[Evidence summary:] What characterizes atypical clinical presentation of COVID-19 in older patients [age 65+]?
Bibliographic record
Abstract
Older people with COVID-19 often present with atypical clinical symptoms. \nThe HSPC1 states: “It is important to remember that elderly people often \npresent atypically with symptoms such as: lethargy; increased confusion; \nchange in baseline condition; loss of appetite.” \nThe WHO3and CDC4 designate anorexia, malaise, muscle pain, sore throat, \ndyspnea, nasal congestion, headache, confusion, rhinorrhea, hemoptysis, \nvomiting and diarrhea as atypical or less common symptoms. \nBMJ Best Practice5 and UptoDate6 both describe common and atypical \nclinical presentations of COVID-19; less common symptoms include \nheadache, sore throat, chest pain, haemoptysis, dizziness, confusion, nasal \ncongestion, gastrointestinal disorders, anorexia, smell and taste disorders, \nand skin disorders. Canadian guidance also lists atypical symptoms \nincluding delirium, functional decline, weakness, malaise, abdominal pain, \nunexplained tachycardia, anosmia, functional decline, conjunctivitis, falls, \ndiarrhoea and decrease in blood pressure. \nThe international literature describes a variety of atypical presentations \nfrom patients who presented with symptoms of acute ischaemic stroke; to \naltered mental status, dizziness and syncope; confusion and lethargy. \nOther atypical symptoms mentioned in the literature include chills, malaise, \nsore throat, confusion, myalgia, headache, nausea, rash, back pain, \ngastrointestinal disorders, tremor and tachycardia.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 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".