Understanding symptoms suggestive of long COVID syndrome and healthcare use among community-based populations in Manitoba, Canada: an observational cross-sectional survey
Bibliographic record
Abstract
OBJECTIVE: This study aims to characterise respondents who have COVID-19 and long COVID syndrome (LCS), and describe their symptoms and healthcare utilisation. DESIGN: Observational cross-sectional survey. SETTING: The one-time online survey was available from June 2022 to November 2022 to capture the experience of residents in Manitoba, Canada. PARTICIPANT: Individuals shared their experience with COVID-19 including their COVID-19 symptoms, symptoms suggestive of LCS and healthcare utilisation. We used descriptive statistics to characterise patients with COVID-19, describe symptoms suggestive of LCS and explore respondent health system use based on presenting symptoms. RESULTS: There were 654 Manitobans who responded to our survey, 616 (94.2%) of whom had or provided care to someone who had COVID-19, and 334 (54.2%) reported symptoms lasting 3 or more months. On average, respondents reported having 10 symptoms suggestive of LCS, with the most common being extreme fatigue (79.6%), issues with concentration, thinking and memory (76.6%), shortness of breath with activity (65.3%) and headaches (64.1%). Half of the respondents (49.2%) did not seek healthcare for COVID-19 or LCS. Primary care was sought by 66.2% respondents with symptoms suggestive of LCS, 15.2% visited an emergency department and 32.0% obtained care from a specialist or therapist. 62.6% of respondents with symptoms suggestive of LCS reported reducing work, school or other activities which demonstrate its impact on physical function and health-related quality of life. CONCLUSION: Consistent with the literature, there are a variety of symptoms experienced among individuals with COVID-19 and LCS. Healthcare providers face challenge in providing care for patients with a wide range of symptoms unlikely to respond to a single intervention. These findings support the value of interdisciplinary COVID-19 clinics due to the complexity of the syndrome. This study confirms that data collected from the healthcare system do not provide a comprehensive reflection of LCS.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".