COVID-19 and Spinal Cord Injury: Clinical Presentation, Clinical Course, and Clinical Outcomes: A Rapid Systematic Review
Bibliographic record
Abstract
Persons living with spinal cord injury (SCI) are potentially at risk for severe COVID-19 disease given that they often have decreased lung capacity and may lack the ability to effectively evacuate their lungs. Known risk factors for negative outcomes after COVID-19, such as obesity, diabetes, and cardiovascular disease, disproportionally affect people with SCI and raise concerns for the mortality risk among persons with SCI. A rapid systematic review of English, Spanish, Portuguese, and Chinese literature on COVID-19 and SCI was performed using the keywords “spinal cord injury” and “COVID-19.” We included studies that provided information on clinical presentation, characteristics, course, and outcomes of COVID-19 disease in SCI. We excluded studies on patients who did not have an SCI before severe acute respiratory syndrome coronavirus-2 infection or did not report clinical information. We included 10 studies in total: nine studies with a total of 171 patients and a survey study of 783 healthcare professionals. Fever (74%), cough (52%), and dyspnea (33%) were the most frequently reported symptoms, and 63% showed abnormalities on X-ray imaging. In the included case series and reports ( N = 31), only 1 patient required mechanical ventilation, but 3 patients died (10%). The mortality rate in a large registry study ( N = 140) was 19%. Clinical presentation of COVID-19 in SCI patients was similar to the general population, and though adverse events and intensive care unit admission were low, the mortality rate was high (10–19%). No prognostic factors for severe disease or mortality could be identified. Registration (PROSPERO): CRD42020196565.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.019 | 0.076 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.004 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.006 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".