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
Bibliographic record
Abstract
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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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".