Using Active Standing Orthostatic Stress Test to Assess Physiological Responses in Individuals with Long-COVID: A Systematic Review
Bibliographic record
Abstract
Background/Objective: Individuals experiencing long-COVID frequently report or-thostatic intolerance symptoms, which may be linked to autonomic and cardiovascular dysfunction. The active standing test provides a simple, clinically relevant means to assess these impairments. This systematic review aims to determine the use of the ac-tive standing orthostatic stress test in evaluating cardiovascular, autonomic, and res-piratory responses in people experiencing LC. Methods: A systematic search, accord-ing to PRISMA guidelines, was conducted in PubMed, MEDLINE, EMBASE, CINAHL, and Scopus for articles published between 2020 and 2025. This study was registered in PROSPERO CRD-42024615872. Studies were included if they used the active standing test, enrolled adults (≥18 years), included both Long-COVID and healthy control groups, used continuous beat-to-beat measurements, and reported physiological out-comes. Risk of bias was assessed using the nine-point Newcastle-Ottawa-Scale. Re-sults: Three studies (216 participants with Long-COVID and 186 controls) met the in-clusion criteria. Across studies, Long-COVID individuals consistently exhibited ele-vated heart rate in both supine and standing positions. However, blood pressure find-ings were more variable: only one study reported 13% of participants met orthostatic hypotension criteria, while another found significant increases in diastolic blood pres-sure during standing. Long-COVID groups also showed reduced heart rate variability compared to controls. Conclusions: Individuals experiencing Long-COVID show ele-vated heart rate and impaired autonomic function during active standing, with sub-group-specific blood pressure changes. These alterations may contribute to dizziness, fatigue, and reduced activity tolerance. Incorporating active standing into clinical as-sessment could aid early identification of autonomic dysfunction and inform rehabili-tation strategies, though more research is urgently needed.
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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 | 0.007 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".