Population-Level Trends in Kidney Function before and during the COVID-19 Pandemic: A Province-Wide Retrospective Study from Alberta, Canada
Bibliographic record
Abstract
Background: COVID19 infection is linked to the development of kidney-related adverse consequences via direct and indirect kidney injury. We explored changes in kidney function pre and during COVID-19 pandemic at population-level in Alberta, Canada. Methods: This retrospective study using a province-wide administrative health data from Alberta, Canada, between 2018 and 2021. We included all adults residing in Alberta who had ≥1 annual visit to general practitioner and underwent outpatient serum creatinine tests. Data from each quarter of 2018-2019 was considered as pre-pandemic, while data from each quarter of 2020-2021 was considered during pandemic. Primary outcome was the proportion of individuals with eGFR decline, defined by sustained drop of ≥25% from baseline ≥3 months apart. Secondary outcome was the proportion of individuals with reduced eGFR who progressed to advanced stages of kidney dysfunction (eGFR <30 ml/min/m2). Results: A total of 214,496 and 214,103 individuals were included in the study, pre-pandemic and during pandemic, respectively. The mean age was 58.3±17 years and 43% were male. At baseline, 16.5% and 17.3% of individuals had a reduced eGFR of <60 ml/min/m2 pre and during pandemic. The proportion of individuals with eGFR decline was higher during compared to pre pandemic era, particularly in the third and fourth quarter of 2020 (Q3: 3.2% vs 2.2%, Q4: 3.9% vs 2.9%) (Figure 1). Of those with reduced baseline eGFR, the proportion of individuals who progressed to advanced stages of kidney dysfunction was higher during the pandemic era. Conclusion: This population-based, province-wide retrospective cohort showed a significant trend in the trajectory of kidney function decline with COVID-19 at the population level. These findings highlight the impact of the COVID-19 pandemic on kidney function, and a need for close monitoring of kidney function (particularly for the high-risk group) at the population level.Proportion of individuals with eGFR decline in each quarter pre and during pandemic
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".