Long-term effect of COVID-19 infection on kidney function among COVID-19 patients followed in post-COVID-19 recovery clinics in British Columbia, Canada
Bibliographic record
Abstract
BACKGROUND: We investigated the effect of Post-Acute COVID Syndrome or "long-COVID" on kidney function among patients followed in post-COVID recovery clinics (PCRC) in British Columbia, Canada. METHODS: Long-COVID patients referred to PCRC between July 2020 to April 2022, aged ≥18 years who had an estimated glomerular filtration rate (eGFR) value recorded at 3 months from the coronavirus disease 2019 (COVID-19) diagnosis (index) date were included. Those requiring renal replacement therapy prior to index date were excluded. Primary outcome was change in eGFR and urine albumin-creatinine ratio (UACR) after COVID-19 infection. The proportion of patients in each of the six eGFR categories (<30, 30-44, 45-59, 60-89, 90-120 and >120 mL/min/1.73 m2) and three UACR categories (<3, 3-30 and >30 mg/mmol) in all of the study time points were calculated. Linear mixed model was used to investigate change in eGFR over time. RESULTS: The study sample included 2212 long-COVID patients. Median age was 56 years, 51% were male. Half (∼47%-50%) of the study sample had normal eGFR (≥90 mL/min/1.73 m2) from COVID-19 diagnosis to 12 months post-COVID and <5% of patients had an eGFR <30 mL/min/1.73 m2. There was an estimated 2.96 mL/min/1.73 m2 decrease in eGFR within 1 year after COVID-19 infection that was equivalent to 3.39% reduction from the baseline. Decline in eGFR was highest in patients hospitalized for COVID-19 (6.72%) followed by diabetic patients (6.15%). More than 40% of patients were at risk of CKD. CONCLUSIONS: People with long-COVID experienced a substantial decline in eGFR within 1 year from the infection date. The prevalence of proteinuria appeared to be high. Close monitoring of kidney function is prudent among patients with persistent COVID-19 symptoms.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.050 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".