The impact of long COVID on physical and cardiorespiratory parameters: A systematic review
Bibliographic record
Abstract
BACKGROUND: Since the emergence of COVID-19, millions worldwide have continued to experience persistent symptoms months after infection. Among these, physical and cardiorespiratory impairments are frequently reported, but remain poorly understood. This systematic review aimed to identify and synthesize evidence regarding physical and cardiorespiratory impairments in individuals with long COVID, defined as symptoms persisting for at least three months post-infection. METHODS AND FINDINGS: A structured search was conducted across the MEDLINE, Embase, CINAHL, and Web of Science databases to identify cross-sectional and longitudinal cohort studies on physical and cardiorespiratory deficits in adults with long COVID. Twenty-two studies involving 3,041 adults with long COVID were included. Critical appraisal using the JBI-APT indicated that most studies had clear inclusion criteria (17/22), well-defined study populations (17/22), and valid exposure measurements (16/22), though confounding factors were often unaddressed (9/22 unclear or not reported). Findings indicate that while adults with long COVID displayed normal pulmonary function at rest, including Forced Vital Capacity (FVC), Forced Expiratory Volume (FEV1), Total Lung Capacity (TLC), and resting Arterial oxygen saturation (SpO2), significant impairments in exercise capacity were identified. Notably, all studies assessing the 6-minute walk test (6MWT) reported reduced distances, consistently falling below the 50th percentile of normative values. Additionally, VO₂peak was decreased in most studies (7/10), falling below 80% of the predicted value, indicating impaired aerobic capacity. Lower Diffusing Capacity of the Lungs for Carbon Monoxide (DLCO) values were observed in three out of six studies, with values below 75% of predicted, suggesting impaired gas exchange efficiency during exertion. CONCLUSION: Despite preserved resting lung function, these findings highlight significant physical deconditioning in Long COVID adults, with substantial reduction in exercise capacity. Routine assessments should include more sensitive measures, such as the 6MWT and VO₂peak, to detect subtle exercise limitations, even in patients with normal resting SpO₂, to better inform rehabilitation interventions.
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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 | 0.008 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.010 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".