No Association between SARS-CoV-2 Infection and Quality of Life 6- and 12-Months After Infection
Bibliographic record
Abstract
OBJECTIVE: To assess the association between Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection and long-term quality of life (QoL). METHODS: Prospective cohort study with 6- and 12-months follow-up conducted in 14 Canadian institutions. Children tested for SARS-CoV-2 between August 2020 and February 2022 were eligible. QoL was measured using PedsQL-4.0, overall health status scores 6- and 12-months after testing. RESULTS: Among SARS-CoV-2 positive and negative participants eligible for long-term follow-up, 74.8% (505/675) and 71.8% (1106/1541) at 6- and 59.0% (727/1233) and 68.1% (2520/3699) at 12-months, completed follow-up, respectively. Mean ± SD PedsQL scores did not differ between positive and negative groups; difference: -0.86 (95% CI: -2.33, 0.61) at 6- and -0.48 (95% CI: -1.6, 0.64) at 12-months, respectively. SARS-CoV-2 test-positivity was associated with higher social subscale scores. Although in bivariate analysis, overall health status at 6-months was higher among SARS-CoV-2 cases [difference: 2.16 (95% CI: 0.80, 3.53)], after adjustment for co-variates, SARS-CoV-2 infection was not independently associated with total PedsQL or overall health status at either time point. Parental perception of recovery did not differ based on SARS-CoV-2 test-status at either time point. CONCLUSIONS: SARS-CoV-2 infection was not associated with QoL, overall health status, or parental perception of recovery 6- and 12-months following infection.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".