 (32.3%), a reading of anoxia by 68 (23.4%), abdominal pain by 58 (20.0%), diarrhea by 56 (19.4%), and finally throat pain by 19 (6.6%). Manifestations and pathologies of the CNS included headache (25.4%), dizziness (21.5%), impaired consciousness (17.2%), delirium (6.6%), ischemic stroke (4.1%), focal cranial nerve dysfunction (2.8%), seizure (2.8%), intracerebral hemorrhage (ICH) (0.3%), and ataxia (0.3%). Moreover, pathologies of the PNS manifested as taste impairment in 46 patients (15.9%), smell impairment in 33 (11.4%), nerve pain in 7 (24%), visual impairment in 5 (1.7%), Bell’s palsy in 2 (0.7%), and Guillain-Barre syndrome in 1 (0.3%). Moreover, the majority of patients who developed an ischemic stroke or ICH, or required admission to the ICU had either DM or HTN. In addition, 17 (25.4%) of the 67 patients admitted to the ICU developed impaired consciousness. All-cause mortality in our study was 31 (10.71%) cases. Conclusion Neurological manifestations of COVID-19 are common and can result in serious complications if not detected and managed early, especially in the elderly. These complications are mostly seen in severely ill patients and may be the only symptoms in COVID-19 patients. In addition, patients' clinical conditions could deteriorate rapidly and result in significant morbidity and mortality. Therefore, a high index of suspicion is required among healthcare providers when dealing with such cases. Moreover, we recommend systematically collecting data on the short- and long-term neurological complications of COVID-19 globally and documenting the functional long-term outcomes after these complications.
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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 | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».